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.gitattributes

@@ -33,3 +33,9 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
+src/img/icmc.png filter=lfs diff=lfs merge=lfs -text
+src/img/wordcloud_brasil5.png filter=lfs diff=lfs merge=lfs -text
+src/portTokenizer/VERB.tsv filter=lfs diff=lfs merge=lfs -text
+src/portTokenizer/WORDmaster.txt filter=lfs diff=lfs merge=lfs -text
+src/postproc/VERB.tsv filter=lfs diff=lfs merge=lfs -text
+src/postproc/WORDmaster.txt filter=lfs diff=lfs merge=lfs -text

README.md

@@ -1,15 +1,23 @@
 ---
 title: Portparser.v2
-emoji: 📈
-colorFrom: blue
-colorTo: indigo
+emoji: 📚
+colorFrom: red
+colorTo: red
 sdk: streamlit
-sdk_version: 5.35.0
-app_file: app.py
+app_port: 8501
+tags:
+- Universal Dependencies
+- Portuguese
 pinned: false
-license: mit
-short_description: A parsing model for Brazilian Portuguese
+short_description: Parser for Portuguese texts using UD standards
+license: cc-by-4.0
+sdk_version: 1.46.1
 python_version: 3.11
 ---
 
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
+# Welcome to Streamlit!
+
+Edit `app.py` to customize this app to your heart's desire. :heart:
+
+If you have any questions, checkout our [documentation](https://docs.streamlit.io) and [community
+forums](https://discuss.streamlit.io).

app.py

@@ -0,0 +1,284 @@
+import sys, os, datetime, random, base64, time
+import streamlit as st
+import streamlit.components.v1 as components
+from tempfile import mkdtemp
+from pathlib import Path
+import pandas as pd
+from huggingface_hub import hf_hub_download
+
+#-----Initial Parameters----
+
+# Must be always False in production. When DEBUG is set to True the interface do not call the parser. Mode to debug interface features in local development.   
+DEBUG=False
+# Embedding model. Options are: 'bert-base-portuguese-cased' or 'bert-base-multilingual-uncased'
+MODEL='bert-base-portuguese-cased'
+
+
+#-----Fuctions-----
+
+# Format external files for interface compatibility
+def img_to_bytes(img_path):
+    img_bytes = Path(img_path).read_bytes()
+    encoded = base64.b64encode(img_bytes).decode()
+    return encoded
+
+def img_to_html(img_path, img_style='max-width: 100%;'):
+    img_html = f"<img src='data:image/png;base64,{img_to_bytes(img_path)}' style='{img_style}'>"
+    return img_html
+
+# Call parser steps
+def make_sentences(path_raw_text, path_text):
+    try:
+        #st.text(f'python ./src/portSentencer/portSent.py -o {path_text} -r -l 2048 {path_raw_text}')
+        outcome = os.system(f'python ./src/portSentencer/portSent.py -o {path_text} -r -l 2048 {path_raw_text}')
+        return f'S'+str(outcome)
+    except Exception as e:
+        return str(e)
+
+def make_conllu(path_text, path_empty_conllu):
+    try:
+        outcome = os.system(f'python ./src/portTokenizer/portTok.py -o {path_empty_conllu} -m -s S0000 {path_text}')
+        return 'T'+str(outcome)
+    except Exception as e:
+        return str(e)
+        
+def make_pred(path_empty_conllu, target_directory, model):
+    try:
+        outcome = os.system(f'python ./src/evalatin2024-latinpipe/latinpipe_evalatin24.py --load {model} --exp {target_directory} --test {path_empty_conllu}')
+        return f'P'+str(outcome)
+    except Exception as e:
+        return str(e)
+
+def make_postproc(path_predicted_conllu, path_final_conllu):
+    try:
+        outcome = os.system(f'python ./src/postproc/postprocess.py -o {path_final_conllu} {path_predicted_conllu}')
+        return f'F'+str(outcome)
+    except Exception as e:
+        return str(e)
+
+def get_predictions(path_prediction):
+    try:
+        with open(path_prediction, 'r') as f:
+            st.text(f.read())
+    except Exception as e:
+        st.text('Resposta: '+e)
+
+
+def run_pipeline(tmp_dir,code):
+
+    path_text             = tmp_dir+"/"+code+"_input.txt"
+    path_empty_conllu     = tmp_dir+"/"+code+"_input.conllu"
+    #path_predicted_annot  = './src/annotation/'+code+'_input.predicted.conllu'
+    path_predicted_conllu = tmp_dir+"/"+code+"_input.predicted.conllu"
+    path_final_conllu     = tmp_dir+"/"+code+"_parsed.conllu"
+    #model = '../Portparser.v2-latinpipe-core/model.weights.h5'
+    model = hf_hub_download(repo_id="lucelene/Portparser.v2-latinpipe-core",
+                            filename="model.weights.h5",
+                            repo_type="model")
+    model_op = hf_hub_download(repo_id="lucelene/Portparser.v2-latinpipe-core",
+                               filename="options.json",
+                               repo_type="model")
+    model_mks = hf_hub_download(repo_id="lucelene/Portparser.v2-latinpipe-core",
+                               filename="mappings.pkl",
+                               repo_type="model")
+    print("links", model, model_op)
+
+#    with st.spinner(f'Tok {path_text} into {path_empty_conllu}'): 
+    with st.spinner('Generating CoNLL-U...'): 
+        #time.sleep(1)
+        try:
+            outcome = make_conllu(path_text, path_empty_conllu)
+            #st.write("Tok executou!")
+            #time.sleep(10)
+        except Exception as e:
+            st.write("Tok: "+e)
+            time.sleep(10)
+#    with st.spinner(f'{outcome} - Pred {path_empty_conllu} with {model} into {path_predicted_conllu}'): 
+    with st.spinner('Predicting annotation...'): 
+        #time.sleep(1)
+        try:
+            outcome = make_pred(path_empty_conllu, tmp_dir, model)
+            #st.write("Pred executou!")
+            #time.sleep(10)
+        except Exception as e:
+            st.write("Pred: "+e)
+            time.sleep(10)
+        #infile = open(path_predicted_conllu, "r")
+        #empFile = infile.read()
+        #infile.close()
+    #with st.spinner(path_predicted_conllu+"\n"+empFile):
+        #time.sleep(10)
+#    with st.spinner(f'{outcome} - Post {path_predicted_conllu} into {path_final_conllu}'): 
+    with st.spinner('Postprocessing...'): 
+        #time.sleep(1)
+        try:
+            outcome = make_postproc(path_predicted_conllu, path_final_conllu)
+            #st.write("Postp executou!")
+            #time.sleep(10)
+        except Exception as e:
+            st.write("Postp: "+e)
+            time.sleep(10)
+#    with st.spinner(f'{outcome} - Done at {path_final_conllu}'):
+    with st.spinner('Parsed!'):
+        #infile = open(path_final_conllu, "r")
+        #empFile = infile.read()
+        #infile.close()
+        time.sleep(1)
+    return path_final_conllu
+
+#-----Main Stuff-----
+print("Running the HF server...")
+print(f"Python version: {sys.version_info.major}.{sys.version_info.minor}")
+tmp_dir = mkdtemp()
+#print(tmp_dir)
+code = f'{datetime.datetime.now().strftime("%d%m%Y_%H%M%S%f")+"_"+str(random.randint(0, 9))}'
+#print(code)
+work_dir = './temp/'
+os.chdir('.')
+path_text = f'{tmp_dir}/{code}_input.txt'
+path_final_conllu = f'{work_dir}parsed.conllu' # default to display
+area=0
+with open(path_final_conllu, 'r', encoding='utf-8') as f:content = f.read().split('\n')
+
+#-----Interface-----
+with open('./src/arborator-draft/arborator-draft.css','rb') as f: arborator_css = f.read().decode()
+with open('./src/style.css') as f: css = f.read()
+
+st.set_page_config(page_title='Portparser v.2', layout="wide")
+st.markdown(f'<style>{css}</style>', unsafe_allow_html=True)
+
+# Grid
+rowall = st.columns([2,26,2])
+with rowall[1]:
+    row2 = st.columns([6,4])
+    # Head
+    with row2[0]:
+        st.markdown("<p id='logo-position'><b id='logo-title'><i>Portparser</i></b><b id='logo-version'>v.2</b><br><b id='logo-subtitle'>A parsing model for Brazilian Portuguese</b></p>",unsafe_allow_html=True)
+        st.markdown("<p class='text'> This is Portparser, a parsing model for Brazilian Portuguese that follows the <a href='https://universaldependencies.org/'>Universal Dependencies (UD)</a> framework.\
+        We built our model by using a recently released manually annotated corpus, the Porttinari-base, \
+        and we explored different parsing methods and parameters for training. We also test multiple embedding models and parsing methods. \
+        Portparser is the result of the best combination achieved in our experiments.</p><p class='text'>This model (version 2) is an evolution of the work previously reported \
+        by <a href='https://aclanthology.org/2024.propor-1.41/'>Lopes and Pardo (2024)</a>, and all datasets and full instructions to reproduce our experiments are\
+        freely available at the <a href='https://github.com/LuceleneL/Portparser.v2'>Portparser v2 repository</a>. More details about this work may also be found at \
+        the <a href='https://sites.google.com/icmc.usp.br/poetisa'>POeTiSA project webpage</a>.</p>",unsafe_allow_html=True)
+        with st.expander('To cite Portparser', expanded=False):
+            st.code("""
+            @inproceedings{lopes2024towards,
+                title={Towards Portparser-a highly accurate parsing system for Brazilian Portuguese following the Universal Dependencies framework},
+                author={Lopes, Lucelene and Pardo, Thiago},
+                booktitle={Proceedings of the 16th International Conference on Computational Processing of Portuguese},
+                pages={401--410},
+                year={2024}
+            }""")
+    with row2[1]:
+        st.markdown(img_to_html('./src/img/wordcloud_brasil5.png','width:100%; object-position: center top;'), unsafe_allow_html=True)
+    # Mode to parse sentence 
+    mode1, mode2 = st.tabs(['Single sentence', 'Multiple sentences'])
+    # 'Single sentence'
+    with mode1:
+        rowmode1 = st.columns([1,28,1])
+        with rowmode1[1]:
+            st.write('Write a sentence and run to parse:')
+            with st.form("parser"):
+                text = st.text_input('Text: ')+' '
+                #print("TEXTO",text,"TEXTO")
+                #model_selected = MODEL+'-last4'
+                submit = st.form_submit_button('Run')
+            tab3, tab2, tab1 = st.tabs(["Tree","Table","CoNLL-U"])
+            #with open(path_prediction, 'r', encoding='utf-8') as f: content = f.read()
+            if submit:
+                if not text.strip(): st.text("Can not parse empty text. Write a text above to parse.")                
+                else:
+                    try:
+                        with open(path_text,'w',encoding='utf-8') as f: f.write(text)
+                        if not DEBUG: path_final_conllu = run_pipeline(tmp_dir,code)
+                        area=650
+                        with open(path_final_conllu, 'r', encoding='utf-8') as f:
+                            content = f.read()
+                            tab1.text(content)
+                            content = content.split('\n')
+                            table = pd.DataFrame([line.split('\t') for line in content[4:]])
+                            table.columns = ['ID','FORM','LEMMA','UPOS','XPOS','FEATS','HEAD','DEPREL','DEPS','MISC']
+                            tab2.dataframe(table[:-2], use_container_width=True,hide_index=True)
+                    except Exception as e:
+                            st.text('Não deu certo a predição.'+str(e)+repr(e))
+            with tab3:
+                # Prepare UD tree
+                content_str = '\n'.join(content)
+                components.html(
+                '<style>'+open('./src/arborator-draft/arborator-draft.css','rb').read().decode()+'</style>'+
+                #'<style>{arborator_css}</style>'+
+                """
+                <script language="JavaScript" type="text/javascript" src="https://cdnjs.cloudflare.com/ajax/libs/d3/4.10.0/d3.js"></script>
+                <script src="https://code.jquery.com/jquery-3.2.1.min.js" integrity="sha256-hwg4gsxgFZhOsEEamdOYGBf13FyQuiTwlAQgxVSNgt4=" crossorigin="anonymous"></script>
+                """+
+                '<script>'+open('./src/arborator-draft/arborator-draft.js','rb').read().decode()+'</script>'+
+                f'<conll>{content_str}</conll>'+
+                '<script>new ArboratorDraft();</script>',height=area)
+
+    # 'Multiple sentences'
+    with mode2:
+        rowmode2 = st.columns([1,13,1,14,1])
+        predictions = False
+        with rowmode2[3]:
+            explanation  = 'Upload a text file in order to parse multiple sentences. The file must be in a txt format with one sentence per line. \
+                In case you have multiple sentences altogether, first select the option "Segment text for me" below, and we split it in lines for you.'
+            option1, option2 = 'Text is ready (one sentence per line)','Segment text for me'
+            split_option = st.radio(explanation,[option1,option2])
+        with rowmode2[1]:
+            with st.form("uploadfile_parser"):
+                uploaded_file = st.file_uploader("Choose a file")
+                submit = st.form_submit_button('Run')
+            if submit:
+                if uploaded_file is not None:
+                    # Segment text first 
+                    if split_option==option2:
+                        path_raw_text = path_text[:-4]+'_raw.txt'
+                        with open(path_raw_text, 'w') as f: f.write(uploaded_file.read().decode('utf-8'))
+                        outcome = make_sentences(path_raw_text, path_text)
+                    # Do not segment text first    
+                    else:
+                        with open(path_text,'w', encoding="utf-8") as f:f.write(uploaded_file.read().decode('utf-8')+' ')
+                    if not DEBUG: path_final_conllu = run_pipeline(tmp_dir,code)
+                    st.download_button( 
+                        label="Download predictions",
+                        data=open(path_final_conllu, 'r', encoding='utf-8').read(),
+                        file_name='portparser_generated.conllu')
+                    predictions = True
+                else:
+                    st.text('Submit a text file to parse.')
+        if predictions:
+            row1mode2 = st.columns([1,28,1])
+            with row1mode2[1]:
+                tab1mode2, tab2mode2 = st.tabs(["Sentences","CoNLL-U"])
+                tab1mode2.text(open(path_text,"r").read())
+                tab2mode2.text(open(path_final_conllu,"r").read())
+
+    # Foot
+    with st.container():
+        logorow1 = st.columns([7,4,1,4,1,4,7])
+        with logorow1[1]:      
+            st.markdown("<a href='https://www.icmc.usp.br/'>"+img_to_html('./src/img/icmc.png')+"</a>",unsafe_allow_html=True)
+        with logorow1[3]:      
+            st.markdown("<a href='https://c4ai.inova.usp.br/pt/inicio/'>"+img_to_html('./src/img/c4ia.png')+"</a>",unsafe_allow_html=True)
+        with logorow1[5]:
+            st.markdown("<a href='https://sites.google.com/view/nilc-usp/'>"+img_to_html('./src/img/nilc-removebg.png','max-width:80%')+"</a>",unsafe_allow_html=True)
+        logorow2 = st.columns([7,4,1,4,1,5,7])
+        with logorow2[1]:      
+            st.markdown("<a href='https://inova.usp.br/'>"+img_to_html('./src/img/inova_nobackground.png')+"</a>",unsafe_allow_html=True)
+        with logorow2[3]:
+            st.markdown("<a href='https://softex.br/'>" + img_to_html('./src/img/softex_nobackground.png') + "</a>",unsafe_allow_html=True)
+        with logorow2[5]:      
+            st.markdown("<a href='https://www.gov.br/mcti/pt-br'>" + img_to_html('./src/img/mcti_nobackground.png') + "</a>",unsafe_allow_html=True)
+        logorow3 = st.columns([7,4,1,4,1,4,7])
+        with logorow3[3]:      
+            st.markdown("<a href='https://www.motorola.com.br/'>"+img_to_html('./src/img/motorola_nobackground.png', 'max-width:70%; object-position: center bottom')+"</a>",unsafe_allow_html=True)
+        creditrow = st.columns([7,14,7])
+        with creditrow[1]:      
+            st.markdown('<p style="text-align: center;margin-top:10px"> Developed by Lucelene Lopes\
+            <a href="https://github.com/LuceleneL"><svg xmlns="http://www.w3.org/2000/svg" width="20" height="20" fill="currentColor" class="bi bi-github" viewBox="0 0 16 16">\
+            <path d="M8 0C3.58 0 0 3.58 0 8c0 3.54 2.29 6.53 5.47 7.59.4.07.55-.17.55-.38 0-.19-.01-.82-.01-1.49-2.01.37-2.53-.49-2.69-.94-.09-.23-.48-.94-.82-1.13-.28-.15-.68-.52-.01-.53.63-.01 1.08.58 1.23.82.72 1.21 1.87.87 2.33.66.07-.52.28-.87.51-1.07-1.78-.2-3.64-.89-3.64-3.95 0-.87.31-1.59.82-2.15-.08-.2-.36-1.02.08-2.12 0 0 .67-.21 2.2.82.64-.18 1.32-.27 2-.27s1.36.09 2 .27c1.53-1.04 2.2-.82 2.2-.82.44 1.1.16 1.92.08 2.12.51.56.82 1.27.82 2.15 0 3.07-1.87 3.75-3.65 3.95.29.25.54.73.54 1.48 0 1.07-.01 1.93-.01 2.2 0 .21.15.46.55.38A8.01 8.01 0 0 0 16 8c0-4.42-3.58-8-8-8"/>\
+            </svg></i></a><br>Interface by Ana Carolina Rodrigues\
+            <a href="https://github.com/anasampa"><svg xmlns="http://www.w3.org/2000/svg" width="20" height="20" fill="currentColor" class="bi bi-github" viewBox="0 0 16 16">\
+            <path d="M8 0C3.58 0 0 3.58 0 8c0 3.54 2.29 6.53 5.47 7.59.4.07.55-.17.55-.38 0-.19-.01-.82-.01-1.49-2.01.37-2.53-.49-2.69-.94-.09-.23-.48-.94-.82-1.13-.28-.15-.68-.52-.01-.53.63-.01 1.08.58 1.23.82.72 1.21 1.87.87 2.33.66.07-.52.28-.87.51-1.07-1.78-.2-3.64-.89-3.64-3.95 0-.87.31-1.59.82-2.15-.08-.2-.36-1.02.08-2.12 0 0 .67-.21 2.2.82.64-.18 1.32-.27 2-.27s1.36.09 2 .27c1.53-1.04 2.2-.82 2.2-.82.44 1.1.16 1.92.08 2.12.51.56.82 1.27.82 2.15 0 3.07-1.87 3.75-3.65 3.95.29.25.54.73.54 1.48 0 1.07-.01 1.93-.01 2.2 0 .21.15.46.55.38A8.01 8.01 0 0 0 16 8c0-4.42-3.58-8-8-8"/>\
+            </svg></i></a></p>',unsafe_allow_html=True)

not_used_Dockerfile

@@ -0,0 +1,21 @@
+FROM python:3.11-slim
+
+WORKDIR /app
+
+RUN apt-get update && apt-get install -y \
+    build-essential \
+    curl \
+    software-properties-common \
+    git \
+    && rm -rf /var/lib/apt/lists/*
+
+COPY requirements.txt ./
+COPY src/ ./src/
+
+RUN pip3 install -r requirements.txt
+
+EXPOSE 8501
+
+HEALTHCHECK CMD curl --fail http://localhost:8501/_stcore/health
+
+ENTRYPOINT ["streamlit", "run", "app.py", "--server.port=8501", "--server.address=0.0.0.0"]

requirements.txt

@@ -0,0 +1,8 @@
+keras
+torch
+--extra-index-url=https://download.pytorch.org/whl/cu118
+transformers
+ufal.chu-liu-edmonds
+streamlit
+pandas
+huggingface_hub

runtime.txt

@@ -0,0 +1 @@
+python-3.11

src/annotation/setP11.sh

@@ -0,0 +1,37 @@
+# Install Python3 and Libraries as a local user. 
+python_config() {
+    export PYTHON_VER="3.11.11" 
+    export PYTHON_VER_SHORT="$(echo ${PYTHON_VER} | cut -d '.' -f1,2)"
+    export PYTHON_REQ="/evalatin2024-latinpipe/requirements.txt"
+    cd ~ 
+    rm -rf ~/python && mkdir -p ~/python 
+    echo "" >> ~/.bashrc 
+    echo "export PATH=~/python/bin:$PATH" >> ~/.bashrc 
+    source ~/.bashrc 
+    wget --quiet --no-check-certificate "https://www.python.org/ftp/python/${PYTHON_VER}/Python-${PYTHON_VER}.tgz" 
+    tar -zxvf ~/Python-${PYTHON_VER}.tgz 1>/dev/null 
+    cd ~/Python-${PYTHON_VER}/ 
+    echo "Python ${PYTHON_VER} - Installing in current logged-in user - $(whoami)" 
+    echo "Python ${PYTHON_VER} - Installation in-progress. Please wait..." 
+    ./configure --enable-optimizations --prefix=$HOME/python > /dev/null 2>&1; 
+    echo "Python ${PYTHON_VER} - ETA: upto 5mins. Please wait..." 
+    make altinstall > /dev/null 2>&1; 
+    ln -s ~/python/bin/python${PYTHON_VER_SHORT} ~/python/bin/python3 
+    ln -s ~/python/bin/pip${PYTHON_VER_SHORT} ~/python/bin/pip3 
+     
+
+    # Install PIP3
+    wget --quiet --no-check-certificate https://bootstrap.pypa.io/get-pip.py -O - | python3 - --prefix=$HOME/python
+    source ~/.bashrc
+    ~/python/bin/pip3 install --upgrade pip 
+    ~/python/bin/pip3 install --upgrade --no-cache-dir -r ${PYTHON_REQ} --use-pep517 
+    cd ~ && rm -rf ~/Python-${PYTHON_VER}*
+
+
+    ~/python/bin/python3 --version 
+    ~/python/bin/pip3 --version 
+    echo "Python ${PYTHON_VER} - Setup Completed!" 
+}
+
+# Function Call
+python_config

src/arborator-draft/ArboratorDraft.js

@@ -0,0 +1 @@
+new ArboratorDraft();

src/arborator-draft/FileSaver.min.js

@@ -0,0 +1,3 @@
+(function(a,b){if("function"==typeof define&&define.amd)define([],b);else if("undefined"!=typeof exports)b();else{b(),a.FileSaver={exports:{}}.exports}})(this,function(){"use strict";function b(a,b){return"undefined"==typeof b?b={autoBom:!1}:"object"!=typeof b&&(console.warn("Deprecated: Expected third argument to be a object"),b={autoBom:!b}),b.autoBom&&/^\s*(?:text\/\S*|application\/xml|\S*\/\S*\+xml)\s*;.*charset\s*=\s*utf-8/i.test(a.type)?new Blob(["\uFEFF",a],{type:a.type}):a}function c(a,b,c){var d=new XMLHttpRequest;d.open("GET",a),d.responseType="blob",d.onload=function(){g(d.response,b,c)},d.onerror=function(){console.error("could not download file")},d.send()}function d(a){var b=new XMLHttpRequest;b.open("HEAD",a,!1);try{b.send()}catch(a){}return 200<=b.status&&299>=b.status}function e(a){try{a.dispatchEvent(new MouseEvent("click"))}catch(c){var b=document.createEvent("MouseEvents");b.initMouseEvent("click",!0,!0,window,0,0,0,80,20,!1,!1,!1,!1,0,null),a.dispatchEvent(b)}}var f="object"==typeof window&&window.window===window?window:"object"==typeof self&&self.self===self?self:"object"==typeof global&&global.global===global?global:void 0,a=/Macintosh/.test(navigator.userAgent)&&/AppleWebKit/.test(navigator.userAgent)&&!/Safari/.test(navigator.userAgent),g=f.saveAs||("object"!=typeof window||window!==f?function(){}:"download"in HTMLAnchorElement.prototype&&!a?function(b,g,h){var i=f.URL||f.webkitURL,j=document.createElement("a");g=g||b.name||"download",j.download=g,j.rel="noopener","string"==typeof b?(j.href=b,j.origin===location.origin?e(j):d(j.href)?c(b,g,h):e(j,j.target="_blank")):(j.href=i.createObjectURL(b),setTimeout(function(){i.revokeObjectURL(j.href)},4E4),setTimeout(function(){e(j)},0))}:"msSaveOrOpenBlob"in navigator?function(f,g,h){if(g=g||f.name||"download","string"!=typeof f)navigator.msSaveOrOpenBlob(b(f,h),g);else if(d(f))c(f,g,h);else{var i=document.createElement("a");i.href=f,i.target="_blank",setTimeout(function(){e(i)})}}:function(b,d,e,g){if(g=g||open("","_blank"),g&&(g.document.title=g.document.body.innerText="downloading..."),"string"==typeof b)return c(b,d,e);var h="application/octet-stream"===b.type,i=/constructor/i.test(f.HTMLElement)||f.safari,j=/CriOS\/[\d]+/.test(navigator.userAgent);if((j||h&&i||a)&&"undefined"!=typeof FileReader){var k=new FileReader;k.onloadend=function(){var a=k.result;a=j?a:a.replace(/^data:[^;]*;/,"data:attachment/file;"),g?g.location.href=a:location=a,g=null},k.readAsDataURL(b)}else{var l=f.URL||f.webkitURL,m=l.createObjectURL(b);g?g.location=m:location.href=m,g=null,setTimeout(function(){l.revokeObjectURL(m)},4E4)}});f.saveAs=g.saveAs=g,"undefined"!=typeof module&&(module.exports=g)});
+
+//# sourceMappingURL=FileSaver.min.js.map 

src/arborator-draft/arborator-draft.css

@@ -0,0 +1,250 @@
+.token {
+	font: 18px DejaVu Sans;
+	fill: black;
+	font-family:sans-serif;
+	--wordDistance:33;
+	text-align: center;
+} 
+.FORM {
+	/* 	font: 18px DejaVu Sans; */
+	/* 	fill: black; */
+	/* 	font-family:sans-serif; */
+		--wordDistance:55;
+		fill:black;
+		text-align: center;
+	} 
+
+.LEMMA {
+		font: 15px DejaVu Sans;
+		fill: black;
+		font-family:sans-serif;
+		text-align: center;
+		font-style: italic;
+		--wordDistance:22;
+	} 
+
+.MISC-Gloss {
+		font: 15px DejaVu Sans;
+		fill: rgb(124, 96, 86);
+		font-family:sans-serif;
+		text-align: center;
+		font-style: italic;
+		--wordDistance:11;
+	} 
+.UPOS {
+		font: 11px DejaVu Sans;
+		fill: rgb(80, 29, 125);
+		text-align: center;
+		--wordDistance:22;
+	} 
+
+
+
+.DEPREL {
+		font: 12px Arial;
+		fill: #501d7d;
+		font-style: oblique;
+		font-family:sans-serif;
+		--funcCurveDist:3; /* distance between the function name and the curves highest point */
+	} 
+
+
+.lemma {
+	font: 15px DejaVu Sans;
+	fill: black;
+	font-family:sans-serif;
+	text-align: center;
+	font-style: italic;
+} 
+
+
+.MISC-Gloss {
+	font: 15px DejaVu Sans;
+	fill: rgb(124, 96, 86);
+	font-family:sans-serif;
+	text-align: center;
+	font-style: italic;
+	--wordDistance:11;
+} 
+
+.xdeprel {
+	font: 12px Arial;
+	font-style: oblique;
+	fill: #21ba45;
+	--funcCurveDist:3; /* distance between the function name and the curves highest point */
+
+} 
+
+.xdep {
+	stroke: #21ba45;
+	fill: none;
+	--startOffset: 8;
+	--tokDepDist: 15; /* distance between tokens and depdendency relation */
+	--depMinHeight: 15; /* minimum height for dependency */
+	--wordDistanceFactor: -1; /* distant words get higher curves. this factor fixes how much higher */
+} 
+
+.arrowhead {
+	fill: white;
+	stroke: black;
+	stroke-width: .8;
+}
+
+.arrowheadxdep {
+	fill: white;
+	stroke: #21ba45;
+	stroke-width: .8;
+}
+
+.curve {
+	stroke: black;
+	stroke-width: 1;
+	fill: none;
+	--startOffset: 8;
+	--tokDepDist: 15; /* distance between tokens and depdendency relation */
+	--depMinHeight: 15; /* minimum height for dependency */
+	--wordDistanceFactor: -1; /* distant words get higher curves. this factor fixes how much higher */
+}
+
+.conll {
+	display:none; /*toggles to inline*/
+	unicode-bidi: embed;
+	font-family: monospace;
+	white-space: pre;
+	margin-bottom: 0.6em;
+	border-bottom: 1px solid #aaa;
+	padding: 0.5em 0 0.17em 0;
+	tab-size: 12;
+	background-color: #fff ;
+	box-shadow: 0 2px 5px 0 rgba(0, 0, 0, 0.26);
+}
+
+.sentencebox {
+	margin-bottom: 0.6em;
+	border-bottom: 1px solid lightgrey;
+	padding: 0.5em 0 0.17em 0;
+	margin-top: 1em;
+}
+
+/* Button */
+.button {
+	display: inline-block;
+	position: relative;
+	width: 120px;
+	height: 32px;
+	line-height: 32px;
+	border-radius: 2px;
+	font-size: 0.9em;
+	background-color: #fff;
+	color: #646464;
+	cursor:pointer;
+  }
+  
+  .button > paper-ripple {
+	border-radius: 0px;
+	overflow: hidden;
+  }
+
+
+.button.raised {
+	transition: box-shadow 0.2s cubic-bezier(0.4, 0, 0.2, 1);
+	transition-delay: 0.2s;
+	box-shadow: 0 2px 5px 0 rgba(0, 0, 0, 0.26);
+  }
+
+  .button.raised:active {
+	box-shadow: 0 8px 17px 0 rgba(0, 0, 0, 0.2);
+	transition-delay: 0s;
+  }
+
+  .center {
+	text-align: center;
+  }
+
+
+	.svgbox {
+		overflow-x: auto;
+	}
+
+
+
+
+nav {
+	display: inline-block;
+	vertical-align: middle;
+}
+
+
+
+nav ul {
+    font-size: 0;
+    list-style: none;
+    margin: 0;
+    padding: 0;
+    /* text-align: center; */
+	width: 100%;
+	
+}
+nav li {
+    display: inline-block;
+    margin: 0;
+    padding: 0;
+    position: relative;
+	/* min-width: 33%; */
+	
+}
+nav a {
+  
+	display: block;
+	font: normal 16px sans-serif;
+    padding-right: 9px;
+    text-decoration: none;
+    -webkit-transition: all .25s ease;
+       -moz-transition: all .25s ease;
+        -ms-transition: all .25s ease;
+         -o-transition: all .25s ease;
+			transition: all .25s ease;
+		
+}
+
+nav li ul li:hover a {
+    background: #f5f5f5;
+}
+nav li ul {
+	
+	background: #fff;
+    left: 0;
+    opacity: 0;
+    position: absolute;
+    top: 10px;
+    visibility: hidden;
+    z-index: 1;
+    -webkit-transition: all .25s ease;
+       -moz-transition: all .25s ease;
+        -ms-transition: all .25s ease;
+         -o-transition: all .25s ease;
+            transition: all .25s ease;
+}
+nav li:hover ul {
+    opacity: 1;
+    top: 23px;
+	visibility: visible;
+}
+nav li ul li {
+	width: 130px;
+	display: inline-block;
+	border-bottom: 1px solid lightgrey;
+	background: #fff;
+	cursor:pointer;
+	
+}
+nav li ul a {
+	color: #000;
+	font: normal 16px/32px sans-serif
+}
+nav li ul a:hover {
+	color: #501d7d;
+	
+	text-decoration: none;
+}
+

src/arborator-draft/arborator-draft.js

@@ -0,0 +1,691 @@
+(function () {
+
+/*!
+ * arborator script for dependency drawing 
+ * version 2.0
+ * http://arborator.ilpga.fr/
+ *
+ * Copyright 2010-2020, Kim Gerdes & Gaël Guibon
+ *
+ * This program is free software:
+ * Licensed under version 3 of the GNU Affero General Public License (the "License");
+ * you may not use this file except in compliance with the License. 
+ * You may obtain a copy of the License at http://www.gnu.org/licenses/agpl-3.0.html
+ * Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. 
+ * See the License for the specific language governing permissions and limitations under the License. 
+ *
+ */
+
+// global variables:
+fontSize = 0; // computed from css value for .token in arborator-draft.css
+svgDefaultHeight = 350;//500;
+el=10; // type of conll (10, 14, or 4), computed in conllNodesToTree
+trees=[]; // list of tree objects
+uextras=[]; // list of comments. each comment is a hashtable position(=line)->comment 
+conlltrees=[]; // list of conll strings
+sentences=[]; // list of sentence strings
+theshownfeatures=["FORM", "UPOS", "LEMMA", "MISC.Gloss"]; // recomputed in readConll
+shownmetas=['text_en'];
+showAllConllButton = false;
+progressiveLoading = true; // false to make it load all trees at once (may overload the browser)
+reverseMode = false; // set true for right to left conll
+conlls = {	
+	10: 	{"ID": 0, "FORM":1, "LEMMA": 2, "UPOS": 3, "XPOS":4, "FEATS":5, "HEAD":6, "DEPREL":7, "DEPS":8, "MISC":9}, 
+	14: 	{"ID": 0, "FORM":1, "LEMMA": 3, "UPOS": 5, "HEAD":9, "DEPREL":11}, 
+	4: 		{"FORM":0, "LEMMA": 0, "UPOS": 1, "HEAD":2, "DEPREL":3} 
+};
+
+isFirefox = navigator.userAgent.toLowerCase().indexOf('firefox') > -1; // needed for bezier bounding box bug
+svgIdIndex = 0;
+
+// debug:
+log = console.log.bind(console);
+
+arborator = `<svg
+xmlns:dc="http://purl.org/dc/elements/1.1/"
+xmlns:cc="http://creativecommons.org/ns#"
+xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#"
+xmlns:svg="http://www.w3.org/2000/svg"
+xmlns="http://www.w3.org/2000/svg"
+version="1.1"
+viewBox="-4202 0 5704.1939 1840.839"
+style="image-rendering:optimizeQuality;"
+height="13"
+width="27"
+xml:space="preserve">
+<path
+     style="fill:none;stroke:#4a2769;stroke-width:128.73750305;stroke-linecap:butt;stroke-linejoin:miter;stroke-miterlimit:4;"
+     d="m -1890.5398,1002.7933 -1822.5445,615.288 c -261.3344,-190.4146 -424.5469,-433.2903 -424.5469,-661.59345 0,-685.88115 1244.2446,-1296.6446 2780.191,-1296.6446 1534.97478,0 2795.2653,610.76345 2795.2653,1296.6446 0,685.88105 -1252.26757,1244.49535 -2787.2424,1244.49535 -239.9613,0 -490.6091,-19.4301 -718.9123,-43.7176 L -751.94297,618.40481 -882.8496,663.4494" /><path
+     style="fill:none;stroke:#dd137b;stroke-width:128.73750305;stroke-miterlimit:4;"
+     d="M -864.53567,745.22843 C -964.68477,501.46149 -1354.4152,-183.90675 -1694.5756,-3.2652517 -2014.6556,165.68318 -2049.9732,423.17981 -1871.2632,1084.3717 c 67.0564,232.3776 161.3346,398.0135 238.7197,540.6756" /><path
+     style="fill:none;stroke:#4a2769;stroke-width:128.73750305;stroke-linecap:butt;stroke-linejoin:miter;stroke-miterlimit:4;"
+     d="M -2068.3297,2157.2657 -751.94297,618.40481"
+      />
+</svg>`;
+
+const defaultcss = ` 
+	.FORM {  font: 18px DejaVu Sans;  fill: black;  font-family:sans-serif;   text-align: center; }
+	.LEMMA {  font: 15px DejaVu Sans;  fill: black;  font-family:sans-serif;  text-align: center;  font-style: italic; }   
+	.UPOS {  font: 11px DejaVu Sans; fill: rgb(80, 29, 125);  text-align: center; }  
+	.MISC-Gloss {font: 15px DejaVu Sans; fill: rgb(124, 96, 86); font-family:sans-serif; text-align: center; font-style: italic;}  
+	.DEPREL {  font: 12px Arial;  fill: #1d2ec1;  font-style: oblique;  font-family:sans-serif;  }   
+	.arrowhead {  fill: white;  stroke: black;  stroke-width:.8;} 
+	.arrowheadxdep { fill: white;stroke: #21ba45;stroke-width:.8;} 
+	.xdep {  stroke: #21ba45;  stroke-width: 1;  fill: none;}  
+	.curve {  stroke: black;  stroke-width: 1;  fill: none;}  
+	.xdeprel { font: 12px Arial;	font-style: oblique; fill: #21ba45; } 
+	.svgbox {   overflow-x: auto;  }`;
+
+
+// public initialisation function
+this.ArboratorDraft = function(shownfeatures=false, reverse = false, visuMode = 0) {
+	// main function called from html file
+	if (shownfeatures) {theshownfeatures = shownfeatures;}
+	if(reverse) reverseMode = true;
+	if(visuMode==0){
+		$( ".expander" ).click(function(){
+			$(this).next('conll').toggle();});    
+		readConll();
+	} 
+	else{
+		// log('[ArboratorDraft] visumode');
+		trees=[]; 
+		uextras=[]; 
+		conlltrees=[]; 
+		sentences=[]; 
+		$('conll').hide();
+		refresh( $('#conllarea').text() );
+	}
+}
+
+// public function
+ArboratorDraft.prototype.emptyThenRefresh = function(content, reverse = false, toggle = false) {	
+	if(reverse) reverseMode = true; // to set reverse or not
+	if(toggle) reverseMode = !reverseMode; // to toggle reverse
+	empty().done( refresh( content ) );
+}
+
+function refresh(content) {
+	$('#svgwell').html('');
+	$('#svgwell').append( $("<conll></conll>").attr('id', 'transformhere').text( content ) );
+	var conll = d3.selectAll('#transformhere')['_groups'][0][0];
+	drawConll(conll);
+	return;
+}
+
+function empty() {
+	var def = new jQuery.Deferred();
+	clearTimeout(readInsideConllTimeout);
+	treelines = [];
+	$('#svgwell').html('');
+	def.resolve();
+	return def.promise();
+}
+
+function progressiveReadConll() {
+	// draw each conll tags progressively (only conll tags)
+	var conllLoop = d3.selectAll('conll')['_groups'][0]; // need to go out d3js to load it progressively
+	var i = 0;
+	function waitBetweenElements(range) {
+		readConllTimeout = setTimeout(function () {
+			drawConll(conllLoop[i]);
+			i++;
+			if (i < range) {
+				waitBetweenElements(range);
+			}
+		}, 10)
+	}
+	waitBetweenElements(conllLoop.length);
+}
+
+function progressiveReadInsideConll(trees, pnode) {
+	// draw each tree INSIDE a conll progressively
+	var iWait = 0;
+	function waitBetweenElements(range) {
+		readInsideConllTimeout = setTimeout(function () {
+			pushAndDrawSVG(trees[iWait], pnode);
+			iWait++;
+			if (iWait < range) waitBetweenElements(range);
+		}, 10)
+	}
+	waitBetweenElements(trees.length);
+}
+
+function pushAndDrawSVG(element, pnode) {
+	conlltrees.push(element);
+	var data=conllNodesToTree(element);
+	trees.push(data.tree);
+	uextras.push(data.uextra)
+	sentences.push(data.sentence)
+
+	var toggle = true;
+	var divsvgbox = pnode.insert('div').attr("class", 'svgbox');
+	var divsentbox = divsvgbox.insert('div').attr("class", 'sentencebox')
+	divsentbox.insert('nav').html(`
+		<ul>
+			<li>
+				<a>`+arborator+`</a>
+				<ul>
+					<li id="showconll`+svgIdIndex+`"><a>🗏 Show CoNLL</a></li>
+					<li id="pnglink`+svgIdIndex+`"><a>🖼 Save PNG</a></li>
+					<li id="svglink`+svgIdIndex+`"><a>🖍️ Save SVG</a></li>
+					<li ><a href="https://github.com/Arborator/arborator-draft" target="_blank">🛈 Info Arborator</a></li>
+				</ul>
+			</li>
+		</ul>`);
+	$("#pnglink"+svgIdIndex).click(function(){savePng(this.id);});
+	$("#svglink"+svgIdIndex).click(function(){saveSvg(this.id);});
+	divsentbox.insert('span').html(data.sentence);
+	for (shom of shownmetas) {
+		if (shom in data.metas)	
+			if (shom.startsWith("text")) divsentbox.insert('div').html("<i>‘"+data.metas[shom]+"’</i>")
+			else divsentbox.insert('div').html(data.metas[shom])
+	}
+	var thisconll = divsentbox.insert('conll').html(element).attr('class', 'conll');
+	$("#showconll"+svgIdIndex).click(function(){
+		toggle = !toggle;
+		thisconll.style("display", toggle ? "none" : "block");
+		$(this.childNodes[0]).html(toggle ? "🗏 Show CoNLL": "🗏 Hide CoNLL") //
+		});
+	thisconll.style("display", toggle ? "none" : "block");
+	draw(divsvgbox, data.tree);
+	svgIdIndex=svgIdIndex +1;
+}
+
+function readConll() {
+	// reads the conll representation of the whole treebank that is in the conll field	
+	trees=[]; // list of tree objects 
+	uextras=[]; // list of comments. each comment is a hashtable position(=line)->comment 
+	conlltrees=[]; // list of conll strings, one string per tree
+	sentences=[]; // list of sentence strings, one string per tree
+	$('conll').hide(); // to hide the huge conll data
+	if(progressiveLoading) {
+		progressiveReadConll(); // progressive draw
+	}
+	else {
+		d3.selectAll('conll').each(function(d){ drawConll(this); }); // all at once
+	}
+}
+
+function drawConll(conllElement) { // for each <conll> section:
+	var pnode = d3.select(conllElement.parentNode);
+	if(showAllConllButton){
+		var conll = d3.select(conllElement).attr("class", 'conll'); 
+		conll.html(conll.html().trim())
+		var toggle = false;
+		var showHideConll = pnode.insert('div').html('<div class="center" fit>VIEW CONLL</div> <paper-ripple fit></paper-ripple>').attr("class", 'button raised');	
+		var conllContent = conll.html().trim();
+		conll.remove(); // remove the old conll because its place wasn't good
+		conll = pnode.insert('conll').html(conllContent).attr('class', 'conll'); //re insert to bind the content
+		showHideConll.on("click", ()=>{
+			conll.style("display", toggle ? "none" : "block");
+			showHideConll.html(toggle ? '<div class="center" fit>VIEW CONLL</div> <paper-ripple fit></paper-ripple>': '<div class="center" fit>HIDE CONLL</div> <paper-ripple fit></paper-ripple>');
+			toggle = !toggle;
+		});
+	}
+	treelines = conllElement.textContent.trim().split(/\n\s*\n\s*\n*/);	
+	if(progressiveLoading) {
+		progressiveReadInsideConll(treelines, pnode);
+	}
+	else {
+		for (let singleConll of treelines) { // for each conll tree at once, can block the browser
+			pushAndDrawSVG(singleConll, pnode);
+		}
+	}
+}
+
+function conllNodesToTree(treeline) {
+	var nodes = treeline.split('\n');
+	if(reverseMode) nodes.reverse();
+	var tree={};
+	var META={}; // sentence features before the actual conll
+	var addLines={}; // node position to additional line
+	var uextra={}; // todo: check this for reconstruction of conllu
+	var lastid=0;
+	var skipuntil=0;
+	var words=[]
+	nodes.forEach(function (nodeline, id) 
+	{ // for each conll line:
+		nodeline=nodeline.trim().replace(/^[\s\uFEFF\xA0]+|[\s\uFEFF\xA0]+$/g, '');
+		if (nodeline.charAt(0) == "#") // META
+		{
+			var [a,v] = nodeline.substring(1).trim().split("=")
+			if (v!=null) var [a,v]=[a.trim(),v.trim()]
+			META[a]=v
+			return true;
+		}
+		var elements = nodeline.split('\t');
+		el=elements.length;
+		if(el > 1)
+		{
+			if (!(el in conlls) && el>10) el=10;
+			if (el > 4) id=elements[conlls[el]["ID"]];
+			else if (elements[conlls[el]['FORM']] != "_") id++;
+			var form=elements[conlls[el]['FORM']];
+			var tokids=id.split("-")
+			if (tokids.length == 1) { // simple token
+				tree[id]={};
+				tree[id]["ID"]=id;
+				tree[id]['FORM']=form;
+				tree[id]["LEMMA"]=elements[conlls[el]["LEMMA"]];
+				tree[id]['UPOS']=elements[conlls[el]['UPOS']];
+				tree[id]['HEAD']=parseInt(elements[conlls[el]['HEAD']]);
+				tree[id]['DEPREL']=elements[conlls[el]['DEPREL']];
+				tree[id]["FEATS"]={};
+				tree[id]["DEPS"]={};	
+				tree[id]["MISC"]={};
+				if (id>skipuntil) words.push(form);
+				if (el==10) {
+					tree[id]["XPOS"] =elements[conlls[el]["XPOS"]];
+					tree[id]["FEATS"] =	analyzeFeaturestring(elements[conlls[el]["FEATS"]], '=', '|');
+					tree[id]["DEPS"] =	analyzeFeaturestring(elements[conlls[el]["DEPS"]], ':', '|');
+					tree[id]["MISC"] =	analyzeFeaturestring(elements[conlls[el]["MISC"]], '=', '|');
+				}
+			}
+			else if (tokids.length == 2){ // n-m type multi-word encoding
+				skipuntil = parseInt(tokids[1])
+				words.push(elements[conlls[el]['FORM']]);
+				if (!(lastid in uextra)) uextra[lastid]=[];
+				uextra[lastid].push(nodeline);
+			}
+			else {
+				if (!(lastid in uextra)) uextra[lastid]=[];
+				uextra[lastid].push(nodeline);
+			}
+		}//end if el >1
+		else  { // bizarre line
+			if (!(lastid in addLines)) addLines[lastid]=[];
+			addLines[lastid].push(nodeline);
+			if (tokids.length == 2){ // n-m type multi-word encoding
+				skipuntil = parseInt(tokids[1])
+				words.push(elements[conlls[el]['FORM']]);
+			}
+			tree[id]['HEAD']=parseInt(elements[conlls[el]['HEAD']]); // todo: think about this
+			tree[id]['DEPREL']=elements[conlls[el]['DEPREL']];
+		}
+		lastid=id;
+	});	
+	// now always correcting the META.text feature. if this is not desired, uncomment this line:
+	// if {tree:tree, uextra:uextra, sentence:META['text']};
+	// got to contstruct the sentence
+	var sentence = [];
+	words.forEach(function (word, i) {
+		sentence.push(word);
+		if (!("SpaceAfter" in tree[i+1]["MISC"] && tree[i+1]["MISC"]["SpaceAfter"]=="No" )) sentence.push(" ");
+		// if(!reverseMode){
+		// 	if (i+1 in tree && !(("NoSpaceAfter" in tree[i+1]) && tree[i+1]["NoSpaceAfter"]==false)) sentence.push(" ");
+		// } else{ sentence.push(word); }
+	});
+	META['text'] = sentence.join('')
+	if ('shownfeatures' in META) {
+		theshownfeatures = META['shownfeatures'].split(/,\s*/);
+		console.log(theshownfeatures);
+	}
+	return {tree:tree, uextra:uextra, sentence:META['text'], metas:META};
+}
+
+function analyzeFeaturestring(featstr, eq, spl) {
+	o={}
+	if (featstr.indexOf(eq) > -1){
+		featstr.split(spl).forEach(function (f) // for each feature:
+		{
+			var fs=f.split(eq)
+			if (fs.length >=2) {// if it's not just _
+				o[fs[0]]=fs.slice(1).join(eq);
+			}
+		});
+	}
+	return o;
+}
+
+function getSVGPath(startPoint,endPoint,computedStyle,ymove) {
+	// startPoint and endPoint are objects for the corresponding nodes
+	var tokDepDist = parseInt(computedStyle.getPropertyValue('--tokDepDist'));
+	var depMinHeight = parseInt(computedStyle.getPropertyValue('--depMinHeight'));
+	var wordDistanceFactor = parseInt(computedStyle.getPropertyValue('--wordDistanceFactor'));
+	if(reverseMode) wordDistanceFactor = -Math.abs(wordDistanceFactor);
+	var startOffset = parseInt(computedStyle.getPropertyValue('--startOffset'));
+	if(reverseMode) startOffset = -Math.abs(startOffset);
+	var startOff=(startPoint['ID']-endPoint['ID']>0)?-startOffset:startOffset
+	var x1 = startPoint['x']+startPoint['w']/2+startOff;
+	var x2 = endPoint['x']+endPoint['w']/2;
+	var y1 = svgDefaultHeight-fontSize*2;
+	var y2 = svgDefaultHeight-fontSize*2;
+	var x1x2=Math.abs(x1-x2)/2;		
+	var yy = Math.max(y1-x1x2-wordDistanceFactor*Math.abs(endPoint['ID']-startPoint['ID']),-tokDepDist);
+	var yy = Math.min(yy,y1)-depMinHeight;
+	var cstr="M"+x1+","+y1+" C"+x1+","+yy+" "+x2+","+yy+" "+x2+","+(y2-2+ymove); // -2 so that the arrow is really pointed
+	//(x0,y0) is start point; (x1,y1),(x2,y2) is control points; (x3,y3) is end point.
+	return {cstr:cstr,  x0:x1,y0:y1,  x1:x1,y1:yy,  x2:x2,y2:yy,x3:x2,y3:(y2-2)};
+}
+
+
+function arrowhead(x,y) {
+	// gives path for arrowhead x,y startpoint (end of arrow)
+	var size = 5;
+	var startpoint = x+","+y; // to move the arrowhead lower: (y+size/3);
+	var lefttop = "0,0" +(-size/2)+","+(-size*1.5)+" "+(-size/2)+","+(-size*1.5);
+	var righttop = (size/2)+"," +(size/2)+" "+(size/2)+"," +(size/2)+ " "+(size)+",0";
+	var arrowPath = "M"+ startpoint+"c"+lefttop+ "c"+righttop+ "z";
+	return arrowPath;
+}
+
+
+function drawDep(tree, id, govid, label, group, smallestY, curvestyle, relstyle, arrowstyle, rootlabels, ymove) {
+	var x = tree[id]['x'] + tree[id]['w'] / 2;
+	var depLine = group.append("path")
+		.attr("class", curvestyle)
+		.attr("d", function (dd) {
+			if (govid == 0) // sentence root:
+			{
+				var y = svgDefaultHeight - fontSize * 2;
+				return "M" + x + "," + (y - 2 + ymove) + "L" + x + "," + 0;
+			}
+			else // normal link:
+			{
+				pathInfo = getSVGPath(tree[govid], tree[id], getComputedStyle(this), ymove);
+				return pathInfo.cstr;
+			}
+		});
+	group.append("path")
+		.attr("class", arrowstyle)
+		.attr("d", function (dd) {
+			return arrowhead(x, svgDefaultHeight - fontSize * 2 +ymove);
+		});
+	var depLineBbox = depLine.node().getBBox();
+	if (govid == 0) // root link:
+	{
+		rootlabels.push(
+			group.append('text')
+				.attr("class", relstyle)
+				.text(label)
+				.attr("x", x+2)
+				.attr("y", 0)
+			);
+	}
+	else // normal link:
+	{
+		group.append('text')
+			.attr("class", relstyle)
+			.text(label)
+			.attr("x", function (d) {
+				relFontSize = parseInt(getComputedStyle(this).fontSize, 10);
+				var w = this.getComputedTextLength(); //<-- length of this node
+				return depLineBbox.x + depLineBbox.width / 2 - w / 2;
+			})
+			.attr("y", function (d) {
+				funcCurveDist = parseInt(getComputedStyle(this).getPropertyValue('--funcCurveDist'));
+				if (isFirefox) {
+					// firefox needs: stackoverflow.com/questions/24809978/calculating-the-bounding-box-of-cubic-bezier-curve
+					const { x0, y0, x1, y1, x2, y2, x3, y3 } = pathInfo; // firefox
+					y = bezierMinMax(x0, y0, x1, y1, x2, y2, x3, y3).min.y - funcCurveDist ;
+					return y; // firefox
+				}
+				else {
+					// standard Chrome etc
+					y = depLineBbox.y - funcCurveDist;
+					return y;
+				}
+			});
+		// if not root, check how high we got:
+		var smallY = y - relFontSize;
+		smallestY = smallY < smallestY ? smallY : smallestY;
+	}
+	return 3//smallestY
+}
+
+
+function draw(div, tree) {
+	// draws json tree on svg in div
+	var runningWidth = 0;
+	var smallestY = svgDefaultHeight;
+	var treeArray = $.map(tree, function(value) {return [value];});
+	var svg = div.append("svg:svg")
+	.attr("width",  1000)
+	.attr("height", svgDefaultHeight);
+	var group = svg.append("g");
+	var rootlabels = [];
+	// write tokens:
+	if(reverseMode) treeArray.reverse();
+	var eachTexts = group.selectAll("text")
+		.data(treeArray)
+		.enter();
+	eachTexts.append('text') // FORM
+		.attr("class", "FORM")
+		.text(function(d){ return d["FORM"]; } )
+		.attr("ID",function(d) { return d["ID"]; } )
+		.attr("x", function(d) {
+			var w = this.getComputedTextLength();
+			wordDistance = parseInt(getComputedStyle(this).getPropertyValue('--wordDistance'));
+			var x = runningWidth; //<-- previous length to return
+			runningWidth += w + wordDistance; //<-- total
+			tree[d["ID"]]["x"]=x;
+			tree[d["ID"]]["w"]=w;
+			fontSize = parseInt(getComputedStyle(this).fontSize, 10);
+			return x;
+		})
+		.attr("y", svgDefaultHeight-fontSize);	
+	svg.attr("width", runningWidth); // adapt svg width
+	// draw dependency links:
+	group.selectAll("text").each(function(d) { // for each token:
+		var id = d3.select(this).attr("ID");
+		var govid = tree[id]["HEAD"];
+		var label = tree[id]["DEPREL"];
+		smallestY = drawDep(tree, id, govid, label, group, smallestY, "curve", "DEPREL","arrowhead", rootlabels, 0); // standard governor relation
+		for (var headid in tree[id]["DEPS"]) { // for each governor of extended dependency
+			smallestY = drawDep(tree, id, headid, tree[id]["DEPS"][headid], group, smallestY, "xdep", "xdeprel", "arrowheadxdep", rootlabels, -fontSize/2);
+		}
+	});	
+	var lastheight = 0;
+	var h=0;
+	
+	for (var fea of theshownfeatures) {
+		if (fea=="FORM") continue;
+		somet=false;		
+		eachTexts.append('text')
+			.attr("class", fea.replace('.', '-'))
+			.text(function(d) {var t=fea.split('.').reduce((value,el) => value[el], d); if(!somet && t) somet=true; return t; } )
+			.attr("ID",function(d) {return d["ID"];})
+			.attr("x", function(d) {
+				// var lemmaLength = this.getComputedTextLength();
+				// var w = tree[d["ID"]]["w"];
+				wordDistance = parseInt(getComputedStyle(this).getPropertyValue('--wordDistance'));
+				h = parseInt(getComputedStyle(this).fontSize, 20);
+				return tree[d["ID"]]["x"]; //<-- previous length to return
+			})
+			.attr("y", svgDefaultHeight-fontSize+lastheight+h)
+			.append('title').text(function(d) {return  fea.split('.').slice(-1)[0]+": "+fea.split('.').reduce((value,el) => value[el], d); });
+			if (somet) lastheight+=h; // found at least once the feature
+	}
+	// final adjustments:
+	for (rl of rootlabels) rl.attr("y",smallestY+fontSize)
+	group.attr("transform", "translate(" + 0 + "," + (-smallestY) + ")");
+	svg.attr("height", svgDefaultHeight-smallestY+lastheight+fontSize); // adapt svg height
+	svg.attr("id", "svg"+svgIdIndex);
+	svg.attr("version", '1.1'); // to prepare ddl of svg
+	svg.attr("xmlns", "http://www.w3.org/2000/svg"); // to prepare ddl of svg
+}
+
+
+function bezierMinMax(x0, y0, x1, y1, x2, y2, x3, y3) {
+	//(x0,y0) is start point; (x1,y1),(x2,y2) is control points; (x3,y3) is end point.
+    var tvalues = [], xvalues = [], yvalues = [], a, b, c, t, t1, t2, b2ac, sqrtb2ac;
+    for (var i = 0; i < 2; ++i) {
+        if (i == 0) {
+            b = 6 * x0 - 12 * x1 + 6 * x2;
+            a = -3 * x0 + 9 * x1 - 9 * x2 + 3 * x3;
+            c = 3 * x1 - 3 * x0;
+		} 
+		else {
+            b = 6 * y0 - 12 * y1 + 6 * y2;
+            a = -3 * y0 + 9 * y1 - 9 * y2 + 3 * y3;
+            c = 3 * y1 - 3 * y0;
+        }
+        if (Math.abs(a) < 1e-12) {
+            if (Math.abs(b) < 1e-12) {
+                continue;
+            }
+            t = -c / b;
+            if (0 < t && t < 1) {
+                tvalues.push(t);
+            }
+            continue;
+        }
+        b2ac = b * b - 4 * c * a;
+        if (b2ac < 0) {
+            continue;
+        }
+        sqrtb2ac = Math.sqrt(b2ac);
+        t1 = (-b + sqrtb2ac) / (2 * a);
+        if (0 < t1 && t1 < 1) {
+            tvalues.push(t1);
+        }
+        t2 = (-b - sqrtb2ac) / (2 * a);
+        if (0 < t2 && t2 < 1) {
+            tvalues.push(t2);
+        }
+    }
+    var j = tvalues.length, mt;
+    while (j--) {
+        t = tvalues[j];
+        mt = 1 - t;
+        xvalues[j] = (mt * mt * mt * x0) + (3 * mt * mt * t * x1) + (3 * mt * t * t * x2) + (t * t * t * x3);
+        yvalues[j] = (mt * mt * mt * y0) + (3 * mt * mt * t * y1) + (3 * mt * t * t * y2) + (t * t * t * y3);
+    }
+    xvalues.push(x0,x3);
+    yvalues.push(y0,y3);
+    return {
+        min: {x: Math.min.apply(0, xvalues), y: Math.min.apply(0, yvalues)},
+        max: {x: Math.max.apply(0, xvalues), y: Math.max.apply(0, yvalues)}
+    };
+}
+
+function svg2Data(svg) {
+	var tempCSS = document.createElement("style");
+	tempCSS.innerHTML = defaultcss;
+	svg.insertBefore(tempCSS, svg.firstChild);
+	// svg.appendChild(tempCSS);
+	return {svg:svg, tempCSS:tempCSS};
+}
+
+function png2Data(svg) {
+	var canvas = document.createElement('canvas');
+	canvas.height = svg.height.baseVal.value*5;
+	canvas.width = svg.width.baseVal.value*5;
+	var tempCSS = document.createElement("style");
+	tempCSS.innerHTML = defaultcss;
+	svg.insertBefore(tempCSS, svg.firstChild);	// === the missing prepend option
+	var data = (new XMLSerializer()).serializeToString(svg);
+	canvg(canvas, data, {'scaleWidth':canvas.width,'canvas.height':canvas.height,'ignoreDimensions':true});
+	return canvas.toDataURL().replace('data:image/png;base64,','');
+}
+
+function savePng(btnId) {
+	var id = btnId.replace("pnglink","");
+	var canvas = document.createElement('canvas');
+	var svg = document.getElementById("svg"+id);
+	var sdat = svg2Data(svg);	
+	canvas.height = svg.height.baseVal.value*5;
+	canvas.width = svg.width.baseVal.value*5;
+	var ctx = canvas.getContext('2d');
+	var data = (new XMLSerializer()).serializeToString(svg);
+	var DOMURL = window.URL || window.webkitURL || window;
+	var img = new Image(); 
+	var svgBlob = new Blob([data], {type: 'image/svg+xml;charset=utf-8'});
+	var url = DOMURL.createObjectURL(svgBlob);
+	
+	img.onload = function () {
+		ctx.drawImage(img, 0, 0, canvas.width, canvas.height);//, 0, 0, ctx.width, ctx.height);
+		DOMURL.revokeObjectURL(url);
+		var imgURI = canvas
+			.toDataURL('image/png')
+			.replace('image/png', 'image/octet-stream');
+		var evt = new MouseEvent('click', {
+			view: window,
+			bubbles: false,
+			cancelable: true
+		});
+		var a = document.createElement('a');
+		a.setAttribute('download', sentences[id].match(/[a-zA-Z\u00c0-\u024f\u1e00-\u1eff]+/g).join(' ').split(" ").slice(0,5).join('_').slice(0,50)+'.png');
+		a.setAttribute('href', imgURI );
+		a.setAttribute('target', '_blank');
+		a.dispatchEvent(evt);
+	};
+	img.src = url;
+	
+	svg.removeChild(sdat.tempCSS);
+}
+
+function saveSvg(btnId) {
+	var id = btnId.replace("svglink","");
+	var svg = document.getElementById("svg"+id);
+	sdat = svg2Data(svg);
+	var svgData = svg.outerHTML;
+	var svgBlob = new Blob([svgData], {type:"image/svg+xml;charset=utf-8"});
+	var svgUrl = URL.createObjectURL(svgBlob);
+	var downloadLink = document.createElement("a");
+	downloadLink.href = svgUrl;
+	downloadLink.download = sentences[id].match(/[a-zA-Z\u00c0-\u024f\u1e00-\u1eff]+/g).join(' ').split(" ").slice(0,5).join('_').slice(0,50)+".svg";
+	document.body.appendChild(downloadLink);
+	downloadLink.click();
+	document.body.removeChild(downloadLink);
+	svg.removeChild(sdat.tempCSS);
+}
+
+function exportPngZip() {
+	var filename = document.URL? document.URL.substring(document.URL.lastIndexOf('/')+1, document.URL.lastIndexOf('.')):'trees'
+	var zip = new JSZip();
+	var folder = zip.folder(filename+".PNGfiles");
+	var svgList = $('svg');
+	$.each( svgList, function( index, svg ){
+		if (svg.id) {
+			var pngData = png2Data(svg);
+		var sent = sentences[svg.id.replace('svg','')].match(/[a-zA-Z\u00c0-\u024f\u1e00-\u1eff]+/g).join(' ').split(" ").slice(0,5).join('_').slice(0,50)
+		folder.file('tree'+svg.id.replace('svg','')+'.'+sent+'.png', pngData, {base64: true});
+		}
+	});
+	zip.generateAsync({type:"blob"})
+		.then(function(content) {
+			saveAs(content, filename + ".png.export.zip");
+		
+	});
+}
+
+function exportSvgZip() {
+	var zip = new JSZip();
+	var folder = zip.folder("svgfiles");
+	var svgList = $('svg');
+	$.each( svgList, function( index, svg ){
+		if (svg.id) {
+			var svgData = svg2Data(svg);
+			var sent = sentences[svg.id.replace('svg','')].match(/[a-zA-Z\u00c0-\u024f\u1e00-\u1eff]+/g).join(' ').split(" ").slice(0,5).join('_').slice(0,50)
+			folder.file('tree'+svg.id.replace('svg','')+'.'+sent+'.svg', svgData.svg.outerHTML);
+		}
+	});
+	// TODO:
+	// Add an top-level, arbitrary text file with contents
+	// zip.file("Hello.txt", "Hello World\n");
+	// Generate a directory within the Zip file structure
+	// var img = zip.folder("images");
+	// Add a file to the directory, in this case an image with data URI as contents
+	// img.file("smile.gif", imgData, {base64: true});
+	zip.generateAsync({type:"blob"})
+		.then(function(content) {
+			
+			saveAs(content, (document.URL? document.URL.substring(document.URL.lastIndexOf('/')+1, document.URL.lastIndexOf('.')):'trees') + ".svg.export.zip");
+	});
+}
+
+$("#btnSvgZip").on("click", function (){
+	exportSvgZip();
+});
+
+$("#btnPngZip").on("click", function (){
+	exportPngZip();
+});
+
+
+}());
+
+

src/arborator-draft/arborator-draft2.css

@@ -0,0 +1,118 @@
+.token {
+	font: 18px DejaVu Sans;
+	fill: black;
+	font-family:sans-serif;
+	--wordDistance:33;
+	text-align: center;
+} 
+
+.lemma {
+	font: 15px DejaVu Sans;
+	fill: black;
+	font-family:sans-serif;
+	text-align: center;
+	font-style: italic;
+} 
+
+.postag {
+	font: 11px DejaVu Sans;
+	fill: #E03737;
+	/* font-family:sans-serif; */
+	text-align: center;
+} 
+
+.deprel {
+	font: 12px Arial;
+	fill: #1d2ec1;
+	font-style: oblique;
+	font-family:sans-serif;
+	--funcCurveDist:3; /* distance between the function name and the curves highest point */
+} 
+
+.arrowhead {
+	fill: white;
+	stroke: black;
+	stroke-width: .8;
+}
+
+.curve {
+	stroke: black;
+	stroke-width: 1;
+	fill: none;
+	--startOffset: 8;
+	--tokDepDist: 15; /* distance between tokens and depdendency relation */
+	--depMinHeight: 15; /* minimum height for dependency */
+	--wordDistanceFactor: -1; /* distant words get higher curves. this factor fixes how much higher */
+}
+
+.conll {
+	display:none; /*toggles to inline*/
+	unicode-bidi: embed;
+	font-family: monospace;
+	white-space: pre;
+	margin-bottom: 0.6em;
+	border-bottom: 1px solid #aaa;
+	padding: 0.5em 0 0.17em 0;
+	tab-size: 12;
+	background-color: #fff ;
+	box-shadow: 0 2px 5px 0 rgba(0, 0, 0, 0.26);
+}
+
+.sentencebox {
+	margin-bottom: 0.6em;
+	border-bottom: 1px solid #aaa;
+	padding: 0.5em 0 0.17em 0;
+	margin-top: 1em;
+}
+
+/* Button */
+.button {
+	display: inline-block;
+	position: relative;
+	width: 120px;
+	height: 32px;
+	line-height: 32px;
+	border-radius: 2px;
+	font-size: 0.9em;
+	background-color: #fff;
+	color: #646464;
+	cursor:pointer;
+  }
+  
+  .button > paper-ripple {
+	border-radius: 2px;
+	overflow: hidden;
+  }
+
+
+.button.raised {
+	transition: box-shadow 0.2s cubic-bezier(0.4, 0, 0.2, 1);
+	transition-delay: 0.2s;
+	box-shadow: 0 2px 5px 0 rgba(0, 0, 0, 0.26);
+  }
+
+  .button.raised:active {
+	box-shadow: 0 8px 17px 0 rgba(0, 0, 0, 0.2);
+	transition-delay: 0s;
+  }
+
+  .center {
+	text-align: center;
+  }
+
+  /* logo animation transitions */
+  .arboratorlogo {
+	transition: all 0.4s ease-in-out;
+	-webkit-transition: all 0.4s ease-in-out;
+  }
+
+  .arboratorlogo:hover {
+	transform: scale(1.1);
+    transition: all 0.2s ease-in-out;
+	-webkit-transition: all 0.2s ease-in-out;
+	opacity: .9;
+  }
+
+	.svgbox {
+		overflow-x: auto;
+	}

src/arborator-draft/arborator-draft2.js

@@ -0,0 +1,720 @@
+(function () {
+
+    /*!
+     * arborator script for dependency drawing 
+     * version 1.0
+     * http://arborator.ilpga.fr/
+     *
+     * Copyright 2010-2017, Kim Gerdes & Gaël Guibon
+     *
+     * This program is free software:
+     * Licensed under version 3 of the GNU Affero General Public License (the "License");
+     * you may not use this file except in compliance with the License. 
+     * You may obtain a copy of the License at http://www.gnu.org/licenses/agpl-3.0.html
+     * Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an "AS IS" BASIS,
+     * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. 
+     * See the License for the specific language governing permissions and limitations under the License. 
+     *
+     */
+    
+    var drag = d3.drag();
+    
+    // global variables:
+    fontSize = 0; // computed from css value for .token in arborator-draft.css
+    lemmaHeight = 0;
+    posHeight = 0;
+    svgDefaultHeight = 500;
+    el=10; // type of conll (10, 14, or 4), computed in conllNodesToTree
+    trees=[]; // list of tree objects
+    uextras=[]; // list of comments. each comment is a hashtable position(=line)->comment TODO: add this to the display
+    conlltrees=[]; // list of conll strings
+    defaultCat="_"
+    shownfeatures=["t", "cat", "lemma","gloss"]; // recomputed in readConll
+    progressiveLoading = true; // false to make it load all trees at once (may overload the browser)
+    pngBtn = true;
+    svgBtn = true;
+    reverseMode = false; // set true for right to left conll
+    conlls = {	
+        10: 	{"id": 0, "t":1, "lemma": 2, "cat": 3, "xpos":4, "morph":5, "gov":6, "func":7, "xgov":8, "gloss":9}, 
+        14: 	{"id": 0, "t":1, "lemma": 3, "cat": 5, "gov":9, "func":11}, 
+        4: 	{"t":0, "lemma": 0, "cat": 1, "gov":2, "func":3} 
+    }
+    isFirefox = navigator.userAgent.toLowerCase().indexOf('firefox') > -1; // needed for bezier bounding box bug
+    
+    // debug:
+    log = console.log.bind(console);
+    
+    // TODO: add lemmas and pos!!!
+    lemmaColor = '#006400';
+    posColor = '#9e04de';
+    
+    // base 64 logo of arborator for the link image
+    base64Logo = 'data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAADQAAAAXCAYAAABEQGxzAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAABtQAAAbUBnmWvHAAAABl0RVh0U29mdHdhcmUAd3d3Lmlua3NjYXBlLm9yZ5vuPBoAAANXSURBVFiFtZhLbA1RGMd/59x7e5XeVrXU45aF9ztCLEQ3gojMwkZiJ7GYRDALhAUJa/FIZjk7EYKWCIMQG0qIx4JIQyREqxWP1uNyH729MxYzreu29zF3xj85mznf+X///8x3Zr4zwrZtqoWqaDXALKClggHwqYLx3jD1wWo1Ca+GVEWbAmwGFGAjECsWK22oyQkyYRsPWRLAbcAEbhim/tmLvooMqYq2HMeAAqwGZLk18USINb1RGjKSn1GLmpzgzOLfXrQBWMBjHHOmYerPyy0oakhVtGbgALANaPWioiEj2fGijmguT5mweThjkGdTsyTDlhe6fPQA54Fjhql/HStglCFV0WLAPmAvJcqpGOKJEOvej2P6r9CouZy0uT47TVdT1ittIRLASeCEYeqJ/Il/SkdVtJVAF3CEKswA1A0Kpv0ebQYgZAnaeqIs7A9XQ52PGI7GLlfzCEYMqYq2FegE4n4ytSRDiBLbsjEtaUyX3YKVIg50utoB15CqaBuBC0Ct3wxNqbGfTj7mDUSY9aN8XIWoBS64Hgj1PR1oBm5RZYkVYlDaLO6PlIyZkJV8q7Vf9dTnJAHcREAA66+du3laAvuBaQGQArDsS6TsN0cA44ZEDJgUVF4cD/sl0BYgKVfmphioLf1a7qvLca81PSPIvC7aJLAsSMZJaWk1pmVRR9+jFh3zkwwF9l74B0sk8C4AIgu4C+y2RHamgINjBaXDNu0LkiQj1fePZfAyDFwFllax2AIeABeBS4apfxyeeNd8uLVQck7A5Xkp+suUo090hoFTwE4q26A2jol2oMMw9b4icWeB9cCi4Qs3Z6forh/yJ7c0PgLHhW3bwx3CHWDiGIE28BDnSXQYpt5blloI8bbp0BNgJcD9eIb78Uxgyoto3GSY+u2RXk5VtFU4phrcgEf8NfHBa4a3kw8dwRZHXzZnMeekgpM+Gilgu2Hq7VDQnKqKthpYC7Qbpt7jJ8vryQdj3Q2i9/L8ZCwn/DCVxAdgi2Hqz4YveD7gVYpdm/dsBXkxK/8Lf9Fu+78YUhVtBfAECKxhc+H9POQXqqK14HzbgujRgjuxVgNV0SI4dT3FB42vfwq+T1oF2AC8ABqBeneMd4eFI/Yb8AXoA7qBNwT41+cPAlA7a3SX2xoAAAAASUVORK5CYII=';
+    
+    svgIdIndex = 0;
+    
+    // public initialisation function
+    this.ArboratorDraft = function(visuMode = 0, reverse = false) {
+        // main function called from html file
+        if(reverse) reverseMode = true;
+        if(visuMode==0){
+            $( ".expander" ).click(function(){
+                log(99,$(this).next('conll'));
+                $(this).next('conll').toggle();});    
+            readConll();
+        }else{
+            console.log('[ArboratorDraft] visumode');
+            trees=[]; 
+            uextras=[]; 
+            conlltrees=[]; 
+            $('conll').hide();
+            refresh( $('#conllarea').text() );
+        }
+    }
+    
+    // public function
+    ArboratorDraft.prototype.emptyThenRefresh = function(content, reverse = false, toggle = false) {	
+        if(reverse) reverseMode = true; // to set reverse or not
+        if(toggle) reverseMode = !reverseMode; // to toggle reverse
+        empty().done( refresh( content ) );
+    }
+    
+    
+    function refresh(content) {
+        $('#svgwell').html('');
+        $('#svgwell').append( $("<conll></conll>").attr('id', 'transformhere').text( content ) );
+        var conll = d3.selectAll('#transformhere')['_groups'][0][0];
+        drawConll(conll);
+        return;
+    }
+    
+    function sleep(milliseconds) {
+        var start = new Date().getTime();
+        for (var i = 0; i < 1e7; i++) {
+          if ((new Date().getTime() - start) > milliseconds){
+            break;
+          }
+        }
+      }
+    
+    function empty() {
+        console.log("empty");
+        var def = new jQuery.Deferred();
+        clearTimeout(readInsideConllTimeout);
+        treelines = [];
+        $('#svgwell').html('');
+        def.resolve();
+        return def.promise();
+    }
+    
+    
+    function progressiveReadConll() {
+        // draw each conll tags progressively (only conll tags)
+        var conllLoop = d3.selectAll('conll')['_groups'][0]; // need to go out d3js to load it progressively
+        var i = 0;
+        function waitBetweenElements(range) {
+            readConllTimeout = setTimeout(function () {
+    
+                drawConll(conllLoop[i]);
+                i++;
+                if (i < range) {
+                    waitBetweenElements(range);
+                }
+            }, 10)
+        }
+    
+        waitBetweenElements(conllLoop.length);
+    }
+    
+    function progressiveReadInsideConll(trees, pnode) {
+        // draw each tree INSIDE a conll progressively
+        var iWait = 0;
+        function waitBetweenElements(range) {
+            readInsideConllTimeout = setTimeout(function () {
+    
+                pushAndDrawSVG(trees[iWait], pnode);
+    
+                iWait++;
+                if (iWait < range) {
+                    waitBetweenElements(range);
+                }
+            }, 10)
+        }
+        waitBetweenElements(trees.length);
+    }
+    
+    function pushAndDrawSVG(element, pnode) {
+        conlltrees.push(element);
+        var data=conllNodesToTree(element);
+        trees.push(data.tree);
+        uextras.push(data.uextra)
+        
+        // add the save png button according to boolean option (default = false)
+        if(pngBtn){
+            var btn = pnode.insert('button').attr("class", "btn btn-primary").attr("id", "pngbtn"+svgIdIndex).html('Save PNG');
+            $("#pngbtn"+svgIdIndex).click(function(){
+                console.log("svgIdIndex",this.id);
+                savePng(this.id);
+            });
+        }
+    
+        if(svgBtn){
+            var btn = pnode.insert('button').attr("class", "btn btn-success").attr("id", "svgbtn"+svgIdIndex).html('Save SVG');
+            $("#svgbtn"+svgIdIndex).click(function(){
+                console.log("svgIdIndex",this.id);
+                saveSvg(this.id);
+            });
+        }
+        
+        
+    
+        var divsvgbox = pnode.insert('div').attr("class", 'svgbox');  	
+        divsvgbox.insert('div').html(data.sentence).attr("class", 'sentencebox'); 
+        draw(divsvgbox, data.tree);
+    
+        svgIdIndex=svgIdIndex +1;
+    }
+    
+    
+    
+    
+    
+    function readConll() {
+        // reads the conll representation of the whole treebank that is in the conll field
+            
+        trees=[]; // list of tree objects 
+        uextras=[]; // list of comments. each comment is a hashtable position(=line)->comment # TODO: show sentence features!
+        conlltrees=[]; // list of conll strings, one string per tree
+        
+        $('conll').hide(); // to hide the huge conll data
+    
+        if(progressiveLoading){
+            progressiveReadConll(); // progressive draw
+        }else{
+            d3.selectAll('conll').each(function(d){ drawConll(this); }); // all at once
+        }
+    
+        // 	TODO: check whether this is useful: adapt which nodes should be shown depending on what we find on the first node
+        // TODO : make it faster. This part is really slow
+        /*firstnode=trees[0][Math.min.apply(Math,Object.keys(trees[0]))]; // take lowest existing treenode number
+        shownfeatures = $.grep(shownfeatures, function (attri,i)
+            { // for each shownfeatures :
+            if (i < 2 || ((attri in firstnode) && firstnode[attri]!=defaultCat)) { 
+                // either the first two (token and cat) or non default value:
+                return true; // keep it
+                }
+            return false; // kick it out
+        });*/
+    }
+    
+    function drawConll(conllElement) { // for each <conll> section:
+        var conll = d3.select(conllElement).attr("class", 'conll'); 
+        conll.html(conll.html().trim())
+        var pnode = d3.select(conllElement.parentNode);
+        var toggle = false;
+        pnode.insert('a').html('<img src="'+base64Logo+'" alt="Arborator" title="arborator" class="arboratorlogo">').attr('href', 'https://arborator.github.io/').attr('target', '_blank');
+        var showHideConll = pnode.insert('div').html('<div class="center" fit>VIEW CONLL</div> <paper-ripple fit></paper-ripple>').attr("class", 'button raised');
+    
+        // <div class="button raised"> <div class="center" fit>SUBMIT</div> <paper-ripple fit></paper-ripple>  </div>
+        
+        var conllContent = conll.html().trim();
+        conll.remove(); // remove the old conll because it's place wasn't good
+        conll = pnode.insert('conll').html(conllContent).attr('class', 'conll'); //re insert to bind the content
+        
+        
+        showHideConll.on("click", ()=>{
+            log(111,toggle);
+            conll.style("display", toggle ? "none" : "block");
+            showHideConll.html(toggle ? '<div class="center" fit>VIEW CONLL</div> <paper-ripple fit></paper-ripple>': '<div class="center" fit>HIDE CONLL</div> <paper-ripple fit></paper-ripple>');
+            toggle = !toggle;
+        });
+    
+    
+        treelines = conll.html().trim().split(/\n\s*\n\s*\n*/);	
+    
+        if(progressiveLoading){
+            progressiveReadInsideConll(treelines, pnode);
+        }else{
+            for (let singleConll of treelines) { // for each conll tree at once, can block the browser
+                pushAndDrawSVG(singleConll, pnode);
+            }
+        }
+        
+    }
+    
+    
+    function conllNodesToTree(treeline) {
+        // reads a conll representation of a single tree TODO: replace jquery by d3
+        
+        var nodes = treeline.split('\n');
+        if(reverseMode)nodes.reverse();
+        // nodes = nodes.reverse();
+        var tree={};
+        var uextra={};
+        var lastid=0;
+        var skipuntil=0;
+        var words=[]
+        $.each(nodes, function(id,nodeline){ // for each conll line:
+            var nodeline=$.trim(nodeline);
+            if (nodeline.charAt(0) == "#") {
+                if (!(lastid in uextra)) uextra[lastid]=[];
+                uextra[lastid].push(nodeline)
+                return true;
+            }
+            var elements = nodeline.split('\t');
+            el=elements.length;
+    
+            if (!(el in conlls) && el>10) el=10;
+            if (el > 4) id=elements[conlls[el]["id"]];
+            else if (elements[conlls[el]["t"]] != "_") id++;
+            if (lastid!=id) // needed for the arborator encoding of multiple govs
+            {
+                var t=elements[conlls[el]["t"]];
+                var tokids=id.split("-")
+                if (tokids.length == 1) {
+                    tree[id]={}
+                    tree[id]["gov"]={};
+                    tree[id]["t"]=t;
+                    tree[id]["id"]=id;
+                    tree[id]["lemma"]=elements[conlls[el]["lemma"]];
+                    tree[id]["cat"]=elements[conlls[el]["cat"]];
+                    if (id>skipuntil) words.push(t);
+                    if (el==10) {
+                        tree[id]["xpos"]=elements[conlls[el]["xpos"]];
+                        tree[id]["morph"]=elements[conlls[el]["morph"]];
+                        tree[id]["gloss"]=elements[conlls[el]["gloss"]];
+                        if (tree[id]["gloss"]=="SpaceAfter=No"){
+                            tree[id]["gloss"]="_";
+                            tree[id]["NoSpaceAfter"]=false;
+                        }
+                        var xgov = elements[conlls[el]["xgov"]];
+                        if (xgov.indexOf(':') > -1){
+                            var xgovs=xgov.split("|");
+                            $.each(xgovs, function(ind,xg){ 
+                                // for each extra governor line:
+                                var xgs=xg.split(":")
+                                if (xgs.length >=2) {
+                                    // if it's not just _
+                                    var gov=xgs[0];
+                                    var func= xgs.slice(1).join(":");
+                                    tree[id]["gov"][gov]=func;
+                                }
+                            });
+                        }
+                    }
+                }
+                else if (tokids.length == 2){
+                    skipuntil = parseInt(tokids[1])
+                    words.push(elements[conlls[el]["t"]]);
+                    if (!(lastid in uextra)) uextra[lastid]=[];
+                    uextra[lastid].push(nodeline)
+                }
+                else {
+                    if (!(lastid in uextra)) uextra[lastid]=[];
+                    uextra[lastid].push(nodeline)
+                }
+            }
+            gov = elements[conlls[el]["gov"]];
+            if (gov!="" && gov!="_") 
+            {
+                if (gov==-1)
+                {
+                    gov = elements[conlls[el]["gov"]+1];
+                }
+                var func = elements[conlls[el]["func"]];
+                if (func.indexOf('::') !== -1) 
+                    {	
+                        var stydic = func.substring(func.indexOf("::") + 1);
+                        func = func.split("::")[0];
+                        if (stydic!="") funcDic[func] = $.parseJSON(stydic);
+                        $('#styleconllcheck').prop('checked', true);
+                    };
+                tree[id]["gov"][gov]=func;
+                
+            }
+            lastid=id;
+            });
+        
+        
+        var sentence="";
+        words.forEach(function (word, i) {
+            sentence+=word;
+            if(!reverseMode){
+                if (i+1 in tree && !(("NoSpaceAfter" in tree[i+1]) && tree[i+1]["NoSpaceAfter"]==false)) sentence+=" ";
+            }else{
+                sentence+=" ";
+            }
+        });
+        return {tree:tree, uextra:uextra, sentence:sentence};
+    }
+    
+    
+    function getSVGPath(startPoint,endPoint,computedStyle) {
+        // startPoint and endPoint are objects for the corresponding nodes
+        
+        var tokDepDist = parseInt(computedStyle.getPropertyValue('--tokDepDist'));
+        var depMinHeight = parseInt(computedStyle.getPropertyValue('--depMinHeight'));
+        var wordDistanceFactor = parseInt(computedStyle.getPropertyValue('--wordDistanceFactor'));
+        if(reverseMode) wordDistanceFactor = -Math.abs(wordDistanceFactor);
+        var startOffset = parseInt(computedStyle.getPropertyValue('--startOffset'));
+        if(reverseMode) startOffset = -Math.abs(startOffset);
+        var startOff=(startPoint['id']-endPoint['id']>0)?-startOffset:startOffset
+        var x1 = startPoint['x']+startPoint['w']/2+startOff;
+        var x2 = endPoint['x']+endPoint['w']/2;
+        var y1 = svgDefaultHeight-fontSize*2;
+        var y2 = svgDefaultHeight-fontSize*2;
+        var x1x2=Math.abs(x1-x2)/2;		
+        var yy = Math.max(y1-x1x2-wordDistanceFactor*Math.abs(endPoint['id']-startPoint['id']),-tokDepDist);
+        var yy = Math.min(yy,y1)-depMinHeight;
+        var cstr="M"+x1+","+y1+" C"+x1+","+yy+" "+x2+","+yy+" "+x2+","+(y2-2); // -2 so that the arrow is really pointed
+        //(x0,y0) is start point; (x1,y1),(x2,y2) is control points; (x3,y3) is end point.
+        return {cstr:cstr,  x0:x1,y0:y1,  x1:x1,y1:yy,  x2:x2,y2:yy,x3:x2,y3:(y2-2)};
+    }
+    
+    
+    function arrowhead(x,y) {
+        // gives path for arrowhead x,y startpoint (end of arrow)
+        var size = 5;
+        var startpoint = x+","+y; // to move the arrowhead lower: (y+size/3);
+        var lefttop = "0,0" +(-size/2)+","+(-size*1.5)+" "+(-size/2)+","+(-size*1.5);
+        var righttop = (size/2)+"," +(size/2)+" "+(size/2)+"," +(size/2)+ " "+(size)+",0";
+        var arrowPath = "M"+ startpoint+"c"+lefttop+ "c"+righttop+ "z";
+        return arrowPath;
+    }
+    
+    
+    function draw(div, tree) {
+        // draws json tree on svg in div
+        
+        var runningWidth = 0;
+        var smallestY = svgDefaultHeight;
+        var treeArray = $.map(tree, function(value, index) {return [value];});
+        var svg = div.append("svg:svg")
+        .attr("width",  1000)
+        .attr("height", svgDefaultHeight);
+        var group = svg.append("g");
+        // write tokens:
+        if(reverseMode) treeArray.reverse();
+        var eachTexts = group.selectAll("text")
+            .data(treeArray)
+            .enter();
+    
+    
+            var runningWidth2 = 0;
+    
+        eachTexts.append('text')
+            .attr("class", "token")
+            .text(function(d){return d["t"];})
+            .attr("id",function(d) {return d["id"];})
+            .attr("x", function(d) {
+                var w = this.getComputedTextLength();
+                wordDistance = parseInt(getComputedStyle(this).getPropertyValue('--wordDistance'));
+                var x = runningWidth; //<-- previous length to return
+                runningWidth += w + wordDistance; //<-- total
+                tree[d["id"]]["x"]=x;
+                tree[d["id"]]["w"]=w;
+                fontSize = parseInt(getComputedStyle(this).fontSize, 10);
+                return x;
+            })
+            .attr("y", svgDefaultHeight-fontSize);	
+            
+        svg.attr("width", runningWidth); // adapt svg width
+    
+        // draw dependency links
+        group.selectAll("text").each(function(d) { // for each token:
+            var txt = d3.select(this); 
+            for (var govid in tree[d3.select(this).attr("id")]["gov"]) { // for each governor
+                x=tree[txt.attr("id")]['x']+tree[txt.attr("id")]['w']/2;
+                var ligneDep = group.append("path")
+                .attr("class", "curve")
+                .attr("d", function (dd) {
+                    if (govid==0) // sentence root:
+                    {
+                        var y=svgDefaultHeight-fontSize*2;
+                        return "M"+x+","+(y-2)+"L"+x+","+0; // -2 so that the arrow is really pointed
+                    }
+                    else // normal link:
+                    {	
+                        pathInfo=getSVGPath(tree[govid],tree[txt.attr("id")], getComputedStyle(this))
+                        return pathInfo.cstr ;
+                    }
+                    
+                });
+                group.append("path")
+                .attr("class", "arrowhead")
+                .attr("d", function (dd) {
+                    return arrowhead(x, svgDefaultHeight - fontSize*2);
+                });
+                var label=tree[d3.select(this).attr("id")]["gov"][govid];
+                var depLineBbox=ligneDep.node().getBBox();
+                
+                // TODO: move the "root" label to a good position! (possibly to a group that has to be transformed separately!)
+                // TODO: handle mutliple governors!
+                if (govid!=0) // normal link:
+                {
+                    group.append('text') 
+                    .attr("class", "deprel")
+                    .text(function(d){return label})
+                    .attr("x", function(d) {
+                        relFontSize = parseInt(getComputedStyle(this).fontSize, 10);
+                        var w = this.getComputedTextLength(); //<-- length of this node
+                        return depLineBbox.x + depLineBbox.width/2 - w/2})
+                    .attr("y", function(d) {
+                            funcCurveDist = parseInt(getComputedStyle(this).getPropertyValue('--funcCurveDist'));
+                            if (isFirefox)
+                            {
+                                // firefox needs: stackoverflow.com/questions/24809978/calculating-the-bounding-box-of-cubic-bezier-curve
+                                const {x0, y0, x1, y1, x2, y2, x3, y3} = pathInfo // firefox
+                                y = bezierMinMax(x0, y0, x1, y1, x2, y2, x3, y3).min.y-funcCurveDist;
+                                return y; // firefox
+                            }
+                            else 
+                            {
+                                // standard Chrome etc
+                                y = depLineBbox.y-funcCurveDist
+                                return y; 
+                            }
+                        })
+                    // if not root, check how high we got:
+                    var smallY = y-relFontSize
+                    smallestY = smallY < smallestY ? smallY : smallestY;
+                    
+                }
+            }
+            // txt.on("click", started);
+            txt.on("drag", function(d){console.log('draggg')});
+        });	
+    
+    
+        // write lemmas
+        eachTexts.append('text')
+            .attr("class", "lemma")
+            .text(function(d){return d["lemma"];})
+            .attr("id",function(d) {return d["id"];})
+            .attr("x", function(d) {
+                var lemmaLength = this.getComputedTextLength();
+                var w = tree[d["id"]]["w"];
+                wordDistance = parseInt(getComputedStyle(this).getPropertyValue('--wordDistance'));
+                var x = tree[d["id"]]["x"] ; //<-- previous length to return
+                lemmaHeight = parseInt(getComputedStyle(this).fontSize, 20);
+                return x;
+            })
+            .attr("y", svgDefaultHeight-fontSize+lemmaHeight);
+    
+        // write pos
+        eachTexts.append('text')
+            .attr("class", "postag")
+            .text(function(d){return d["cat"];})
+            .attr("id",function(d) {return d["id"];})
+            .attr("x", function(d) {
+                var posLength = this.getComputedTextLength();
+                var w = tree[d["id"]]["w"];
+                wordDistance = parseInt(getComputedStyle(this).getPropertyValue('--wordDistance'));
+                if(posLength>w+10){
+                    var x = tree[d["id"]]["x"] - posLength/3 ; //<-- previous length to return
+                }else{
+                    var x = tree[d["id"]]["x"] ; //<-- previous length to return
+                }
+                posHeight = parseInt(getComputedStyle(this).fontSize, 20);
+                return x;
+            })
+            .attr("y", svgDefaultHeight-fontSize+lemmaHeight+posHeight);
+    
+    
+        group.attr("transform", "translate(" + 0 + "," + (-smallestY) + ")");
+        svg.attr("height", svgDefaultHeight-smallestY+posHeight+lemmaHeight+fontSize); // adapt svg height
+    
+        svg.attr("id", "svg"+svgIdIndex);
+        svg.attr("version", '1.1'); // to prepare ddl of svg
+        svg.attr("xmlns", "http://www.w3.org/2000/svg"); // to prepare ddl of svg
+    }
+    
+    
+    //(x0,y0) is start point; (x1,y1),(x2,y2) is control points; (x3,y3) is end point.
+    function bezierMinMax(x0, y0, x1, y1, x2, y2, x3, y3) {
+        var tvalues = [], xvalues = [], yvalues = [],
+            a, b, c, t, t1, t2, b2ac, sqrtb2ac;
+        for (var i = 0; i < 2; ++i) {
+            if (i == 0) {
+                b = 6 * x0 - 12 * x1 + 6 * x2;
+                a = -3 * x0 + 9 * x1 - 9 * x2 + 3 * x3;
+                c = 3 * x1 - 3 * x0;
+            } else {
+                b = 6 * y0 - 12 * y1 + 6 * y2;
+                a = -3 * y0 + 9 * y1 - 9 * y2 + 3 * y3;
+                c = 3 * y1 - 3 * y0;
+            }
+            if (Math.abs(a) < 1e-12) {
+                if (Math.abs(b) < 1e-12) {
+                    continue;
+                }
+                t = -c / b;
+                if (0 < t && t < 1) {
+                    tvalues.push(t);
+                }
+                continue;
+            }
+            b2ac = b * b - 4 * c * a;
+            if (b2ac < 0) {
+                continue;
+            }
+            sqrtb2ac = Math.sqrt(b2ac);
+            t1 = (-b + sqrtb2ac) / (2 * a);
+            if (0 < t1 && t1 < 1) {
+                tvalues.push(t1);
+            }
+            t2 = (-b - sqrtb2ac) / (2 * a);
+            if (0 < t2 && t2 < 1) {
+                tvalues.push(t2);
+            }
+        }
+    
+        var j = tvalues.length, mt;
+        while (j--) {
+            t = tvalues[j];
+            mt = 1 - t;
+            xvalues[j] = (mt * mt * mt * x0) + (3 * mt * mt * t * x1) + (3 * mt * t * t * x2) + (t * t * t * x3);
+            yvalues[j] = (mt * mt * mt * y0) + (3 * mt * mt * t * y1) + (3 * mt * t * t * y2) + (t * t * t * y3);
+        }
+    
+        xvalues.push(x0,x3);
+        yvalues.push(y0,y3);
+    
+        return {
+            min: {x: Math.min.apply(0, xvalues), y: Math.min.apply(0, yvalues)},
+            max: {x: Math.max.apply(0, xvalues), y: Math.max.apply(0, yvalues)}
+        };
+    }
+    
+    function svg2Data(svg) {
+        var tempCSS = document.createElement("style");
+        tempCSS.innerHTML = '.token {  font: 18px DejaVu Sans;  fill: black;  font-family:sans-serif;   text-align: center; }   .lemma {  font: 15px DejaVu Sans;  fill: black;  font-family:sans-serif;  text-align: center;  font-style: italic; }   .postag {  font: 11px DejaVu Sans;  fill: #E03737;   text-align: center; }   .deprel {  font: 12px Arial;  fill: #1d2ec1;  font-style: oblique;  font-family:sans-serif;  }   .arrowhead {  fill: white;  stroke: black;  stroke-width: .8; }  .curve {  stroke: black;  stroke-width: 1;  fill: none;     .arboratorlogo {  transition: all 0.4s ease-in-out;  -webkit-transition: all 0.4s ease-in-out;   }    .arboratorlogo:hover {  transform: scale(1.1);     transition: all 0.2s ease-in-out;  -webkit-transition: all 0.2s ease-in-out;  opacity: .9;   }   .svgbox {   overflow-x: auto;  }"';
+        svg.appendChild(tempCSS);
+        return svg.outerHTML;
+    }
+    
+    function png2Data(svg) {
+        var canvas = document.createElement('canvas');
+        var tempCSS = document.createElement("style");
+        tempCSS.innerHTML = '.token {  font: 18px DejaVu Sans;  fill: black;  font-family:sans-serif;   text-align: center; }   .lemma {  font: 15px DejaVu Sans;  fill: black;  font-family:sans-serif;  text-align: center;  font-style: italic; }   .postag {  font: 11px DejaVu Sans;  fill: #E03737;   text-align: center; }   .deprel {  font: 12px Arial;  fill: #1d2ec1;  font-style: oblique;  font-family:sans-serif;  }   .arrowhead {  fill: white;  stroke: black;  stroke-width: .8; }  .curve {  stroke: black;  stroke-width: 1;  fill: none;}';
+        svg.insertBefore(tempCSS, svg.firstChild);	// === the missing prepend option
+    
+        var bb = svg.getBBox();
+        // canvas.height = bb.height*5;
+        // canvas.width = bb.width*5;
+        // svg.width = svg.width*3;
+        // svg.height = svg.height*3;
+        // svg.setAttribute('width', bb.width*5);
+        // svg.setAttribute('height', bb.height*5);
+        var data = (new XMLSerializer()).serializeToString(svg);
+        console.log('svgData', data);
+        canvg(canvas, data);
+        return canvas.toDataURL().replace('data:image/png;base64,','');
+        
+    }
+    
+    function savePng(btnId) {
+        var id = btnId.replace("pngbtn","");
+        var canvas = document.createElement('canvas');
+        var tempCSS = document.createElement("style");
+        tempCSS.innerHTML = '.token {  font: 18px DejaVu Sans;  fill: black;  font-family:sans-serif;   text-align: center; }   .lemma {  font: 15px DejaVu Sans;  fill: black;  font-family:sans-serif;  text-align: center;  font-style: italic; }   .postag {  font: 11px DejaVu Sans;  fill: #E03737;   text-align: center; }   .deprel {  font: 12px Arial;  fill: #1d2ec1;  font-style: oblique;  font-family:sans-serif;  }   .arrowhead {  fill: white;  stroke: black;  stroke-width: .8; }  .curve {  stroke: black;  stroke-width: 1;  fill: none;}';
+        var svg = document.getElementById("svg"+id);
+        svg.appendChild(tempCSS);
+        var bb = svg.getBBox();
+        canvas.height = bb.height*5;
+        canvas.width = bb.width*5;
+        var ctx = canvas.getContext('2d');
+        var data = (new XMLSerializer()).serializeToString(svg);
+        var DOMURL = window.URL || window.webkitURL || window;
+        var img = new Image(); 
+        var svgBlob = new Blob([data], {type: 'image/svg+xml;charset=utf-8'});
+        var url = DOMURL.createObjectURL(svgBlob);
+        img.onload = function () {
+            ctx.drawImage(img, 0, 0, canvas.width, canvas.height);//, 0, 0, ctx.width, ctx.height);
+            DOMURL.revokeObjectURL(url);
+            var imgURI = canvas
+                .toDataURL('image/png')
+                .replace('image/png', 'image/octet-stream');
+            var evt = new MouseEvent('click', {
+                view: window,
+                bubbles: false,
+                cancelable: true
+            });
+            var a = document.createElement('a');
+            a.setAttribute('download', 'svg'+id+'.png');
+            a.setAttribute('href', imgURI );
+            a.setAttribute('target', '_blank');
+            a.dispatchEvent(evt);
+        };
+        img.src = url;
+    }
+    
+    function saveSvg(btnId) {
+        console.log(btnId);
+        var id = btnId.replace("svgbtn","");
+        var canvas = document.createElement('canvas');
+        console.log("canvas", canvas);
+        
+    
+        var tempCSS = document.createElement("style");
+        tempCSS.innerHTML = '.token {  font: 18px DejaVu Sans;  fill: black;  font-family:sans-serif;   text-align: center; }   .lemma {  font: 15px DejaVu Sans;  fill: black;  font-family:sans-serif;  text-align: center;  font-style: italic; }   .postag {  font: 11px DejaVu Sans;  fill: #E03737;   text-align: center; }   .deprel {  font: 12px Arial;  fill: #1d2ec1;  font-style: oblique;  font-family:sans-serif;  }   .arrowhead {  fill: white;  stroke: black;  stroke-width: .8; }  .curve {  stroke: black;  stroke-width: 1;  fill: none;     .arboratorlogo {  transition: all 0.4s ease-in-out;  -webkit-transition: all 0.4s ease-in-out;   }    .arboratorlogo:hover {  transform: scale(1.1);     transition: all 0.2s ease-in-out;  -webkit-transition: all 0.2s ease-in-out;  opacity: .9;   }   .svgbox {   overflow-x: auto;  }" width="1140" height="470.1878970357652"';
+    
+        var svg = document.getElementById("svg"+id);
+        svg.appendChild(tempCSS);
+    
+        var svgData = svg.outerHTML;
+        var svgBlob = new Blob([svgData], {type:"image/svg+xml;charset=utf-8"});
+        var svgUrl = URL.createObjectURL(svgBlob);
+        var downloadLink = document.createElement("a");
+        downloadLink.href = svgUrl;
+        downloadLink.download = "treeSvg"+id+".svg";
+        document.body.appendChild(downloadLink);
+        downloadLink.click();
+        document.body.removeChild(downloadLink);
+        
+    }
+    
+    
+    function exportPngZip() {
+        var zip = new JSZip();
+        var folder = zip.folder("pngfiles");
+        var svgList = $('svg');
+        var svgD3List = window.d3.selectAll("svg");
+        console.log(2222,svgD3List);
+        $.each( svgD3List['_groups'][0], function( index, value ){
+            console.log('value', index, value);
+            var pngData = png2Data(value);
+            folder.file('tree'+value.id+'.png', pngData, {base64: true});
+        });
+        zip.generateAsync({type:"blob"})
+            .then(function(content) {
+                saveAs(content, "export.zip");
+        });
+    }
+    
+    function exportSvgZip() {
+        var zip = new JSZip();
+        var folder = zip.folder("svgfiles");
+        var svgList = $('svg');
+        $.each( svgList, function( index, value ){
+            var svgData = svg2Data(value);
+            folder.file('tree'+svg.id+'.svg', svgData);
+        });
+    
+        zip.generateAsync({type:"blob"})
+            .then(function(content) {
+                saveAs(content, "export.zip");
+        });
+    }
+    
+    $("#btnSvgZip").on("click", function (){
+        exportSvgZip();
+    });
+    
+    $("#btnPngZip").on("click", function (){
+        exportPngZip();
+    });
+    
+    
+    }());
+    

src/arborator-draft/example_arborator-draft.html

@@ -0,0 +1,198 @@
+<!DOCTYPE HTML>
+
+<html>
+
+<head>
+    <meta charset="UTF-8" />
+    <link rel="stylesheet" href="https://maxcdn.bootstrapcdn.com/bootstrap/3.3.7/css/bootstrap.min.css">
+    <link rel="stylesheet" href="bootstrap.min.css">
+    <link rel="stylesheet" href="arborator-draft.css" type="text/css" />
+    <title>Arborator Draft - Example of visualization of CoNLL-U data</title>
+</head>
+
+<body>
+    <div class="container">   
+        
+        <div style="text-align: center;">
+            <svg
+            xmlns:dc="http://purl.org/dc/elements/1.1/"
+            xmlns:cc="http://creativecommons.org/ns#"
+            xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#"
+            xmlns:svg="http://www.w3.org/2000/svg"
+            xmlns="http://www.w3.org/2000/svg"
+            version="1.1"
+            viewBox="-4202 0 5704.1939 1840.839"
+            style="image-rendering:optimizeQuality;"
+            height="130"
+            width="270"
+            xml:space="preserve">
+            <path
+                style="fill:none;stroke:#4a2769;stroke-width:128.73750305;stroke-linecap:butt;stroke-linejoin:miter;stroke-miterlimit:4;"
+                d="m -1890.5398,1002.7933 -1822.5445,615.288 c -261.3344,-190.4146 -424.5469,-433.2903 -424.5469,-661.59345 0,-685.88115 1244.2446,-1296.6446 2780.191,-1296.6446 1534.97478,0 2795.2653,610.76345 2795.2653,1296.6446 0,685.88105 -1252.26757,1244.49535 -2787.2424,1244.49535 -239.9613,0 -490.6091,-19.4301 -718.9123,-43.7176 L -751.94297,618.40481 -882.8496,663.4494" /><path
+                style="fill:none;stroke:#dd137b;stroke-width:128.73750305;stroke-miterlimit:4;"
+                d="M -864.53567,745.22843 C -964.68477,501.46149 -1354.4152,-183.90675 -1694.5756,-3.2652517 -2014.6556,165.68318 -2049.9732,423.17981 -1871.2632,1084.3717 c 67.0564,232.3776 161.3346,398.0135 238.7197,540.6756" /><path
+                style="fill:none;stroke:#4a2769;stroke-width:128.73750305;stroke-linecap:butt;stroke-linejoin:miter;stroke-miterlimit:4;"
+                d="M -2068.3297,2157.2657 -751.94297,618.40481"
+                />
+            </svg>
+        </div>
+        <div class="row" style="margin-top: 15px;">
+                <div class="panel panel-primary" style="border-color: #4a2769;">
+                    <div class="panel-heading" style="background-color: #4a2769;"><h2 >It's easy to add dependency graphs to your web page</h2></div>
+                    <div class="panel-body">
+
+                        <ol>
+                            <li> <strong>Simply put the CoNLL-U data between &lt;conll&gt; tags where you want to show the dependency graph.</strong></li>
+                            <li><strong>Import arborator-draft.css, arborator-draft.js, d3.js, and jquery.</strong></li>
+                            <li><strong>Add this in the end of your html page:</strong></li>
+                          </ol> 
+
+                      
+                        <pre><code>     window.onload = function () { 
+		new ArboratorDraft(); // START
+        }</code></pre>
+                        <p><strong>Automatically, the CoNLL-U data will be transformed into beautiful dependency graphs!</strong></p>
+
+                        <p>Graphical options are in arborator-draft.css</p>
+                        <p>If you want to generally modify which features are shown, modify these lines in the arborator-draft.js:</p>
+                        <pre><code>    shownfeatures=["FORM", "UPOS", "LEMMA", "MISC.Gloss"];
+    shownmetas=['text_en']</code></pre>
+        <p>If you want to temporarily modify which features are shown, add the shownfeatures attribute to the meta-features of the conll representations, and provide the list of features separated by commas. Morphosyntactic features must be prefixed by FEATS. and miscellaneous features by MISC. as in:</p>
+         <pre><code># shownfeatures = FORM, UPOS, LEMMA, MISC.Gloss, FEATS.ExtPos, FEATS.PhraseType, FEATS.InTitle
+</code></pre>
+
+    <p>If you want to have a button to show the complete conll data (not only per tree), change <code>showAllConllButton</code> to true</p>
+    <p>If you want to add those two blue buttons just below to your page, which allow to download the complete set of svg or png images in a zip, add <code>jszip.min.js</code> and <code>FileSaver.min.js</code> to the imports</p>
+   
+    <hr/>
+    <p>Please admire the speed of the non-blocking rendering in <a href="speedtest.separateConllTags.html">this file with many separate CoNLL nodes</a> and <a href="speedtest.oneBigConllTag.html">that file with one very long CoNLL node</a></p>
+    <p>Todo: 
+        <ul>
+            <li>add sound player if sound_url is present.</li>
+            <li>For SVG and PNG download, update automatically the information from the .css file, instead of copying it into the code as defaultcss. See problem at https://stackoverflow.com/questions/3211536/accessing-cross-domain-style-sheet-with-cssrules</li>
+            <li>When hanging back in the conll node, fix the order with the neighbors, so that a surrounding div becomes unnecessary.</li>
+           
+          </ul> </p>
+
+                    </div>
+                    <div class="panel-footer">
+                        <button id="btnSvgZip" class="btn btn-primary"  style="background-color: #4a2769; border-color: #4a2769;">Export SVG files in Zip</button>
+                        <button id="btnPngZip" class="btn btn-primary"  style="background-color: #4a2769; border-color: #4a2769;">Export PNG files in Zip</button>
+                    </div>
+                </div>
+            </div>
+
+        <div class="row">
+            <div class="panel panel-primary" style="border-color: #4a2769;">
+                <div class="panel-heading" style="background-color: #4a2769; border-color: #4a2769;"><h2>First example of CoNLL-U data surrounded by Conll tags</h2></div>
+                <p>Random text before the div containing the conll tag</p>
+                <div class="panel-body">
+                    
+                    <conll>
+
+# sent_id = KAD_15_Money-Wahala_MG__22
+# sound_url = http://www.tal.univ-paris3.fr/trameur/iTrameur-naija/mp3/KAD_15_Money-Wahala_MG.mp3
+# speaker_id = Sp194
+# text = # how { di gene- || generation } go be ?//
+# text_en = How will the next gene… generation be?
+# text_ortho = How di gene-... generation go be?
+# shownfeatures = FORM, UPOS, LEMMA, MISC.Gloss, FEATS.PronType, FEATS.Aspect
+1	#	#	PUNCT	_	_	2	punct	_	AlignBegin=85160|AlignEnd=85800|Gloss=PUNCT
+2	how	how	ADV	_	PronType=Int	0	root	10:@mod	AlignBegin=85800|AlignEnd=86049|Gloss=how.Q
+3	{	{	PUNCT	_	_	5	punct	_	AlignBegin=86049|AlignEnd=86079|Gloss=PUNCT
+4	di	the	DET	_	Definite=Def|PronType=Art	5	det	_	AlignBegin=86079|AlignEnd=86230|Gloss=DEF.ART
+5	gene-	X	X	_	_	9	subj	_	AlignBegin=86230|AlignEnd=86530|Gloss=X
+6	||	||	PUNCT	_	_	7	punct	_	AlignBegin=86530|AlignEnd=86560|Gloss=PUNCT
+7	generation	generation	NOUN	_	_	5	conj:coord	_	AlignBegin=86560|AlignEnd=86950|Gloss=generation
+8	}	}	PUNCT	_	_	5	punct	_	AlignBegin=86950|AlignEnd=86980|Gloss=PUNCT
+9	go	go	AUX	_	Aspect=Prosp	2	comp:cleft	_	AlignBegin=86980|AlignEnd=87110|Gloss=PROSP
+10	be	be	VERB	_	PartType=Cop	9	comp:aux	_	AlignBegin=87110|AlignEnd=87310|Gloss=be
+11	?//	?//	PUNCT	_	_	2	punct	_	AlignBegin=87310|AlignEnd=87340|Gloss=PUNCT
+                    
+1	l'	le	DET	_	_	2	spe	_	_
+2	avenir	avenir	NOM	_	_	3	subj	_	_
+3	dépend	dépendre	VRB	_	_	0	root	_	_
+4	de	de	PRE	_	_	3	comp	_	_
+5	notre	son	DET	_	_	6	spe	_	_
+6	capacité	capacité	NOM	_	_	4	dep	_	_
+7	à	à	PRE	_	_	6	dep	_	_
+8	construire	construire	VNF	_	_	7	dep	_	_
+9	à	à	PRE	_	_	7	para	_	_
+10	créer	créer	VNF	_	_	9	dep	_	_
+11	à	à	PRE	_	_	9	para	_	_
+12	rêver	rêver	VNF	_	_	11	dep	_	_
+13	ensemble	ensemble	ADV	_	_	12	ad	_	_
+14	les	le	DET	_	_	15	spe	_	_
+15	voies	voie	NOM	_	_	12	comp	_	_
+16	de	de	PRE	_	_	15	dep	_	_
+17	l'	le	DET	_	_	18	spe	_	_
+18	aventure	aventure	NOM	_	_	16	dep	_	_
+19	humaine	humain	ADJ	_	_	18	dep	_	_
+                    </conll>
+                    
+                </div>
+                <p>Random text after the div containing the conll tag</p>
+            </div>
+        </div>
+        
+        <div class="row">
+            <div class="panel panel-danger">
+                <div class="panel-heading"  style="background-color: #dd137b;color:white; border-color: #dd137b;"><h2>Another example of CoNLL-U data surrounded by Conll tags</h2></div>
+                <div class="panel-body">
+                        <conll>
+
+# text_en = I wrote the letter with a quill.
+1	Я	ja	PRON	_	Case=Nom|Number=Sing|Person=1|PronType=Prs	2	nsubj	_	Gloss=I
+2	написал	napisat'	VERB	_	Gender=Masc|Number=Sing|VerbForm=Part|Voice=Act	0	root	_	Gloss=wrote
+3	письмо	pis'mo	NOUN	_	Case=Acc|Gender=Neut|Number=Sing	2	dobj	_	Gloss=the-letter
+4	пером	pero	NOUN	_	Case=Ins|Gender=Neut|Number=Sing	2	nmod	_	Gloss=with-a-quill
+
+1	car	car	COO	_	_	12	mark	_	_
+2	dans	dans	PRE	_	_	12	periph	_	_
+3	un	un	DET	_	_	4	spe	_	_
+4	monde	monde	NOM	_	_	2	dep	_	_
+5	où	où	PRQ	_	_	9	ad	_	_
+6	rien	rien	PRO	_	_	8	subj	_	_
+7	n'	ne	CLN	_	_	8	ad	_	_
+8	est	être	VRB	_	_	4	dep	_	_
+9	figé	figer	VPP	_	_	8	aux	_	_
+10	l'	le	DET	_	_	11	spe	_	_
+11	avenir	avenir	NOM	_	_	12	subj	_	_
+12	dépend	dépendre	VRB	_	_	0	root	_	_
+13	de	de	PRE	_	_	12	comp	_	_
+14	nous	lui	PRO	_	_	13	dep	_	_
+                        </conll>
+                </div>
+            </div>  
+        </div>
+    </div>
+
+<!-- 
+        
+
+                     -->
+
+    <!-- <script language="JavaScript" type="text/javascript" src="https://cdnjs.cloudflare.com/ajax/libs/d3/4.10.0/d3.js"></script> -->
+    <script src="d3.js"></script>
+    <!-- <script src="d3-drag.min.js"></script> -->
+    <!-- <script src="https://code.jquery.com/jquery-3.2.1.min.js"
+	integrity="sha256-hwg4gsxgFZhOsEEamdOYGBf13FyQuiTwlAQgxVSNgt4="
+    crossorigin="anonymous"></script> -->
+    <script src="jquery-3.2.1.min.js"></script>
+    <!-- <script src="https://maxcdn.bootstrapcdn.com/bootstrap/3.3.7/js/bootstrap.min.js"></script> -->
+    <!-- <script src="bootstrap.min.css"></script> -->
+    <script src="FileSaver.min.js"></script>
+    <script src="jszip.min.js"></script>
+    <!-- <script type="text/javascript" src="rgbcolor.js"></script> 
+    <script type="text/javascript" src="StackBlur.js"></script> -->
+    <script type="text/javascript" src="canvg.js"></script> 
+    <script language="JavaScript" type="text/javascript" src="arborator-draft.js"></script>
+    <script>
+   
+	window.onload = function () {
+		new ArboratorDraft(myshownfeatures=["FORM", "UPOS", "LEMMA", "MISC.Gloss"]); // START. myshownfeatures has the standard value here and can be omitted if this is the desired set of features to be shown.
+        }
+    </script>
+</body>
+
+</html>

src/arborator-draft/jquery-3.2.1.min.js

@@ -0,0 +1,4 @@
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src/arborator-draft/jszip.min.js

@@ -0,0 +1,13 @@
+/*!
+
+JSZip v3.3.0 - A JavaScript class for generating and reading zip files
+<http://stuartk.com/jszip>
+
+(c) 2009-2016 Stuart Knightley <stuart [at] stuartk.com>
+Dual licenced under the MIT license or GPLv3. See https://raw.github.com/Stuk/jszip/master/LICENSE.markdown.
+
+JSZip uses the library pako released under the MIT license :
+https://github.com/nodeca/pako/blob/master/LICENSE
+*/
+
+!function(t){if("object"==typeof exports&&"undefined"!=typeof module)module.exports=t();else if("function"==typeof define&&define.amd)define([],t);else{("undefined"!=typeof window?window:"undefined"!=typeof global?global:"undefined"!=typeof self?self:this).JSZip=t()}}(function(){return function s(a,o,h){function u(r,t){if(!o[r]){if(!a[r]){var e="function"==typeof require&&require;if(!t&&e)return e(r,!0);if(l)return l(r,!0);var i=new Error("Cannot find module '"+r+"'");throw i.code="MODULE_NOT_FOUND",i}var n=o[r]={exports:{}};a[r][0].call(n.exports,function(t){var e=a[r][1][t];return u(e||t)},n,n.exports,s,a,o,h)}return o[r].exports}for(var l="function"==typeof require&&require,t=0;t<h.length;t++)u(h[t]);return u}({1:[function(t,e,r){"use strict";var c=t("./utils"),d=t("./support"),p="ABCDEFGHIJKLMNOPQRSTUVWXYZabcdefghijklmnopqrstuvwxyz0123456789+/=";r.encode=function(t){for(var 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for(this.push({data:r.fileRecord,meta:{percent:0}});this.contentBuffer.length;)this.push(this.contentBuffer.shift());this.currentFile=null},s.prototype.flush=function(){for(var t=this.bytesWritten,e=0;e<this.dirRecords.length;e++)this.push({data:this.dirRecords[e],meta:{percent:100}});var r=this.bytesWritten-t,i=function(t,e,r,i,n){var s=I.transformTo("string",n(i));return R.CENTRAL_DIRECTORY_END+"\0\0\0\0"+A(t,2)+A(t,2)+A(e,4)+A(r,4)+A(s.length,2)+s}(this.dirRecords.length,r,t,this.zipComment,this.encodeFileName);this.push({data:i,meta:{percent:100}})},s.prototype.prepareNextSource=function(){this.previous=this._sources.shift(),this.openedSource(this.previous.streamInfo),this.isPaused?this.previous.pause():this.previous.resume()},s.prototype.registerPrevious=function(t){this._sources.push(t);var e=this;return t.on("data",function(t){e.processChunk(t)}),t.on("end",function(){e.closedSource(e.previous.streamInfo),e._sources.length?e.prepareNextSource():e.end()}),t.on("error",function(t){e.error(t)}),this},s.prototype.resume=function(){return!!n.prototype.resume.call(this)&&(!this.previous&&this._sources.length?(this.prepareNextSource(),!0):this.previous||this._sources.length||this.generatedError?void 0:(this.end(),!0))},s.prototype.error=function(t){var e=this._sources;if(!n.prototype.error.call(this,t))return!1;for(var r=0;r<e.length;r++)try{e[r].error(t)}catch(t){}return!0},s.prototype.lock=function(){n.prototype.lock.call(this);for(var t=this._sources,e=0;e<t.length;e++)t[e].lock()},e.exports=s},{"../crc32":4,"../signature":23,"../stream/GenericWorker":28,"../utf8":31,"../utils":32}],9:[function(t,e,r){"use strict";var u=t("../compressions"),i=t("./ZipFileWorker");r.generateWorker=function(t,a,e){var o=new i(a.streamFiles,e,a.platform,a.encodeFileName),h=0;try{t.forEach(function(t,e){h++;var r=function(t,e){var r=t||e,i=u[r];if(!i)throw new Error(r+" is not a valid compression method !");return i}(e.options.compression,a.compression),i=e.options.compressionOptions||a.compressionOptions||{},n=e.dir,s=e.date;e._compressWorker(r,i).withStreamInfo("file",{name:t,dir:n,date:s,comment:e.comment||"",unixPermissions:e.unixPermissions,dosPermissions:e.dosPermissions}).pipe(o)}),o.entriesCount=h}catch(t){o.error(t)}return o}},{"../compressions":3,"./ZipFileWorker":8}],10:[function(t,e,r){"use strict";function i(){if(!(this instanceof i))return new i;if(arguments.length)throw new Error("The constructor with parameters has been removed in JSZip 3.0, please check the upgrade guide.");this.files={},this.comment=null,this.root="",this.clone=function(){var t=new i;for(var e in this)"function"!=typeof this[e]&&(t[e]=this[e]);return t}}(i.prototype=t("./object")).loadAsync=t("./load"),i.support=t("./support"),i.defaults=t("./defaults"),i.version="3.4.0",i.loadAsync=function(t,e){return(new i).loadAsync(t,e)},i.external=t("./external"),e.exports=i},{"./defaults":5,"./external":6,"./load":11,"./object":15,"./support":30}],11:[function(t,e,r){"use strict";var i=t("./utils"),n=t("./external"),o=t("./utf8"),h=(i=t("./utils"),t("./zipEntries")),s=t("./stream/Crc32Probe"),u=t("./nodejsUtils");function l(i){return new n.Promise(function(t,e){var r=i.decompressed.getContentWorker().pipe(new s);r.on("error",function(t){e(t)}).on("end",function(){r.streamInfo.crc32!==i.decompressed.crc32?e(new Error("Corrupted zip : CRC32 mismatch")):t()}).resume()})}e.exports=function(t,s){var a=this;return s=i.extend(s||{},{base64:!1,checkCRC32:!1,optimizedBinaryString:!1,createFolders:!1,decodeFileName:o.utf8decode}),u.isNode&&u.isStream(t)?n.Promise.reject(new Error("JSZip can't accept a stream when loading a zip file.")):i.prepareContent("the loaded zip file",t,!0,s.optimizedBinaryString,s.base64).then(function(t){var e=new h(s);return e.load(t),e}).then(function(t){var e=[n.Promise.resolve(t)],r=t.files;if(s.checkCRC32)for(var i=0;i<r.length;i++)e.push(l(r[i]));return n.Promise.all(e)}).then(function(t){for(var e=t.shift(),r=e.files,i=0;i<r.length;i++){var n=r[i];a.file(n.fileNameStr,n.decompressed,{binary:!0,optimizedBinaryString:!0,date:n.date,dir:n.dir,comment:n.fileCommentStr.length?n.fileCommentStr:null,unixPermissions:n.unixPermissions,dosPermissions:n.dosPermissions,createFolders:s.createFolders})}return e.zipComment.length&&(a.comment=e.zipComment),a})}},{"./external":6,"./nodejsUtils":14,"./stream/Crc32Probe":25,"./utf8":31,"./utils":32,"./zipEntries":33}],12:[function(t,e,r){"use strict";var i=t("../utils"),n=t("../stream/GenericWorker");function s(t,e){n.call(this,"Nodejs stream input adapter for "+t),this._upstreamEnded=!1,this._bindStream(e)}i.inherits(s,n),s.prototype._bindStream=function(t){var e=this;(this._stream=t).pause(),t.on("data",function(t){e.push({data:t,meta:{percent:0}})}).on("error",function(t){e.isPaused?this.generatedError=t:e.error(t)}).on("end",function(){e.isPaused?e._upstreamEnded=!0:e.end()})},s.prototype.pause=function(){return!!n.prototype.pause.call(this)&&(this._stream.pause(),!0)},s.prototype.resume=function(){return!!n.prototype.resume.call(this)&&(this._upstreamEnded?this.end():this._stream.resume(),!0)},e.exports=s},{"../stream/GenericWorker":28,"../utils":32}],13:[function(t,e,r){"use strict";var n=t("readable-stream").Readable;function i(t,e,r){n.call(this,e),this._helper=t;var i=this;t.on("data",function(t,e){i.push(t)||i._helper.pause(),r&&r(e)}).on("error",function(t){i.emit("error",t)}).on("end",function(){i.push(null)})}t("../utils").inherits(i,n),i.prototype._read=function(){this._helper.resume()},e.exports=i},{"../utils":32,"readable-stream":16}],14:[function(t,e,r){"use strict";e.exports={isNode:"undefined"!=typeof Buffer,newBufferFrom:function(t,e){if(Buffer.from&&Buffer.from!==Uint8Array.from)return Buffer.from(t,e);if("number"==typeof t)throw new Error('The "data" argument must not be a number');return new Buffer(t,e)},allocBuffer:function(t){if(Buffer.alloc)return Buffer.alloc(t);var e=new Buffer(t);return e.fill(0),e},isBuffer:function(t){return Buffer.isBuffer(t)},isStream:function(t){return t&&"function"==typeof t.on&&"function"==typeof t.pause&&"function"==typeof t.resume}}},{}],15:[function(t,e,r){"use strict";function s(t,e,r){var i,n=u.getTypeOf(e),s=u.extend(r||{},f);s.date=s.date||new Date,null!==s.compression&&(s.compression=s.compression.toUpperCase()),"string"==typeof s.unixPermissions&&(s.unixPermissions=parseInt(s.unixPermissions,8)),s.unixPermissions&&16384&s.unixPermissions&&(s.dir=!0),s.dosPermissions&&16&s.dosPermissions&&(s.dir=!0),s.dir&&(t=g(t)),s.createFolders&&(i=_(t))&&b.call(this,i,!0);var a="string"===n&&!1===s.binary&&!1===s.base64;r&&void 0!==r.binary||(s.binary=!a),(e instanceof d&&0===e.uncompressedSize||s.dir||!e||0===e.length)&&(s.base64=!1,s.binary=!0,e="",s.compression="STORE",n="string");var o=null;o=e instanceof d||e instanceof l?e:p.isNode&&p.isStream(e)?new m(t,e):u.prepareContent(t,e,s.binary,s.optimizedBinaryString,s.base64);var h=new c(t,o,s);this.files[t]=h}var n=t("./utf8"),u=t("./utils"),l=t("./stream/GenericWorker"),a=t("./stream/StreamHelper"),f=t("./defaults"),d=t("./compressedObject"),c=t("./zipObject"),o=t("./generate"),p=t("./nodejsUtils"),m=t("./nodejs/NodejsStreamInputAdapter"),_=function(t){"/"===t.slice(-1)&&(t=t.substring(0,t.length-1));var e=t.lastIndexOf("/");return 0<e?t.substring(0,e):""},g=function(t){return"/"!==t.slice(-1)&&(t+="/"),t},b=function(t,e){return e=void 0!==e?e:f.createFolders,t=g(t),this.files[t]||s.call(this,t,null,{dir:!0,createFolders:e}),this.files[t]};function h(t){return"[object RegExp]"===Object.prototype.toString.call(t)}var i={load:function(){throw new Error("This method has been removed in JSZip 3.0, please check the upgrade guide.")},forEach:function(t){var e,r,i;for(e in this.files)this.files.hasOwnProperty(e)&&(i=this.files[e],(r=e.slice(this.root.length,e.length))&&e.slice(0,this.root.length)===this.root&&t(r,i))},filter:function(r){var i=[];return this.forEach(function(t,e){r(t,e)&&i.push(e)}),i},file:function(t,e,r){if(1!==arguments.length)return t=this.root+t,s.call(this,t,e,r),this;if(h(t)){var i=t;return this.filter(function(t,e){return!e.dir&&i.test(t)})}var n=this.files[this.root+t];return n&&!n.dir?n:null},folder:function(r){if(!r)return this;if(h(r))return this.filter(function(t,e){return e.dir&&r.test(t)});var t=this.root+r,e=b.call(this,t),i=this.clone();return i.root=e.name,i},remove:function(r){r=this.root+r;var t=this.files[r];if(t||("/"!==r.slice(-1)&&(r+="/"),t=this.files[r]),t&&!t.dir)delete this.files[r];else for(var e=this.filter(function(t,e){return e.name.slice(0,r.length)===r}),i=0;i<e.length;i++)delete this.files[e[i].name];return this},generate:function(t){throw new Error("This method has been removed in JSZip 3.0, please check the upgrade guide.")},generateInternalStream:function(t){var e,r={};try{if((r=u.extend(t||{},{streamFiles:!1,compression:"STORE",compressionOptions:null,type:"",platform:"DOS",comment:null,mimeType:"application/zip",encodeFileName:n.utf8encode})).type=r.type.toLowerCase(),r.compression=r.compression.toUpperCase(),"binarystring"===r.type&&(r.type="string"),!r.type)throw new Error("No output type specified.");u.checkSupport(r.type),"darwin"!==r.platform&&"freebsd"!==r.platform&&"linux"!==r.platform&&"sunos"!==r.platform||(r.platform="UNIX"),"win32"===r.platform&&(r.platform="DOS");var i=r.comment||this.comment||"";e=o.generateWorker(this,r,i)}catch(t){(e=new l("error")).error(t)}return new a(e,r.type||"string",r.mimeType)},generateAsync:function(t,e){return this.generateInternalStream(t).accumulate(e)},generateNodeStream:function(t,e){return(t=t||{}).type||(t.type="nodebuffer"),this.generateInternalStream(t).toNodejsStream(e)}};e.exports=i},{"./compressedObject":2,"./defaults":5,"./generate":9,"./nodejs/NodejsStreamInputAdapter":12,"./nodejsUtils":14,"./stream/GenericWorker":28,"./stream/StreamHelper":29,"./utf8":31,"./utils":32,"./zipObject":35}],16:[function(t,e,r){e.exports=t("stream")},{stream:void 0}],17:[function(t,e,r){"use strict";var i=t("./DataReader");function n(t){i.call(this,t);for(var e=0;e<this.data.length;e++)t[e]=255&t[e]}t("../utils").inherits(n,i),n.prototype.byteAt=function(t){return this.data[this.zero+t]},n.prototype.lastIndexOfSignature=function(t){for(var e=t.charCodeAt(0),r=t.charCodeAt(1),i=t.charCodeAt(2),n=t.charCodeAt(3),s=this.length-4;0<=s;--s)if(this.data[s]===e&&this.data[s+1]===r&&this.data[s+2]===i&&this.data[s+3]===n)return s-this.zero;return-1},n.prototype.readAndCheckSignature=function(t){var e=t.charCodeAt(0),r=t.charCodeAt(1),i=t.charCodeAt(2),n=t.charCodeAt(3),s=this.readData(4);return e===s[0]&&r===s[1]&&i===s[2]&&n===s[3]},n.prototype.readData=function(t){if(this.checkOffset(t),0===t)return[];var e=this.data.slice(this.zero+this.index,this.zero+this.index+t);return this.index+=t,e},e.exports=n},{"../utils":32,"./DataReader":18}],18:[function(t,e,r){"use strict";var i=t("../utils");function n(t){this.data=t,this.length=t.length,this.index=0,this.zero=0}n.prototype={checkOffset:function(t){this.checkIndex(this.index+t)},checkIndex:function(t){if(this.length<this.zero+t||t<0)throw new Error("End of data reached (data length = "+this.length+", asked index = "+t+"). Corrupted zip ?")},setIndex:function(t){this.checkIndex(t),this.index=t},skip:function(t){this.setIndex(this.index+t)},byteAt:function(t){},readInt:function(t){var e,r=0;for(this.checkOffset(t),e=this.index+t-1;e>=this.index;e--)r=(r<<8)+this.byteAt(e);return this.index+=t,r},readString:function(t){return i.transformTo("string",this.readData(t))},readData:function(t){},lastIndexOfSignature:function(t){},readAndCheckSignature:function(t){},readDate:function(){var t=this.readInt(4);return new Date(Date.UTC(1980+(t>>25&127),(t>>21&15)-1,t>>16&31,t>>11&31,t>>5&63,(31&t)<<1))}},e.exports=n},{"../utils":32}],19:[function(t,e,r){"use strict";var i=t("./Uint8ArrayReader");function n(t){i.call(this,t)}t("../utils").inherits(n,i),n.prototype.readData=function(t){this.checkOffset(t);var e=this.data.slice(this.zero+this.index,this.zero+this.index+t);return this.index+=t,e},e.exports=n},{"../utils":32,"./Uint8ArrayReader":21}],20:[function(t,e,r){"use strict";var i=t("./DataReader");function n(t){i.call(this,t)}t("../utils").inherits(n,i),n.prototype.byteAt=function(t){return this.data.charCodeAt(this.zero+t)},n.prototype.lastIndexOfSignature=function(t){return this.data.lastIndexOf(t)-this.zero},n.prototype.readAndCheckSignature=function(t){return t===this.readData(4)},n.prototype.readData=function(t){this.checkOffset(t);var e=this.data.slice(this.zero+this.index,this.zero+this.index+t);return this.index+=t,e},e.exports=n},{"../utils":32,"./DataReader":18}],21:[function(t,e,r){"use strict";var i=t("./ArrayReader");function n(t){i.call(this,t)}t("../utils").inherits(n,i),n.prototype.readData=function(t){if(this.checkOffset(t),0===t)return new Uint8Array(0);var e=this.data.subarray(this.zero+this.index,this.zero+this.index+t);return this.index+=t,e},e.exports=n},{"../utils":32,"./ArrayReader":17}],22:[function(t,e,r){"use strict";var i=t("../utils"),n=t("../support"),s=t("./ArrayReader"),a=t("./StringReader"),o=t("./NodeBufferReader"),h=t("./Uint8ArrayReader");e.exports=function(t){var e=i.getTypeOf(t);return i.checkSupport(e),"string"!==e||n.uint8array?"nodebuffer"===e?new o(t):n.uint8array?new h(i.transformTo("uint8array",t)):new s(i.transformTo("array",t)):new a(t)}},{"../support":30,"../utils":32,"./ArrayReader":17,"./NodeBufferReader":19,"./StringReader":20,"./Uint8ArrayReader":21}],23:[function(t,e,r){"use strict";r.LOCAL_FILE_HEADER="PK",r.CENTRAL_FILE_HEADER="PK
",r.CENTRAL_DIRECTORY_END="PK",r.ZIP64_CENTRAL_DIRECTORY_LOCATOR="PK",r.ZIP64_CENTRAL_DIRECTORY_END="PK",r.DATA_DESCRIPTOR="PK\b"},{}],24:[function(t,e,r){"use strict";var i=t("./GenericWorker"),n=t("../utils");function s(t){i.call(this,"ConvertWorker to "+t),this.destType=t}n.inherits(s,i),s.prototype.processChunk=function(t){this.push({data:n.transformTo(this.destType,t.data),meta:t.meta})},e.exports=s},{"../utils":32,"./GenericWorker":28}],25:[function(t,e,r){"use strict";var i=t("./GenericWorker"),n=t("../crc32");function s(){i.call(this,"Crc32Probe"),this.withStreamInfo("crc32",0)}t("../utils").inherits(s,i),s.prototype.processChunk=function(t){this.streamInfo.crc32=n(t.data,this.streamInfo.crc32||0),this.push(t)},e.exports=s},{"../crc32":4,"../utils":32,"./GenericWorker":28}],26:[function(t,e,r){"use strict";var i=t("../utils"),n=t("./GenericWorker");function s(t){n.call(this,"DataLengthProbe for 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e=this;this.dataIsReady=!1,this.index=0,this.max=0,this.data=null,this.type="",this._tickScheduled=!1,t.then(function(t){e.dataIsReady=!0,e.data=t,e.max=t&&t.length||0,e.type=i.getTypeOf(t),e.isPaused||e._tickAndRepeat()},function(t){e.error(t)})}i.inherits(s,n),s.prototype.cleanUp=function(){n.prototype.cleanUp.call(this),this.data=null},s.prototype.resume=function(){return!!n.prototype.resume.call(this)&&(!this._tickScheduled&&this.dataIsReady&&(this._tickScheduled=!0,i.delay(this._tickAndRepeat,[],this)),!0)},s.prototype._tickAndRepeat=function(){this._tickScheduled=!1,this.isPaused||this.isFinished||(this._tick(),this.isFinished||(i.delay(this._tickAndRepeat,[],this),this._tickScheduled=!0))},s.prototype._tick=function(){if(this.isPaused||this.isFinished)return!1;var t=null,e=Math.min(this.max,this.index+16384);if(this.index>=this.max)return this.end();switch(this.type){case"string":t=this.data.substring(this.index,e);break;case"uint8array":t=this.data.subarray(this.index,e);break;case"array":case"nodebuffer":t=this.data.slice(this.index,e)}return this.index=e,this.push({data:t,meta:{percent:this.max?this.index/this.max*100:0}})},e.exports=s},{"../utils":32,"./GenericWorker":28}],28:[function(t,e,r){"use strict";function i(t){this.name=t||"default",this.streamInfo={},this.generatedError=null,this.extraStreamInfo={},this.isPaused=!0,this.isFinished=!1,this.isLocked=!1,this._listeners={data:[],end:[],error:[]},this.previous=null}i.prototype={push:function(t){this.emit("data",t)},end:function(){if(this.isFinished)return!1;this.flush();try{this.emit("end"),this.cleanUp(),this.isFinished=!0}catch(t){this.emit("error",t)}return!0},error:function(t){return!this.isFinished&&(this.isPaused?this.generatedError=t:(this.isFinished=!0,this.emit("error",t),this.previous&&this.previous.error(t),this.cleanUp()),!0)},on:function(t,e){return this._listeners[t].push(e),this},cleanUp:function(){this.streamInfo=this.generatedError=this.extraStreamInfo=null,this._listeners=[]},emit:function(t,e){if(this._listeners[t])for(var r=0;r<this._listeners[t].length;r++)this._listeners[t][r].call(this,e)},pipe:function(t){return t.registerPrevious(this)},registerPrevious:function(t){if(this.isLocked)throw new Error("The stream '"+this+"' has already been used.");this.streamInfo=t.streamInfo,this.mergeStreamInfo(),this.previous=t;var e=this;return t.on("data",function(t){e.processChunk(t)}),t.on("end",function(){e.end()}),t.on("error",function(t){e.error(t)}),this},pause:function(){return!this.isPaused&&!this.isFinished&&(this.isPaused=!0,this.previous&&this.previous.pause(),!0)},resume:function(){if(!this.isPaused||this.isFinished)return!1;var t=this.isPaused=!1;return this.generatedError&&(this.error(this.generatedError),t=!0),this.previous&&this.previous.resume(),!t},flush:function(){},processChunk:function(t){this.push(t)},withStreamInfo:function(t,e){return this.extraStreamInfo[t]=e,this.mergeStreamInfo(),this},mergeStreamInfo:function(){for(var t in this.extraStreamInfo)this.extraStreamInfo.hasOwnProperty(t)&&(this.streamInfo[t]=this.extraStreamInfo[t])},lock:function(){if(this.isLocked)throw new Error("The stream '"+this+"' has already been used.");this.isLocked=!0,this.previous&&this.previous.lock()},toString:function(){var t="Worker "+this.name;return this.previous?this.previous+" -> "+t:t}},e.exports=i},{}],29:[function(t,e,r){"use strict";var h=t("../utils"),n=t("./ConvertWorker"),s=t("./GenericWorker"),u=t("../base64"),i=t("../support"),a=t("../external"),o=null;if(i.nodestream)try{o=t("../nodejs/NodejsStreamOutputAdapter")}catch(t){}function l(t,o){return new a.Promise(function(e,r){var i=[],n=t._internalType,s=t._outputType,a=t._mimeType;t.on("data",function(t,e){i.push(t),o&&o(e)}).on("error",function(t){i=[],r(t)}).on("end",function(){try{var t=function(t,e,r){switch(t){case"blob":return h.newBlob(h.transformTo("arraybuffer",e),r);case"base64":return u.encode(e);default:return h.transformTo(t,e)}}(s,function(t,e){var r,i=0,n=null,s=0;for(r=0;r<e.length;r++)s+=e[r].length;switch(t){case"string":return e.join("");case"array":return Array.prototype.concat.apply([],e);case"uint8array":for(n=new Uint8Array(s),r=0;r<e.length;r++)n.set(e[r],i),i+=e[r].length;return n;case"nodebuffer":return Buffer.concat(e);default:throw new Error("concat : unsupported type '"+t+"'")}}(n,i),a);e(t)}catch(t){r(t)}i=[]}).resume()})}function f(t,e,r){var i=e;switch(e){case"blob":case"arraybuffer":i="uint8array";break;case"base64":i="string"}try{this._internalType=i,this._outputType=e,this._mimeType=r,h.checkSupport(i),this._worker=t.pipe(new n(i)),t.lock()}catch(t){this._worker=new s("error"),this._worker.error(t)}}f.prototype={accumulate:function(t){return l(this,t)},on:function(t,e){var r=this;return"data"===t?this._worker.on(t,function(t){e.call(r,t.data,t.meta)}):this._worker.on(t,function(){h.delay(e,arguments,r)}),this},resume:function(){return h.delay(this._worker.resume,[],this._worker),this},pause:function(){return this._worker.pause(),this},toNodejsStream:function(t){if(h.checkSupport("nodestream"),"nodebuffer"!==this._outputType)throw new Error(this._outputType+" is not supported by this method");return new o(this,{objectMode:"nodebuffer"!==this._outputType},t)}},e.exports=f},{"../base64":1,"../external":6,"../nodejs/NodejsStreamOutputAdapter":13,"../support":30,"../utils":32,"./ConvertWorker":24,"./GenericWorker":28}],30:[function(t,e,r){"use strict";if(r.base64=!0,r.array=!0,r.string=!0,r.arraybuffer="undefined"!=typeof ArrayBuffer&&"undefined"!=typeof Uint8Array,r.nodebuffer="undefined"!=typeof Buffer,r.uint8array="undefined"!=typeof Uint8Array,"undefined"==typeof ArrayBuffer)r.blob=!1;else{var i=new ArrayBuffer(0);try{r.blob=0===new Blob([i],{type:"application/zip"}).size}catch(t){try{var n=new(self.BlobBuilder||self.WebKitBlobBuilder||self.MozBlobBuilder||self.MSBlobBuilder);n.append(i),r.blob=0===n.getBlob("application/zip").size}catch(t){r.blob=!1}}}try{r.nodestream=!!t("readable-stream").Readable}catch(t){r.nodestream=!1}},{"readable-stream":16}],31:[function(t,e,s){"use strict";for(var o=t("./utils"),h=t("./support"),r=t("./nodejsUtils"),i=t("./stream/GenericWorker"),u=new Array(256),n=0;n<256;n++)u[n]=252<=n?6:248<=n?5:240<=n?4:224<=n?3:192<=n?2:1;u[254]=u[254]=1;function a(){i.call(this,"utf-8 decode"),this.leftOver=null}function l(){i.call(this,"utf-8 encode")}s.utf8encode=function(t){return h.nodebuffer?r.newBufferFrom(t,"utf-8"):function(t){var e,r,i,n,s,a=t.length,o=0;for(n=0;n<a;n++)55296==(64512&(r=t.charCodeAt(n)))&&n+1<a&&56320==(64512&(i=t.charCodeAt(n+1)))&&(r=65536+(r-55296<<10)+(i-56320),n++),o+=r<128?1:r<2048?2:r<65536?3:4;for(e=h.uint8array?new Uint8Array(o):new Array(o),n=s=0;s<o;n++)55296==(64512&(r=t.charCodeAt(n)))&&n+1<a&&56320==(64512&(i=t.charCodeAt(n+1)))&&(r=65536+(r-55296<<10)+(i-56320),n++),r<128?e[s++]=r:(r<2048?e[s++]=192|r>>>6:(r<65536?e[s++]=224|r>>>12:(e[s++]=240|r>>>18,e[s++]=128|r>>>12&63),e[s++]=128|r>>>6&63),e[s++]=128|63&r);return e}(t)},s.utf8decode=function(t){return h.nodebuffer?o.transformTo("nodebuffer",t).toString("utf-8"):function(t){var e,r,i,n,s=t.length,a=new Array(2*s);for(e=r=0;e<s;)if((i=t[e++])<128)a[r++]=i;else if(4<(n=u[i]))a[r++]=65533,e+=n-1;else{for(i&=2===n?31:3===n?15:7;1<n&&e<s;)i=i<<6|63&t[e++],n--;1<n?a[r++]=65533:i<65536?a[r++]=i:(i-=65536,a[r++]=55296|i>>10&1023,a[r++]=56320|1023&i)}return a.length!==r&&(a.subarray?a=a.subarray(0,r):a.length=r),o.applyFromCharCode(a)}(t=o.transformTo(h.uint8array?"uint8array":"array",t))},o.inherits(a,i),a.prototype.processChunk=function(t){var e=o.transformTo(h.uint8array?"uint8array":"array",t.data);if(this.leftOver&&this.leftOver.length){if(h.uint8array){var r=e;(e=new Uint8Array(r.length+this.leftOver.length)).set(this.leftOver,0),e.set(r,this.leftOver.length)}else e=this.leftOver.concat(e);this.leftOver=null}var i=function(t,e){var r;for((e=e||t.length)>t.length&&(e=t.length),r=e-1;0<=r&&128==(192&t[r]);)r--;return r<0?e:0===r?e:r+u[t[r]]>e?r:e}(e),n=e;i!==e.length&&(h.uint8array?(n=e.subarray(0,i),this.leftOver=e.subarray(i,e.length)):(n=e.slice(0,i),this.leftOver=e.slice(i,e.length))),this.push({data:s.utf8decode(n),meta:t.meta})},a.prototype.flush=function(){this.leftOver&&this.leftOver.length&&(this.push({data:s.utf8decode(this.leftOver),meta:{}}),this.leftOver=null)},s.Utf8DecodeWorker=a,o.inherits(l,i),l.prototype.processChunk=function(t){this.push({data:s.utf8encode(t.data),meta:t.meta})},s.Utf8EncodeWorker=l},{"./nodejsUtils":14,"./stream/GenericWorker":28,"./support":30,"./utils":32}],32:[function(t,e,a){"use strict";var o=t("./support"),h=t("./base64"),r=t("./nodejsUtils"),i=t("set-immediate-shim"),u=t("./external");function n(t){return t}function l(t,e){for(var r=0;r<t.length;++r)e[r]=255&t.charCodeAt(r);return e}a.newBlob=function(e,r){a.checkSupport("blob");try{return new Blob([e],{type:r})}catch(t){try{var i=new(self.BlobBuilder||self.WebKitBlobBuilder||self.MozBlobBuilder||self.MSBlobBuilder);return i.append(e),i.getBlob(r)}catch(t){throw new Error("Bug : can't construct the Blob.")}}};var s={stringifyByChunk:function(t,e,r){var i=[],n=0,s=t.length;if(s<=r)return String.fromCharCode.apply(null,t);for(;n<s;)"array"===e||"nodebuffer"===e?i.push(String.fromCharCode.apply(null,t.slice(n,Math.min(n+r,s)))):i.push(String.fromCharCode.apply(null,t.subarray(n,Math.min(n+r,s)))),n+=r;return i.join("")},stringifyByChar:function(t){for(var e="",r=0;r<t.length;r++)e+=String.fromCharCode(t[r]);return e},applyCanBeUsed:{uint8array:function(){try{return o.uint8array&&1===String.fromCharCode.apply(null,new Uint8Array(1)).length}catch(t){return!1}}(),nodebuffer:function(){try{return o.nodebuffer&&1===String.fromCharCode.apply(null,r.allocBuffer(1)).length}catch(t){return!1}}()}};function f(t){var e=65536,r=a.getTypeOf(t),i=!0;if("uint8array"===r?i=s.applyCanBeUsed.uint8array:"nodebuffer"===r&&(i=s.applyCanBeUsed.nodebuffer),i)for(;1<e;)try{return s.stringifyByChunk(t,r,e)}catch(t){e=Math.floor(e/2)}return s.stringifyByChar(t)}function d(t,e){for(var r=0;r<t.length;r++)e[r]=t[r];return e}a.applyFromCharCode=f;var c={};c.string={string:n,array:function(t){return l(t,new Array(t.length))},arraybuffer:function(t){return c.string.uint8array(t).buffer},uint8array:function(t){return l(t,new Uint8Array(t.length))},nodebuffer:function(t){return l(t,r.allocBuffer(t.length))}},c.array={string:f,array:n,arraybuffer:function(t){return new Uint8Array(t).buffer},uint8array:function(t){return new Uint8Array(t)},nodebuffer:function(t){return r.newBufferFrom(t)}},c.arraybuffer={string:function(t){return f(new Uint8Array(t))},array:function(t){return d(new Uint8Array(t),new Array(t.byteLength))},arraybuffer:n,uint8array:function(t){return new Uint8Array(t)},nodebuffer:function(t){return r.newBufferFrom(new Uint8Array(t))}},c.uint8array={string:f,array:function(t){return d(t,new Array(t.length))},arraybuffer:function(t){return t.buffer},uint8array:n,nodebuffer:function(t){return r.newBufferFrom(t)}},c.nodebuffer={string:f,array:function(t){return d(t,new Array(t.length))},arraybuffer:function(t){return c.nodebuffer.uint8array(t).buffer},uint8array:function(t){return d(t,new Uint8Array(t.length))},nodebuffer:n},a.transformTo=function(t,e){if(e=e||"",!t)return e;a.checkSupport(t);var r=a.getTypeOf(e);return c[r][t](e)},a.getTypeOf=function(t){return"string"==typeof t?"string":"[object Array]"===Object.prototype.toString.call(t)?"array":o.nodebuffer&&r.isBuffer(t)?"nodebuffer":o.uint8array&&t instanceof Uint8Array?"uint8array":o.arraybuffer&&t instanceof ArrayBuffer?"arraybuffer":void 0},a.checkSupport=function(t){if(!o[t.toLowerCase()])throw new Error(t+" is not supported by this platform")},a.MAX_VALUE_16BITS=65535,a.MAX_VALUE_32BITS=-1,a.pretty=function(t){var e,r,i="";for(r=0;r<(t||"").length;r++)i+="\\x"+((e=t.charCodeAt(r))<16?"0":"")+e.toString(16).toUpperCase();return i},a.delay=function(t,e,r){i(function(){t.apply(r||null,e||[])})},a.inherits=function(t,e){function r(){}r.prototype=e.prototype,t.prototype=new r},a.extend=function(){var t,e,r={};for(t=0;t<arguments.length;t++)for(e in arguments[t])arguments[t].hasOwnProperty(e)&&void 0===r[e]&&(r[e]=arguments[t][e]);return r},a.prepareContent=function(r,t,i,n,s){return u.Promise.resolve(t).then(function(i){return o.blob&&(i instanceof Blob||-1!==["[object File]","[object Blob]"].indexOf(Object.prototype.toString.call(i)))&&"undefined"!=typeof FileReader?new u.Promise(function(e,r){var t=new FileReader;t.onload=function(t){e(t.target.result)},t.onerror=function(t){r(t.target.error)},t.readAsArrayBuffer(i)}):i}).then(function(t){var e=a.getTypeOf(t);return e?("arraybuffer"===e?t=a.transformTo("uint8array",t):"string"===e&&(s?t=h.decode(t):i&&!0!==n&&(t=function(t){return l(t,o.uint8array?new Uint8Array(t.length):new Array(t.length))}(t))),t):u.Promise.reject(new Error("Can't read the data of '"+r+"'. Is it in a supported JavaScript type (String, Blob, ArrayBuffer, etc) ?"))})}},{"./base64":1,"./external":6,"./nodejsUtils":14,"./support":30,"set-immediate-shim":54}],33:[function(t,e,r){"use strict";var i=t("./reader/readerFor"),n=t("./utils"),s=t("./signature"),a=t("./zipEntry"),o=(t("./utf8"),t("./support"));function h(t){this.files=[],this.loadOptions=t}h.prototype={checkSignature:function(t){if(!this.reader.readAndCheckSignature(t)){this.reader.index-=4;var e=this.reader.readString(4);throw new Error("Corrupted zip or bug: unexpected signature ("+n.pretty(e)+", expected "+n.pretty(t)+")")}},isSignature:function(t,e){var r=this.reader.index;this.reader.setIndex(t);var i=this.reader.readString(4)===e;return this.reader.setIndex(r),i},readBlockEndOfCentral:function(){this.diskNumber=this.reader.readInt(2),this.diskWithCentralDirStart=this.reader.readInt(2),this.centralDirRecordsOnThisDisk=this.reader.readInt(2),this.centralDirRecords=this.reader.readInt(2),this.centralDirSize=this.reader.readInt(4),this.centralDirOffset=this.reader.readInt(4),this.zipCommentLength=this.reader.readInt(2);var t=this.reader.readData(this.zipCommentLength),e=o.uint8array?"uint8array":"array",r=n.transformTo(e,t);this.zipComment=this.loadOptions.decodeFileName(r)},readBlockZip64EndOfCentral:function(){this.zip64EndOfCentralSize=this.reader.readInt(8),this.reader.skip(4),this.diskNumber=this.reader.readInt(4),this.diskWithCentralDirStart=this.reader.readInt(4),this.centralDirRecordsOnThisDisk=this.reader.readInt(8),this.centralDirRecords=this.reader.readInt(8),this.centralDirSize=this.reader.readInt(8),this.centralDirOffset=this.reader.readInt(8),this.zip64ExtensibleData={};for(var t,e,r,i=this.zip64EndOfCentralSize-44;0<i;)t=this.reader.readInt(2),e=this.reader.readInt(4),r=this.reader.readData(e),this.zip64ExtensibleData[t]={id:t,length:e,value:r}},readBlockZip64EndOfCentralLocator:function(){if(this.diskWithZip64CentralDirStart=this.reader.readInt(4),this.relativeOffsetEndOfZip64CentralDir=this.reader.readInt(8),this.disksCount=this.reader.readInt(4),1<this.disksCount)throw new Error("Multi-volumes zip are not supported")},readLocalFiles:function(){var t,e;for(t=0;t<this.files.length;t++)e=this.files[t],this.reader.setIndex(e.localHeaderOffset),this.checkSignature(s.LOCAL_FILE_HEADER),e.readLocalPart(this.reader),e.handleUTF8(),e.processAttributes()},readCentralDir:function(){var t;for(this.reader.setIndex(this.centralDirOffset);this.reader.readAndCheckSignature(s.CENTRAL_FILE_HEADER);)(t=new a({zip64:this.zip64},this.loadOptions)).readCentralPart(this.reader),this.files.push(t);if(this.centralDirRecords!==this.files.length&&0!==this.centralDirRecords&&0===this.files.length)throw new Error("Corrupted zip or bug: expected "+this.centralDirRecords+" records in central dir, got "+this.files.length)},readEndOfCentral:function(){var t=this.reader.lastIndexOfSignature(s.CENTRAL_DIRECTORY_END);if(t<0)throw!this.isSignature(0,s.LOCAL_FILE_HEADER)?new Error("Can't find end of central directory : is this a zip file ? If it is, see https://stuk.github.io/jszip/documentation/howto/read_zip.html"):new Error("Corrupted zip: can't find end of central directory");this.reader.setIndex(t);var e=t;if(this.checkSignature(s.CENTRAL_DIRECTORY_END),this.readBlockEndOfCentral(),this.diskNumber===n.MAX_VALUE_16BITS||this.diskWithCentralDirStart===n.MAX_VALUE_16BITS||this.centralDirRecordsOnThisDisk===n.MAX_VALUE_16BITS||this.centralDirRecords===n.MAX_VALUE_16BITS||this.centralDirSize===n.MAX_VALUE_32BITS||this.centralDirOffset===n.MAX_VALUE_32BITS){if(this.zip64=!0,(t=this.reader.lastIndexOfSignature(s.ZIP64_CENTRAL_DIRECTORY_LOCATOR))<0)throw new Error("Corrupted zip: can't find the ZIP64 end of central directory locator");if(this.reader.setIndex(t),this.checkSignature(s.ZIP64_CENTRAL_DIRECTORY_LOCATOR),this.readBlockZip64EndOfCentralLocator(),!this.isSignature(this.relativeOffsetEndOfZip64CentralDir,s.ZIP64_CENTRAL_DIRECTORY_END)&&(this.relativeOffsetEndOfZip64CentralDir=this.reader.lastIndexOfSignature(s.ZIP64_CENTRAL_DIRECTORY_END),this.relativeOffsetEndOfZip64CentralDir<0))throw new Error("Corrupted zip: can't find the ZIP64 end of central directory");this.reader.setIndex(this.relativeOffsetEndOfZip64CentralDir),this.checkSignature(s.ZIP64_CENTRAL_DIRECTORY_END),this.readBlockZip64EndOfCentral()}var r=this.centralDirOffset+this.centralDirSize;this.zip64&&(r+=20,r+=12+this.zip64EndOfCentralSize);var i=e-r;if(0<i)this.isSignature(e,s.CENTRAL_FILE_HEADER)||(this.reader.zero=i);else if(i<0)throw new Error("Corrupted zip: missing "+Math.abs(i)+" bytes.")},prepareReader:function(t){this.reader=i(t)},load:function(t){this.prepareReader(t),this.readEndOfCentral(),this.readCentralDir(),this.readLocalFiles()}},e.exports=h},{"./reader/readerFor":22,"./signature":23,"./support":30,"./utf8":31,"./utils":32,"./zipEntry":34}],34:[function(t,e,r){"use strict";var i=t("./reader/readerFor"),s=t("./utils"),n=t("./compressedObject"),a=t("./crc32"),o=t("./utf8"),h=t("./compressions"),u=t("./support");function l(t,e){this.options=t,this.loadOptions=e}l.prototype={isEncrypted:function(){return 1==(1&this.bitFlag)},useUTF8:function(){return 2048==(2048&this.bitFlag)},readLocalPart:function(t){var e,r;if(t.skip(22),this.fileNameLength=t.readInt(2),r=t.readInt(2),this.fileName=t.readData(this.fileNameLength),t.skip(r),-1===this.compressedSize||-1===this.uncompressedSize)throw new Error("Bug or corrupted zip : didn't get enough information from the central directory (compressedSize === -1 || uncompressedSize === -1)");if(null===(e=function(t){for(var e in h)if(h.hasOwnProperty(e)&&h[e].magic===t)return h[e];return null}(this.compressionMethod)))throw new Error("Corrupted zip : compression "+s.pretty(this.compressionMethod)+" unknown (inner file : "+s.transformTo("string",this.fileName)+")");this.decompressed=new n(this.compressedSize,this.uncompressedSize,this.crc32,e,t.readData(this.compressedSize))},readCentralPart:function(t){this.versionMadeBy=t.readInt(2),t.skip(2),this.bitFlag=t.readInt(2),this.compressionMethod=t.readString(2),this.date=t.readDate(),this.crc32=t.readInt(4),this.compressedSize=t.readInt(4),this.uncompressedSize=t.readInt(4);var e=t.readInt(2);if(this.extraFieldsLength=t.readInt(2),this.fileCommentLength=t.readInt(2),this.diskNumberStart=t.readInt(2),this.internalFileAttributes=t.readInt(2),this.externalFileAttributes=t.readInt(4),this.localHeaderOffset=t.readInt(4),this.isEncrypted())throw new Error("Encrypted zip are not supported");t.skip(e),this.readExtraFields(t),this.parseZIP64ExtraField(t),this.fileComment=t.readData(this.fileCommentLength)},processAttributes:function(){this.unixPermissions=null,this.dosPermissions=null;var t=this.versionMadeBy>>8;this.dir=!!(16&this.externalFileAttributes),0==t&&(this.dosPermissions=63&this.externalFileAttributes),3==t&&(this.unixPermissions=this.externalFileAttributes>>16&65535),this.dir||"/"!==this.fileNameStr.slice(-1)||(this.dir=!0)},parseZIP64ExtraField:function(t){if(this.extraFields[1]){var e=i(this.extraFields[1].value);this.uncompressedSize===s.MAX_VALUE_32BITS&&(this.uncompressedSize=e.readInt(8)),this.compressedSize===s.MAX_VALUE_32BITS&&(this.compressedSize=e.readInt(8)),this.localHeaderOffset===s.MAX_VALUE_32BITS&&(this.localHeaderOffset=e.readInt(8)),this.diskNumberStart===s.MAX_VALUE_32BITS&&(this.diskNumberStart=e.readInt(4))}},readExtraFields:function(t){var e,r,i,n=t.index+this.extraFieldsLength;for(this.extraFields||(this.extraFields={});t.index<n;)e=t.readInt(2),r=t.readInt(2),i=t.readData(r),this.extraFields[e]={id:e,length:r,value:i}},handleUTF8:function(){var t=u.uint8array?"uint8array":"array";if(this.useUTF8())this.fileNameStr=o.utf8decode(this.fileName),this.fileCommentStr=o.utf8decode(this.fileComment);else{var e=this.findExtraFieldUnicodePath();if(null!==e)this.fileNameStr=e;else{var r=s.transformTo(t,this.fileName);this.fileNameStr=this.loadOptions.decodeFileName(r)}var i=this.findExtraFieldUnicodeComment();if(null!==i)this.fileCommentStr=i;else{var n=s.transformTo(t,this.fileComment);this.fileCommentStr=this.loadOptions.decodeFileName(n)}}},findExtraFieldUnicodePath:function(){var t=this.extraFields[28789];if(t){var e=i(t.value);return 1!==e.readInt(1)?null:a(this.fileName)!==e.readInt(4)?null:o.utf8decode(e.readData(t.length-5))}return null},findExtraFieldUnicodeComment:function(){var t=this.extraFields[25461];if(t){var e=i(t.value);return 1!==e.readInt(1)?null:a(this.fileComment)!==e.readInt(4)?null:o.utf8decode(e.readData(t.length-5))}return null}},e.exports=l},{"./compressedObject":2,"./compressions":3,"./crc32":4,"./reader/readerFor":22,"./support":30,"./utf8":31,"./utils":32}],35:[function(t,e,r){"use strict";function i(t,e,r){this.name=t,this.dir=r.dir,this.date=r.date,this.comment=r.comment,this.unixPermissions=r.unixPermissions,this.dosPermissions=r.dosPermissions,this._data=e,this._dataBinary=r.binary,this.options={compression:r.compression,compressionOptions:r.compressionOptions}}var s=t("./stream/StreamHelper"),n=t("./stream/DataWorker"),a=t("./utf8"),o=t("./compressedObject"),h=t("./stream/GenericWorker");i.prototype={internalStream:function(t){var e=null,r="string";try{if(!t)throw new Error("No output type specified.");var i="string"===(r=t.toLowerCase())||"text"===r;"binarystring"!==r&&"text"!==r||(r="string"),e=this._decompressWorker();var n=!this._dataBinary;n&&!i&&(e=e.pipe(new a.Utf8EncodeWorker)),!n&&i&&(e=e.pipe(new a.Utf8DecodeWorker))}catch(t){(e=new h("error")).error(t)}return new s(e,r,"")},async:function(t,e){return this.internalStream(t).accumulate(e)},nodeStream:function(t,e){return this.internalStream(t||"nodebuffer").toNodejsStream(e)},_compressWorker:function(t,e){if(this._data instanceof o&&this._data.compression.magic===t.magic)return this._data.getCompressedWorker();var r=this._decompressWorker();return this._dataBinary||(r=r.pipe(new a.Utf8EncodeWorker)),o.createWorkerFrom(r,t,e)},_decompressWorker:function(){return this._data instanceof o?this._data.getContentWorker():this._data instanceof h?this._data:new n(this._data)}};for(var u=["asText","asBinary","asNodeBuffer","asUint8Array","asArrayBuffer"],l=function(){throw new Error("This method has been removed in JSZip 3.0, please check the upgrade 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r,i;;){if(t.lookahead<z){if(j(t),t.lookahead<z&&e===l)return A;if(0===t.lookahead)break}if(r=0,t.lookahead>=x&&(t.ins_h=(t.ins_h<<t.hash_shift^t.window[t.strstart+x-1])&t.hash_mask,r=t.prev[t.strstart&t.w_mask]=t.head[t.ins_h],t.head[t.ins_h]=t.strstart),0!==r&&t.strstart-r<=t.w_size-z&&(t.match_length=L(t,r)),t.match_length>=x)if(i=u._tr_tally(t,t.strstart-t.match_start,t.match_length-x),t.lookahead-=t.match_length,t.match_length<=t.max_lazy_match&&t.lookahead>=x){for(t.match_length--;t.strstart++,t.ins_h=(t.ins_h<<t.hash_shift^t.window[t.strstart+x-1])&t.hash_mask,r=t.prev[t.strstart&t.w_mask]=t.head[t.ins_h],t.head[t.ins_h]=t.strstart,0!=--t.match_length;);t.strstart++}else t.strstart+=t.match_length,t.match_length=0,t.ins_h=t.window[t.strstart],t.ins_h=(t.ins_h<<t.hash_shift^t.window[t.strstart+1])&t.hash_mask;else i=u._tr_tally(t,0,t.window[t.strstart]),t.lookahead--,t.strstart++;if(i&&(N(t,!1),0===t.strm.avail_out))return A}return t.insert=t.strstart<x-1?t.strstart:x-1,e===f?(N(t,!0),0===t.strm.avail_out?O:B):t.last_lit&&(N(t,!1),0===t.strm.avail_out)?A:I}function W(t,e){for(var r,i,n;;){if(t.lookahead<z){if(j(t),t.lookahead<z&&e===l)return 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if(t.match_available){if((i=u._tr_tally(t,0,t.window[t.strstart-1]))&&N(t,!1),t.strstart++,t.lookahead--,0===t.strm.avail_out)return A}else t.match_available=1,t.strstart++,t.lookahead--}return t.match_available&&(i=u._tr_tally(t,0,t.window[t.strstart-1]),t.match_available=0),t.insert=t.strstart<x-1?t.strstart:x-1,e===f?(N(t,!0),0===t.strm.avail_out?O:B):t.last_lit&&(N(t,!1),0===t.strm.avail_out)?A:I}function M(t,e,r,i,n){this.good_length=t,this.max_lazy=e,this.nice_length=r,this.max_chain=i,this.func=n}function H(){this.strm=null,this.status=0,this.pending_buf=null,this.pending_buf_size=0,this.pending_out=0,this.pending=0,this.wrap=0,this.gzhead=null,this.gzindex=0,this.method=v,this.last_flush=-1,this.w_size=0,this.w_bits=0,this.w_mask=0,this.window=null,this.window_size=0,this.prev=null,this.head=null,this.ins_h=0,this.hash_size=0,this.hash_bits=0,this.hash_mask=0,this.hash_shift=0,this.block_start=0,this.match_length=0,this.prev_match=0,this.match_available=0,this.strstart=0,this.match_start=0,this.lookahead=0,this.prev_length=0,this.max_chain_length=0,this.max_lazy_match=0,this.level=0,this.strategy=0,this.good_match=0,this.nice_match=0,this.dyn_ltree=new d.Buf16(2*w),this.dyn_dtree=new d.Buf16(2*(2*a+1)),this.bl_tree=new d.Buf16(2*(2*o+1)),D(this.dyn_ltree),D(this.dyn_dtree),D(this.bl_tree),this.l_desc=null,this.d_desc=null,this.bl_desc=null,this.bl_count=new d.Buf16(k+1),this.heap=new d.Buf16(2*s+1),D(this.heap),this.heap_len=0,this.heap_max=0,this.depth=new d.Buf16(2*s+1),D(this.depth),this.l_buf=0,this.lit_bufsize=0,this.last_lit=0,this.d_buf=0,this.opt_len=0,this.static_len=0,this.matches=0,this.insert=0,this.bi_buf=0,this.bi_valid=0}function G(t){var e;return t&&t.state?(t.total_in=t.total_out=0,t.data_type=n,(e=t.state).pending=0,e.pending_out=0,e.wrap<0&&(e.wrap=-e.wrap),e.status=e.wrap?C:E,t.adler=2===e.wrap?0:1,e.last_flush=l,u._tr_init(e),m):R(t,_)}function K(t){var e=G(t);return e===m&&function(t){t.window_size=2*t.w_size,D(t.head),t.max_lazy_match=h[t.level].max_lazy,t.good_match=h[t.level].good_length,t.nice_match=h[t.level].nice_length,t.max_chain_length=h[t.level].max_chain,t.strstart=0,t.block_start=0,t.lookahead=0,t.insert=0,t.match_length=t.prev_length=x-1,t.match_available=0,t.ins_h=0}(t.state),e}function Y(t,e,r,i,n,s){if(!t)return _;var a=1;if(e===g&&(e=6),i<0?(a=0,i=-i):15<i&&(a=2,i-=16),n<1||y<n||r!==v||i<8||15<i||e<0||9<e||s<0||b<s)return R(t,_);8===i&&(i=9);var o=new H;return(t.state=o).strm=t,o.wrap=a,o.gzhead=null,o.w_bits=i,o.w_size=1<<o.w_bits,o.w_mask=o.w_size-1,o.hash_bits=n+7,o.hash_size=1<<o.hash_bits,o.hash_mask=o.hash_size-1,o.hash_shift=~~((o.hash_bits+x-1)/x),o.window=new d.Buf8(2*o.w_size),o.head=new d.Buf16(o.hash_size),o.prev=new d.Buf16(o.w_size),o.lit_bufsize=1<<n+6,o.pending_buf_size=4*o.lit_bufsize,o.pending_buf=new d.Buf8(o.pending_buf_size),o.d_buf=1*o.lit_bufsize,o.l_buf=3*o.lit_bufsize,o.level=e,o.strategy=s,o.method=r,K(t)}h=[new M(0,0,0,0,function(t,e){var r=65535;for(r>t.pending_buf_size-5&&(r=t.pending_buf_size-5);;){if(t.lookahead<=1){if(j(t),0===t.lookahead&&e===l)return A;if(0===t.lookahead)break}t.strstart+=t.lookahead,t.lookahead=0;var i=t.block_start+r;if((0===t.strstart||t.strstart>=i)&&(t.lookahead=t.strstart-i,t.strstart=i,N(t,!1),0===t.strm.avail_out))return A;if(t.strstart-t.block_start>=t.w_size-z&&(N(t,!1),0===t.strm.avail_out))return A}return t.insert=0,e===f?(N(t,!0),0===t.strm.avail_out?O:B):(t.strstart>t.block_start&&(N(t,!1),t.strm.avail_out),A)}),new M(4,4,8,4,Z),new M(4,5,16,8,Z),new M(4,6,32,32,Z),new M(4,4,16,16,W),new M(8,16,32,32,W),new M(8,16,128,128,W),new M(8,32,128,256,W),new M(32,128,258,1024,W),new M(32,258,258,4096,W)],r.deflateInit=function(t,e){return Y(t,e,v,15,8,0)},r.deflateInit2=Y,r.deflateReset=K,r.deflateResetKeep=G,r.deflateSetHeader=function(t,e){return t&&t.state?2!==t.state.wrap?_:(t.state.gzhead=e,m):_},r.deflate=function(t,e){var r,i,n,s;if(!t||!t.state||5<e||e<0)return t?R(t,_):_;if(i=t.state,!t.output||!t.input&&0!==t.avail_in||666===i.status&&e!==f)return R(t,0===t.avail_out?-5:_);if(i.strm=t,r=i.last_flush,i.last_flush=e,i.status===C)if(2===i.wrap)t.adler=0,U(i,31),U(i,139),U(i,8),i.gzhead?(U(i,(i.gzhead.text?1:0)+(i.gzhead.hcrc?2:0)+(i.gzhead.extra?4:0)+(i.gzhead.name?8:0)+(i.gzhead.comment?16:0)),U(i,255&i.gzhead.time),U(i,i.gzhead.time>>8&255),U(i,i.gzhead.time>>16&255),U(i,i.gzhead.time>>24&255),U(i,9===i.level?2:2<=i.strategy||i.level<2?4:0),U(i,255&i.gzhead.os),i.gzhead.extra&&i.gzhead.extra.length&&(U(i,255&i.gzhead.extra.length),U(i,i.gzhead.extra.length>>8&255)),i.gzhead.hcrc&&(t.adler=p(t.adler,i.pending_buf,i.pending,0)),i.gzindex=0,i.status=69):(U(i,0),U(i,0),U(i,0),U(i,0),U(i,0),U(i,9===i.level?2:2<=i.strategy||i.level<2?4:0),U(i,3),i.status=E);else{var a=v+(i.w_bits-8<<4)<<8;a|=(2<=i.strategy||i.level<2?0:i.level<6?1:6===i.level?2:3)<<6,0!==i.strstart&&(a|=32),a+=31-a%31,i.status=E,P(i,a),0!==i.strstart&&(P(i,t.adler>>>16),P(i,65535&t.adler)),t.adler=1}if(69===i.status)if(i.gzhead.extra){for(n=i.pending;i.gzindex<(65535&i.gzhead.extra.length)&&(i.pending!==i.pending_buf_size||(i.gzhead.hcrc&&i.pending>n&&(t.adler=p(t.adler,i.pending_buf,i.pending-n,n)),F(t),n=i.pending,i.pending!==i.pending_buf_size));)U(i,255&i.gzhead.extra[i.gzindex]),i.gzindex++;i.gzhead.hcrc&&i.pending>n&&(t.adler=p(t.adler,i.pending_buf,i.pending-n,n)),i.gzindex===i.gzhead.extra.length&&(i.gzindex=0,i.status=73)}else i.status=73;if(73===i.status)if(i.gzhead.name){n=i.pending;do{if(i.pending===i.pending_buf_size&&(i.gzhead.hcrc&&i.pending>n&&(t.adler=p(t.adler,i.pending_buf,i.pending-n,n)),F(t),n=i.pending,i.pending===i.pending_buf_size)){s=1;break}s=i.gzindex<i.gzhead.name.length?255&i.gzhead.name.charCodeAt(i.gzindex++):0,U(i,s)}while(0!==s);i.gzhead.hcrc&&i.pending>n&&(t.adler=p(t.adler,i.pending_buf,i.pending-n,n)),0===s&&(i.gzindex=0,i.status=91)}else i.status=91;if(91===i.status)if(i.gzhead.comment){n=i.pending;do{if(i.pending===i.pending_buf_size&&(i.gzhead.hcrc&&i.pending>n&&(t.adler=p(t.adler,i.pending_buf,i.pending-n,n)),F(t),n=i.pending,i.pending===i.pending_buf_size)){s=1;break}s=i.gzindex<i.gzhead.comment.length?255&i.gzhead.comment.charCodeAt(i.gzindex++):0,U(i,s)}while(0!==s);i.gzhead.hcrc&&i.pending>n&&(t.adler=p(t.adler,i.pending_buf,i.pending-n,n)),0===s&&(i.status=103)}else i.status=103;if(103===i.status&&(i.gzhead.hcrc?(i.pending+2>i.pending_buf_size&&F(t),i.pending+2<=i.pending_buf_size&&(U(i,255&t.adler),U(i,t.adler>>8&255),t.adler=0,i.status=E)):i.status=E),0!==i.pending){if(F(t),0===t.avail_out)return i.last_flush=-1,m}else if(0===t.avail_in&&T(e)<=T(r)&&e!==f)return R(t,-5);if(666===i.status&&0!==t.avail_in)return R(t,-5);if(0!==t.avail_in||0!==i.lookahead||e!==l&&666!==i.status){var o=2===i.strategy?function(t,e){for(var r;;){if(0===t.lookahead&&(j(t),0===t.lookahead)){if(e===l)return A;break}if(t.match_length=0,r=u._tr_tally(t,0,t.window[t.strstart]),t.lookahead--,t.strstart++,r&&(N(t,!1),0===t.strm.avail_out))return A}return t.insert=0,e===f?(N(t,!0),0===t.strm.avail_out?O:B):t.last_lit&&(N(t,!1),0===t.strm.avail_out)?A:I}(i,e):3===i.strategy?function(t,e){for(var r,i,n,s,a=t.window;;){if(t.lookahead<=S){if(j(t),t.lookahead<=S&&e===l)return A;if(0===t.lookahead)break}if(t.match_length=0,t.lookahead>=x&&0<t.strstart&&(i=a[n=t.strstart-1])===a[++n]&&i===a[++n]&&i===a[++n]){s=t.strstart+S;do{}while(i===a[++n]&&i===a[++n]&&i===a[++n]&&i===a[++n]&&i===a[++n]&&i===a[++n]&&i===a[++n]&&i===a[++n]&&n<s);t.match_length=S-(s-n),t.match_length>t.lookahead&&(t.match_length=t.lookahead)}if(t.match_length>=x?(r=u._tr_tally(t,1,t.match_length-x),t.lookahead-=t.match_length,t.strstart+=t.match_length,t.match_length=0):(r=u._tr_tally(t,0,t.window[t.strstart]),t.lookahead--,t.strstart++),r&&(N(t,!1),0===t.strm.avail_out))return A}return t.insert=0,e===f?(N(t,!0),0===t.strm.avail_out?O:B):t.last_lit&&(N(t,!1),0===t.strm.avail_out)?A:I}(i,e):h[i.level].func(i,e);if(o!==O&&o!==B||(i.status=666),o===A||o===O)return 0===t.avail_out&&(i.last_flush=-1),m;if(o===I&&(1===e?u._tr_align(i):5!==e&&(u._tr_stored_block(i,0,0,!1),3===e&&(D(i.head),0===i.lookahead&&(i.strstart=0,i.block_start=0,i.insert=0))),F(t),0===t.avail_out))return i.last_flush=-1,m}return e!==f?m:i.wrap<=0?1:(2===i.wrap?(U(i,255&t.adler),U(i,t.adler>>8&255),U(i,t.adler>>16&255),U(i,t.adler>>24&255),U(i,255&t.total_in),U(i,t.total_in>>8&255),U(i,t.total_in>>16&255),U(i,t.total_in>>24&255)):(P(i,t.adler>>>16),P(i,65535&t.adler)),F(t),0<i.wrap&&(i.wrap=-i.wrap),0!==i.pending?m:1)},r.deflateEnd=function(t){var e;return t&&t.state?(e=t.state.status)!==C&&69!==e&&73!==e&&91!==e&&103!==e&&e!==E&&666!==e?R(t,_):(t.state=null,e===E?R(t,-3):m):_},r.deflateSetDictionary=function(t,e){var r,i,n,s,a,o,h,u,l=e.length;if(!t||!t.state)return _;if(2===(s=(r=t.state).wrap)||1===s&&r.status!==C||r.lookahead)return _;for(1===s&&(t.adler=c(t.adler,e,l,0)),r.wrap=0,l>=r.w_size&&(0===s&&(D(r.head),r.strstart=0,r.block_start=0,r.insert=0),u=new d.Buf8(r.w_size),d.arraySet(u,e,l-r.w_size,r.w_size,0),e=u,l=r.w_size),a=t.avail_in,o=t.next_in,h=t.input,t.avail_in=l,t.next_in=0,t.input=e,j(r);r.lookahead>=x;){for(i=r.strstart,n=r.lookahead-(x-1);r.ins_h=(r.ins_h<<r.hash_shift^r.window[i+x-1])&r.hash_mask,r.prev[i&r.w_mask]=r.head[r.ins_h],r.head[r.ins_h]=i,i++,--n;);r.strstart=i,r.lookahead=x-1,j(r)}return r.strstart+=r.lookahead,r.block_start=r.strstart,r.insert=r.lookahead,r.lookahead=0,r.match_length=r.prev_length=x-1,r.match_available=0,t.next_in=o,t.input=h,t.avail_in=a,r.wrap=s,m},r.deflateInfo="pako deflate (from Nodeca project)"},{"../utils/common":41,"./adler32":43,"./crc32":45,"./messages":51,"./trees":52}],47:[function(t,e,r){"use strict";e.exports=function(){this.text=0,this.time=0,this.xflags=0,this.os=0,this.extra=null,this.extra_len=0,this.name="",this.comment="",this.hcrc=0,this.done=!1}},{}],48:[function(t,e,r){"use strict";e.exports=function(t,e){var r,i,n,s,a,o,h,u,l,f,d,c,p,m,_,g,b,v,y,w,k,x,S,z,C;r=t.state,i=t.next_in,z=t.input,n=i+(t.avail_in-5),s=t.next_out,C=t.output,a=s-(e-t.avail_out),o=s+(t.avail_out-257),h=r.dmax,u=r.wsize,l=r.whave,f=r.wnext,d=r.window,c=r.hold,p=r.bits,m=r.lencode,_=r.distcode,g=(1<<r.lenbits)-1,b=(1<<r.distbits)-1;t:do{p<15&&(c+=z[i++]<<p,p+=8,c+=z[i++]<<p,p+=8),v=m[c&g];e:for(;;){if(c>>>=y=v>>>24,p-=y,0===(y=v>>>16&255))C[s++]=65535&v;else{if(!(16&y)){if(0==(64&y)){v=m[(65535&v)+(c&(1<<y)-1)];continue e}if(32&y){r.mode=12;break t}t.msg="invalid literal/length code",r.mode=30;break t}w=65535&v,(y&=15)&&(p<y&&(c+=z[i++]<<p,p+=8),w+=c&(1<<y)-1,c>>>=y,p-=y),p<15&&(c+=z[i++]<<p,p+=8,c+=z[i++]<<p,p+=8),v=_[c&b];r:for(;;){if(c>>>=y=v>>>24,p-=y,!(16&(y=v>>>16&255))){if(0==(64&y)){v=_[(65535&v)+(c&(1<<y)-1)];continue r}t.msg="invalid distance code",r.mode=30;break t}if(k=65535&v,p<(y&=15)&&(c+=z[i++]<<p,(p+=8)<y&&(c+=z[i++]<<p,p+=8)),h<(k+=c&(1<<y)-1)){t.msg="invalid distance too far back",r.mode=30;break t}if(c>>>=y,p-=y,(y=s-a)<k){if(l<(y=k-y)&&r.sane){t.msg="invalid distance too far back",r.mode=30;break t}if(S=d,(x=0)===f){if(x+=u-y,y<w){for(w-=y;C[s++]=d[x++],--y;);x=s-k,S=C}}else if(f<y){if(x+=u+f-y,(y-=f)<w){for(w-=y;C[s++]=d[x++],--y;);if(x=0,f<w){for(w-=y=f;C[s++]=d[x++],--y;);x=s-k,S=C}}}else if(x+=f-y,y<w){for(w-=y;C[s++]=d[x++],--y;);x=s-k,S=C}for(;2<w;)C[s++]=S[x++],C[s++]=S[x++],C[s++]=S[x++],w-=3;w&&(C[s++]=S[x++],1<w&&(C[s++]=S[x++]))}else{for(x=s-k;C[s++]=C[x++],C[s++]=C[x++],C[s++]=C[x++],2<(w-=3););w&&(C[s++]=C[x++],1<w&&(C[s++]=C[x++]))}break}}break}}while(i<n&&s<o);i-=w=p>>3,c&=(1<<(p-=w<<3))-1,t.next_in=i,t.next_out=s,t.avail_in=i<n?n-i+5:5-(i-n),t.avail_out=s<o?o-s+257:257-(s-o),r.hold=c,r.bits=p}},{}],49:[function(t,e,r){"use strict";var I=t("../utils/common"),O=t("./adler32"),B=t("./crc32"),R=t("./inffast"),T=t("./inftrees"),D=1,F=2,N=0,U=-2,P=1,i=852,n=592;function L(t){return(t>>>24&255)+(t>>>8&65280)+((65280&t)<<8)+((255&t)<<24)}function s(){this.mode=0,this.last=!1,this.wrap=0,this.havedict=!1,this.flags=0,this.dmax=0,this.check=0,this.total=0,this.head=null,this.wbits=0,this.wsize=0,this.whave=0,this.wnext=0,this.window=null,this.hold=0,this.bits=0,this.length=0,this.offset=0,this.extra=0,this.lencode=null,this.distcode=null,this.lenbits=0,this.distbits=0,this.ncode=0,this.nlen=0,this.ndist=0,this.have=0,this.next=null,this.lens=new I.Buf16(320),this.work=new I.Buf16(288),this.lendyn=null,this.distdyn=null,this.sane=0,this.back=0,this.was=0}function a(t){var e;return t&&t.state?(e=t.state,t.total_in=t.total_out=e.total=0,t.msg="",e.wrap&&(t.adler=1&e.wrap),e.mode=P,e.last=0,e.havedict=0,e.dmax=32768,e.head=null,e.hold=0,e.bits=0,e.lencode=e.lendyn=new I.Buf32(i),e.distcode=e.distdyn=new I.Buf32(n),e.sane=1,e.back=-1,N):U}function o(t){var e;return t&&t.state?((e=t.state).wsize=0,e.whave=0,e.wnext=0,a(t)):U}function h(t,e){var r,i;return t&&t.state?(i=t.state,e<0?(r=0,e=-e):(r=1+(e>>4),e<48&&(e&=15)),e&&(e<8||15<e)?U:(null!==i.window&&i.wbits!==e&&(i.window=null),i.wrap=r,i.wbits=e,o(t))):U}function u(t,e){var r,i;return t?(i=new s,(t.state=i).window=null,(r=h(t,e))!==N&&(t.state=null),r):U}var l,f,d=!0;function j(t){if(d){var e;for(l=new I.Buf32(512),f=new I.Buf32(32),e=0;e<144;)t.lens[e++]=8;for(;e<256;)t.lens[e++]=9;for(;e<280;)t.lens[e++]=7;for(;e<288;)t.lens[e++]=8;for(T(D,t.lens,0,288,l,0,t.work,{bits:9}),e=0;e<32;)t.lens[e++]=5;T(F,t.lens,0,32,f,0,t.work,{bits:5}),d=!1}t.lencode=l,t.lenbits=9,t.distcode=f,t.distbits=5}function Z(t,e,r,i){var n,s=t.state;return null===s.window&&(s.wsize=1<<s.wbits,s.wnext=0,s.whave=0,s.window=new I.Buf8(s.wsize)),i>=s.wsize?(I.arraySet(s.window,e,r-s.wsize,s.wsize,0),s.wnext=0,s.whave=s.wsize):(i<(n=s.wsize-s.wnext)&&(n=i),I.arraySet(s.window,e,r-i,n,s.wnext),(i-=n)?(I.arraySet(s.window,e,r-i,i,0),s.wnext=i,s.whave=s.wsize):(s.wnext+=n,s.wnext===s.wsize&&(s.wnext=0),s.whave<s.wsize&&(s.whave+=n))),0}r.inflateReset=o,r.inflateReset2=h,r.inflateResetKeep=a,r.inflateInit=function(t){return u(t,15)},r.inflateInit2=u,r.inflate=function(t,e){var r,i,n,s,a,o,h,u,l,f,d,c,p,m,_,g,b,v,y,w,k,x,S,z,C=0,E=new I.Buf8(4),A=[16,17,18,0,8,7,9,6,10,5,11,4,12,3,13,2,14,1,15];if(!t||!t.state||!t.output||!t.input&&0!==t.avail_in)return U;12===(r=t.state).mode&&(r.mode=13),a=t.next_out,n=t.output,h=t.avail_out,s=t.next_in,i=t.input,o=t.avail_in,u=r.hold,l=r.bits,f=o,d=h,x=N;t:for(;;)switch(r.mode){case P:if(0===r.wrap){r.mode=13;break}for(;l<16;){if(0===o)break t;o--,u+=i[s++]<<l,l+=8}if(2&r.wrap&&35615===u){E[r.check=0]=255&u,E[1]=u>>>8&255,r.check=B(r.check,E,2,0),l=u=0,r.mode=2;break}if(r.flags=0,r.head&&(r.head.done=!1),!(1&r.wrap)||(((255&u)<<8)+(u>>8))%31){t.msg="incorrect header check",r.mode=30;break}if(8!=(15&u)){t.msg="unknown compression method",r.mode=30;break}if(l-=4,k=8+(15&(u>>>=4)),0===r.wbits)r.wbits=k;else if(k>r.wbits){t.msg="invalid window size",r.mode=30;break}r.dmax=1<<k,t.adler=r.check=1,r.mode=512&u?10:12,l=u=0;break;case 2:for(;l<16;){if(0===o)break t;o--,u+=i[s++]<<l,l+=8}if(r.flags=u,8!=(255&r.flags)){t.msg="unknown compression method",r.mode=30;break}if(57344&r.flags){t.msg="unknown header flags set",r.mode=30;break}r.head&&(r.head.text=u>>8&1),512&r.flags&&(E[0]=255&u,E[1]=u>>>8&255,r.check=B(r.check,E,2,0)),l=u=0,r.mode=3;case 3:for(;l<32;){if(0===o)break t;o--,u+=i[s++]<<l,l+=8}r.head&&(r.head.time=u),512&r.flags&&(E[0]=255&u,E[1]=u>>>8&255,E[2]=u>>>16&255,E[3]=u>>>24&255,r.check=B(r.check,E,4,0)),l=u=0,r.mode=4;case 4:for(;l<16;){if(0===o)break t;o--,u+=i[s++]<<l,l+=8}r.head&&(r.head.xflags=255&u,r.head.os=u>>8),512&r.flags&&(E[0]=255&u,E[1]=u>>>8&255,r.check=B(r.check,E,2,0)),l=u=0,r.mode=5;case 5:if(1024&r.flags){for(;l<16;){if(0===o)break t;o--,u+=i[s++]<<l,l+=8}r.length=u,r.head&&(r.head.extra_len=u),512&r.flags&&(E[0]=255&u,E[1]=u>>>8&255,r.check=B(r.check,E,2,0)),l=u=0}else r.head&&(r.head.extra=null);r.mode=6;case 6:if(1024&r.flags&&(o<(c=r.length)&&(c=o),c&&(r.head&&(k=r.head.extra_len-r.length,r.head.extra||(r.head.extra=new Array(r.head.extra_len)),I.arraySet(r.head.extra,i,s,c,k)),512&r.flags&&(r.check=B(r.check,i,c,s)),o-=c,s+=c,r.length-=c),r.length))break t;r.length=0,r.mode=7;case 7:if(2048&r.flags){if(0===o)break t;for(c=0;k=i[s+c++],r.head&&k&&r.length<65536&&(r.head.name+=String.fromCharCode(k)),k&&c<o;);if(512&r.flags&&(r.check=B(r.check,i,c,s)),o-=c,s+=c,k)break t}else r.head&&(r.head.name=null);r.length=0,r.mode=8;case 8:if(4096&r.flags){if(0===o)break t;for(c=0;k=i[s+c++],r.head&&k&&r.length<65536&&(r.head.comment+=String.fromCharCode(k)),k&&c<o;);if(512&r.flags&&(r.check=B(r.check,i,c,s)),o-=c,s+=c,k)break t}else r.head&&(r.head.comment=null);r.mode=9;case 9:if(512&r.flags){for(;l<16;){if(0===o)break t;o--,u+=i[s++]<<l,l+=8}if(u!==(65535&r.check)){t.msg="header crc mismatch",r.mode=30;break}l=u=0}r.head&&(r.head.hcrc=r.flags>>9&1,r.head.done=!0),t.adler=r.check=0,r.mode=12;break;case 10:for(;l<32;){if(0===o)break t;o--,u+=i[s++]<<l,l+=8}t.adler=r.check=L(u),l=u=0,r.mode=11;case 11:if(0===r.havedict)return t.next_out=a,t.avail_out=h,t.next_in=s,t.avail_in=o,r.hold=u,r.bits=l,2;t.adler=r.check=1,r.mode=12;case 12:if(5===e||6===e)break t;case 13:if(r.last){u>>>=7&l,l-=7&l,r.mode=27;break}for(;l<3;){if(0===o)break t;o--,u+=i[s++]<<l,l+=8}switch(r.last=1&u,l-=1,3&(u>>>=1)){case 0:r.mode=14;break;case 1:if(j(r),r.mode=20,6!==e)break;u>>>=2,l-=2;break t;case 2:r.mode=17;break;case 3:t.msg="invalid block type",r.mode=30}u>>>=2,l-=2;break;case 14:for(u>>>=7&l,l-=7&l;l<32;){if(0===o)break t;o--,u+=i[s++]<<l,l+=8}if((65535&u)!=(u>>>16^65535)){t.msg="invalid stored block lengths",r.mode=30;break}if(r.length=65535&u,l=u=0,r.mode=15,6===e)break t;case 15:r.mode=16;case 16:if(c=r.length){if(o<c&&(c=o),h<c&&(c=h),0===c)break t;I.arraySet(n,i,s,c,a),o-=c,s+=c,h-=c,a+=c,r.length-=c;break}r.mode=12;break;case 17:for(;l<14;){if(0===o)break t;o--,u+=i[s++]<<l,l+=8}if(r.nlen=257+(31&u),u>>>=5,l-=5,r.ndist=1+(31&u),u>>>=5,l-=5,r.ncode=4+(15&u),u>>>=4,l-=4,286<r.nlen||30<r.ndist){t.msg="too many length or distance symbols",r.mode=30;break}r.have=0,r.mode=18;case 18:for(;r.have<r.ncode;){for(;l<3;){if(0===o)break t;o--,u+=i[s++]<<l,l+=8}r.lens[A[r.have++]]=7&u,u>>>=3,l-=3}for(;r.have<19;)r.lens[A[r.have++]]=0;if(r.lencode=r.lendyn,r.lenbits=7,S={bits:r.lenbits},x=T(0,r.lens,0,19,r.lencode,0,r.work,S),r.lenbits=S.bits,x){t.msg="invalid code lengths set",r.mode=30;break}r.have=0,r.mode=19;case 19:for(;r.have<r.nlen+r.ndist;){for(;g=(C=r.lencode[u&(1<<r.lenbits)-1])>>>16&255,b=65535&C,!((_=C>>>24)<=l);){if(0===o)break t;o--,u+=i[s++]<<l,l+=8}if(b<16)u>>>=_,l-=_,r.lens[r.have++]=b;else{if(16===b){for(z=_+2;l<z;){if(0===o)break t;o--,u+=i[s++]<<l,l+=8}if(u>>>=_,l-=_,0===r.have){t.msg="invalid bit length repeat",r.mode=30;break}k=r.lens[r.have-1],c=3+(3&u),u>>>=2,l-=2}else if(17===b){for(z=_+3;l<z;){if(0===o)break t;o--,u+=i[s++]<<l,l+=8}l-=_,k=0,c=3+(7&(u>>>=_)),u>>>=3,l-=3}else{for(z=_+7;l<z;){if(0===o)break t;o--,u+=i[s++]<<l,l+=8}l-=_,k=0,c=11+(127&(u>>>=_)),u>>>=7,l-=7}if(r.have+c>r.nlen+r.ndist){t.msg="invalid bit length repeat",r.mode=30;break}for(;c--;)r.lens[r.have++]=k}}if(30===r.mode)break;if(0===r.lens[256]){t.msg="invalid code -- missing end-of-block",r.mode=30;break}if(r.lenbits=9,S={bits:r.lenbits},x=T(D,r.lens,0,r.nlen,r.lencode,0,r.work,S),r.lenbits=S.bits,x){t.msg="invalid literal/lengths set",r.mode=30;break}if(r.distbits=6,r.distcode=r.distdyn,S={bits:r.distbits},x=T(F,r.lens,r.nlen,r.ndist,r.distcode,0,r.work,S),r.distbits=S.bits,x){t.msg="invalid distances set",r.mode=30;break}if(r.mode=20,6===e)break t;case 20:r.mode=21;case 21:if(6<=o&&258<=h){t.next_out=a,t.avail_out=h,t.next_in=s,t.avail_in=o,r.hold=u,r.bits=l,R(t,d),a=t.next_out,n=t.output,h=t.avail_out,s=t.next_in,i=t.input,o=t.avail_in,u=r.hold,l=r.bits,12===r.mode&&(r.back=-1);break}for(r.back=0;g=(C=r.lencode[u&(1<<r.lenbits)-1])>>>16&255,b=65535&C,!((_=C>>>24)<=l);){if(0===o)break t;o--,u+=i[s++]<<l,l+=8}if(g&&0==(240&g)){for(v=_,y=g,w=b;g=(C=r.lencode[w+((u&(1<<v+y)-1)>>v)])>>>16&255,b=65535&C,!(v+(_=C>>>24)<=l);){if(0===o)break t;o--,u+=i[s++]<<l,l+=8}u>>>=v,l-=v,r.back+=v}if(u>>>=_,l-=_,r.back+=_,r.length=b,0===g){r.mode=26;break}if(32&g){r.back=-1,r.mode=12;break}if(64&g){t.msg="invalid literal/length code",r.mode=30;break}r.extra=15&g,r.mode=22;case 22:if(r.extra){for(z=r.extra;l<z;){if(0===o)break t;o--,u+=i[s++]<<l,l+=8}r.length+=u&(1<<r.extra)-1,u>>>=r.extra,l-=r.extra,r.back+=r.extra}r.was=r.length,r.mode=23;case 23:for(;g=(C=r.distcode[u&(1<<r.distbits)-1])>>>16&255,b=65535&C,!((_=C>>>24)<=l);){if(0===o)break t;o--,u+=i[s++]<<l,l+=8}if(0==(240&g)){for(v=_,y=g,w=b;g=(C=r.distcode[w+((u&(1<<v+y)-1)>>v)])>>>16&255,b=65535&C,!(v+(_=C>>>24)<=l);){if(0===o)break t;o--,u+=i[s++]<<l,l+=8}u>>>=v,l-=v,r.back+=v}if(u>>>=_,l-=_,r.back+=_,64&g){t.msg="invalid distance code",r.mode=30;break}r.offset=b,r.extra=15&g,r.mode=24;case 24:if(r.extra){for(z=r.extra;l<z;){if(0===o)break t;o--,u+=i[s++]<<l,l+=8}r.offset+=u&(1<<r.extra)-1,u>>>=r.extra,l-=r.extra,r.back+=r.extra}if(r.offset>r.dmax){t.msg="invalid distance too far back",r.mode=30;break}r.mode=25;case 25:if(0===h)break t;if(c=d-h,r.offset>c){if((c=r.offset-c)>r.whave&&r.sane){t.msg="invalid distance too far back",r.mode=30;break}p=c>r.wnext?(c-=r.wnext,r.wsize-c):r.wnext-c,c>r.length&&(c=r.length),m=r.window}else m=n,p=a-r.offset,c=r.length;for(h<c&&(c=h),h-=c,r.length-=c;n[a++]=m[p++],--c;);0===r.length&&(r.mode=21);break;case 26:if(0===h)break t;n[a++]=r.length,h--,r.mode=21;break;case 27:if(r.wrap){for(;l<32;){if(0===o)break t;o--,u|=i[s++]<<l,l+=8}if(d-=h,t.total_out+=d,r.total+=d,d&&(t.adler=r.check=r.flags?B(r.check,n,d,a-d):O(r.check,n,d,a-d)),d=h,(r.flags?u:L(u))!==r.check){t.msg="incorrect data check",r.mode=30;break}l=u=0}r.mode=28;case 28:if(r.wrap&&r.flags){for(;l<32;){if(0===o)break t;o--,u+=i[s++]<<l,l+=8}if(u!==(4294967295&r.total)){t.msg="incorrect length check",r.mode=30;break}l=u=0}r.mode=29;case 29:x=1;break t;case 30:x=-3;break t;case 31:return-4;case 32:default:return U}return t.next_out=a,t.avail_out=h,t.next_in=s,t.avail_in=o,r.hold=u,r.bits=l,(r.wsize||d!==t.avail_out&&r.mode<30&&(r.mode<27||4!==e))&&Z(t,t.output,t.next_out,d-t.avail_out)?(r.mode=31,-4):(f-=t.avail_in,d-=t.avail_out,t.total_in+=f,t.total_out+=d,r.total+=d,r.wrap&&d&&(t.adler=r.check=r.flags?B(r.check,n,d,t.next_out-d):O(r.check,n,d,t.next_out-d)),t.data_type=r.bits+(r.last?64:0)+(12===r.mode?128:0)+(20===r.mode||15===r.mode?256:0),(0==f&&0===d||4===e)&&x===N&&(x=-5),x)},r.inflateEnd=function(t){if(!t||!t.state)return U;var e=t.state;return e.window&&(e.window=null),t.state=null,N},r.inflateGetHeader=function(t,e){var r;return t&&t.state?0==(2&(r=t.state).wrap)?U:((r.head=e).done=!1,N):U},r.inflateSetDictionary=function(t,e){var r,i=e.length;return t&&t.state?0!==(r=t.state).wrap&&11!==r.mode?U:11===r.mode&&O(1,e,i,0)!==r.check?-3:Z(t,e,i,i)?(r.mode=31,-4):(r.havedict=1,N):U},r.inflateInfo="pako inflate (from Nodeca project)"},{"../utils/common":41,"./adler32":43,"./crc32":45,"./inffast":48,"./inftrees":50}],50:[function(t,e,r){"use strict";var D=t("../utils/common"),F=[3,4,5,6,7,8,9,10,11,13,15,17,19,23,27,31,35,43,51,59,67,83,99,115,131,163,195,227,258,0,0],N=[16,16,16,16,16,16,16,16,17,17,17,17,18,18,18,18,19,19,19,19,20,20,20,20,21,21,21,21,16,72,78],U=[1,2,3,4,5,7,9,13,17,25,33,49,65,97,129,193,257,385,513,769,1025,1537,2049,3073,4097,6145,8193,12289,16385,24577,0,0],P=[16,16,16,16,17,17,18,18,19,19,20,20,21,21,22,22,23,23,24,24,25,25,26,26,27,27,28,28,29,29,64,64];e.exports=function(t,e,r,i,n,s,a,o){var h,u,l,f,d,c,p,m,_,g=o.bits,b=0,v=0,y=0,w=0,k=0,x=0,S=0,z=0,C=0,E=0,A=null,I=0,O=new D.Buf16(16),B=new D.Buf16(16),R=null,T=0;for(b=0;b<=15;b++)O[b]=0;for(v=0;v<i;v++)O[e[r+v]]++;for(k=g,w=15;1<=w&&0===O[w];w--);if(w<k&&(k=w),0===w)return n[s++]=20971520,n[s++]=20971520,o.bits=1,0;for(y=1;y<w&&0===O[y];y++);for(k<y&&(k=y),b=z=1;b<=15;b++)if(z<<=1,(z-=O[b])<0)return-1;if(0<z&&(0===t||1!==w))return-1;for(B[1]=0,b=1;b<15;b++)B[b+1]=B[b]+O[b];for(v=0;v<i;v++)0!==e[r+v]&&(a[B[e[r+v]]++]=v);if(c=0===t?(A=R=a,19):1===t?(A=F,I-=257,R=N,T-=257,256):(A=U,R=P,-1),b=y,d=s,S=v=E=0,l=-1,f=(C=1<<(x=k))-1,1===t&&852<C||2===t&&592<C)return 1;for(;;){for(p=b-S,_=a[v]<c?(m=0,a[v]):a[v]>c?(m=R[T+a[v]],A[I+a[v]]):(m=96,0),h=1<<b-S,y=u=1<<x;n[d+(E>>S)+(u-=h)]=p<<24|m<<16|_|0,0!==u;);for(h=1<<b-1;E&h;)h>>=1;if(0!==h?(E&=h-1,E+=h):E=0,v++,0==--O[b]){if(b===w)break;b=e[r+a[v]]}if(k<b&&(E&f)!==l){for(0===S&&(S=k),d+=y,z=1<<(x=b-S);x+S<w&&!((z-=O[x+S])<=0);)x++,z<<=1;if(C+=1<<x,1===t&&852<C||2===t&&592<C)return 1;n[l=E&f]=k<<24|x<<16|d-s|0}}return 0!==E&&(n[d+E]=b-S<<24|64<<16|0),o.bits=k,0}},{"../utils/common":41}],51:[function(t,e,r){"use strict";e.exports={2:"need dictionary",1:"stream end",0:"","-1":"file error","-2":"stream error","-3":"data error","-4":"insufficient memory","-5":"buffer error","-6":"incompatible version"}},{}],52:[function(t,e,r){"use strict";var n=t("../utils/common"),o=0,h=1;function i(t){for(var e=t.length;0<=--e;)t[e]=0}var s=0,a=29,u=256,l=u+1+a,f=30,d=19,_=2*l+1,g=15,c=16,p=7,m=256,b=16,v=17,y=18,w=[0,0,0,0,0,0,0,0,1,1,1,1,2,2,2,2,3,3,3,3,4,4,4,4,5,5,5,5,0],k=[0,0,0,0,1,1,2,2,3,3,4,4,5,5,6,6,7,7,8,8,9,9,10,10,11,11,12,12,13,13],x=[0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,2,3,7],S=[16,17,18,0,8,7,9,6,10,5,11,4,12,3,13,2,14,1,15],z=new Array(2*(l+2));i(z);var C=new Array(2*f);i(C);var E=new Array(512);i(E);var A=new Array(256);i(A);var I=new Array(a);i(I);var O,B,R,T=new Array(f);function D(t,e,r,i,n){this.static_tree=t,this.extra_bits=e,this.extra_base=r,this.elems=i,this.max_length=n,this.has_stree=t&&t.length}function F(t,e){this.dyn_tree=t,this.max_code=0,this.stat_desc=e}function N(t){return t<256?E[t]:E[256+(t>>>7)]}function U(t,e){t.pending_buf[t.pending++]=255&e,t.pending_buf[t.pending++]=e>>>8&255}function P(t,e,r){t.bi_valid>c-r?(t.bi_buf|=e<<t.bi_valid&65535,U(t,t.bi_buf),t.bi_buf=e>>c-t.bi_valid,t.bi_valid+=r-c):(t.bi_buf|=e<<t.bi_valid&65535,t.bi_valid+=r)}function L(t,e,r){P(t,r[2*e],r[2*e+1])}function j(t,e){for(var r=0;r|=1&t,t>>>=1,r<<=1,0<--e;);return r>>>1}function Z(t,e,r){var i,n,s=new Array(g+1),a=0;for(i=1;i<=g;i++)s[i]=a=a+r[i-1]<<1;for(n=0;n<=e;n++){var o=t[2*n+1];0!==o&&(t[2*n]=j(s[o]++,o))}}function W(t){var e;for(e=0;e<l;e++)t.dyn_ltree[2*e]=0;for(e=0;e<f;e++)t.dyn_dtree[2*e]=0;for(e=0;e<d;e++)t.bl_tree[2*e]=0;t.dyn_ltree[2*m]=1,t.opt_len=t.static_len=0,t.last_lit=t.matches=0}function M(t){8<t.bi_valid?U(t,t.bi_buf):0<t.bi_valid&&(t.pending_buf[t.pending++]=t.bi_buf),t.bi_buf=0,t.bi_valid=0}function H(t,e,r,i){var n=2*e,s=2*r;return t[n]<t[s]||t[n]===t[s]&&i[e]<=i[r]}function G(t,e,r){for(var i=t.heap[r],n=r<<1;n<=t.heap_len&&(n<t.heap_len&&H(e,t.heap[n+1],t.heap[n],t.depth)&&n++,!H(e,i,t.heap[n],t.depth));)t.heap[r]=t.heap[n],r=n,n<<=1;t.heap[r]=i}function K(t,e,r){var i,n,s,a,o=0;if(0!==t.last_lit)for(;i=t.pending_buf[t.d_buf+2*o]<<8|t.pending_buf[t.d_buf+2*o+1],n=t.pending_buf[t.l_buf+o],o++,0===i?L(t,n,e):(L(t,(s=A[n])+u+1,e),0!==(a=w[s])&&P(t,n-=I[s],a),L(t,s=N(--i),r),0!==(a=k[s])&&P(t,i-=T[s],a)),o<t.last_lit;);L(t,m,e)}function Y(t,e){var r,i,n,s=e.dyn_tree,a=e.stat_desc.static_tree,o=e.stat_desc.has_stree,h=e.stat_desc.elems,u=-1;for(t.heap_len=0,t.heap_max=_,r=0;r<h;r++)0!==s[2*r]?(t.heap[++t.heap_len]=u=r,t.depth[r]=0):s[2*r+1]=0;for(;t.heap_len<2;)s[2*(n=t.heap[++t.heap_len]=u<2?++u:0)]=1,t.depth[n]=0,t.opt_len--,o&&(t.static_len-=a[2*n+1]);for(e.max_code=u,r=t.heap_len>>1;1<=r;r--)G(t,s,r);for(n=h;r=t.heap[1],t.heap[1]=t.heap[t.heap_len--],G(t,s,1),i=t.heap[1],t.heap[--t.heap_max]=r,t.heap[--t.heap_max]=i,s[2*n]=s[2*r]+s[2*i],t.depth[n]=(t.depth[r]>=t.depth[i]?t.depth[r]:t.depth[i])+1,s[2*r+1]=s[2*i+1]=n,t.heap[1]=n++,G(t,s,1),2<=t.heap_len;);t.heap[--t.heap_max]=t.heap[1],function(t,e){var r,i,n,s,a,o,h=e.dyn_tree,u=e.max_code,l=e.stat_desc.static_tree,f=e.stat_desc.has_stree,d=e.stat_desc.extra_bits,c=e.stat_desc.extra_base,p=e.stat_desc.max_length,m=0;for(s=0;s<=g;s++)t.bl_count[s]=0;for(h[2*t.heap[t.heap_max]+1]=0,r=t.heap_max+1;r<_;r++)p<(s=h[2*h[2*(i=t.heap[r])+1]+1]+1)&&(s=p,m++),h[2*i+1]=s,u<i||(t.bl_count[s]++,a=0,c<=i&&(a=d[i-c]),o=h[2*i],t.opt_len+=o*(s+a),f&&(t.static_len+=o*(l[2*i+1]+a)));if(0!==m){do{for(s=p-1;0===t.bl_count[s];)s--;t.bl_count[s]--,t.bl_count[s+1]+=2,t.bl_count[p]--,m-=2}while(0<m);for(s=p;0!==s;s--)for(i=t.bl_count[s];0!==i;)u<(n=t.heap[--r])||(h[2*n+1]!==s&&(t.opt_len+=(s-h[2*n+1])*h[2*n],h[2*n+1]=s),i--)}}(t,e),Z(s,u,t.bl_count)}function X(t,e,r){var i,n,s=-1,a=e[1],o=0,h=7,u=4;for(0===a&&(h=138,u=3),e[2*(r+1)+1]=65535,i=0;i<=r;i++)n=a,a=e[2*(i+1)+1],++o<h&&n===a||(o<u?t.bl_tree[2*n]+=o:0!==n?(n!==s&&t.bl_tree[2*n]++,t.bl_tree[2*b]++):o<=10?t.bl_tree[2*v]++:t.bl_tree[2*y]++,s=n,u=(o=0)===a?(h=138,3):n===a?(h=6,3):(h=7,4))}function V(t,e,r){var i,n,s=-1,a=e[1],o=0,h=7,u=4;for(0===a&&(h=138,u=3),i=0;i<=r;i++)if(n=a,a=e[2*(i+1)+1],!(++o<h&&n===a)){if(o<u)for(;L(t,n,t.bl_tree),0!=--o;);else 0!==n?(n!==s&&(L(t,n,t.bl_tree),o--),L(t,b,t.bl_tree),P(t,o-3,2)):o<=10?(L(t,v,t.bl_tree),P(t,o-3,3)):(L(t,y,t.bl_tree),P(t,o-11,7));s=n,u=(o=0)===a?(h=138,3):n===a?(h=6,3):(h=7,4)}}i(T);var q=!1;function J(t,e,r,i){P(t,(s<<1)+(i?1:0),3),function(t,e,r,i){M(t),i&&(U(t,r),U(t,~r)),n.arraySet(t.pending_buf,t.window,e,r,t.pending),t.pending+=r}(t,e,r,!0)}r._tr_init=function(t){q||(function(){var t,e,r,i,n,s=new Array(g+1);for(i=r=0;i<a-1;i++)for(I[i]=r,t=0;t<1<<w[i];t++)A[r++]=i;for(A[r-1]=i,i=n=0;i<16;i++)for(T[i]=n,t=0;t<1<<k[i];t++)E[n++]=i;for(n>>=7;i<f;i++)for(T[i]=n<<7,t=0;t<1<<k[i]-7;t++)E[256+n++]=i;for(e=0;e<=g;e++)s[e]=0;for(t=0;t<=143;)z[2*t+1]=8,t++,s[8]++;for(;t<=255;)z[2*t+1]=9,t++,s[9]++;for(;t<=279;)z[2*t+1]=7,t++,s[7]++;for(;t<=287;)z[2*t+1]=8,t++,s[8]++;for(Z(z,l+1,s),t=0;t<f;t++)C[2*t+1]=5,C[2*t]=j(t,5);O=new D(z,w,u+1,l,g),B=new D(C,k,0,f,g),R=new D(new Array(0),x,0,d,p)}(),q=!0),t.l_desc=new F(t.dyn_ltree,O),t.d_desc=new F(t.dyn_dtree,B),t.bl_desc=new F(t.bl_tree,R),t.bi_buf=0,t.bi_valid=0,W(t)},r._tr_stored_block=J,r._tr_flush_block=function(t,e,r,i){var n,s,a=0;0<t.level?(2===t.strm.data_type&&(t.strm.data_type=function(t){var e,r=4093624447;for(e=0;e<=31;e++,r>>>=1)if(1&r&&0!==t.dyn_ltree[2*e])return o;if(0!==t.dyn_ltree[18]||0!==t.dyn_ltree[20]||0!==t.dyn_ltree[26])return h;for(e=32;e<u;e++)if(0!==t.dyn_ltree[2*e])return h;return o}(t)),Y(t,t.l_desc),Y(t,t.d_desc),a=function(t){var e;for(X(t,t.dyn_ltree,t.l_desc.max_code),X(t,t.dyn_dtree,t.d_desc.max_code),Y(t,t.bl_desc),e=d-1;3<=e&&0===t.bl_tree[2*S[e]+1];e--);return t.opt_len+=3*(e+1)+5+5+4,e}(t),n=t.opt_len+3+7>>>3,(s=t.static_len+3+7>>>3)<=n&&(n=s)):n=s=r+5,r+4<=n&&-1!==e?J(t,e,r,i):4===t.strategy||s===n?(P(t,2+(i?1:0),3),K(t,z,C)):(P(t,4+(i?1:0),3),function(t,e,r,i){var n;for(P(t,e-257,5),P(t,r-1,5),P(t,i-4,4),n=0;n<i;n++)P(t,t.bl_tree[2*S[n]+1],3);V(t,t.dyn_ltree,e-1),V(t,t.dyn_dtree,r-1)}(t,t.l_desc.max_code+1,t.d_desc.max_code+1,a+1),K(t,t.dyn_ltree,t.dyn_dtree)),W(t),i&&M(t)},r._tr_tally=function(t,e,r){return t.pending_buf[t.d_buf+2*t.last_lit]=e>>>8&255,t.pending_buf[t.d_buf+2*t.last_lit+1]=255&e,t.pending_buf[t.l_buf+t.last_lit]=255&r,t.last_lit++,0===e?t.dyn_ltree[2*r]++:(t.matches++,e--,t.dyn_ltree[2*(A[r]+u+1)]++,t.dyn_dtree[2*N(e)]++),t.last_lit===t.lit_bufsize-1},r._tr_align=function(t){P(t,2,3),L(t,m,z),function(t){16===t.bi_valid?(U(t,t.bi_buf),t.bi_buf=0,t.bi_valid=0):8<=t.bi_valid&&(t.pending_buf[t.pending++]=255&t.bi_buf,t.bi_buf>>=8,t.bi_valid-=8)}(t)}},{"../utils/common":41}],53:[function(t,e,r){"use strict";e.exports=function(){this.input=null,this.next_in=0,this.avail_in=0,this.total_in=0,this.output=null,this.next_out=0,this.avail_out=0,this.total_out=0,this.msg="",this.state=null,this.data_type=2,this.adler=0}},{}],54:[function(t,e,r){"use strict";e.exports="function"==typeof setImmediate?setImmediate:function(){var t=[].slice.apply(arguments);t.splice(1,0,0),setTimeout.apply(null,t)}},{}]},{},[10])(10)});

src/evalatin2024-latinpipe/LICENSE

@@ -0,0 +1,373 @@
+Mozilla Public License Version 2.0
+==================================
+
+1. Definitions
+--------------
+
+1.1. "Contributor"
+    means each individual or legal entity that creates, contributes to
+    the creation of, or owns Covered Software.
+
+1.2. "Contributor Version"
+    means the combination of the Contributions of others (if any) used
+    by a Contributor and that particular Contributor's Contribution.
+
+1.3. "Contribution"
+    means Covered Software of a particular Contributor.
+
+1.4. "Covered Software"
+    means Source Code Form to which the initial Contributor has attached
+    the notice in Exhibit A, the Executable Form of such Source Code
+    Form, and Modifications of such Source Code Form, in each case
+    including portions thereof.
+
+1.5. "Incompatible With Secondary Licenses"
+    means
+
+    (a) that the initial Contributor has attached the notice described
+        in Exhibit B to the Covered Software; or
+
+    (b) that the Covered Software was made available under the terms of
+        version 1.1 or earlier of the License, but not also under the
+        terms of a Secondary License.
+
+1.6. "Executable Form"
+    means any form of the work other than Source Code Form.
+
+1.7. "Larger Work"
+    means a work that combines Covered Software with other material, in
+    a separate file or files, that is not Covered Software.
+
+1.8. "License"
+    means this document.
+
+1.9. "Licensable"
+    means having the right to grant, to the maximum extent possible,
+    whether at the time of the initial grant or subsequently, any and
+    all of the rights conveyed by this License.
+
+1.10. "Modifications"
+    means any of the following:
+
+    (a) any file in Source Code Form that results from an addition to,
+        deletion from, or modification of the contents of Covered
+        Software; or
+
+    (b) any new file in Source Code Form that contains any Covered
+        Software.
+
+1.11. "Patent Claims" of a Contributor
+    means any patent claim(s), including without limitation, method,
+    process, and apparatus claims, in any patent Licensable by such
+    Contributor that would be infringed, but for the grant of the
+    License, by the making, using, selling, offering for sale, having
+    made, import, or transfer of either its Contributions or its
+    Contributor Version.
+
+1.12. "Secondary License"
+    means either the GNU General Public License, Version 2.0, the GNU
+    Lesser General Public License, Version 2.1, the GNU Affero General
+    Public License, Version 3.0, or any later versions of those
+    licenses.
+
+1.13. "Source Code Form"
+    means the form of the work preferred for making modifications.
+
+1.14. "You" (or "Your")
+    means an individual or a legal entity exercising rights under this
+    License. For legal entities, "You" includes any entity that
+    controls, is controlled by, or is under common control with You. For
+    purposes of this definition, "control" means (a) the power, direct
+    or indirect, to cause the direction or management of such entity,
+    whether by contract or otherwise, or (b) ownership of more than
+    fifty percent (50%) of the outstanding shares or beneficial
+    ownership of such entity.
+
+2. License Grants and Conditions
+--------------------------------
+
+2.1. Grants
+
+Each Contributor hereby grants You a world-wide, royalty-free,
+non-exclusive license:
+
+(a) under intellectual property rights (other than patent or trademark)
+    Licensable by such Contributor to use, reproduce, make available,
+    modify, display, perform, distribute, and otherwise exploit its
+    Contributions, either on an unmodified basis, with Modifications, or
+    as part of a Larger Work; and
+
+(b) under Patent Claims of such Contributor to make, use, sell, offer
+    for sale, have made, import, and otherwise transfer either its
+    Contributions or its Contributor Version.
+
+2.2. Effective Date
+
+The licenses granted in Section 2.1 with respect to any Contribution
+become effective for each Contribution on the date the Contributor first
+distributes such Contribution.
+
+2.3. Limitations on Grant Scope
+
+The licenses granted in this Section 2 are the only rights granted under
+this License. No additional rights or licenses will be implied from the
+distribution or licensing of Covered Software under this License.
+Notwithstanding Section 2.1(b) above, no patent license is granted by a
+Contributor:
+
+(a) for any code that a Contributor has removed from Covered Software;
+    or
+
+(b) for infringements caused by: (i) Your and any other third party's
+    modifications of Covered Software, or (ii) the combination of its
+    Contributions with other software (except as part of its Contributor
+    Version); or
+
+(c) under Patent Claims infringed by Covered Software in the absence of
+    its Contributions.
+
+This License does not grant any rights in the trademarks, service marks,
+or logos of any Contributor (except as may be necessary to comply with
+the notice requirements in Section 3.4).
+
+2.4. Subsequent Licenses
+
+No Contributor makes additional grants as a result of Your choice to
+distribute the Covered Software under a subsequent version of this
+License (see Section 10.2) or under the terms of a Secondary License (if
+permitted under the terms of Section 3.3).
+
+2.5. Representation
+
+Each Contributor represents that the Contributor believes its
+Contributions are its original creation(s) or it has sufficient rights
+to grant the rights to its Contributions conveyed by this License.
+
+2.6. Fair Use
+
+This License is not intended to limit any rights You have under
+applicable copyright doctrines of fair use, fair dealing, or other
+equivalents.
+
+2.7. Conditions
+
+Sections 3.1, 3.2, 3.3, and 3.4 are conditions of the licenses granted
+in Section 2.1.
+
+3. Responsibilities
+-------------------
+
+3.1. Distribution of Source Form
+
+All distribution of Covered Software in Source Code Form, including any
+Modifications that You create or to which You contribute, must be under
+the terms of this License. You must inform recipients that the Source
+Code Form of the Covered Software is governed by the terms of this
+License, and how they can obtain a copy of this License. You may not
+attempt to alter or restrict the recipients' rights in the Source Code
+Form.
+
+3.2. Distribution of Executable Form
+
+If You distribute Covered Software in Executable Form then:
+
+(a) such Covered Software must also be made available in Source Code
+    Form, as described in Section 3.1, and You must inform recipients of
+    the Executable Form how they can obtain a copy of such Source Code
+    Form by reasonable means in a timely manner, at a charge no more
+    than the cost of distribution to the recipient; and
+
+(b) You may distribute such Executable Form under the terms of this
+    License, or sublicense it under different terms, provided that the
+    license for the Executable Form does not attempt to limit or alter
+    the recipients' rights in the Source Code Form under this License.
+
+3.3. Distribution of a Larger Work
+
+You may create and distribute a Larger Work under terms of Your choice,
+provided that You also comply with the requirements of this License for
+the Covered Software. If the Larger Work is a combination of Covered
+Software with a work governed by one or more Secondary Licenses, and the
+Covered Software is not Incompatible With Secondary Licenses, this
+License permits You to additionally distribute such Covered Software
+under the terms of such Secondary License(s), so that the recipient of
+the Larger Work may, at their option, further distribute the Covered
+Software under the terms of either this License or such Secondary
+License(s).
+
+3.4. Notices
+
+You may not remove or alter the substance of any license notices
+(including copyright notices, patent notices, disclaimers of warranty,
+or limitations of liability) contained within the Source Code Form of
+the Covered Software, except that You may alter any license notices to
+the extent required to remedy known factual inaccuracies.
+
+3.5. Application of Additional Terms
+
+You may choose to offer, and to charge a fee for, warranty, support,
+indemnity or liability obligations to one or more recipients of Covered
+Software. However, You may do so only on Your own behalf, and not on
+behalf of any Contributor. You must make it absolutely clear that any
+such warranty, support, indemnity, or liability obligation is offered by
+You alone, and You hereby agree to indemnify every Contributor for any
+liability incurred by such Contributor as a result of warranty, support,
+indemnity or liability terms You offer. You may include additional
+disclaimers of warranty and limitations of liability specific to any
+jurisdiction.
+
+4. Inability to Comply Due to Statute or Regulation
+---------------------------------------------------
+
+If it is impossible for You to comply with any of the terms of this
+License with respect to some or all of the Covered Software due to
+statute, judicial order, or regulation then You must: (a) comply with
+the terms of this License to the maximum extent possible; and (b)
+describe the limitations and the code they affect. Such description must
+be placed in a text file included with all distributions of the Covered
+Software under this License. Except to the extent prohibited by statute
+or regulation, such description must be sufficiently detailed for a
+recipient of ordinary skill to be able to understand it.
+
+5. Termination
+--------------
+
+5.1. The rights granted under this License will terminate automatically
+if You fail to comply with any of its terms. However, if You become
+compliant, then the rights granted under this License from a particular
+Contributor are reinstated (a) provisionally, unless and until such
+Contributor explicitly and finally terminates Your grants, and (b) on an
+ongoing basis, if such Contributor fails to notify You of the
+non-compliance by some reasonable means prior to 60 days after You have
+come back into compliance. Moreover, Your grants from a particular
+Contributor are reinstated on an ongoing basis if such Contributor
+notifies You of the non-compliance by some reasonable means, this is the
+first time You have received notice of non-compliance with this License
+from such Contributor, and You become compliant prior to 30 days after
+Your receipt of the notice.
+
+5.2. If You initiate litigation against any entity by asserting a patent
+infringement claim (excluding declaratory judgment actions,
+counter-claims, and cross-claims) alleging that a Contributor Version
+directly or indirectly infringes any patent, then the rights granted to
+You by any and all Contributors for the Covered Software under Section
+2.1 of this License shall terminate.
+
+5.3. In the event of termination under Sections 5.1 or 5.2 above, all
+end user license agreements (excluding distributors and resellers) which
+have been validly granted by You or Your distributors under this License
+prior to termination shall survive termination.
+
+************************************************************************
+*                                                                      *
+*  6. Disclaimer of Warranty                                           *
+*  -------------------------                                           *
+*                                                                      *
+*  Covered Software is provided under this License on an "as is"       *
+*  basis, without warranty of any kind, either expressed, implied, or  *
+*  statutory, including, without limitation, warranties that the       *
+*  Covered Software is free of defects, merchantable, fit for a        *
+*  particular purpose or non-infringing. The entire risk as to the     *
+*  quality and performance of the Covered Software is with You.        *
+*  Should any Covered Software prove defective in any respect, You     *
+*  (not any Contributor) assume the cost of any necessary servicing,   *
+*  repair, or correction. This disclaimer of warranty constitutes an   *
+*  essential part of this License. No use of any Covered Software is   *
+*  authorized under this License except under this disclaimer.         *
+*                                                                      *
+************************************************************************
+
+************************************************************************
+*                                                                      *
+*  7. Limitation of Liability                                          *
+*  --------------------------                                          *
+*                                                                      *
+*  Under no circumstances and under no legal theory, whether tort      *
+*  (including negligence), contract, or otherwise, shall any           *
+*  Contributor, or anyone who distributes Covered Software as          *
+*  permitted above, be liable to You for any direct, indirect,         *
+*  special, incidental, or consequential damages of any character      *
+*  including, without limitation, damages for lost profits, loss of    *
+*  goodwill, work stoppage, computer failure or malfunction, or any    *
+*  and all other commercial damages or losses, even if such party      *
+*  shall have been informed of the possibility of such damages. This   *
+*  limitation of liability shall not apply to liability for death or   *
+*  personal injury resulting from such party's negligence to the       *
+*  extent applicable law prohibits such limitation. Some               *
+*  jurisdictions do not allow the exclusion or limitation of           *
+*  incidental or consequential damages, so this exclusion and          *
+*  limitation may not apply to You.                                    *
+*                                                                      *
+************************************************************************
+
+8. Litigation
+-------------
+
+Any litigation relating to this License may be brought only in the
+courts of a jurisdiction where the defendant maintains its principal
+place of business and such litigation shall be governed by laws of that
+jurisdiction, without reference to its conflict-of-law provisions.
+Nothing in this Section shall prevent a party's ability to bring
+cross-claims or counter-claims.
+
+9. Miscellaneous
+----------------
+
+This License represents the complete agreement concerning the subject
+matter hereof. If any provision of this License is held to be
+unenforceable, such provision shall be reformed only to the extent
+necessary to make it enforceable. Any law or regulation which provides
+that the language of a contract shall be construed against the drafter
+shall not be used to construe this License against a Contributor.
+
+10. Versions of the License
+---------------------------
+
+10.1. New Versions
+
+Mozilla Foundation is the license steward. Except as provided in Section
+10.3, no one other than the license steward has the right to modify or
+publish new versions of this License. Each version will be given a
+distinguishing version number.
+
+10.2. Effect of New Versions
+
+You may distribute the Covered Software under the terms of the version
+of the License under which You originally received the Covered Software,
+or under the terms of any subsequent version published by the license
+steward.
+
+10.3. Modified Versions
+
+If you create software not governed by this License, and you want to
+create a new license for such software, you may create and use a
+modified version of this License if you rename the license and remove
+any references to the name of the license steward (except to note that
+such modified license differs from this License).
+
+10.4. Distributing Source Code Form that is Incompatible With Secondary
+Licenses
+
+If You choose to distribute Source Code Form that is Incompatible With
+Secondary Licenses under the terms of this version of the License, the
+notice described in Exhibit B of this License must be attached.
+
+Exhibit A - Source Code Form License Notice
+-------------------------------------------
+
+  This Source Code Form is subject to the terms of the Mozilla Public
+  License, v. 2.0. If a copy of the MPL was not distributed with this
+  file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+If it is not possible or desirable to put the notice in a particular
+file, then You may include the notice in a location (such as a LICENSE
+file in a relevant directory) where a recipient would be likely to look
+for such a notice.
+
+You may add additional accurate notices of copyright ownership.
+
+Exhibit B - "Incompatible With Secondary Licenses" Notice
+---------------------------------------------------------
+
+  This Source Code Form is "Incompatible With Secondary Licenses", as
+  defined by the Mozilla Public License, v. 2.0.

src/evalatin2024-latinpipe/README.md

@@ -0,0 +1,118 @@
+# ÚFAL LatinPipe at EvaLatin 2024: Morphosyntactic Analysis of Latin
+
+This repository contains the LatinPipe parser implementation described in
+the _ÚFAL LatinPipe at EvaLatin 2024: Morphosyntactic Analysis of Latin_ paper.
+
+📢 Besides this source code and the [trained model](https://hdl.handle.net/11234/1-5671),
+LatinPipe is also available in the [UDPipe LINDAT/CLARIN service](http://lindat.mff.cuni.cz/services/udpipe/)
+and can be used either in a web form or through a REST service.
+
+---
+
+<img src="figures/LatinPipe.svg" alt="LatinPipe Architecture" align="right" style="width: 45%">
+
+<h3 align="center"><a href="https://aclanthology.org/2024.lt4hala-1.24/">ÚFAL LatinPipe at EvaLatin 2024: Morphosyntactic Analysis of Latin</a></h3>
+
+<p align="center">
+  <b>Milan Straka</b> and <b>Jana Straková</b> and <b>Federica Gamba</b><br>
+  Charles University<br>
+  Faculty of Mathematics and Physics<br>
+  Institute of Formal and Applied Lingustics<br>
+  Malostranské nám. 25, Prague, Czech Republic
+</p>
+
+**Abstract:** We present LatinPipe, the winning submission to the EvaLatin 2024
+Dependency Parsing shared task. Our system consists of a fine-tuned
+concatenation of base and large pre-trained LMs, with a dot-product attention
+head for parsing and softmax classification heads for morphology to jointly
+learn both dependency parsing and morphological analysis. It is trained by
+sampling from seven publicly available Latin corpora, utilizing additional
+harmonization of annotations to achieve a more unified annotation style. Before
+fine-tuning, we train the system for a few initial epochs with frozen weights.
+We also add additional local relative contextualization by stacking the BiLSTM
+layers on top of the Transformer(s). Finally, we ensemble output probability
+distributions from seven randomly instantiated networks for the final
+submission. The code is available at <a href="https://github.com/ufal/evalatin2024-latinpipe">https://github.com/ufal/evalatin2024-latinpipe</a>.<br clear="both">
+
+---
+
+## Content of this Repository
+
+- The directory `data` is for all the required data (UD 2.13 data, harmonized
+  PROIEL, Sabellicus, Archimedes Latinus, EvaLatin 2024 test data).
+  - The script `data/fetch_data.sh` downloads and extracts all the data:
+    ```sh
+    (cd data && sh fetch_data.sh)
+    ```
+
+- The `latinpipe_evalatin24.py` is the LatinPipe EvaLatin24 source.
+  - It depends on `latinpipe_evalatin24_eval.py`, which is a modularized version
+    of the official evaluation script.
+
+- The `latinpipe_evalatin24_server.py` is a REST server with UDPipe-2-compatible
+  API, using `latinpipe_evalatin24.py` to perform tagging and parsing.
+
+## The Released `latinpipe-evalatin24-240520` Model
+
+The `latinpipe-evalatin24-240520` is a `PhilBerta`-based model for tagging,
+lemmatization, and dependency parsing of Latin, based on the winning entry
+to the EvaLatin 2024 <https://circse.github.io/LT4HALA/2024/EvaLatin> shared
+task. It is released at https://hdl.handle.net/11234/1-5671 under the CC
+BY-NC-SA 4.0 license.
+
+The model is also available in the [UDPipe LINDAT/CLARIN service](http://lindat.mff.cuni.cz/services/udpipe/)
+ and can be used either in a web form or through a REST service.
+
+See the [latinpipe-evalatin24-240520 directory](latinpipe-evalatin24-240520/) for
+the download link, the model performance, and additional information.
+
+## Training a Model
+
+To train a model on all data, you should
+1. run the `data/fetch_data.sh` script to download all required data,
+2. create a Python environments with the packages listed in `requirements.txt`,
+3. train the model itself using the `latinpipe_evalatin24.py` script.
+
+   To train a model performing UPOS/UFeats tagging, lemmatization, and
+   dependency parsing, we use
+   ```sh
+   la_ud213_all="la_ittb la_llct la_perseus la_proiel la_udante"
+   la_other="la_archimedes la_sabellicus"
+   transformer="bowphs/PhilBerta"  # or bowphs/LaBerta
+
+   latinpipe_evalatin24.py $(for split in dev test train; do echo --$split; for tb in $la_ud213_all; do [ $tb-$split = la_proiel-train ] && tb=la_proielh; echo data/$tb/$tb-ud-$split.conllu; done; done) $(for tb in $la_other; do echo data/$tb/$tb-train.conllu; done) --transformers $transformer --epochs=30 --exp=evalatin24_model --subword_combination=last --epochs_frozen=10 --batch_size=64 --save_checkpoint
+   ```
+
+## Predicting with a Trained Model
+
+To predict with a trained model, you can use the following command:
+```sh
+latinpipe_evalatin24.py --load evalatin24_model/model.weights.h5 --exp target_directory --test input1.conllu input2.conllu
+```
+- the outputs are generated in the target directory, with a `.predicted.conllu` suffix;
+- if you want to also evaluate the predicted files, you can use `--dev` option instead of `--test`.
+
+---
+
+## Contact
+
+Milan Straka: ``[email protected]``\
+Jana Straková: ``[email protected]``\
+Federica Gamba: ``[email protected]``
+
+## How to Cite
+
+```
+@inproceedings{straka-etal-2024-ufal,
+    title = "{{\'U}FAL} {L}atin{P}ipe at {E}va{L}atin 2024: Morphosyntactic Analysis of {L}atin",
+    author = "Straka, Milan  and Strakov{\'a}, Jana  and Gamba, Federica",
+    editor = "Sprugnoli, Rachele  and Passarotti, Marco",
+    booktitle = "Proceedings of the Third Workshop on Language Technologies for Historical and Ancient Languages (LT4HALA) @ LREC-COLING-2024",
+    month = may,
+    year = "2024",
+    address = "Torino, Italia",
+    publisher = "ELRA and ICCL",
+    url = "https://aclanthology.org/2024.lt4hala-1.24",
+    pages = "207--214"
+}
+```

src/evalatin2024-latinpipe/data/conllu_split.py

@@ -0,0 +1,39 @@
+#!/usr/bin/env python3
+#
+# This file is part of LatinPipe EvaLatin 24
+# <https://github.com/ufal/evalatin2024-latinpipe>.
+#
+# Copyright 2024 Institute of Formal and Applied Linguistics, Faculty of
+# Mathematics and Physics, Charles University in Prague, Czech Republic.
+#
+# This Source Code Form is subject to the terms of the Mozilla Public
+# License, v. 2.0. If a copy of the MPL was not distributed with this
+# file, You can obtain one at http://mozilla.org/MPL/2.0/.
+import argparse
+
+import numpy as np
+
+if __name__ == "__main__":
+    parser = argparse.ArgumentParser()
+    parser.add_argument("source", type=str, help="CoNLL-U file to split")
+    parser.add_argument("train", type=str, help="CoNLL-U file to write training data to")
+    parser.add_argument("dev", type=str, help="CoNLL-U file to write development data to")
+    parser.add_argument("--dev_size", type=float, default=0.1, help="Size of the development data")
+    args = parser.parse_args()
+
+    sentences = []
+    with open(args.source, "r", encoding="utf-8") as source:
+        sentence = []
+        for line in source:
+            sentence.append(line)
+            if not line.rstrip("\r\n"):
+                sentences.append("".join(sentence))
+                sentence = []
+        assert not sentence, "Missing empty line after the last sentence"
+
+    dev_indices = set(np.random.RandomState(42).choice(len(sentences), int(len(sentences) * args.dev_size), replace=False))
+
+    with open(args.train, "w", encoding="utf-8") as train:
+        with open(args.dev, "w", encoding="utf-8") as dev:
+            for i, sentence in enumerate(sentences):
+                (dev if i in dev_indices else train).write(sentence)

src/evalatin2024-latinpipe/data/fetch_data.sh

@@ -0,0 +1,66 @@
+#!/bin/bash
+#
+# This file is part of LatinPipe EvaLatin 24
+# <https://github.com/ufal/evalatin2024-latinpipe>.
+#
+# Copyright 2024 Institute of Formal and Applied Linguistics, Faculty of
+# Mathematics and Physics, Charles University in Prague, Czech Republic.
+#
+# This Source Code Form is subject to the terms of the Mozilla Public
+# License, v. 2.0. If a copy of the MPL was not distributed with this
+# file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+# Refresh conllu_to_text.pl
+curl -O https://raw.githubusercontent.com/UniversalDependencies/tools/master/conllu_to_text.pl
+
+# Get the UD 2.13 data
+curl -O https://lindat.mff.cuni.cz/repository/xmlui/bitstream/handle/11234/1-5287/ud-treebanks-v2.13.tgz
+tar xf ud-treebanks-v2.13.tgz
+
+for tb in ud-treebanks-v2.13/*Latin*/*-ud-train.conllu; do
+  dir=`dirname $tb`
+  long_name=`basename $dir`
+  code=`basename $tb`
+  code=${code%%-*}
+  echo Fetching $long_name as $code
+
+  mkdir -p $code
+  cp $dir/* $code
+  if [ ! -f $code/$code-ud-dev.conllu ]; then
+    python3 conllu_split.py $dir/$code-ud-train.conllu $code/$code-ud-train.conllu $code/$code-ud-dev.conllu
+    for conllu in $code/$code-ud-train.conllu $code/$code-ud-dev.conllu; do
+      perl conllu_to_text.pl --language=$code <$conllu >${conllu%.conllu}.txt
+    done
+  fi
+done
+rm -rf ud-treebanks-v2.13.tgz ud-treebanks-v2.13/
+
+for dir in */; do
+  echo "${dir%/}	$(grep -cP "^\d+\t" $dir*train.conllu)"
+done | sort -rnk2 >langs_sizes
+
+# Get the non-UD small datasets
+corpus=la_sabellicus
+echo Fetching $corpus
+mkdir -p $corpus
+wget https://raw.githubusercontent.com/CIRCSE/Sabellicus/main/Sabellicus_DeLatinaeLinguaeReparatione.conllu -O $corpus/$corpus-train.conllu
+
+corpus=la_archimedes
+echo Fetching $corpus
+mkdir -p $corpus
+wget https://raw.githubusercontent.com/mfantoli/ArchimedesLatinus/main/training_data_final_git.conllu -O $corpus/tmp1.conllu
+wget https://raw.githubusercontent.com/mfantoli/ArchimedesLatinus/main/spirals_XIX_XX_test_git.conllu -O $corpus/tmp2.conllu
+cat $corpus/tmp1.conllu $corpus/tmp2.conllu > $corpus/$corpus-train.conllu
+rm $corpus/tmp1.conllu $corpus/tmp2.conllu
+
+# Get the test data
+wget https://github.com/CIRCSE/LT4HALA/raw/db51eaa114f437ac5c6cc04e802fc50cbd8b9f67/2024/data_and_doc/EvaLatin_2024_Syntactic_Parsing_test_data.zip
+mkdir -p evalatin24
+unzip -j EvaLatin_2024_Syntactic_Parsing_test_data.zip -d evalatin24/ -x "*/.*"
+rm EvaLatin_2024_Syntactic_Parsing_test_data.zip
+
+# Get harmonized PROIEL
+mkdir -p la_proielh/
+for split in train dev test; do
+  wget https://github.com/fjambe/Latin-variability/raw/98f676c8a4575aee24c66fee73a09aecbe515643/morpho_harmonization/morpho-harmonized-treebanks/UD_Latin-PROIEL/MM-la_proiel-ud-$split.conllu -O la_proielh/la_proielh-ud-$split.conllu
+done

src/evalatin2024-latinpipe/latinpipe-evalatin24-240520/LICENSE

@@ -0,0 +1,435 @@
+Attribution-NonCommercial-ShareAlike 4.0 International
+
+=======================================================================
+
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+does not provide legal services or legal advice. Distribution of
+Creative Commons public licenses does not create a lawyer-client or
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+
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src/evalatin2024-latinpipe/latinpipe-evalatin24-240520/README.md

@@ -0,0 +1,71 @@
+# The `latinpipe-evalatin24-240520` Model
+
+The `latinpipe-evalatin24-240520` is a `PhilBerta`-based model for tagging,
+lemmatization, and dependency parsing of Latin, based on the winning entry
+to the EvaLatin 2024 <https://circse.github.io/LT4HALA/2024/EvaLatin> shared
+task. It is released at https://hdl.handle.net/11234/1-5671 under the CC
+BY-NC-SA 4.0 license.
+
+The model is also available in the [UDPipe LINDAT/CLARIN service](http://lindat.mff.cuni.cz/services/udpipe/)
+ and can be used either in a web form or through a REST service.
+
+The model was trained using the following command:
+```sh
+la_ud213_all="la_ittb la_llct la_perseus la_proiel la_udante"
+la_other="la_archimedes la_sabellicus"
+transformer="bowphs/PhilBerta"  # or bowphs/LaBerta
+
+latinpipe_evalatin24.py $(for split in dev test train; do echo --$split; for tb in $la_ud213_all; do [ $tb-$split = la_proiel-train ] && tb=la_proielh; echo data/$tb/$tb-ud-$split.conllu; done; done) $(for tb in $la_other; do echo data/$tb/$tb-train.conllu; done) --transformers $transformer --epochs=30 --exp=latinpipe-evalatin24-240520 --subword_combination=last --epochs_frozen=10 --batch_size=64 --save_checkpoint
+```
+
+## EvaLatin 2024 LAS Results
+
+The model achieves the following EvaLatin 2024 results (measured by the
+official scorer). Note that the results are worse than in the paper, where the
+model used the gold POS tags and was ensembled.
+
+Treebank              | UAS   | LAS   |
+:-------------------- |:-----:|:-----:|
+EvaLatin 2024 Poetry  | 78.31 | 72.36 |
+EvaLatin 2024 Prose   | 80.49 | 75.20 |
+EvaLatin 2024 Average | 79.40 | 73.78 |
+
+## UD 2.13 Results
+
+The model achieves the following UPOS, UFeats, Lemmas, UAS, LAS metrics (as
+measured by the official scorer) on the UD 2.13 test data. Note that the model
+was trained on harmonized PROIEL, so we do not include the official PROIEL
+treebank in the evaluation.
+
+Treebank | UPOS  | UFeats | Lemmas | UAS   | LAS   |
+:--------|:-----:|:------:|:------:|:-----:|:-----:|
+ITTB     | 99.30 | 98.53  | 98.64  | 93.82 | 92.31 |
+LLCT     | 99.80 | 97.60  | 96.39  | 96.37 | 95.35 |
+Perseus  | 96.01 | 91.14  | 88.88  | 87.93 | 82.50 |
+UDante   | 93.73 | 89.27  | 87.76  | 83.97 | 78.67 |
+
+## Predicting with the `latinpipe-evalatin24-240520` Model
+
+To predict with the `latinpipe-evalatin24-240520` model, you can use the following command:
+```sh
+latinpipe_evalatin24.py --load latinpipe-evalatin24-240520/model.weights.h5 --exp target_directory --test input1.conllu input2.conllu
+```
+- the outputs are generated in the target directory, with a `.predicted.conllu` suffix;
+- if you want to also evaluate the predicted files, you can use `--dev` option instead of `--test`.
+
+## How to Cite
+
+```
+@inproceedings{straka-etal-2024-ufal,
+    title = "{{\'U}FAL} {L}atin{P}ipe at {E}va{L}atin 2024: Morphosyntactic Analysis of {L}atin",
+    author = "Straka, Milan  and Strakov{\'a}, Jana  and Gamba, Federica",
+    editor = "Sprugnoli, Rachele  and Passarotti, Marco",
+    booktitle = "Proceedings of the Third Workshop on Language Technologies for Historical and Ancient Languages (LT4HALA) @ LREC-COLING-2024",
+    month = may,
+    year = "2024",
+    address = "Torino, Italia",
+    publisher = "ELRA and ICCL",
+    url = "https://aclanthology.org/2024.lt4hala-1.24",
+    pages = "207--214"
+}
+```

src/evalatin2024-latinpipe/latinpipe_evalatin24.py

@@ -0,0 +1,944 @@
+#!/usr/bin/env python3
+#
+# This file is part of LatinPipe EvaLatin 24
+# <https://github.com/ufal/evalatin2024-latinpipe>.
+#
+# Copyright 2024 Institute of Formal and Applied Linguistics, Faculty of
+# Mathematics and Physics, Charles University in Prague, Czech Republic.
+#
+# This Source Code Form is subject to the terms of the Mozilla Public
+# License, v. 2.0. If a copy of the MPL was not distributed with this
+# file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+import argparse
+import collections
+import datetime
+import difflib
+import io
+import json
+import os
+import pickle
+import re
+from typing import Self
+os.environ.setdefault("KERAS_BACKEND", "torch")
+
+import keras
+import numpy as np
+import torch
+import transformers
+import ufal.chu_liu_edmonds
+
+import latinpipe_evalatin24_eval
+
+parser = argparse.ArgumentParser()
+parser.add_argument("--batch_size", default=32, type=int, help="Batch size.")
+parser.add_argument("--deprel", default="full", choices=["full", "universal"], type=str, help="Deprel kind.")
+parser.add_argument("--dev", default=[], nargs="+", type=str, help="Dev CoNLL-U files.")
+parser.add_argument("--dropout", default=0.5, type=float, help="Dropout")
+parser.add_argument("--embed_tags", default="", type=str, help="Tags to embed on input.")
+parser.add_argument("--epochs", default=30, type=int, help="Number of epochs.")
+parser.add_argument("--epochs_frozen", default=0, type=int, help="Number of epochs with frozen transformer.")
+parser.add_argument("--exp", default=None, type=str, help="Experiment name.")
+parser.add_argument("--label_smoothing", default=0.03, type=float, help="Label smoothing.")
+parser.add_argument("--learning_rate", default=2e-5, type=float, help="Learning rate.")
+parser.add_argument("--learning_rate_decay", default="cos", choices=["none", "cos"], type=str, help="Learning rate decay.")
+parser.add_argument("--learning_rate_warmup", default=2_000, type=int, help="Number of warmup steps.")
+parser.add_argument("--load", default=[], type=str, nargs="*", help="Path to load models from.")
+parser.add_argument("--max_train_sentence_len", default=150, type=int, help="Max sentence subwords in training.")
+parser.add_argument("--optimizer", default="adam", choices=["adam", "adafactor"], type=str, help="Optimizer.")
+parser.add_argument("--parse", default=1, type=int, help="Parse.")
+parser.add_argument("--parse_attention_dim", default=512, type=int, help="Parse attention dimension.")
+parser.add_argument("--rnn_dim", default=512, type=int, help="RNN layers size.")
+parser.add_argument("--rnn_layers", default=2, type=int, help="RNN layers.")
+parser.add_argument("--rnn_type", default="LSTMTorch", choices=["LSTM", "GRU", "LSTMTorch", "GRUTorch"], help="RNN type.")
+parser.add_argument("--save_checkpoint", default=False, action="store_true", help="Save checkpoint.")
+parser.add_argument("--seed", default=42, type=int, help="Initial random seed.")
+parser.add_argument("--steps_per_epoch", default=1_000, type=int, help="Steps per epoch.")
+parser.add_argument("--single_root", default=1, type=int, help="Single root allowed only.")
+parser.add_argument("--subword_combination", default="first", choices=["first", "last", "sum", "concat"], type=str, help="Subword combination.")
+parser.add_argument("--tags", default="UPOS,LEMMAS,FEATS", type=str, help="Tags to predict.")
+parser.add_argument("--task_hidden_layer", default=2_048, type=int, help="Task hidden layer size.")
+parser.add_argument("--test", default=[], nargs="+", type=str, help="Test CoNLL-U files.")
+parser.add_argument("--train", default=[], nargs="+", type=str, help="Train CoNLL-U files.")
+parser.add_argument("--train_sampling_exponent", default=0.5, type=float, help="Train sampling exponent.")
+parser.add_argument("--transformers", nargs="+", type=str, help="Transformers models to use.")
+parser.add_argument("--treebank_ids", default=False, action="store_true", help="Include treebank IDs on input.")
+parser.add_argument("--threads", default=4, type=int, help="Maximum number of threads to use.")
+parser.add_argument("--verbose", default=2, type=int, help="Verbosity")
+parser.add_argument("--wandb", default=False, action="store_true", help="Log in WandB.")
+parser.add_argument("--word_masking", default=None, type=float, help="Word masking")
+
+os.environ["PYTORCH_MPS_HIGH_WATERMARK_RATIO"] = "0.0"
+
+class UDDataset:
+    FORMS, LEMMAS, UPOS, XPOS, FEATS, HEAD, DEPREL, DEPS, MISC, FACTORS = range(10)
+    FACTORS_MAP = {"FORMS": FORMS, "LEMMAS": LEMMAS, "UPOS": UPOS, "XPOS": XPOS, "FEATS": FEATS,
+                   "HEAD": HEAD, "DEPREL": DEPREL, "DEPS": DEPS, "MISC": MISC}
+    RE_EXTRAS = re.compile(r"^#|^\d+-|^\d+\.")
+
+    class Factor:
+        def __init__(self, train_factor: Self = None):
+            self.words_map = train_factor.words_map if train_factor else {"<unk>": 0}
+            self.words = train_factor.words if train_factor else ["<unk>"]
+            self.word_ids = []
+            self.strings = []
+
+    def __init__(self, path: str, args: argparse.Namespace, treebank_id: int|None = None, train_dataset: Self = None, text: str|None = None):
+        self.path = path
+
+        # Create factors and other variables
+        self.factors = []
+        for f in range(self.FACTORS):
+            self.factors.append(self.Factor(train_dataset.factors[f] if train_dataset is not None else None))
+        self._extras = []
+
+        lemma_transforms = collections.Counter()
+
+        # Load the CoNLL-U file
+        with open(path, "r", encoding="utf-8") if text is None else io.StringIO(text) as file:
+            in_sentence = False
+            for line in file:
+                line = line.rstrip("\r\n")
+
+                if line:
+                    if self.RE_EXTRAS.match(line):
+                        if in_sentence:
+                            while len(self._extras) < len(self.factors[0].strings): self._extras.append([])
+                            while len(self._extras[-1]) <= len(self.factors[0].strings[-1]):
+                                self._extras[-1].append("")
+                        else:
+                            while len(self._extras) <= len(self.factors[0].strings): self._extras.append([])
+                            if not len(self._extras[-1]): self._extras[-1].append("")
+                        self._extras[-1][-1] += ("\n" if self._extras[-1][-1] else "") + line
+                        continue
+
+                    columns = line.split("\t")[1:]
+                    for f in range(self.FACTORS):
+                        factor = self.factors[f]
+                        if not in_sentence:
+                            factor.word_ids.append([])
+                            factor.strings.append([])
+
+                        word = columns[f]
+                        factor.strings[-1].append(word)
+
+                        # Add word to word_ids
+                        if f == self.FORMS:
+                            # For formw, we do not remap strings into IDs because the tokenizer will create the subwords IDs for us.
+                            factor.word_ids[-1].append(0)
+                        elif f == self.HEAD:
+                            factor.word_ids[-1].append(int(word) if word != "_" else -1)
+                        elif f == self.LEMMAS:
+                            factor.word_ids[-1].append(0)
+                            lemma_transforms[(columns[self.FORMS], word)] += 1
+                        else:
+                            if f == self.DEPREL and args.deprel == "universal":
+                                word = word.split(":")[0]
+                            if word not in factor.words_map:
+                                if train_dataset is not None:
+                                    word = "<unk>"
+                                else:
+                                    factor.words_map[word] = len(factor.words)
+                                    factor.words.append(word)
+                            factor.word_ids[-1].append(factor.words_map[word])
+                    in_sentence = True
+                else:
+                    in_sentence = False
+                    for factor in self.factors:
+                        if len(factor.word_ids): factor.word_ids[-1] = np.array(factor.word_ids[-1], np.int32)
+
+            # Also load the file for evaluation if it is not a training dataset
+            if train_dataset is not None:
+                file.seek(0, io.SEEK_SET)
+                self.conllu_for_eval = latinpipe_evalatin24_eval.load_conllu(file)
+
+        # Construct lemma rules
+        self.finalize_lemma_rules(lemma_transforms, create_rules=train_dataset is None)
+
+        # The dataset consists of a single treebank
+        self.treebank_ranges = [(0, len(self))]
+        self.treebank_ids = [treebank_id]
+
+        # Create an empty tokenize cache
+        self._tokenizer_cache = {}
+
+    def __len__(self):
+        return len(self.factors[0].strings)
+
+    def save_mappings(self, path: str) -> None:
+        mappings = UDDataset.__new__(UDDataset)
+        mappings.factors = []
+        for factor in self.factors:
+            mappings.factors.append(UDDataset.Factor.__new__(UDDataset.Factor))
+            mappings.factors[-1].words = factor.words
+        with open(path, "wb") as mappings_file:
+            pickle.dump(mappings, mappings_file, protocol=4)
+
+    @staticmethod
+    def from_mappings(path: str) -> Self:
+        with open(path, "rb") as mappings_file:
+            mappings = pickle.load(mappings_file)
+        for factor in mappings.factors:
+            factor.words_map = {word: i for i, word in enumerate(factor.words)}
+        return mappings
+
+    @staticmethod
+    def create_lemma_rule(form: str, lemma: str) -> str:
+        diff = difflib.SequenceMatcher(None, form.lower(), lemma.lower(), False)
+        rule, in_prefix = [], True
+        for tag, i1, i2, j1, j2 in diff.get_opcodes():
+            if i2 > len(form) // 3 and in_prefix:
+                in_prefix = False
+                if tag == "equal":
+                    mode, jd = "L" if lemma[j2 - 1].islower() else "U", j2 - 1
+                    while jd > j1 and lemma[jd - 1].islower() == lemma[j2 - 1].islower(): jd -= 1
+                    rule.extend(["l" if lemma[j].islower() else "u" for j in range(j1, jd)])
+                    rule.extend(mode * (len(form) - i2 + 1))
+                if tag in ["replace", "delete"]:
+                    rule.extend("D" * (len(form) - i2 + 1))
+                if tag in ["replace", "insert"]:
+                    rule.extend("i" + lemma[j] for j in range(j1, j2))
+            else:
+                if tag == "equal":
+                    rule.extend(["l" if lemma[j].islower() else "u" for j in range(j1, j2)])
+                if tag in ["replace", "delete"]:
+                    rule.extend("d" * (i2 - i1))
+                if tag in ["replace", "insert"]:
+                    rule.extend("i" + lemma[j] for j in range(j1, j2))
+        return "".join(rule)
+
+    @staticmethod
+    def apply_lemma_rule(rule: str, form: str) -> str:
+        def error():
+            # print("Error: cannot decode lemma rule '{}' with form '{}', copying input.".format(rule, form))
+            return form
+
+        if rule == "<unk>":
+            return form
+
+        lemma, r, i = [], 0, 0
+        while r < len(rule):
+            if rule[r] == "i":
+                if r + 1 == len(rule):
+                    return error()
+                r += 1
+                lemma.append(rule[r])
+            elif rule[r] == "d":
+                i += 1
+            elif rule[r] in ("l", "u"):
+                if i == len(form):
+                    return error()
+                lemma.append(form[i].lower() if rule[r] == "l" else form[i].upper())
+                i += 1
+            elif rule[r] in ("L", "U", "D"):
+                i2 = len(form)
+                while r + 1 < len(rule) and rule[r + 1] == rule[r]:
+                    r += 1
+                    i2 -= 1
+                if i2 < i:
+                    return error()
+                if rule[r] == "L":
+                    lemma.extend(form[i:i2].lower())
+                if rule[r] == "U":
+                    lemma.extend(form[i:i2].upper())
+                i = i2
+            else:
+                return error()
+            r += 1
+        if i != len(form) or not lemma:
+            return error()
+        return "".join(lemma)
+
+    def finalize_lemma_rules(self, lemma_transforms: collections.Counter, create_rules: bool) -> None:
+        forms, lemmas = self.factors[self.FORMS], self.factors[self.LEMMAS]
+
+        # Generate all rules
+        rules_merged, rules_all = collections.Counter(), {}
+        for form, lemma in lemma_transforms:
+            rule = self.create_lemma_rule(form, lemma)
+            rules_all[(form, lemma)] = rule
+            if create_rules:
+                rules_merged[rule] += 1
+
+        # Keep the rules that are used more than once
+        if create_rules:
+            for rule, count in rules_merged.items():
+                if count > 1:
+                    lemmas.words_map[rule] = len(lemmas.words)
+                    lemmas.words.append(rule)
+
+        # Store the rules in the dataset
+        for i in range(len(forms.strings)):
+            for j in range(len(forms.strings[i])):
+                rule = rules_all.get((forms.strings[i][j], lemmas.strings[i][j]))
+                lemmas.word_ids[i][j] = lemmas.words_map.get(rule, 0)
+
+    def tokenize(self, tokenizer: transformers.PreTrainedTokenizer) -> tuple[list[np.ndarray], list[np.ndarray]]:
+        if tokenizer not in self._tokenizer_cache:
+            assert tokenizer.cls_token_id is not None, "The tokenizer must have a CLS token"
+
+            tokenized = tokenizer(self.factors[0].strings, add_special_tokens=True, is_split_into_words=True)
+
+            tokens, word_indices = [], []
+            for i, sentence in enumerate(tokenized.input_ids):
+                offset = 0
+                if not len(sentence) or sentence[0] != tokenizer.cls_token_id:
+                    # Handle tokenizers that do not add CLS tokens, which we need for prediction
+                    # of the root nodes during parsing. For such tokenizers, we added the CLS token
+                    # manually already, but the build_inputs_with_special_tokens() might not have added it.
+                    sentence = [tokenizer.cls_token_id] + sentence
+                    offset = 1
+
+                treebank_id = None
+                for id_, (start, end) in zip(self.treebank_ids, self.treebank_ranges):
+                    if start <= i < end:
+                        treebank_id = id_
+                if treebank_id is not None:
+                    sentence.insert(1, tokenizer.additional_special_tokens_ids[treebank_id])
+                    offset += 1
+
+                tokens.append(np.array(sentence, dtype=np.int32))
+                word_indices.append([(0, 0)])
+                for j in range(len(self.factors[0].strings[i])):
+                    span = tokenized.word_to_tokens(i, j)
+                    if (span == None):
+                        print("-x-x-x-", i, j)
+                    try:
+                        word_indices[-1].append((offset + span.start, offset + span.end - 1))
+                    except:
+                        #abracadabra = 0
+                        print(treebank_id)
+                        input("??")
+                word_indices[-1] = np.array(word_indices[-1], dtype=np.int32)
+
+
+            self._tokenizer_cache[tokenizer] = (tokens, word_indices)
+
+        return self._tokenizer_cache[tokenizer]
+
+    def write_sentence(self, output: io.TextIOBase, index: int, overrides: list = None) -> None:
+        assert index < len(self.factors[0].strings), "Sentence index out of range"
+
+        for i in range(len(self.factors[0].strings[index]) + 1):
+            # Start by writing extras
+            if index < len(self._extras) and i < len(self._extras[index]) and self._extras[index][i]:
+                print(self._extras[index][i], file=output)
+            if i == len(self.factors[0].strings[index]): break
+
+            fields = []
+            fields.append(str(i + 1))
+            for f in range(self.FACTORS):
+                factor = self.factors[f]
+                field = factor.strings[index][i]
+
+                # Overrides
+                if overrides is not None and f < len(overrides) and overrides[f] is not None:
+                    override = overrides[f][i]
+                    if f == self.HEAD:
+                        field = str(override) if override >= 0 else "_"
+                    else:
+                        field = factor.words[override]
+                        if f == self.LEMMAS:
+                            field = self.apply_lemma_rule(field, self.factors[self.FORMS].strings[index][i])
+                fields.append(field)
+
+            print("\t".join(fields), file=output)
+        print(file=output)
+
+
+class UDDatasetMerged(UDDataset):
+    def __init__(self, datasets: list[UDDataset]):
+        # Create factors and other variables
+        self.factors = []
+        for f in range(self.FACTORS):
+            self.factors.append(self.Factor(None))
+
+        lemma_transforms = collections.Counter()
+
+        self.treebank_ranges, self.treebank_ids = [], []
+        for dataset in datasets:
+            assert len(dataset.treebank_ranges) == len(dataset.treebank_ids) == 1
+            self.treebank_ranges.append((len(self), len(self) + len(dataset)))
+            self.treebank_ids.append(dataset.treebank_ids[0])
+            for s in range(len(dataset)):
+                for f in range(self.FACTORS):
+                    factor = self.factors[f]
+                    factor.strings.append(dataset.factors[f].strings[s])
+                    factor.word_ids.append([])
+                    for i, word in enumerate(dataset.factors[f].strings[s]):
+                        if f == self.FORMS:
+                            # We do not remap strings into IDs because the tokenizer will create the subwords IDs for us.
+                            factor.word_ids[-1].append(0)
+                        if f == self.HEAD:
+                            factor.word_ids[-1].append(word)
+                        elif f == self.LEMMAS:
+                            factor.word_ids[-1].append(0)
+                            lemma_transforms[(dataset.factors[self.FORMS].strings[s][i], word)] += 1
+                        else:
+                            if word not in factor.words_map:
+                                factor.words_map[word] = len(factor.words)
+                                factor.words.append(word)
+                            factor.word_ids[-1].append(factor.words_map[word])
+                    self.factors[f].word_ids[-1] = np.array(self.factors[f].word_ids[-1], np.int32)
+
+        # Construct lemma rules
+        self.finalize_lemma_rules(lemma_transforms, create_rules=True)
+
+        # Create an empty tokenize cache
+        self._tokenizer_cache = {}
+
+
+class TorchUDDataset(torch.utils.data.Dataset):
+    def __init__(self, ud_dataset: UDDataset, tokenizers: list[transformers.PreTrainedTokenizer], args: argparse.Namespace, training: bool):
+        self.ud_dataset = ud_dataset
+        self.training = training
+        self._outputs_to_input = [args.tags.index(tag) for tag in args.embed_tags]
+
+        self._inputs = [ud_dataset.tokenize(tokenizer) for tokenizer in tokenizers]
+        self._outputs = [ud_dataset.factors[tag].word_ids for tag in args.tags]
+        if args.parse:
+            self._outputs.append(ud_dataset.factors[ud_dataset.HEAD].word_ids)
+            self._outputs.append(ud_dataset.factors[ud_dataset.DEPREL].word_ids)
+
+        # Trim the sentences if needed
+        if training and args.max_train_sentence_len:
+            trimmed_sentences = 0
+            for index in range(len(self)):  # Over sentences
+                max_words, need_trimming = None, False
+                for tokens, word_indices in self._inputs:  # Over transformers
+                    if max_words is None:
+                        max_words = len(word_indices[index])
+                    while word_indices[index][max_words - 1, 1] >= args.max_train_sentence_len:
+                        max_words -= 1
+                        need_trimming = True
+                assert max_words >= 2, "Sentence too short after trimming"
+
+                if need_trimming:
+                    for tokens, word_indices in self._inputs:  # Over transformers
+                        tokens[index] = tokens[index][:word_indices[index][max_words - 1, 1] + 1]
+                        word_indices[index] = word_indices[index][:max_words]
+
+                    for output in self._outputs:
+                        output[index] = output[index][:max_words - 1]  # No CLS tokens in outputs
+                    if args.parse:
+                        self._outputs[-2][index] = np.array([head if head < max_words else -1 for head in self._outputs[-2][index]], np.int32)
+
+                    trimmed_sentences += 1
+            if trimmed_sentences:
+                print("Trimmed {} out of {} sentences".format(trimmed_sentences, len(self)))
+
+    def __len__(self):
+        return len(self.ud_dataset)
+
+    def __getitem__(self, index: int):
+        inputs = []
+        for tokens, word_indices in self._inputs:
+            inputs.append(torch.from_numpy(tokens[index]))
+            inputs.append(torch.from_numpy(word_indices[index]))
+        for i in self._outputs_to_input:
+            inputs.append(torch.from_numpy(self._outputs[i][index]))
+
+        outputs = []
+        for output in self._outputs:
+            outputs.append(torch.from_numpy(output[index]))
+
+        return inputs, outputs
+
+
+class TorchUDDataLoader(torch.utils.data.DataLoader):
+    class MergedDatasetSampler(torch.utils.data.Sampler):
+        def __init__(self, ud_dataset: UDDataset, args: argparse.Namespace):
+            self._treebank_ranges = ud_dataset.treebank_ranges
+            self._sentences_per_epoch = args.steps_per_epoch * args.batch_size
+            self._generator = torch.Generator().manual_seed(args.seed)
+
+            treebank_weights = np.array([r[1] - r[0] for r in self._treebank_ranges], np.float32)
+            treebank_weights = treebank_weights ** args.train_sampling_exponent
+            treebank_weights /= np.sum(treebank_weights)
+            self._treebank_sizes = np.array(treebank_weights * self._sentences_per_epoch, np.int32)
+            self._treebank_sizes[:self._sentences_per_epoch - np.sum(self._treebank_sizes)] += 1
+            self._treebank_indices = [[] for _ in self._treebank_ranges]
+
+        def __len__(self):
+            return self._sentences_per_epoch
+
+        def __iter__(self):
+            indices = []
+            for i in range(len(self._treebank_ranges)):
+                required = self._treebank_sizes[i]
+                while required:
+                    if not len(self._treebank_indices[i]):
+                        self._treebank_indices[i] = self._treebank_ranges[i][0] + torch.randperm(
+                            self._treebank_ranges[i][1] - self._treebank_ranges[i][0], generator=self._generator)
+                    indices.append(self._treebank_indices[i][:required])
+                    required -= min(len(self._treebank_indices[i]), required)
+            indices = torch.concatenate(indices, axis=0)
+            return iter(indices[torch.randperm(len(indices), generator=self._generator)])
+
+    def _collate_fn(self, batch):
+        inputs, outputs = zip(*batch)
+
+        batch_inputs = []
+        for sequences in zip(*inputs):
+            batch_inputs.append(torch.nn.utils.rnn.pad_sequence(sequences, batch_first=True, padding_value=-1))
+
+        batch_outputs = []
+        for output in zip(*outputs):
+            batch_outputs.append(torch.nn.utils.rnn.pad_sequence(output, batch_first=True, padding_value=-1))
+
+        batch_weights = [batch_output != -1 for batch_output in batch_outputs]
+
+        return tuple(batch_inputs), tuple(batch_outputs), tuple(batch_weights)
+
+    def __init__(self, dataset: TorchUDDataset, args: argparse.Namespace, **kwargs):
+        sampler = None
+        if dataset.training:
+            if len(dataset.ud_dataset.treebank_ranges) == 1:
+                sampler = torch.utils.data.RandomSampler(dataset, generator=torch.Generator().manual_seed(args.seed))
+            else:
+                assert args.steps_per_epoch is not None, "Steps per epoch must be specified when training on multiple treebanks"
+                sampler = self.MergedDatasetSampler(dataset.ud_dataset, args)
+        super().__init__(dataset, batch_size=args.batch_size, sampler=sampler, collate_fn=self._collate_fn, **kwargs)
+
+
+class LatinPipeModel(keras.Model):
+    class HFTransformerLayer(keras.layers.Layer):
+        def __init__(self, transformer: transformers.PreTrainedModel, subword_combination: str, word_masking: float = None, mask_token_id: int = None, **kwargs):
+            super().__init__(**kwargs)
+            self._transformer = transformer
+            self._subword_combination = subword_combination
+            self._word_masking = word_masking
+            self._mask_token_id = mask_token_id
+
+        def call(self, inputs, word_indices, training=None):
+            if training and self._word_masking:
+                mask = keras.ops.cast(keras.random.uniform(keras.ops.shape(inputs), dtype="float32") < self._word_masking, inputs.dtype)
+                inputs = (1 - mask) * inputs + mask * self._mask_token_id
+            if (training or False) != self._transformer.training:
+                self._transformer.train(training or False)
+            if self._subword_combination != "last":
+                first_subwords = keras.ops.take_along_axis(
+                    self._transformer(keras.ops.maximum(inputs, 0), attention_mask=inputs > -1).last_hidden_state,
+                    keras.ops.expand_dims(keras.ops.maximum(word_indices[..., 0], 0), axis=-1),
+                    axis=1,
+                )
+            if self._subword_combination != "first":
+                last_subwords = keras.ops.take_along_axis(
+                    self._transformer(keras.ops.maximum(inputs, 0), attention_mask=inputs > -1).last_hidden_state,
+                    keras.ops.expand_dims(keras.ops.maximum(word_indices[..., 1], 0), axis=-1),
+                    axis=1,
+                )
+            if self._subword_combination == "first":
+                return first_subwords
+            elif self._subword_combination == "last":
+                return last_subwords
+            elif self._subword_combination == "sum":
+                return first_subwords + last_subwords
+            elif self._subword_combination == "concat":
+                return keras.ops.concatenate([first_subwords, last_subwords], axis=-1)
+            else:
+                raise ValueError("Unknown subword combination '{}'".format(self._subword_combination))
+
+    class LSTMTorch(keras.layers.Layer):
+        def __init__(self, units: int, **kwargs):
+            super().__init__(**kwargs)
+            self._units = units
+
+        def build(self, input_shape):
+            self._lstm = torch.nn.LSTM(input_shape[-1], self._units, batch_first=True, bidirectional=True)
+
+        def call(self, inputs, lengths):
+            packed_result, _ = self._lstm.module(torch.nn.utils.rnn.pack_padded_sequence(inputs, lengths.cpu(), batch_first=True, enforce_sorted=False))
+            unpacked_result = torch.nn.utils.rnn.unpack_sequence(packed_result)
+            return torch.nn.utils.rnn.pad_sequence(unpacked_result, batch_first=True, padding_value=0)
+
+    class GRUTorch(keras.layers.Layer):
+        def __init__(self, units: int, **kwargs):
+            super().__init__(**kwargs)
+            self._units = units
+
+        def build(self, input_shape):
+            self._gru = torch.nn.GRU(input_shape[-1], self._units, batch_first=True, bidirectional=True)
+
+        def call(self, inputs, lengths):
+            packed_result, _ = self._gru(torch.nn.utils.rnn.pack_padded_sequence(inputs, lengths.cpu(), batch_first=True, enforce_sorted=False))
+            unpacked_result = torch.nn.utils.rnn.unpack_sequence(packed_result)
+            return torch.nn.utils.rnn.pad_sequence(unpacked_result, batch_first=True, padding_value=0)
+
+    class ParsingHead(keras.layers.Layer):
+        def __init__(self, num_deprels: int, task_hidden_layer: int, parse_attention_dim: int, dropout: float, **kwargs):
+            super().__init__(**kwargs)
+            self._head_queries_hidden = keras.layers.Dense(task_hidden_layer, activation="relu")
+            self._head_queries_output = keras.layers.Dense(parse_attention_dim)
+            self._head_keys_hidden = keras.layers.Dense(task_hidden_layer, activation="relu")
+            self._head_keys_output = keras.layers.Dense(parse_attention_dim)
+            self._deprel_hidden = keras.layers.Dense(task_hidden_layer, activation="relu")
+            self._deprel_output = keras.layers.Dense(num_deprels)
+            self._dropout = keras.layers.Dropout(dropout)
+
+        def call(self, embeddings, embeddings_wo_root, embeddings_mask):
+            head_queries = self._head_queries_output(self._dropout(self._head_queries_hidden(embeddings_wo_root)))
+            head_keys = self._head_keys_output(self._dropout(self._head_keys_hidden(embeddings)))
+            head_scores = keras.ops.matmul(head_queries, keras.ops.transpose(head_keys, axes=[0, 2, 1])) / keras.ops.sqrt(head_queries.shape[-1])
+
+            head_scores_mask = keras.ops.cast(keras.ops.expand_dims(embeddings_mask, axis=1), head_scores.dtype)
+            head_scores = head_scores * head_scores_mask - 1e9 * (1 - head_scores_mask)
+
+            predicted_heads = keras.ops.argmax(head_scores, axis=-1)
+            predicted_head_embeddings = keras.ops.take_along_axis(embeddings, keras.ops.expand_dims(predicted_heads, axis=-1), axis=1)
+            deprel_hidden = keras.ops.concatenate([embeddings_wo_root, predicted_head_embeddings], axis=-1)
+            deprel_scores = self._deprel_output(self._dropout(self._deprel_hidden(deprel_hidden)))
+
+            return head_scores, deprel_scores
+
+    class SparseCategoricalCrossentropyWithLabelSmoothing(keras.losses.Loss):
+        def __init__(self, from_logits: bool, label_smoothing: float, **kwargs):
+            super().__init__(**kwargs)
+            self._from_logits = from_logits
+            self._label_smoothing = label_smoothing
+
+        def call(self, y_true, y_pred):
+            y_gold = keras.ops.one_hot(keras.ops.maximum(y_true, 0), y_pred.shape[-1])
+            if self._label_smoothing:
+                y_pred_mask = keras.ops.cast(y_pred > -1e9, y_pred.dtype)
+                y_gold = y_gold * (1 - self._label_smoothing) + y_pred_mask / keras.ops.sum(y_pred_mask, axis=-1, keepdims=True) * self._label_smoothing
+            return keras.losses.categorical_crossentropy(y_gold, y_pred, from_logits=self._from_logits)
+
+    def __init__(self, dataset: UDDataset, args: argparse.Namespace):
+        self._dataset = dataset
+        self._args = args
+
+        # Create the transformer models
+        self._tokenizers, self._transformers = [], []
+        for name in args.transformers:
+            self._tokenizers.append(transformers.AutoTokenizer.from_pretrained(name, add_prefix_space=True))
+
+            transformer, transformer_opts = transformers.AutoModel, {}
+            if "mt5" in name.lower():
+                transformer = transformers.MT5EncoderModel
+            if name.endswith(("LaTa", "PhilTa")):
+                transformer = transformers.T5EncoderModel
+            if name.endswith(("LaBerta", "PhilBerta")):
+                transformer_opts["add_pooling_layer"] = False
+
+            if args.load:
+                transformer = transformer.from_config(transformers.AutoConfig.from_pretrained(name), **transformer_opts)
+            else:
+                transformer = transformer.from_pretrained(name, **transformer_opts)
+
+            # Create additional tokens
+            additional_tokens = {}
+            if args.treebank_ids:
+                additional_tokens["additional_special_tokens"] = ["[TREEBANK_ID_{}]".format(i) for i in range(len(dataset.treebank_ids))]
+            if self._tokenizers[-1].cls_token_id is None:  # Generate CLS token if not present (for representing sentence root in parsing).
+                additional_tokens["cls_token"] = "[CLS]"
+            if additional_tokens:
+                self._tokenizers[-1].add_special_tokens(additional_tokens)
+                transformer.resize_token_embeddings(len(self._tokenizers[-1]))
+            if args.treebank_ids:
+                assert len(self._tokenizers[-1].additional_special_tokens) == len(dataset.treebank_ids)
+
+            self._transformers.append(self.HFTransformerLayer(transformer, args.subword_combination, args.word_masking, self._tokenizers[-1].mask_token_id))
+
+        # Create the network
+        inputs = []
+        for _ in args.transformers:
+            inputs.extend([keras.layers.Input(shape=[None], dtype="int32"), keras.layers.Input(shape=[None, 2], dtype="int32")])
+        for _ in args.embed_tags:
+            inputs.append(keras.layers.Input(shape=[None], dtype="int32"))
+
+        # Run the transformer models
+        embeddings = []
+        for tokens, word_indices, transformer in zip(inputs[::2], inputs[1::2], self._transformers):
+            embeddings.append(transformer(tokens, word_indices))
+        embeddings = keras.layers.Concatenate(axis=-1)(embeddings)
+        embeddings = keras.layers.Dropout(args.dropout)(embeddings)
+
+        # Heads for the tagging tasks
+        outputs = []
+        for tag in args.tags:
+            hidden = keras.layers.Dense(args.task_hidden_layer, activation="relu")(embeddings[:, 1:])
+            hidden = keras.layers.Dropout(args.dropout)(hidden)
+            outputs.append(keras.layers.Dense(len(dataset.factors[tag].words))(hidden))
+
+        # Head for parsing
+        if args.parse:
+            if args.embed_tags:
+                all_embeddings = [embeddings]
+                for factor, input_tags in zip(args.embed_tags, inputs[-len(args.embed_tags):]):
+                    embedding_layer = keras.layers.Embedding(len(dataset.factors[factor].words) + 1, 256)
+                    all_embeddings.append(keras.layers.Dropout(args.dropout)(embedding_layer(keras.ops.pad(input_tags + 1, [(0, 0), (1, 0)]))))
+                embeddings = keras.ops.concatenate(all_embeddings, axis=-1)
+
+            for i in range(args.rnn_layers):
+                if args.rnn_type in ["LSTM", "GRU"]:
+                    hidden = keras.layers.Bidirectional(getattr(keras.layers, args.rnn_type)(args.rnn_dim, return_sequences=True))(embeddings, mask=inputs[1][..., 0] > -1)
+                elif args.rnn_type in ["LSTMTorch", "GRUTorch"]:
+                    hidden = getattr(self, args.rnn_type)(args.rnn_dim)(embeddings, keras.ops.sum(inputs[1][..., 0] > -1, axis=-1))
+                hidden = keras.layers.Dropout(args.dropout)(hidden)
+                embeddings = hidden + (embeddings if i else 0)
+
+            outputs.extend(self.ParsingHead(
+                len(dataset.factors[dataset.DEPREL].words), args.task_hidden_layer, args.parse_attention_dim, args.dropout,
+            )(embeddings, embeddings[:, 1:], inputs[1][..., 0] > -1))
+
+        super().__init__(inputs=inputs, outputs=outputs)
+        if args.load:
+            self.load_weights(args.load[0])
+
+    def compile(self, epoch_batches: int, frozen: bool):
+        args = self._args
+
+        for transformer in self._transformers:
+            transformer.trainable = not frozen
+
+        if frozen:
+            schedule = 1e-3
+        else:
+            schedule = keras.optimizers.schedules.CosineDecay(
+                0. if args.learning_rate_warmup else args.learning_rate,
+                args.epochs * epoch_batches - args.learning_rate_warmup,
+                alpha=0.0 if args.learning_rate_decay != "none" else 1.0,
+                warmup_target=args.learning_rate if args.learning_rate_warmup else None,
+                warmup_steps=args.learning_rate_warmup,
+            )
+        if args.optimizer == "adam":
+            optimizer = keras.optimizers.Adam(schedule)
+        elif args.optimizer == "adafactor":
+            optimizer = keras.optimizers.Adafactor(schedule)
+        else:
+            raise ValueError("Unknown optimizer '{}'".format(args.optimizer))
+        super().compile(
+            optimizer=optimizer,
+            loss=self.SparseCategoricalCrossentropyWithLabelSmoothing(from_logits=True, label_smoothing=args.label_smoothing),
+        )
+
+    @property
+    def tokenizers(self) -> list[transformers.PreTrainedTokenizer]:
+        return self._tokenizers
+
+    def predict(self, dataloader: TorchUDDataLoader, save_as: str|None = None, args_override: argparse.Namespace|None = None) -> str:
+        ud_dataset = dataloader.dataset.ud_dataset
+        args = self._args if args_override is None else args_override
+        conllu, sentence = io.StringIO(), 0
+
+        for batch_inputs, _, _ in dataloader:
+            predictions = self.predict_on_batch(batch_inputs)
+            for b in range(len(batch_inputs[0])):
+                sentence_len = len(ud_dataset.factors[ud_dataset.FORMS].strings[sentence])
+                overrides = [None] * ud_dataset.FACTORS
+                for tag, prediction in zip(args.tags, predictions):
+                    overrides[tag] = np.argmax(prediction[b, :sentence_len], axis=-1)
+                if args.parse:
+                    heads, deprels = predictions[-2:]
+                    padded_heads = np.zeros([sentence_len + 1, sentence_len + 1], dtype=np.float64)
+                    padded_heads[1:] = heads[b, :sentence_len, :sentence_len + 1]
+                    padded_heads[1:] -= np.max(padded_heads[1:], axis=-1, keepdims=True)
+                    padded_heads[1:] -= np.log(np.sum(np.exp(padded_heads[1:]), axis=-1, keepdims=True))
+                    if args.single_root:
+                        selected_root = 1 + np.argmax(padded_heads[1:, 0])
+                        padded_heads[:, 0] = np.nan
+                        padded_heads[selected_root, 0] = 0
+                    chosen_heads, _ = ufal.chu_liu_edmonds.chu_liu_edmonds(padded_heads)
+                    overrides[ud_dataset.HEAD] = chosen_heads[1:]
+                    overrides[ud_dataset.DEPREL] = np.argmax(deprels[b, :sentence_len], axis=-1)
+                ud_dataset.write_sentence(conllu, sentence, overrides)
+                sentence += 1
+
+        conllu = conllu.getvalue()
+        if save_as is not None:
+            os.makedirs(os.path.dirname(save_as), exist_ok=True)
+            with open(save_as, "w", encoding="utf-8") as conllu_file:
+                conllu_file.write(conllu)
+        return conllu
+
+    def evaluate(self, dataloader: TorchUDDataLoader, save_as: str|None = None, args_override: argparse.Namespace|None = None) -> tuple[str, dict[str, float]]:
+        conllu = self.predict(dataloader, save_as=save_as, args_override=args_override)
+        evaluation = latinpipe_evalatin24_eval.evaluate(dataloader.dataset.ud_dataset.conllu_for_eval, latinpipe_evalatin24_eval.load_conllu(io.StringIO(conllu)))
+        if save_as is not None:
+            os.makedirs(os.path.dirname(save_as), exist_ok=True)
+            with open(save_as + ".eval", "w", encoding="utf-8") as eval_file:
+                for metric, score in evaluation.items():
+                    print("{}: {:.2f}%".format(metric, 100 * score.f1), file=eval_file)
+        return conllu, evaluation
+
+
+class LatinPipeModelEnsemble:
+    def __init__(self, latinpipe_model: LatinPipeModel, args: argparse.Namespace):
+        self._latinpipe_model = latinpipe_model
+        self._args = args
+
+    def predict(self, dataloader: TorchUDDataLoader, save_as: str|None = None) -> str:
+        def log_softmax(logits):
+            logits -= np.max(logits, axis=-1, keepdims=True)
+            logits -= np.log(np.sum(np.exp(logits), axis=-1, keepdims=True))
+            return logits
+        ud_dataset = dataloader.dataset.ud_dataset
+
+        # First compute all predictions
+        overrides = [[0] * len(ud_dataset) if tag in self._args.tags + ([ud_dataset.HEAD, ud_dataset.DEPREL] if self._args.parse else []) else None
+                     for tag in range(ud_dataset.FACTORS)]
+        for path in self._args.load:
+            self._latinpipe_model.load_weights(path)
+            sentence = 0
+            for batch_inputs, _, _ in dataloader:
+                predictions = self._latinpipe_model.predict_on_batch(batch_inputs)
+                for b in range(len(batch_inputs[0])):
+                    sentence_len = len(ud_dataset.factors[ud_dataset.FORMS].strings[sentence])
+                    for tag, prediction in zip(self._args.tags, predictions):
+                        overrides[tag][sentence] += log_softmax(prediction[b, :sentence_len])
+                    if self._args.parse:
+                        overrides[ud_dataset.HEAD][sentence] += log_softmax(predictions[-2][b, :sentence_len, :sentence_len + 1])
+                        overrides[ud_dataset.DEPREL][sentence] += log_softmax(predictions[-1][b, :sentence_len])
+                    sentence += 1
+
+        # Predict the most likely class and generate CoNLL-U output
+        conllu = io.StringIO()
+        for sentence in range(len(ud_dataset)):
+            sentence_overrides = [None] * ud_dataset.FACTORS
+            for tag in self._args.tags:
+                sentence_overrides[tag] = np.argmax(overrides[tag][sentence], axis=-1)
+            if self._args.parse:
+                padded_heads = np.pad(overrides[ud_dataset.HEAD][sentence], [(1, 0), (0, 0)]).astype(np.float64)
+                if self._args.single_root:
+                    selected_root = 1 + np.argmax(padded_heads[1:, 0])
+                    padded_heads[:, 0] = np.nan
+                    padded_heads[selected_root, 0] = 0
+                chosen_heads, _ = ufal.chu_liu_edmonds.chu_liu_edmonds(padded_heads)
+                sentence_overrides[ud_dataset.HEAD] = chosen_heads[1:]
+                sentence_overrides[ud_dataset.DEPREL] = np.argmax(overrides[ud_dataset.DEPREL][sentence], axis=-1)
+            ud_dataset.write_sentence(conllu, sentence, sentence_overrides)
+
+        conllu = conllu.getvalue()
+        if save_as is not None:
+            os.makedirs(os.path.dirname(save_as), exist_ok=True)
+            with open(save_as, "w", encoding="utf-8") as conllu_file:
+                conllu_file.write(conllu)
+        return conllu
+
+    def evaluate(self, dataloader: TorchUDDataLoader, save_as: str|None = None) -> tuple[str, dict[str, float]]:
+        return LatinPipeModel.evaluate(self, dataloader, save_as=save_as)
+
+
+def main(params: list[str] | None = None) -> None:
+    args = parser.parse_args(params)
+
+    # If supplied, load configuration from a trained model
+    if args.load:
+        with open(os.path.join(os.path.dirname(args.load[0]), "options.json"), mode="r") as options_file:
+            args = argparse.Namespace(**{k: v for k, v in json.load(options_file).items() if k not in [
+                "dev", "exp", "load", "test", "threads", "verbose"]})
+            args = parser.parse_args(params, namespace=args)
+    else:
+        assert args.train, "Either --load or --train must be set."
+        assert args.transformers, "At least one transformer must be specified."
+
+        # Post-process arguments
+        args.embed_tags = [UDDataset.FACTORS_MAP[tag] for tag in args.embed_tags.split(",") if tag]
+        args.tags = [UDDataset.FACTORS_MAP[tag] for tag in args.tags.split(",") if tag]
+        args.script = os.path.basename(__file__)
+
+        # Create logdir
+        args.logdir = os.path.join("logs", "{}{}-{}-{}-s{}".format(
+            args.exp + "-" if args.exp else "",
+            os.path.splitext(os.path.basename(globals().get("__file__", "notebook")))[0],
+            os.environ.get("SLURM_JOB_ID", ""),
+            datetime.datetime.now().strftime("%y%m%d_%H%M%S"),
+            args.seed,
+            # ",".join(("{}={}".format(
+            #     re.sub("(.)[^_]*_?", r"\1", k),
+            #     ",".join(re.sub(r"^.*/", "", str(x)) for x in ((v if len(v) <= 1 else [v[0], "..."]) if isinstance(v, list) else [v])),
+            # ) for k, v in sorted(vars(args).items()) if k not in ["dev", "exp", "load", "test", "threads", "verbose"]))
+        ))
+        print(json.dumps(vars(args), sort_keys=True, ensure_ascii=False, indent=2))
+        os.makedirs(args.logdir, exist_ok=True)
+        with open(os.path.join(args.logdir, "options.json"), mode="w") as options_file:
+            json.dump(vars(args), options_file, sort_keys=True, ensure_ascii=False, indent=2)
+
+    # Set the random seed and the number of threads
+    keras.utils.set_random_seed(args.seed)
+    torch.set_num_threads(args.threads)
+    torch.set_num_interop_threads(args.threads)
+
+    # Load the data
+    if args.treebank_ids and max(len(args.train), len(args.dev), len(args.test)) > 1:
+        print("WARNING: With treebank_ids, treebanks must always be in the same position in the train/dev/test.")
+    if args.load:
+        train = UDDataset.from_mappings(os.path.join(os.path.dirname(args.load[0]), "mappings.pkl"))
+    else:
+        train = UDDatasetMerged([UDDataset(path, args, treebank_id=i if args.treebank_ids else None) for i, path in enumerate(args.train)])
+        train.save_mappings(os.path.join(args.logdir, "mappings.pkl"))
+    devs = [UDDataset(path, args, treebank_id=i if args.treebank_ids else None, train_dataset=train) for i, path in enumerate(args.dev)]
+    tests = [UDDataset(path, args, treebank_id=i if args.treebank_ids else None, train_dataset=train) for i, path in enumerate(args.test)]
+
+    # Create the model
+    model = LatinPipeModel(train, args)
+
+    # Create the dataloaders
+    if not args.load:
+        train_dataloader = TorchUDDataLoader(TorchUDDataset(train, model.tokenizers, args, training=True), args)
+    dev_dataloaders = [TorchUDDataLoader(TorchUDDataset(dataset, model.tokenizers, args, training=False), args) for dataset in devs]
+    test_dataloaders = [TorchUDDataLoader(TorchUDDataset(dataset, model.tokenizers, args, training=False), args) for dataset in tests]
+
+    # Perform prediction if requested
+    if args.load:
+        if len(args.load) > 1:
+            model = LatinPipeModelEnsemble(model, args)
+        for dataloader in dev_dataloaders:
+            model.evaluate(dataloader, save_as=os.path.splitext(
+                os.path.join(args.exp, os.path.basename(dataloader.dataset.ud_dataset.path)) if args.exp else dataloader.dataset.ud_dataset.path
+            )[0] + ".predicted.conllu")
+        for dataloader in test_dataloaders:
+            model.predict(dataloader, save_as=os.path.splitext(
+                os.path.join(args.exp, os.path.basename(dataloader.dataset.ud_dataset.path)) if args.exp else dataloader.dataset.ud_dataset.path
+            )[0] + ".predicted.conllu")
+        return
+
+    # Train the model
+    class Evaluator(keras.callbacks.Callback):
+        def __init__(self, wandb_log):
+            super().__init__()
+            self._wandb_log = wandb_log
+            self._metrics = [["", "Lemmas", "UPOS", "XPOS", "UFeats"][tag] for tag in args.tags] + (["UAS", "LAS"] if args.parse else [])
+
+        def on_epoch_end(self, epoch, logs=None):
+            logs["learning_rate"] = keras.ops.convert_to_numpy(model.optimizer.learning_rate)
+            for dataloader in dev_dataloaders + (test_dataloaders if epoch + 1 == args.epochs + args.epochs_frozen else []):
+                _, metrics = model.evaluate(dataloader, save_as=os.path.splitext(
+                    os.path.join(args.logdir, os.path.basename(dataloader.dataset.ud_dataset.path))
+                )[0] + ".{:02d}.conllu".format(epoch + 1))
+                for metric, score in metrics.items():
+                    if metric in self._metrics:
+                        logs["{}_{}".format(os.path.splitext(os.path.basename(dataloader.dataset.ud_dataset.path))[0], metric)] = 100 * score.f1
+
+            aggregations = {"la_ud213": [("la_ittb-ud", 390_787), ("la_llct-ud", 194_143), ("la_proiel-ud", 177_558),
+                                         ("la_udante-ud", 30_450), ("la_perseus-ud", 16_486)]}
+            for split in ["dev", "test"]:
+                for metric in self._metrics:
+                    for aggregation, parts in aggregations.items():
+                        values = [logs.get("{}-{}_{}".format(part, split, metric), None) for part, _ in parts]
+                        if all(value is not None for value in values):
+                            logs["{}-{}_{}".format(aggregation, split, metric)] = np.mean(values)
+                            logs["{}-sqrt-{}_{}".format(aggregation, split, metric)] = np.average(values, weights=[size**0.5 for _, size in parts])
+
+            if self._wandb_log:
+                self._wandb_log(logs, step=epoch + 1, commit=True)
+
+    wandb_log = None
+    if args.wandb:
+        import wandb
+        wandb.init(project="ufal-evalatin2024", name=args.exp, config=vars(args))
+        wandb_log = wandb.log
+    evaluator = Evaluator(wandb_log)
+    if args.epochs_frozen:
+        model.compile(len(train_dataloader), frozen=True)
+        model.fit(train_dataloader, epochs=args.epochs_frozen, verbose=args.verbose, callbacks=[evaluator])
+    if args.epochs:
+        model.compile(len(train_dataloader), frozen=False)
+        model.fit(train_dataloader, initial_epoch=args.epochs_frozen, epochs=args.epochs_frozen + args.epochs, verbose=args.verbose, callbacks=[evaluator])
+    if args.save_checkpoint:
+        model.save_weights(os.path.join(args.logdir, "model.weights.h5"))
+
+
+if __name__ == "__main__":
+    main([] if "__file__" not in globals() else None)

src/evalatin2024-latinpipe/latinpipe_evalatin24_eval.py

@@ -0,0 +1,596 @@
+#!/usr/bin/env python
+
+# Compatible with Python 2.7 and 3.2+, can be used either as a module
+# or a standalone executable.
+#
+# Copyright 2017, 2018 Institute of Formal and Applied Linguistics (UFAL),
+# Faculty of Mathematics and Physics, Charles University, Czech Republic.
+#
+# This Source Code Form is subject to the terms of the Mozilla Public
+# License, v. 2.0. If a copy of the MPL was not distributed with this
+# file, You can obtain one at http://mozilla.org/MPL/2.0/.
+#
+# Authors: Milan Straka, Martin Popel <[email protected]>
+#
+# Changelog:
+# - [12 Apr 2018] Version 0.9: Initial release.
+# - [19 Apr 2018] Version 1.0: Fix bug in MLAS (duplicate entries in functional_children).
+#                              Add --counts option.
+# - [02 May 2018] Version 1.1: When removing spaces to match gold and system characters,
+#                              consider all Unicode characters of category Zs instead of
+#                              just ASCII space.
+# - [12 Sep 2020] Version 1.2: Renamed to udpipe2_eval when releasing with UDPipe 2
+#                              Allow evaluation with underscores in HEAD.
+# - [26 Jul 2022] Version 1.3: Allow evaluation with multiple roots, if requested.
+# - [13 Jan 2024] Version 1.4: Renamed to udpipe_evalatin24_eval when releasing with
+#                              UDPipe EvaLatin 24.
+
+# Command line usage
+# ------------------
+# udpipe_evalatin24_eval.py [-v] gold_conllu_file system_conllu_file
+#
+# - if no -v is given, only the official CoNLL18 UD Shared Task evaluation metrics
+#   are printed
+# - if -v is given, more metrics are printed (as precision, recall, F1 score,
+#   and in case the metric is computed on aligned words also accuracy on these):
+#   - Tokens: how well do the gold tokens match system tokens
+#   - Sentences: how well do the gold sentences match system sentences
+#   - Words: how well can the gold words be aligned to system words
+#   - UPOS: using aligned words, how well does UPOS match
+#   - XPOS: using aligned words, how well does XPOS match
+#   - UFeats: using aligned words, how well does universal FEATS match
+#   - AllTags: using aligned words, how well does UPOS+XPOS+FEATS match
+#   - Lemmas: using aligned words, how well does LEMMA match
+#   - UAS: using aligned words, how well does HEAD match
+#   - LAS: using aligned words, how well does HEAD+DEPREL(ignoring subtypes) match
+#   - CLAS: using aligned words with content DEPREL, how well does
+#       HEAD+DEPREL(ignoring subtypes) match
+#   - MLAS: using aligned words with content DEPREL, how well does
+#       HEAD+DEPREL(ignoring subtypes)+UPOS+UFEATS+FunctionalChildren(DEPREL+UPOS+UFEATS) match
+#   - BLEX: using aligned words with content DEPREL, how well does
+#       HEAD+DEPREL(ignoring subtypes)+LEMMAS match
+# - if -c is given, raw counts of correct/gold_total/system_total/aligned words are printed
+#   instead of precision/recall/F1/AlignedAccuracy for all metrics.
+
+# API usage
+# ---------
+# - load_conllu(file)
+#   - loads CoNLL-U file from given file object to an internal representation
+#   - the file object should return str in both Python 2 and Python 3
+#   - raises UDError exception if the given file cannot be loaded
+# - evaluate(gold_ud, system_ud)
+#   - evaluate the given gold and system CoNLL-U files (loaded with load_conllu)
+#   - raises UDError if the concatenated tokens of gold and system file do not match
+#   - returns a dictionary with the metrics described above, each metric having
+#     three fields: precision, recall and f1
+
+# Description of token matching
+# -----------------------------
+# In order to match tokens of gold file and system file, we consider the text
+# resulting from concatenation of gold tokens and text resulting from
+# concatenation of system tokens. These texts should match -- if they do not,
+# the evaluation fails.
+#
+# If the texts do match, every token is represented as a range in this original
+# text, and tokens are equal only if their range is the same.
+
+# Description of word matching
+# ----------------------------
+# When matching words of gold file and system file, we first match the tokens.
+# The words which are also tokens are matched as tokens, but words in multi-word
+# tokens have to be handled differently.
+#
+# To handle multi-word tokens, we start by finding "multi-word spans".
+# Multi-word span is a span in the original text such that
+# - it contains at least one multi-word token
+# - all multi-word tokens in the span (considering both gold and system ones)
+#   are completely inside the span (i.e., they do not "stick out")
+# - the multi-word span is as small as possible
+#
+# For every multi-word span, we align the gold and system words completely
+# inside this span using LCS on their FORMs. The words not intersecting
+# (even partially) any multi-word span are then aligned as tokens.
+
+
+from __future__ import division
+from __future__ import print_function
+
+import argparse
+import io
+import sys
+import unicodedata
+import unittest
+
+__version__ = "2.1.1-dev"
+
+
+# CoNLL-U column names
+ID, FORM, LEMMA, UPOS, XPOS, FEATS, HEAD, DEPREL, DEPS, MISC = range(10)
+
+# Content and functional relations
+CONTENT_DEPRELS = {
+    "nsubj", "obj", "iobj", "csubj", "ccomp", "xcomp", "obl", "vocative",
+    "expl", "dislocated", "advcl", "advmod", "discourse", "nmod", "appos",
+    "nummod", "acl", "amod", "conj", "fixed", "flat", "compound", "list",
+    "parataxis", "orphan", "goeswith", "reparandum", "root", "dep"
+}
+
+FUNCTIONAL_DEPRELS = {
+    "aux", "cop", "mark", "det", "clf", "case", "cc"
+}
+
+UNIVERSAL_FEATURES = {
+    "PronType", "NumType", "Poss", "Reflex", "Foreign", "Abbr", "Gender",
+    "Animacy", "Number", "Case", "Definite", "Degree", "VerbForm", "Mood",
+    "Tense", "Aspect", "Voice", "Evident", "Polarity", "Person", "Polite"
+}
+
+# UD Error is used when raising exceptions in this module
+class UDError(Exception):
+    pass
+
+# Load given CoNLL-U file into internal representation
+def load_conllu(file, single_root=1):
+    # Internal representation classes
+    class UDRepresentation:
+        def __init__(self):
+            # Characters of all the tokens in the whole file.
+            # Whitespace between tokens is not included.
+            self.characters = []
+            # List of UDSpan instances with start&end indices into `characters`.
+            self.tokens = []
+            # List of UDWord instances.
+            self.words = []
+            # List of UDSpan instances with start&end indices into `characters`.
+            self.sentences = []
+    class UDSpan:
+        def __init__(self, start, end):
+            self.start = start
+            # Note that self.end marks the first position **after the end** of span,
+            # so we can use characters[start:end] or range(start, end).
+            self.end = end
+    class UDWord:
+        def __init__(self, span, columns, is_multiword):
+            # Span of this word (or MWT, see below) within ud_representation.characters.
+            self.span = span
+            # 10 columns of the CoNLL-U file: ID, FORM, LEMMA,...
+            self.columns = columns
+            # is_multiword==True means that this word is part of a multi-word token.
+            # In that case, self.span marks the span of the whole multi-word token.
+            self.is_multiword = is_multiword
+            # Reference to the UDWord instance representing the HEAD (or None if root).
+            self.parent = None
+            # List of references to UDWord instances representing functional-deprel children.
+            self.functional_children = []
+            # Only consider universal FEATS.
+            self.columns[FEATS] = "|".join(sorted(feat for feat in columns[FEATS].split("|")
+                                                  if feat.split("=", 1)[0] in UNIVERSAL_FEATURES))
+            # Let's ignore language-specific deprel subtypes.
+            self.columns[DEPREL] = columns[DEPREL].split(":")[0]
+            # Precompute which deprels are CONTENT_DEPRELS and which FUNCTIONAL_DEPRELS
+            self.is_content_deprel = self.columns[DEPREL] in CONTENT_DEPRELS
+            self.is_functional_deprel = self.columns[DEPREL] in FUNCTIONAL_DEPRELS
+
+    ud = UDRepresentation()
+
+    # Load the CoNLL-U file
+    index, sentence_start = 0, None
+    while True:
+        line = file.readline()
+        if not line:
+            break
+        line = line.rstrip("\r\n")
+
+        # Handle sentence start boundaries
+        if sentence_start is None:
+            # Skip comments
+            if line.startswith("#"):
+                continue
+            # Start a new sentence
+            ud.sentences.append(UDSpan(index, 0))
+            sentence_start = len(ud.words)
+        if not line:
+            # Add parent and children UDWord links and check there are no cycles
+            def process_word(word):
+                if word.parent == "remapping":
+                    raise UDError("There is a cycle in a sentence")
+                if word.parent is None:
+                    if word.columns[HEAD] == "_":
+                        word.parent = "missing"
+                    else:
+                        head = int(word.columns[HEAD])
+                        if head < 0 or head > len(ud.words) - sentence_start:
+                            raise UDError("HEAD '{}' points outside of the sentence".format(word.columns[HEAD]))
+                        if head:
+                            parent = ud.words[sentence_start + head - 1]
+                            word.parent = "remapping"
+                            process_word(parent)
+                            word.parent = parent
+
+            for word in ud.words[sentence_start:]:
+                process_word(word)
+            # func_children cannot be assigned within process_word
+            # because it is called recursively and may result in adding one child twice.
+            for word in ud.words[sentence_start:]:
+                if word.parent and word.is_functional_deprel:
+                    word.parent.functional_children.append(word)
+
+            # Check there is a single root node
+            if single_root:
+                if len([word for word in ud.words[sentence_start:] if word.parent is None]) > 1:
+                    raise UDError("There are multiple roots in a sentence")
+
+            # End the sentence
+            ud.sentences[-1].end = index
+            sentence_start = None
+            continue
+
+        # Read next token/word
+        columns = line.split("\t")
+        if len(columns) != 10:
+            raise UDError("The CoNLL-U line does not contain 10 tab-separated columns: '{}'".format(line))
+
+        # Skip empty nodes
+        if "." in columns[ID]:
+            continue
+
+        # Delete spaces from FORM, so gold.characters == system.characters
+        # even if one of them tokenizes the space. Use any Unicode character
+        # with category Zs.
+        if sys.version_info < (3, 0) and isinstance(line, str):
+            columns[FORM] = columns[FORM].decode("utf-8")
+        columns[FORM] = "".join(filter(lambda c: unicodedata.category(c) != "Zs", columns[FORM]))
+        if sys.version_info < (3, 0) and isinstance(line, str):
+            columns[FORM] = columns[FORM].encode("utf-8")
+        if not columns[FORM]:
+            raise UDError("There is an empty FORM in the CoNLL-U file")
+
+        # Save token
+        ud.characters.extend(columns[FORM])
+        ud.tokens.append(UDSpan(index, index + len(columns[FORM])))
+        index += len(columns[FORM])
+
+        # Handle multi-word tokens to save word(s)
+        if "-" in columns[ID]:
+            try:
+                start, end = map(int, columns[ID].split("-"))
+            except:
+                raise UDError("Cannot parse multi-word token ID '{}'".format(columns[ID]))
+
+            for _ in range(start, end + 1):
+                word_line = file.readline().rstrip("\r\n")
+                word_columns = word_line.split("\t")
+                if len(word_columns) != 10:
+                    raise UDError("The CoNLL-U line does not contain 10 tab-separated columns: '{}'".format(word_line))
+                ud.words.append(UDWord(ud.tokens[-1], word_columns, is_multiword=True))
+        # Basic tokens/words
+        else:
+            try:
+                word_id = int(columns[ID])
+            except:
+                raise UDError("Cannot parse word ID '{}'".format(columns[ID]))
+            if word_id != len(ud.words) - sentence_start + 1:
+                raise UDError("Incorrect word ID '{}' for word '{}', expected '{}'".format(columns[ID], columns[FORM], len(ud.words) - sentence_start + 1))
+
+            if columns[HEAD] != "_":
+                try:
+                    head_id = int(columns[HEAD])
+                except:
+                    raise UDError("Cannot parse HEAD '{}'".format(columns[HEAD]))
+                if head_id < 0:
+                    raise UDError("HEAD cannot be negative")
+
+            ud.words.append(UDWord(ud.tokens[-1], columns, is_multiword=False))
+
+    if sentence_start is not None:
+        raise UDError("The CoNLL-U file does not end with empty line")
+
+    return ud
+
+# Evaluate the gold and system treebanks (loaded using load_conllu).
+def evaluate(gold_ud, system_ud):
+    class Score:
+        def __init__(self, gold_total, system_total, correct, aligned_total=None):
+            self.correct = correct
+            self.gold_total = gold_total
+            self.system_total = system_total
+            self.aligned_total = aligned_total
+            self.precision = correct / system_total if system_total else 0.0
+            self.recall = correct / gold_total if gold_total else 0.0
+            self.f1 = 2 * correct / (system_total + gold_total) if system_total + gold_total else 0.0
+            self.aligned_accuracy = correct / aligned_total if aligned_total else aligned_total
+    class AlignmentWord:
+        def __init__(self, gold_word, system_word):
+            self.gold_word = gold_word
+            self.system_word = system_word
+    class Alignment:
+        def __init__(self, gold_words, system_words):
+            self.gold_words = gold_words
+            self.system_words = system_words
+            self.matched_words = []
+            self.matched_words_map = {}
+        def append_aligned_words(self, gold_word, system_word):
+            self.matched_words.append(AlignmentWord(gold_word, system_word))
+            self.matched_words_map[system_word] = gold_word
+
+    def lower(text):
+        if sys.version_info < (3, 0) and isinstance(text, str):
+            return text.decode("utf-8").lower()
+        return text.lower()
+
+    def spans_score(gold_spans, system_spans):
+        correct, gi, si = 0, 0, 0
+        while gi < len(gold_spans) and si < len(system_spans):
+            if system_spans[si].start < gold_spans[gi].start:
+                si += 1
+            elif gold_spans[gi].start < system_spans[si].start:
+                gi += 1
+            else:
+                correct += gold_spans[gi].end == system_spans[si].end
+                si += 1
+                gi += 1
+
+        return Score(len(gold_spans), len(system_spans), correct)
+
+    def alignment_score(alignment, key_fn=None, filter_fn=None):
+        if filter_fn is not None:
+            gold = sum(1 for gold in alignment.gold_words if filter_fn(gold))
+            system = sum(1 for system in alignment.system_words if filter_fn(system))
+            aligned = sum(1 for word in alignment.matched_words if filter_fn(word.gold_word))
+        else:
+            gold = len(alignment.gold_words)
+            system = len(alignment.system_words)
+            aligned = len(alignment.matched_words)
+
+        if key_fn is None:
+            # Return score for whole aligned words
+            return Score(gold, system, aligned)
+
+        def gold_aligned_gold(word):
+            return word
+        def gold_aligned_system(word):
+            return alignment.matched_words_map.get(word, "NotAligned") if word is not None else None
+        correct = 0
+        for words in alignment.matched_words:
+            if filter_fn is None or filter_fn(words.gold_word):
+                if key_fn(words.gold_word, gold_aligned_gold) == key_fn(words.system_word, gold_aligned_system):
+                    correct += 1
+
+        return Score(gold, system, correct, aligned)
+
+    def beyond_end(words, i, multiword_span_end):
+        if i >= len(words):
+            return True
+        if words[i].is_multiword:
+            return words[i].span.start >= multiword_span_end
+        return words[i].span.end > multiword_span_end
+
+    def extend_end(word, multiword_span_end):
+        if word.is_multiword and word.span.end > multiword_span_end:
+            return word.span.end
+        return multiword_span_end
+
+    def find_multiword_span(gold_words, system_words, gi, si):
+        # We know gold_words[gi].is_multiword or system_words[si].is_multiword.
+        # Find the start of the multiword span (gs, ss), so the multiword span is minimal.
+        # Initialize multiword_span_end characters index.
+        if gold_words[gi].is_multiword:
+            multiword_span_end = gold_words[gi].span.end
+            if not system_words[si].is_multiword and system_words[si].span.start < gold_words[gi].span.start:
+                si += 1
+        else: # if system_words[si].is_multiword
+            multiword_span_end = system_words[si].span.end
+            if not gold_words[gi].is_multiword and gold_words[gi].span.start < system_words[si].span.start:
+                gi += 1
+        gs, ss = gi, si
+
+        # Find the end of the multiword span
+        # (so both gi and si are pointing to the word following the multiword span end).
+        while not beyond_end(gold_words, gi, multiword_span_end) or \
+              not beyond_end(system_words, si, multiword_span_end):
+            if gi < len(gold_words) and (si >= len(system_words) or
+                                         gold_words[gi].span.start <= system_words[si].span.start):
+                multiword_span_end = extend_end(gold_words[gi], multiword_span_end)
+                gi += 1
+            else:
+                multiword_span_end = extend_end(system_words[si], multiword_span_end)
+                si += 1
+        return gs, ss, gi, si
+
+    def compute_lcs(gold_words, system_words, gi, si, gs, ss):
+        lcs = [[0] * (si - ss) for i in range(gi - gs)]
+        for g in reversed(range(gi - gs)):
+            for s in reversed(range(si - ss)):
+                if lower(gold_words[gs + g].columns[FORM]) == lower(system_words[ss + s].columns[FORM]):
+                    lcs[g][s] = 1 + (lcs[g+1][s+1] if g+1 < gi-gs and s+1 < si-ss else 0)
+                lcs[g][s] = max(lcs[g][s], lcs[g+1][s] if g+1 < gi-gs else 0)
+                lcs[g][s] = max(lcs[g][s], lcs[g][s+1] if s+1 < si-ss else 0)
+        return lcs
+
+    def align_words(gold_words, system_words):
+        alignment = Alignment(gold_words, system_words)
+
+        gi, si = 0, 0
+        while gi < len(gold_words) and si < len(system_words):
+            if gold_words[gi].is_multiword or system_words[si].is_multiword:
+                # A: Multi-word tokens => align via LCS within the whole "multiword span".
+                gs, ss, gi, si = find_multiword_span(gold_words, system_words, gi, si)
+
+                if si > ss and gi > gs:
+                    lcs = compute_lcs(gold_words, system_words, gi, si, gs, ss)
+
+                    # Store aligned words
+                    s, g = 0, 0
+                    while g < gi - gs and s < si - ss:
+                        if lower(gold_words[gs + g].columns[FORM]) == lower(system_words[ss + s].columns[FORM]):
+                            alignment.append_aligned_words(gold_words[gs+g], system_words[ss+s])
+                            g += 1
+                            s += 1
+                        elif lcs[g][s] == (lcs[g+1][s] if g+1 < gi-gs else 0):
+                            g += 1
+                        else:
+                            s += 1
+            else:
+                # B: No multi-word token => align according to spans.
+                if (gold_words[gi].span.start, gold_words[gi].span.end) == (system_words[si].span.start, system_words[si].span.end):
+                    alignment.append_aligned_words(gold_words[gi], system_words[si])
+                    gi += 1
+                    si += 1
+                elif gold_words[gi].span.start <= system_words[si].span.start:
+                    gi += 1
+                else:
+                    si += 1
+
+        return alignment
+
+    # Check that the underlying character sequences do match.
+    if gold_ud.characters != system_ud.characters:
+        index = 0
+        while index < len(gold_ud.characters) and index < len(system_ud.characters) and \
+                gold_ud.characters[index] == system_ud.characters[index]:
+            index += 1
+
+        raise UDError(
+            "The concatenation of tokens in gold file and in system file differ!\n" +
+            "First 20 differing characters in gold file: '{}' and system file: '{}'".format(
+                "".join(gold_ud.characters[index:index + 20]),
+                "".join(system_ud.characters[index:index + 20])
+            )
+        )
+
+    # Align words
+    alignment = align_words(gold_ud.words, system_ud.words)
+
+    # Compute the F1-scores
+    return {
+        "Tokens": spans_score(gold_ud.tokens, system_ud.tokens),
+        "Sentences": spans_score(gold_ud.sentences, system_ud.sentences),
+        "Words": alignment_score(alignment),
+        "UPOS": alignment_score(alignment, lambda w, _: w.columns[UPOS]),
+        "XPOS": alignment_score(alignment, lambda w, _: w.columns[XPOS]),
+        "UFeats": alignment_score(alignment, lambda w, _: w.columns[FEATS]),
+        "AllTags": alignment_score(alignment, lambda w, _: (w.columns[UPOS], w.columns[XPOS], w.columns[FEATS])),
+        "Lemmas": alignment_score(alignment, lambda w, ga: w.columns[LEMMA] if ga(w).columns[LEMMA] != "_" else "_"),
+        "UAS": alignment_score(alignment, lambda w, ga: ga(w.parent)),
+        "LAS": alignment_score(alignment, lambda w, ga: (ga(w.parent), w.columns[DEPREL])),
+        "CLAS": alignment_score(alignment, lambda w, ga: (ga(w.parent), w.columns[DEPREL]),
+                                filter_fn=lambda w: w.is_content_deprel),
+        "MLAS": alignment_score(alignment, lambda w, ga: (ga(w.parent), w.columns[DEPREL], w.columns[UPOS], w.columns[FEATS],
+                                                         [(ga(c), c.columns[DEPREL], c.columns[UPOS], c.columns[FEATS])
+                                                          for c in w.functional_children]),
+                                filter_fn=lambda w: w.is_content_deprel),
+        "BLEX": alignment_score(alignment, lambda w, ga: (ga(w.parent), w.columns[DEPREL],
+                                                          w.columns[LEMMA] if ga(w).columns[LEMMA] != "_" else "_"),
+                                filter_fn=lambda w: w.is_content_deprel),
+    }
+
+
+def load_conllu_file(path, single_root=1):
+    _file = open(path, mode="r", **({"encoding": "utf-8"} if sys.version_info >= (3, 0) else {}))
+    return load_conllu(_file, single_root)
+
+def evaluate_wrapper(args):
+    # Load CoNLL-U files
+    gold_ud = load_conllu_file(args.gold_file, args.single_root)
+    system_ud = load_conllu_file(args.system_file, args.single_root)
+    return evaluate(gold_ud, system_ud)
+
+def main():
+    # Parse arguments
+    parser = argparse.ArgumentParser()
+    parser.add_argument("gold_file", type=str,
+                        help="Name of the CoNLL-U file with the gold data.")
+    parser.add_argument("system_file", type=str,
+                        help="Name of the CoNLL-U file with the predicted data.")
+    parser.add_argument("--verbose", "-v", default=False, action="store_true",
+                        help="Print all metrics.")
+    parser.add_argument("--counts", "-c", default=False, action="store_true",
+                        help="Print raw counts of correct/gold/system/aligned words instead of prec/rec/F1 for all metrics.")
+    parser.add_argument("--no_single_root", dest="single_root", default=True, action="store_false",
+                        help="Allow multiple roots in a sentence.")
+    args = parser.parse_args()
+
+    # Evaluate
+    evaluation = evaluate_wrapper(args)
+
+    # Print the evaluation
+    if not args.verbose and not args.counts:
+        print("LAS F1 Score: {:.2f}".format(100 * evaluation["LAS"].f1))
+        print("MLAS Score: {:.2f}".format(100 * evaluation["MLAS"].f1))
+        print("BLEX Score: {:.2f}".format(100 * evaluation["BLEX"].f1))
+    else:
+        if args.counts:
+            print("Metric     | Correct   |      Gold | Predicted | Aligned")
+        else:
+            print("Metric     | Precision |    Recall |  F1 Score | AligndAcc")
+        print("-----------+-----------+-----------+-----------+-----------")
+        for metric in["Tokens", "Sentences", "Words", "UPOS", "XPOS", "UFeats", "AllTags", "Lemmas", "UAS", "LAS", "CLAS", "MLAS", "BLEX"]:
+            if args.counts:
+                print("{:11}|{:10} |{:10} |{:10} |{:10}".format(
+                    metric,
+                    evaluation[metric].correct,
+                    evaluation[metric].gold_total,
+                    evaluation[metric].system_total,
+                    evaluation[metric].aligned_total or (evaluation[metric].correct if metric == "Words" else "")
+                ))
+            else:
+                print("{:11}|{:10.2f} |{:10.2f} |{:10.2f} |{}".format(
+                    metric,
+                    100 * evaluation[metric].precision,
+                    100 * evaluation[metric].recall,
+                    100 * evaluation[metric].f1,
+                    "{:10.2f}".format(100 * evaluation[metric].aligned_accuracy) if evaluation[metric].aligned_accuracy is not None else ""
+                ))
+
+if __name__ == "__main__":
+    main()
+
+# Tests, which can be executed with `python -m unittest udpipe_evalatin24_eval`.
+class TestAlignment(unittest.TestCase):
+    @staticmethod
+    def _load_words(words):
+        """Prepare fake CoNLL-U files with fake HEAD to prevent multiple roots errors."""
+        lines, num_words = [], 0
+        for w in words:
+            parts = w.split(" ")
+            if len(parts) == 1:
+                num_words += 1
+                lines.append("{}\t{}\t_\t_\t_\t_\t{}\t_\t_\t_".format(num_words, parts[0], int(num_words>1)))
+            else:
+                lines.append("{}-{}\t{}\t_\t_\t_\t_\t_\t_\t_\t_".format(num_words + 1, num_words + len(parts) - 1, parts[0]))
+                for part in parts[1:]:
+                    num_words += 1
+                    lines.append("{}\t{}\t_\t_\t_\t_\t{}\t_\t_\t_".format(num_words, part, int(num_words>1)))
+        return load_conllu((io.StringIO if sys.version_info >= (3, 0) else io.BytesIO)("\n".join(lines+["\n"])))
+
+    def _test_exception(self, gold, system):
+        self.assertRaises(UDError, evaluate, self._load_words(gold), self._load_words(system))
+
+    def _test_ok(self, gold, system, correct):
+        metrics = evaluate(self._load_words(gold), self._load_words(system))
+        gold_words = sum((max(1, len(word.split(" ")) - 1) for word in gold))
+        system_words = sum((max(1, len(word.split(" ")) - 1) for word in system))
+        self.assertEqual((metrics["Words"].precision, metrics["Words"].recall, metrics["Words"].f1),
+                         (correct / system_words, correct / gold_words, 2 * correct / (gold_words + system_words)))
+
+    def test_exception(self):
+        self._test_exception(["a"], ["b"])
+
+    def test_equal(self):
+        self._test_ok(["a"], ["a"], 1)
+        self._test_ok(["a", "b", "c"], ["a", "b", "c"], 3)
+
+    def test_equal_with_multiword(self):
+        self._test_ok(["abc a b c"], ["a", "b", "c"], 3)
+        self._test_ok(["a", "bc b c", "d"], ["a", "b", "c", "d"], 4)
+        self._test_ok(["abcd a b c d"], ["ab a b", "cd c d"], 4)
+        self._test_ok(["abc a b c", "de d e"], ["a", "bcd b c d", "e"], 5)
+
+    def test_alignment(self):
+        self._test_ok(["abcd"], ["a", "b", "c", "d"], 0)
+        self._test_ok(["abc", "d"], ["a", "b", "c", "d"], 1)
+        self._test_ok(["a", "bc", "d"], ["a", "b", "c", "d"], 2)
+        self._test_ok(["a", "bc b c", "d"], ["a", "b", "cd"], 2)
+        self._test_ok(["abc a BX c", "def d EX f"], ["ab a b", "cd c d", "ef e f"], 4)
+        self._test_ok(["ab a b", "cd bc d"], ["a", "bc", "d"], 2)
+        self._test_ok(["a", "bc b c", "d"], ["ab AX BX", "cd CX a"], 1)

src/evalatin2024-latinpipe/latinpipe_evalatin24_server.py

@@ -0,0 +1,433 @@
+#!/usr/bin/env python3
+
+# This file is part of LatinPipe EvaLatin24
+# <https://github.com/ufal/evalatin2024-latinpipe>.
+#
+# Copyright 2024 Institute of Formal and Applied Linguistics, Faculty of
+# Mathematics and Physics, Charles University in Prague, Czech Republic.
+#
+# This Source Code Form is subject to the terms of the Mozilla Public
+# License, v. 2.0. If a copy of the MPL was not distributed with this
+# file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+import argparse
+import contextlib
+import email.parser
+import http.server
+import itertools
+import json
+import os
+import socketserver
+import sys
+import threading
+import time
+import unicodedata
+import urllib.parse
+
+import latinpipe_evalatin24
+from latinpipe_evalatin24 import UDDataset  # Make sure we can unpickle UDDataset mapping in this module.
+import ufal.udpipe
+
+__version__ = "1.0.0-dev"
+
+
+class TooLongError(Exception):
+    pass
+
+class Models:
+    class Model:
+        class Network:
+            _mutex = threading.Lock()
+
+            def __init__(self, path, server_args):
+                self._path = path
+                self._server_args = server_args
+                self.network, self.args, self.train = None, None, None
+
+            def load(self):
+                if self.network is not None:
+                    return
+                with self._mutex:
+                    if self.network is not None:
+                        return
+
+                    with open(os.path.join(self._path, "options.json"), mode="r") as options_file:
+                        self.args = argparse.Namespace(**json.load(options_file))
+                    self.args.batch_size = self._server_args.batch_size
+                    self.args.load = [os.path.join(self._path, "model.weights.h5")]
+                    self.train = latinpipe_evalatin24.UDDataset.from_mappings(os.path.join(self._path, "mappings.pkl"))
+                    self.network = latinpipe_evalatin24.LatinPipeModel(self.train, self.args)
+
+                    print("Loaded model {}".format(os.path.basename(self._path)), file=sys.stderr, flush=True)
+
+
+        def __init__(self, names, path, network, variant, acknowledgements, server_args):
+            self.names = names
+            self.acknowledgements = acknowledgements
+            self._network = network
+            self._variant = variant
+            self._server_args = server_args
+
+            # Load the tokenizer
+            tokenizer_path = os.path.join(path, "{}.tokenizer".format(variant))
+            self._tokenizer = ufal.udpipe.Model.load(tokenizer_path)
+            if self._tokenizer is None:
+                raise RuntimeError("Cannot load tokenizer from {}".format(tokenizer_path))
+
+            self._conllu_input = ufal.udpipe.InputFormat.newConlluInputFormat()
+            if self._conllu_input is None:
+                raise RuntimeError("Cannot create CoNLL-U input format")
+
+            self._conllu_output = ufal.udpipe.OutputFormat.newConlluOutputFormat()
+            if self._conllu_output is None:
+                raise RuntimeError("Cannot create CoNLL-U output format")
+
+            # Load the network if requested
+            if names[0] in server_args.preload_models or "all" in server_args.preload_models:
+                self._network.load()
+
+        def read(self, text, input_format):
+            reader = ufal.udpipe.InputFormat.newInputFormat(input_format)
+            if reader is None:
+                raise RuntimeError("Unknown input format '{}'".format(input_format))
+            # Do not return a generator, but a list to raise exceptions early
+            return list(self._read(text, reader))
+
+        def tokenize(self, text, tokenizer_options):
+            tokenizer = self._tokenizer.newTokenizer(tokenizer_options)
+            if tokenizer is None:
+                raise RuntimeError("Cannot create tokenizer.")
+            # Do not return a generator, but a list to raise exceptions early
+            return list(self._read(text, tokenizer))
+
+        def _read(self, text, reader):
+            sentence = ufal.udpipe.Sentence()
+            processing_error = ufal.udpipe.ProcessingError()
+            reader.setText(text)
+            while reader.nextSentence(sentence, processing_error):
+                if len(sentence.words) > 1001:
+                    raise TooLongError()
+                yield sentence
+                sentence = ufal.udpipe.Sentence()
+            if processing_error.occurred():
+                raise RuntimeError("Cannot read input data: '{}'".format(processing_error.message))
+
+        def create_writer(self, output_format):
+            writer = ufal.udpipe.OutputFormat.newOutputFormat(output_format)
+            if writer is None:
+                raise RuntimeError("Unknown output format '{}'".format(output_format))
+            return writer
+
+        def predict(self, sentences, tag, parse, writer):
+            # Run the model
+            if tag or parse:
+                # Load the network if it has not been loaded already
+                self._network.load()
+
+                conllu_input = []
+                for sentence in sentences:
+                    conllu_input.append(self._conllu_output.writeSentence(sentence))
+
+                time_ds = time.time()
+                # Create LatinPipe2Dataset
+                dataset = latinpipe_evalatin24.UDDataset(
+                    "<web_input>", self._network.args, text="".join(conllu_input), train_dataset=self._network.train)
+                dataloader = latinpipe_evalatin24.TorchUDDataLoader(latinpipe_evalatin24.TorchUDDataset(
+                    dataset, self._network.network.tokenizers, self._network.args, training=False), self._network.args)
+
+                # Prepare network arguments
+                current_args = argparse.Namespace(**vars(self._network.args))
+                if not tag: current_args.tags = []
+                if not parse: current_args.parse = 0
+
+                # Perform the prediction
+                time_nws = time.time()
+                with self._server_args.optional_semaphore:
+                    time_nw = time.time()
+                    predicted = self._network.network.predict(dataloader, args_override=current_args)
+                    time_rd = time.time()
+
+                # Load the predicted CoNLL-U to ufal.udpipe sentences
+                sentences = self._read(predicted, self._conllu_input)
+
+                print("Request, DS {:.2f}ms,".format(1000 * (time_nws - time_ds)),
+                      "NW {:.2f}+{:.2f}ms,".format(1000 * (time_rd - time_nw), 1000 * (time_nw - time_nws)),
+                      "RD {:.2f}ms.".format(1000 * (time.time() - time_rd)),
+                      file=sys.stderr, flush=True)
+
+            # Generate output
+            output = []
+            for sentence in sentences:
+                output.append(writer.writeSentence(sentence))
+            output.append(writer.finishDocument())
+            return "".join(output)
+
+    def __init__(self, server_args):
+        self.default_model = server_args.default_model
+        self.models_list = []
+        self.models_by_names = {}
+        networks_by_path = {}
+
+        for i in range(0, len(server_args.models), 4):
+            names, path, variant, acknowledgements = server_args.models[i:i+4]
+            names = names.split(":")
+            names = [name.split("-") for name in names]
+            names = ["-".join(parts[:None if not i else -i]) for parts in names for i in range(len(parts))]
+
+            if not path in networks_by_path:
+                networks_by_path[path] = self.Model.Network(path, server_args)
+            self.models_list.append(self.Model(names, path, networks_by_path[path], variant, acknowledgements, server_args))
+            for name in names:
+                self.models_by_names.setdefault(name, self.models_list[-1])
+
+        # Check the default model exists
+        assert self.default_model in self.models_by_names
+
+
+class LatinPipeServer(socketserver.ThreadingTCPServer):
+    class LatinPipeServerRequestHandler(http.server.BaseHTTPRequestHandler):
+        protocol_version = "HTTP/1.1"
+
+        def respond(request, content_type, code=200, additional_headers={}):
+            request.close_connection = True
+            request.send_response(code)
+            request.send_header("Connection", "close")
+            request.send_header("Content-Type", content_type)
+            request.send_header("Access-Control-Allow-Origin", "*")
+            for key, value in additional_headers.items():
+                request.send_header(key, value)
+            request.end_headers()
+
+        def respond_error(request, message, code=400):
+            request.respond("text/plain", code)
+            request.wfile.write(message.encode("utf-8"))
+
+        def do_GET(request):
+            # Parse the URL
+            params = {}
+            try:
+                request.path = request.path.encode("iso-8859-1").decode("utf-8")
+                url = urllib.parse.urlparse(request.path)
+                for name, value in urllib.parse.parse_qsl(url.query, encoding="utf-8", keep_blank_values=True, errors="strict"):
+                    params[name] = value
+            except:
+                return request.respond_error("Cannot parse request URL.")
+
+            # Parse the body of a POST request
+            if request.command == "POST":
+                if request.headers.get("Transfer-Encoding", "identity").lower() != "identity":
+                    return request.respond_error("Only 'identity' Transfer-Encoding of payload is supported for now.")
+
+                try:
+                    content_length = int(request.headers["Content-Length"])
+                except:
+                    return request.respond_error("The Content-Length of payload is required.")
+
+                if content_length > request.server._server_args.max_request_size:
+                    return request.respond_error("The payload size is too large.")
+
+                # Raw text on input for weblicht
+                if url.path.startswith("/weblicht/"):
+                    # Ignore all but `model` GET param
+                    params = {"model": params["model"]} if "model" in params else {}
+
+                    try:
+                        params["data"] = request.rfile.read(content_length).decode("utf-8")
+                    except:
+                        return request.respond_error("The payload is not in UTF-8 encoding.")
+
+                    if url.path == "/weblicht/tokenize": params["tokenizer"] = ""
+                    else: params["input"] = "conllu"
+                    params["output"] = "conllu"
+                    if url.path == "/weblicht/tag": params["tagger"] = ""
+                    if url.path == "/weblicht/parse": params["parser"] = ""
+                # multipart/form-data
+                elif request.headers.get("Content-Type", "").startswith("multipart/form-data"):
+                    try:
+                        parser = email.parser.BytesFeedParser()
+                        parser.feed(b"Content-Type: " + request.headers["Content-Type"].encode("ascii") + b"\r\n\r\n")
+                        while content_length:
+                            parser.feed(request.rfile.read(min(content_length, 4096)))
+                            content_length -= min(content_length, 4096)
+                        for part in parser.close().get_payload():
+                            name = part.get_param("name", header="Content-Disposition")
+                            if name:
+                                params[name] = part.get_payload(decode=True).decode("utf-8")
+                    except:
+                        return request.respond_error("Cannot parse the multipart/form-data payload.")
+                # application/x-www-form-urlencoded
+                elif request.headers.get("Content-Type", "").startswith("application/x-www-form-urlencoded"):
+                    try:
+                        for name, value in urllib.parse.parse_qsl(
+                                request.rfile.read(content_length).decode("utf-8"), encoding="utf-8", keep_blank_values=True, errors="strict"):
+                            params[name] = value
+                    except:
+                        return request.respond_error("Cannot parse the application/x-www-form-urlencoded payload.")
+                else:
+                    return request.respond_error("Unsupported payload Content-Type '{}'.".format(request.headers.get("Content-Type", "<none>")))
+
+            # Handle /models
+            if url.path == "/models":
+                response = {
+                    "models": {model.names[0]: ["tokenizer", "tagger", "parser"] for model in request.server._models.models_list},
+                    "default_model": request.server._models.default_model,
+                }
+                request.respond("application/json")
+                request.wfile.write(json.dumps(response, indent=1).encode("utf-8"))
+            # Handle /process
+            elif url.path in ["/process", "/weblicht/tokenize", "/weblicht/tag", "/weblicht/parse"]:
+                weblicht = url.path.startswith("/weblicht")
+
+                if "data" not in params:
+                    return request.respond_error("The parameter 'data' is required.")
+                params["data"] = unicodedata.normalize("NFC", params["data"])
+
+                model = params.get("model", request.server._models.default_model)
+                if model not in request.server._models.models_by_names:
+                    return request.respond_error("The requested model '{}' does not exist.".format(model))
+                model = request.server._models.models_by_names[model]
+
+                # Start by reading and optionally tokenizing the input data.
+                if "tokenizer" in params:
+                    try:
+                        sentences = model.tokenize(params["data"], params["tokenizer"])
+                    except TooLongError:
+                        return request.respond_error("During tokenization, sentence longer than 1000 words was found, aborting.\nThat should only happen with presegmented input.\nPlease make sure you do not generate such long sentences.\n")
+                    except:
+                        return request.respond_error("An error occured during tokenization of the input.")
+                else:
+                    try:
+                        sentences = model.read(params["data"], params.get("input", "conllu"))
+                    except TooLongError:
+                        return request.respond_error("Sentence longer than 1000 words was found on input, aborting.\nPlease make sure the input sentences have at most 1000 words.\n")
+                    except:
+                        return request.respond_error("Cannot parse the input in '{}' format.".format(params.get("input", "conllu")))
+                infclen = sum(sum(len(word.form) for word in sentence.words[1:]) for sentence in sentences)
+
+                # Create the writer
+                output_format = params.get("output", "conllu")
+                try:
+                    writer = model.create_writer(output_format)
+                except:
+                    return request.respond_error("Unknown output format '{}'.".format(output_format))
+
+                # Process the data
+                tag, parse, output_format = "tagger" in params, "parser" in params, params.get("output", "conllu")
+                batch, started_responding = [], False
+                try:
+                    for sentence in itertools.chain(sentences, ["EOF"]):
+                        if sentence == "EOF" or len(batch) == request.server._server_args.batch_size:
+                            output = model.predict(batch, tag, parse, writer)
+                            if not started_responding:
+                                # The first batch is ready, we commit to generate output.
+                                started_responding=True
+                                if weblicht:
+                                    request.respond("application/conllu")
+                                else:
+                                    request.respond("application/json", additional_headers={"X-Billing-Input-NFC-Len": str(infclen)})
+                                    request.wfile.write(json.dumps({
+                                        "model": model.names[0],
+                                        "acknowledgements": ["https://github.com/ufal/evalatin2024-latinpipe", model.acknowledgements],
+                                        "result": "",
+                                    }, indent=1)[:-3].encode("utf-8"))
+                                    if output_format == "conllu":
+                                        request.wfile.write(json.dumps(
+                                            "# generator = LatinPipe EvaLatin24, https://lindat.mff.cuni.cz/services/udpipe\n"
+                                            "# latinpipe_model = {}\n"
+                                            "# latinpipe_model_licence = CC BY-NC-SA\n".format(model.names[0]))[1:-1].encode("utf-8"))
+                            if weblicht:
+                                request.wfile.write(output.encode("utf-8"))
+                            else:
+                                request.wfile.write(json.dumps(output, ensure_ascii=False)[1:-1].encode("utf-8"))
+                            batch = []
+                        batch.append(sentence)
+                    if not weblicht:
+                        request.wfile.write(b'"\n}\n')
+                except:
+                    import traceback
+                    traceback.print_exc(file=sys.stderr)
+                    sys.stderr.flush()
+
+                    if not started_responding:
+                        request.respond_error("An internal error occurred during processing.")
+                    else:
+                        if weblicht:
+                            request.wfile.write(b'\n\nAn internal error occurred during processing, producing incorrect CoNLL-U!')
+                        else:
+                            request.wfile.write(b'",\n"An internal error occurred during processing, producing incorrect JSON!"')
+            # Unknown URL
+            else:
+                request.respond_error("No handler for the given URL '{}'".format(url.path), code=404)
+
+        def do_POST(request):
+            return request.do_GET()
+
+    daemon_threads = False
+
+    def __init__(self, server_args, models):
+        super().__init__(("", server_args.port), self.LatinPipeServerRequestHandler)
+
+        self._server_args = server_args
+        self._models = models
+
+    def server_bind(self):
+        import socket
+        self.socket.setsockopt(socket.SOL_SOCKET, socket.SO_REUSEADDR, 1)
+        self.socket.setsockopt(socket.SOL_SOCKET, socket.SO_REUSEPORT, 1)
+        super().server_bind()
+
+    def service_actions(self):
+        if isinstance(getattr(self, "_threads", None), list):
+            if len(self._threads) >= 1024:
+                self._threads = [thread for thread in self._threads if thread.is_alive()]
+
+
+if __name__ == "__main__":
+    import signal
+    import threading
+
+    # Parse server arguments
+    parser = argparse.ArgumentParser()
+    parser.add_argument("port", type=int, help="Port to use")
+    parser.add_argument("default_model", type=str, help="Default model")
+    parser.add_argument("models", type=str, nargs="+", help="Models to serve")
+    parser.add_argument("--batch_size", default=32, type=int, help="Batch size")
+    parser.add_argument("--concurrent", default=None, type=int, help="Concurrent computations of NN")
+    parser.add_argument("--logfile", default=None, type=str, help="Log path")
+    parser.add_argument("--max_request_size", default=4096*1024, type=int, help="Maximum request size")
+    parser.add_argument("--preload_models", default=[], nargs="*", type=str, help="Models to preload, or `all`")
+    parser.add_argument("--threads", default=0, type=int, help="Threads to use")
+    args = parser.parse_args()
+
+    # Log stderr to logfile if given
+    if args.logfile is not None:
+        sys.stderr = open(args.logfile, "a", encoding="utf-8")
+
+    if args.threads:
+        # Limit the number of threads if requested
+        import torch
+        torch.set_num_threads(args.threads)
+        torch.set_num_interop_threads(args.threads)
+
+    # Load the models
+    models = Models(args)
+
+    # Create a semaphore if needed
+    args.optional_semaphore = threading.Semaphore(args.concurrent) if args.concurrent is not None else contextlib.nullcontext()
+
+    # Create the server
+    server = LatinPipeServer(args, models)
+    server_thread = threading.Thread(target=server.serve_forever, daemon=True)
+    server_thread.start()
+
+    print("Started LatinPipe server on port {}.".format(args.port), file=sys.stderr)
+    print("To stop it gracefully, either send SIGINT (Ctrl+C) or SIGUSR1.", file=sys.stderr, flush=True)
+
+    # Wait until the server should be closed
+    signal.pthread_sigmask(signal.SIG_BLOCK, [signal.SIGINT, signal.SIGUSR1])
+    signal.sigwait([signal.SIGINT, signal.SIGUSR1])
+    print("Initiating shutdown of the LatinPipe EvaLatin24 server.", file=sys.stderr, flush=True)
+    server.shutdown()
+    print("Stopped handling new requests, processing all current ones.", file=sys.stderr, flush=True)
+    server.server_close()
+    print("Finished shutdown of the LatinPipe EvaLatin24 server.", file=sys.stderr, flush=True)

src/evalatin2024-latinpipe/parsed.conllu

@@ -0,0 +1,20 @@
+# sent_id = S0001
+# text = Uma frase como exemplo.
+1	Uma	um	DET	_	Definite=Ind|Gender=Fem|Number=Sing|PronType=Art	2	det	_	_
+2	frase	frase	NOUN	_	Gender=Fem|Number=Sing	0	root	_	_
+3	como	como	ADP	_	_	4	case	_	_
+4	exemplo	exemplo	NOUN	_	Gender=Masc|Number=Sing	2	nmod	_	SpaceAfter=No
+5	.	.	PUNCT	_	_	2	punct	_	_
+
+# sent_id = S0001
+# text = O menino viu a menina com o telescópio.
+1	O	_	_	_	_	_	_	_	_
+2	menino	_	_	_	_	_	_	_	_
+3	viu	_	_	_	_	_	_	_	_
+4	a	_	_	_	_	_	_	_	_
+5	menina	_	_	_	_	_	_	_	_
+6	com	_	_	_	_	_	_	_	_
+7	o	_	_	_	_	_	_	_	_
+8	telescópio	_	_	_	_	_	_	_	SpaceAfter=No
+9	.	_	_	_	_	_	_	_	_
+

src/evalatin2024-latinpipe/requirements.txt

@@ -0,0 +1,8 @@
+keras
+torch
+--extra-index-url=https://download.pytorch.org/whl/cu118
+transformers
+ufal.chu-liu-edmonds
+
+# For latinpipe_evalatin24_server, you also need
+# ufal.udpipe

src/portSentencer/abbrev.txt

@@ -0,0 +1,397 @@
+dr.
+dra.
+sr.
+sra.
+prof.
+profa.
+Dr.
+Dra.
+Sr.
+Sra.
+Prof.
+Profa.
+DR.
+DRA.
+SR.
+SRA.
+PROF.
+PROFA.
+ilmo.
+Ilmo.
+ILMO.
+bel.
+Bel.
+BEL.
+eng.
+Eng.
+ENG.
+reg.
+Reg.
+REG.
+visc.
+Visc.
+VISC.
+bar.
+Bar.
+BAR.
+cond.
+Cond.
+COND.
+séc.
+Séc.
+SÉC.
+jr.
+Jr.
+JR.
+ir.
+Ir.
+IR.
+st.
+St.
+ST.
+app.
+App.
+APP.
+gov.
+Gov.
+GOV.
+des.
+Des.
+DES.
+gen.
+Gen.
+GEN.
+gal.
+Gal.
+GAL.
+cel.
+Cel.
+CEL.
+col.
+Col.
+COL.
+maj.
+Maj.
+MAJ.
+ten.
+Ten.
+TEN.
+cap.
+Cap.
+CAP.
+capt.
+Capt.
+CAPT.
+com.
+Com.
+COM.
+brig.
+Brig.
+BRIG.
+estac.
+Estac.
+ESTAC.
+tel.
+Tel.
+TEL.
+ave.
+Ave.
+AVE.
+av.
+Av.
+AV.
+trav.
+Trav.
+TRAV.
+con.
+Con.
+CON.
+jd.
+Jd.
+JD.
+ed.
+Ed.
+ED.
+lj.
+Lj.
+LJ.
+cj.
+Cj.
+CJ.
+apto.
+Apto.
+APTO.
+apt.
+Apt.
+APT.
+ingr.
+Ingr.
+INGR.
+ap.
+Ap.
+AP.
+dir.
+Dir.
+DIR.
+min.
+Min.
+MIN.
+sec.
+Sec.
+SEC.
+kg.
+Kg.
+KG.
+ml.
+Ml.
+ML.
+km.
+Km.
+KM.
+cm.
+Cm.
+CM.
+vol.
+Vol.
+VOL.
+PP.
+pp.
+Pp
+pag.
+Pag
+PAG.
+pág.
+Pág
+PÁG.
+al.
+Al.
+AL.
+etc.
+i.e.
+e.g.
+cia.
+Cia.
+CIA.
+co.
+Co.
+CO.
+ltda.
+Ltda.
+LTDA.
+ex.
+Ex.
+EX.
+ac.
+Ac.
+AC.
+dc.
+Dc.
+DC.
+bros.
+Bros.
+BROS.
+pq.
+Pq.
+PQ.
+br.
+Br.
+BR.
+cent.
+Cent.
+CENT.
+ft.
+Ft.
+FT.
+net.
+Net.
+NET.
+no.
+No.
+NO.
+nr.
+Nr.
+NR.
+tr.
+Tr.
+TR.
+mi.
+Mi.
+MI.
+sta.
+Sta.
+STA.
+sto.
+Sto.
+STO.
+int.
+Int.
+INT.
+inf.
+Inf.
+INF.
+cult.
+Cult.
+CULT.
+op.
+Op.
+OP.
+aprox.
+Aprox.
+APROX.
+it.
+It.
+IT.
+ex.
+Ex.
+EX.
+flex.
+Flex.
+FLEX.
+ass.
+Ass.
+ASS.
+pç.
+Pç.
+PÇ.
+ind.
+Ind.
+IND.
+vl.
+Vl.
+VL.
+imp.
+Imp.
+IMP.
+emp.
+Emp.
+EMP.
+esq.
+Esq.
+ESQ.
+dir.
+Dir.
+DIR.
+ingr.
+Ingr.
+INGR.
+pça.
+Pça.
+PÇA.
+art.
+Art.
+ART.
+sec.
+Sec.
+SEC.
+a.
+A.
+b.
+B.
+c.
+C.
+d.
+D.
+e.
+E.
+f.
+F.
+g.
+G.
+h.
+H.
+i.
+I.
+j.
+J.
+k.
+K.
+l.
+L.
+m.
+M.
+n.
+N.
+o.
+O.
+p.
+P.
+q.
+Q.
+r.
+R.
+s.
+S.
+t.
+T.
+u.
+U.
+v.
+V.
+w.
+W.
+x.
+X.
+y.
+Y.
+z.
+Z.
+seg.
+ter.
+qua.
+qui.
+sex.
+sab.
+sáb.
+dom.
+Seg.
+Ter.
+Qua.
+Qui.
+Sex.
+Sab.
+Sáb.
+Dom.
+SEG.
+TER.
+QUA.
+QUI.
+SEX.
+SAB.
+SÁB.
+DOM.
+jan.
+fev.
+mar.
+abr.
+mai.
+jun.
+jul.
+ago.
+sep.
+out.
+nov.
+dez.
+Jan.
+Fev.
+Mar.
+Abr.
+Mai.
+Jun.
+Jul.
+Ago.
+Sep.
+Out.
+Nov.
+Dez.
+JAN.
+FEV.
+MAR.
+ABR.
+MAI.
+JUN.
+JUL.
+AGO.
+SET.
+OUT.
+NOV.
+DEZ.

src/portSentencer/portSent.py

@@ -0,0 +1,242 @@
+# portSentencer - sentenciador de texto puro para o Portugues
+#
+# Este programa recebe diversos arquivos de entrada em formato
+#    textual e gera um arquivo textual com uma sentença por linha.
+#
+# Opções:
+#
+# -h help
+# -o output file
+# -r replace non standart characters
+# -l limit the number of characters per sentence
+#
+# Exemplo de utilização:
+#
+# portSent -o sents.txt -r -l 2048 text1.txt text2.txt
+#
+# Busca o texto nos arquivos 'text1.txt' e 'text2.txt',
+#   substitui caracteres não usuais,
+#   gera sentenças com limite máximo de 2048 carateres e
+#   salva as sentenças no arquivo 'sents.txt'
+#
+# last edit: 01/21/2024
+# created by Lucelene Lopes - [email protected]
+
+import sys, os
+
+#################################################
+### Captura de argumentos da linha de comando
+#################################################
+def parseOptions(arguments):
+    # default options
+    output_file, input_files, replace, limit = "", [], False, 0
+    i = 1
+    while i < len(arguments):
+        if (arguments[i][0] == "-"):
+            # ajuda (help) - mostra ajuda, nada é executado
+            if ((arguments[i][1] == "h") and (len(arguments[i])==2)) or \
+               (arguments[i] == "-help"):
+                print("Opções:\n-h ajuda\n-o arquivo de saída", \
+                      "-r substitui caracteres não padrão", \
+                      "-l limite de caracteres por sentença", \
+                      " -demais opções ignoradas, por favor execute novamente sem opção de ajuda",
+                      "Exemplo de utilização:", \
+                      "portSent -o sents.txt -r -l 2048 text1.txt text2.txt", \
+                      "Busca o texto nos arquivos 'text1.txt' e 'text2.txt'", \
+                      "  substitui caracteres não usuais,", \
+                      "  gera sentenças com limite máximo de 2048 carateres e", \
+                      "  salva as sentenças no arquivo 'sents.txt'", \
+                      sep="\n")
+                return None
+            # opção de substituição (replace) de caracteres não usuais
+            elif ((arguments[i][1] == "r") and (len(arguments[i])==2)) or \
+                 (arguments[i] == "-replace"):
+                replace = True
+                i += 1
+            # opção de limite de tamanho de sentença (limit) - 0 para sem limite
+            elif ((arguments[i][1] == "l") and (len(arguments[i])==2)) or \
+                 (arguments[i] == "-limit"):
+                try:
+                    limit = eval(arguments[i+1])
+                    i += 2
+                except:
+                    print("limite de caracteres por sentença não informado - assumindo sem limite")
+                    i += 1
+            # opção de arquivo de saída (um nome de arquivo)
+            elif ((arguments[i][1] == "o") and (len(arguments[i])==2)) or \
+                 (arguments[i] == "-output"):
+                output_file = arguments[i+1]
+                i += 2
+            # opções inválidas - nada é executado
+            else:
+                print("Opção {} inválida, demais opções ignoradas, por favor execute novamente".format(arguments[i]))
+                return None
+        # arquivos de entrada (qualquer número) - só são incluídos se existirem
+        else:
+            if (os.path.isfile(arguments[i])):
+                input_files.append(arguments[i])
+                i += 1
+            else:
+                print("O arquivo {} não foi encontrado (ignorado)".format(arguments[i]))
+                i += 1
+    return [output_file, input_files, limit, replace]
+
+#################################################
+### função stripSents - faz de fato o sentenciamento
+#################################################
+def stripSents(inputText, outfile, limit, replace):
+    def cleanPrint(sent, outfile):
+        # do not print empty sentences
+        if (sent == "") or (sent == ".") or (sent == ".."):
+            return 0
+        # remove second . in sentences ending by ..
+        elif (len(sent) > 2) and (sent[-3:] != "...") and (sent[-2:] == ".."):
+            print(sent[:-1], file=outfile)
+            return 1
+        # insert . in sentences not ending by punctuation
+        elif (sent[-1] not in [".", "!", "?", ":", ";"]) and \
+            not ((sent[-1] in ["'", '"']) and (sent[-2] in [".", "!", "?"])):
+            print(sent+".", file=outfile)
+            return 1
+        # remove encompassing quotations " or ' if the quotations do not appear inside the sentence
+        elif (sent[0] == sent[1]) and ((sent[0] == "'") or (sent[0] == '"')) and (sent.count(sent[0]) == 2):
+            print(sent[1:-1], file=outfile)
+            return 1
+        # otherwise print it as it is
+        else:
+            print(sent, file=outfile)
+            return 1
+    def isAbbrev(chunk, abbrev):
+        abbr = False
+        for a in abbrev:
+            if (chunk == a):
+                abbr = True
+                break
+            else:
+                lasts = -len(a)
+                if (chunk[lasts:] == a) and (not chunk[lasts-1].isalpha()):
+                    abbr = True
+                    break
+        return abbr
+    # the function stripSents main body
+    abbrev = []
+    infile = open("./src/portSentencer/abbrev.txt", "r")
+    for line in infile:
+        abbrev.append(line[:-1])
+    infile.close()
+    if (replace):
+        replaceables = [[" ", " "], \
+                        ["—", "-"], ["–", "-"], \
+                        ['＂', '"'], \
+                        ['“', '"'], ['”', '"'], \
+                        ['‟', '"'], ['″', '"'], \
+                        ['‶', '"'], ['〃', '"'], \
+                        ['״', '"'], ['˝', '"'], \
+                        ['ʺ', '"'], ['˶', '"'], \
+                        ['ˮ', '"'], ['ײ', '"'], \
+                        [" ‣", "."], [" >>", "."], [" ○", "."], [" *", "."], \
+                        [" | ", ". "], [" .", "."], \
+                        ["\n", " "], ["\t", " "]]
+    else:
+        replaceables = [["\n", " "], ["\t", " "]]
+    tmp = inputText.replace("  "," ")
+    for r in replaceables:
+        tmp = tmp.replace(r[0], r[1])
+    while (tmp.find("  ") != -1):
+        tmp = tmp.replace("  "," ")
+    if (tmp[0] == " "):
+        tmp = tmp[1:]
+    bagOfChunks = tmp.split(" ")
+    s, sent = 0, ""
+    if (bagOfChunks[-1] == ""):
+        bagOfChunks.pop()
+    for i in range(len(bagOfChunks)):
+        # if it is the last chunk, it is the end of sentence
+        if (i == len(bagOfChunks)-1):
+            sent += " " + bagOfChunks[i]
+            s += cleanPrint(sent[1:], outfile)
+            break
+        chunk = bagOfChunks[i]
+        # if there is a limit and the chunk is greater than the limit, discard it
+        if (limit != 0) and (len(chunk) > limit):
+            continue
+        # if there is a limit and it is reached, ends the sentence arbitrarily
+        elif (limit != 0) and (len(sent) + len(chunk) > limit):
+            s += cleanPrint(sent[1:], outfile)
+            sent = chunk
+        # if the chunk is too short
+        elif (len(chunk) < 3) and (len(chunk) != 0):
+            sent += " " + chunk
+        # if the chunk is empty
+        elif (len(chunk) == 0):
+            continue
+        # ! ? or ... always mark an end of sentence
+        elif (chunk[-3:] == "...") or (chunk[-1] == "!") or (chunk[-1] == "?"):
+            sent += " " + chunk
+            s += cleanPrint(sent[1:], outfile)
+            sent = ""
+        # a . : or ; followed by a lowercase chunk is not an end of sentence
+        elif ((chunk[-1] == ".") or (chunk[-1] == ":") or (chunk[-1] == ";")) and (bagOfChunks[i+1][0].islower()):
+            sent += " " + chunk
+        # a : or ; not followed by a lowercase chunk is an end of sentence
+        elif ((chunk[-1] == ":") or (chunk[-1] == ";")) and (not bagOfChunks[i+1][0].islower()):
+            sent += " " + chunk
+            s += cleanPrint(sent[1:], outfile)
+            sent = ""
+        # chunk ends with ! or ? followed by quotations that had appear before an odd number is an end of sentence
+        elif (chunk[-2:] in ["!'", '!"', "?'", '?"']):
+            sent += " " + chunk
+            s += cleanPrint(sent[1:], outfile)
+            sent = ""
+        elif (chunk[-2:] in [".'", '."']):
+            sent += " " + chunk
+            abbr = isAbbrev(chunk[:-1], abbrev)
+            if not abbr:
+                s += cleanPrint(sent[1:], outfile)
+                sent = ""
+        # a chunk not ending with ! ? ... ; : or . is not an end of sentence
+        elif (chunk[-1] != "."):
+            sent += " " + chunk
+        # chunk ending by . is either a know abbreviation (not an end of sentence), or an end of sentence
+        elif (chunk[-1] == "."):
+            abbr = isAbbrev(chunk, abbrev)
+            if (abbr):
+                sent += " " + chunk
+            else:
+                sent += " " + chunk
+                s += cleanPrint(sent[1:], outfile)
+                sent = ""
+    # return the number of generated sentences
+    return s
+
+#################################################
+### função principal do programa - busca argumentos e chama 'stripSents' que faz de fato o sentenciamento
+#################################################
+def portSent():
+    if (len(sys.argv) == 1):
+        arguments = ["sents2.txt", ["relic.txt"], 0, True]
+        print("Assumindo default: 'sents.txt' como arquivo de saída, 'text1.txt' como arquivo de entrada, sem limite e substituições.")
+    else:
+        arguments = parseOptions(sys.argv)
+    if (arguments != None):
+        if (arguments[0] == ""):
+            print("Assumindo 'sents.txt' como arquivo de saída")
+            arguments[0] = 'sents.txt'
+        if (arguments[1] == []):
+            print("Nenhum arquivo de entrada válido - por favor corrija e tente novamente")
+        else:
+            outfile = open(arguments[0], "w")
+            inputText = ""
+            for oneInput in arguments[1]:
+                infile = open(oneInput, "r")
+                inputText += infile.read()
+                infile.close()
+                s = stripSents(inputText, outfile, arguments[2], arguments[3])
+            outfile.close()
+            print("Sentenciamento terminado com {} sentenças extraídas e salvas em {}".format(s, arguments[0]))
+    else:
+        print("Problemas com parâmetros - por favor corrija e tente novamente")
+
+portSent()
+
+

src/portTokenizer/ADP.tsv

@@ -0,0 +1,38 @@
+a	a	_
+afora	afora	_
+ante	ante	_
+após	após	_
+até	até	_
+com	com	_
+como	como	_
+conforme	conforme	_
+consoante	consoante	_
+contra	contra	_
+dado	dado	_
+de	de	_
+desde	desde	_
+devido	devido	_
+durante	durante	_
+em	em	_
+entre	entre	_
+exceto	exceto	_
+fora	fora	_
+malgrado	malgrado	_
+mediante	mediante	_
+menos	menos	_
+para	para	_
+perante	perante	_
+por	por	_
+pra	para	Abbr=Yes
+pró	pró	_
+que	que	_
+salvo	salvo	_
+segundo	segundo	_
+sem	sem	_
+senão	senão	_
+sob	sob	_
+sobre	sobre	_
+versus	versus	_
+via	via	_
+visto	visto	_
+vs	versus	Abbr=Yes

src/portTokenizer/AUX.tsv

@@ -0,0 +1,435 @@
+era	ser	Mood=Ind|Number=Sing|Person=1|Tense=Imp|VerbForm=Fin
+era	ser	Mood=Ind|Number=Sing|Person=3|Tense=Imp|VerbForm=Fin
+eram	ser	Mood=Ind|Number=Plur|Person=3|Tense=Imp|VerbForm=Fin
+eras	ser	Mood=Ind|Number=Sing|Person=2|Tense=Imp|VerbForm=Fin
+estada	estar	Gender=Fem|Number=Sing|VerbForm=Part
+estadas	estar	Gender=Fem|Number=Plur|VerbForm=Part
+estado	estar	Gender=Masc|Number=Sing|VerbForm=Part
+estados	estar	Gender=Masc|Number=Plur|VerbForm=Part
+estai	estar	Mood=Imp|Number=Plur|Person=2|VerbForm=Fin
+estais	estar	Mood=Ind|Number=Plur|Person=2|Tense=Pres|VerbForm=Fin
+estamos	estar	Mood=Ind|Number=Plur|Person=1|Tense=Pres|VerbForm=Fin
+estando	estar	VerbForm=Ger
+estar	estar	Number=Sing|Person=1|VerbForm=Inf
+estar	estar	Number=Sing|Person=3|VerbForm=Inf
+estar	estar	VerbForm=Inf
+estardes	estar	Number=Plur|Person=2|VerbForm=Inf
+estarei	estar	Mood=Ind|Number=Sing|Person=1|Tense=Fut|VerbForm=Fin
+estareis	estar	Mood=Ind|Number=Plur|Person=2|Tense=Fut|VerbForm=Fin
+estarem	estar	Number=Plur|Person=3|VerbForm=Inf
+estaremos	estar	Mood=Ind|Number=Plur|Person=1|Tense=Fut|VerbForm=Fin
+estares	estar	Number=Sing|Person=2|VerbForm=Inf
+estaria	estar	Mood=Cnd|Number=Sing|Person=1|VerbForm=Fin
+estaria	estar	Mood=Cnd|Number=Sing|Person=3|VerbForm=Fin
+estariam	estar	Mood=Cnd|Number=Plur|Person=3|VerbForm=Fin
+estarias	estar	Mood=Cnd|Number=Sing|Person=2|VerbForm=Fin
+estarmos	estar	Number=Plur|Person=1|VerbForm=Inf
+estará	estar	Mood=Ind|Number=Sing|Person=3|Tense=Fut|VerbForm=Fin
+estarás	estar	Mood=Ind|Number=Sing|Person=2|Tense=Fut|VerbForm=Fin
+estarão	estar	Mood=Ind|Number=Plur|Person=3|Tense=Fut|VerbForm=Fin
+estaríamos	estar	Mood=Cnd|Number=Plur|Person=1|VerbForm=Fin
+estaríeis	estar	Mood=Cnd|Number=Plur|Person=2|VerbForm=Fin
+estava	estar	Mood=Ind|Number=Sing|Person=1|Tense=Imp|VerbForm=Fin
+estava	estar	Mood=Ind|Number=Sing|Person=3|Tense=Imp|VerbForm=Fin
+estavam	estar	Mood=Ind|Number=Plur|Person=3|Tense=Imp|VerbForm=Fin
+estavas	estar	Mood=Ind|Number=Sing|Person=2|Tense=Imp|VerbForm=Fin
+esteja	estar	Mood=Imp|Number=Sing|Person=3|VerbForm=Fin
+esteja	estar	Mood=Sub|Number=Sing|Person=1|Tense=Pres|VerbForm=Fin
+esteja	estar	Mood=Sub|Number=Sing|Person=3|Tense=Pres|VerbForm=Fin
+estejais	estar	Mood=Sub|Number=Plur|Person=2|Tense=Pres|VerbForm=Fin
+estejam	estar	Mood=Imp|Number=Plur|Person=3|VerbForm=Fin
+estejam	estar	Mood=Sub|Number=Plur|Person=3|Tense=Pres|VerbForm=Fin
+estejamos	estar	Mood=Imp|Number=Plur|Person=1|VerbForm=Fin
+estejamos	estar	Mood=Sub|Number=Plur|Person=1|Tense=Pres|VerbForm=Fin
+estejas	estar	Mood=Sub|Number=Sing|Person=2|Tense=Pres|VerbForm=Fin
+esteve	estar	Mood=Ind|Number=Sing|Person=3|Tense=Past|VerbForm=Fin
+estive	estar	Mood=Ind|Number=Sing|Person=1|Tense=Past|VerbForm=Fin
+estivemos	estar	Mood=Ind|Number=Plur|Person=1|Tense=Past|VerbForm=Fin
+estiver	estar	Mood=Sub|Number=Sing|Person=1|Tense=Fut|VerbForm=Fin
+estiver	estar	Mood=Sub|Number=Sing|Person=3|Tense=Fut|VerbForm=Fin
+estivera	estar	Mood=Ind|Number=Sing|Person=1|Tense=Pqp|VerbForm=Fin
+estivera	estar	Mood=Ind|Number=Sing|Person=3|Tense=Pqp|VerbForm=Fin
+estiveram	estar	Mood=Ind|Number=Plur|Person=3|Tense=Past|VerbForm=Fin
+estiveram	estar	Mood=Ind|Number=Plur|Person=3|Tense=Pqp|VerbForm=Fin
+estiveras	estar	Mood=Ind|Number=Sing|Person=2|Tense=Pqp|VerbForm=Fin
+estiverdes	estar	Mood=Sub|Number=Plur|Person=2|Tense=Fut|VerbForm=Fin
+estiverem	estar	Mood=Sub|Number=Plur|Person=3|Tense=Fut|VerbForm=Fin
+estiveres	estar	Mood=Sub|Number=Sing|Person=2|Tense=Fut|VerbForm=Fin
+estivermos	estar	Mood=Sub|Number=Plur|Person=1|Tense=Fut|VerbForm=Fin
+estivesse	estar	Mood=Sub|Number=Sing|Person=1|Tense=Past|VerbForm=Fin
+estivesse	estar	Mood=Sub|Number=Sing|Person=3|Tense=Past|VerbForm=Fin
+estivessem	estar	Mood=Sub|Number=Plur|Person=3|Tense=Past|VerbForm=Fin
+estivesses	estar	Mood=Sub|Number=Sing|Person=2|Tense=Past|VerbForm=Fin
+estiveste	estar	Mood=Ind|Number=Sing|Person=2|Tense=Past|VerbForm=Fin
+estivestes	estar	Mood=Ind|Number=Plur|Person=2|Tense=Past|VerbForm=Fin
+estivéramos	estar	Mood=Ind|Number=Plur|Person=1|Tense=Pqp|VerbForm=Fin
+estivéreis	estar	Mood=Ind|Number=Plur|Person=2|Tense=Pqp|VerbForm=Fin
+estivésseis	estar	Mood=Sub|Number=Plur|Person=2|Tense=Past|VerbForm=Fin
+estivéssemos	estar	Mood=Sub|Number=Plur|Person=1|Tense=Past|VerbForm=Fin
+estou	estar	Mood=Ind|Number=Sing|Person=1|Tense=Pres|VerbForm=Fin
+está	estar	Mood=Imp|Number=Sing|Person=2|VerbForm=Fin
+está	estar	Mood=Ind|Number=Sing|Person=3|Tense=Pres|VerbForm=Fin
+estás	estar	Mood=Ind|Number=Sing|Person=2|Tense=Pres|VerbForm=Fin
+estávamos	estar	Mood=Ind|Number=Plur|Person=1|Tense=Imp|VerbForm=Fin
+estáveis	estar	Mood=Ind|Number=Plur|Person=2|Tense=Imp|VerbForm=Fin
+estão	estar	Mood=Ind|Number=Plur|Person=3|Tense=Pres|VerbForm=Fin
+foi	ir	Mood=Ind|Number=Sing|Person=3|Tense=Past|VerbForm=Fin
+foi	ser	Mood=Ind|Number=Sing|Person=3|Tense=Past|VerbForm=Fin
+fomos	ir	Mood=Ind|Number=Plur|Person=1|Tense=Past|VerbForm=Fin
+fomos	ser	Mood=Ind|Number=Plur|Person=1|Tense=Past|VerbForm=Fin
+for	ir	Mood=Sub|Number=Sing|Person=1|Tense=Fut|VerbForm=Fin
+for	ir	Mood=Sub|Number=Sing|Person=3|Tense=Fut|VerbForm=Fin
+for	ser	Mood=Sub|Number=Sing|Person=1|Tense=Fut|VerbForm=Fin
+for	ser	Mood=Sub|Number=Sing|Person=3|Tense=Fut|VerbForm=Fin
+fora	ir	Mood=Ind|Number=Sing|Person=1|Tense=Pqp|VerbForm=Fin
+fora	ir	Mood=Ind|Number=Sing|Person=3|Tense=Pqp|VerbForm=Fin
+fora	ser	Mood=Ind|Number=Sing|Person=1|Tense=Pqp|VerbForm=Fin
+fora	ser	Mood=Ind|Number=Sing|Person=3|Tense=Pqp|VerbForm=Fin
+foram	ir	Mood=Ind|Number=Plur|Person=3|Tense=Past|VerbForm=Fin
+foram	ir	Mood=Ind|Number=Plur|Person=3|Tense=Pqp|VerbForm=Fin
+foram	ser	Mood=Ind|Number=Plur|Person=3|Tense=Past|VerbForm=Fin
+foram	ser	Mood=Ind|Number=Plur|Person=3|Tense=Pqp|VerbForm=Fin
+foras	ir	Mood=Ind|Number=Sing|Person=2|Tense=Pqp|VerbForm=Fin
+foras	ser	Mood=Ind|Number=Sing|Person=2|Tense=Pqp|VerbForm=Fin
+fordes	ir	Mood=Sub|Number=Plur|Person=2|Tense=Fut|VerbForm=Fin
+fordes	ser	Mood=Sub|Number=Plur|Person=2|Tense=Fut|VerbForm=Fin
+forem	ir	Mood=Sub|Number=Plur|Person=3|Tense=Fut|VerbForm=Fin
+forem	ser	Mood=Sub|Number=Plur|Person=3|Tense=Fut|VerbForm=Fin
+fores	ir	Mood=Sub|Number=Sing|Person=2|Tense=Fut|VerbForm=Fin
+fores	ser	Mood=Sub|Number=Sing|Person=2|Tense=Fut|VerbForm=Fin
+formos	ir	Mood=Sub|Number=Plur|Person=1|Tense=Fut|VerbForm=Fin
+formos	ser	Mood=Sub|Number=Plur|Person=1|Tense=Fut|VerbForm=Fin
+fosse	ir	Mood=Sub|Number=Sing|Person=1|Tense=Past|VerbForm=Fin
+fosse	ir	Mood=Sub|Number=Sing|Person=3|Tense=Past|VerbForm=Fin
+fosse	ser	Mood=Sub|Number=Sing|Person=1|Tense=Past|VerbForm=Fin
+fosse	ser	Mood=Sub|Number=Sing|Person=3|Tense=Past|VerbForm=Fin
+fossem	ir	Mood=Sub|Number=Plur|Person=3|Tense=Past|VerbForm=Fin
+fossem	ser	Mood=Sub|Number=Plur|Person=3|Tense=Past|VerbForm=Fin
+fosses	ir	Mood=Sub|Number=Sing|Person=2|Tense=Past|VerbForm=Fin
+fosses	ser	Mood=Sub|Number=Sing|Person=2|Tense=Past|VerbForm=Fin
+foste	ir	Mood=Ind|Number=Sing|Person=2|Tense=Past|VerbForm=Fin
+foste	ser	Mood=Ind|Number=Sing|Person=2|Tense=Past|VerbForm=Fin
+fostes	ir	Mood=Ind|Number=Plur|Person=2|Tense=Past|VerbForm=Fin
+fostes	ser	Mood=Ind|Number=Plur|Person=2|Tense=Past|VerbForm=Fin
+fui	ir	Mood=Ind|Number=Sing|Person=1|Tense=Past|VerbForm=Fin
+fui	ser	Mood=Ind|Number=Sing|Person=1|Tense=Past|VerbForm=Fin
+fôramos	ir	Mood=Ind|Number=Plur|Person=1|Tense=Pqp|VerbForm=Fin
+fôramos	ser	Mood=Ind|Number=Plur|Person=1|Tense=Pqp|VerbForm=Fin
+fôreis	ir	Mood=Ind|Number=Plur|Person=2|Tense=Pqp|VerbForm=Fin
+fôreis	ser	Mood=Ind|Number=Plur|Person=2|Tense=Pqp|VerbForm=Fin
+fôsseis	ir	Mood=Sub|Number=Plur|Person=2|Tense=Past|VerbForm=Fin
+fôsseis	ser	Mood=Sub|Number=Plur|Person=2|Tense=Past|VerbForm=Fin
+fôssemos	ir	Mood=Sub|Number=Plur|Person=1|Tense=Past|VerbForm=Fin
+fôssemos	ser	Mood=Sub|Number=Plur|Person=1|Tense=Past|VerbForm=Fin
+haja	haver	Mood=Imp|Number=Sing|Person=3|VerbForm=Fin
+haja	haver	Mood=Sub|Number=Sing|Person=1|Tense=Pres|VerbForm=Fin
+haja	haver	Mood=Sub|Number=Sing|Person=3|Tense=Pres|VerbForm=Fin
+hajais	haver	Mood=Sub|Number=Plur|Person=2|Tense=Pres|VerbForm=Fin
+hajam	haver	Mood=Imp|Number=Plur|Person=3|VerbForm=Fin
+hajam	haver	Mood=Sub|Number=Plur|Person=3|Tense=Pres|VerbForm=Fin
+hajamos	haver	Mood=Imp|Number=Plur|Person=1|VerbForm=Fin
+hajamos	haver	Mood=Sub|Number=Plur|Person=1|Tense=Pres|VerbForm=Fin
+hajas	haver	Mood=Sub|Number=Sing|Person=2|Tense=Pres|VerbForm=Fin
+havei	haver	Mood=Imp|Number=Plur|Person=2|VerbForm=Fin
+haveis	haver	Mood=Ind|Number=Plur|Person=2|Tense=Pres|VerbForm=Fin
+havemos	haver	Mood=Ind|Number=Plur|Person=1|Tense=Pres|VerbForm=Fin
+havendo	haver	VerbForm=Ger
+haver	haver	Number=Sing|Person=1|VerbForm=Inf
+haver	haver	Number=Sing|Person=3|VerbForm=Inf
+haver	haver	VerbForm=Inf
+haverdes	haver	Number=Plur|Person=2|VerbForm=Inf
+haverei	haver	Mood=Ind|Number=Sing|Person=1|Tense=Fut|VerbForm=Fin
+havereis	haver	Mood=Ind|Number=Plur|Person=2|Tense=Fut|VerbForm=Fin
+haverem	haver	Number=Plur|Person=3|VerbForm=Inf
+haveremos	haver	Mood=Ind|Number=Plur|Person=1|Tense=Fut|VerbForm=Fin
+haveres	haver	Number=Sing|Person=2|VerbForm=Inf
+haveria	haver	Mood=Cnd|Number=Sing|Person=1|VerbForm=Fin
+haveria	haver	Mood=Cnd|Number=Sing|Person=3|VerbForm=Fin
+haveriam	haver	Mood=Cnd|Number=Plur|Person=3|VerbForm=Fin
+haverias	haver	Mood=Cnd|Number=Sing|Person=2|VerbForm=Fin
+havermos	haver	Number=Plur|Person=1|VerbForm=Inf
+haverá	haver	Mood=Ind|Number=Sing|Person=3|Tense=Fut|VerbForm=Fin
+haverás	haver	Mood=Ind|Number=Sing|Person=2|Tense=Fut|VerbForm=Fin
+haverão	haver	Mood=Ind|Number=Plur|Person=3|Tense=Fut|VerbForm=Fin
+haveríamos	haver	Mood=Cnd|Number=Plur|Person=1|VerbForm=Fin
+haveríeis	haver	Mood=Cnd|Number=Plur|Person=2|VerbForm=Fin
+havia	haver	Mood=Ind|Number=Sing|Person=1|Tense=Imp|VerbForm=Fin
+havia	haver	Mood=Ind|Number=Sing|Person=3|Tense=Imp|VerbForm=Fin
+haviam	haver	Mood=Ind|Number=Plur|Person=3|Tense=Imp|VerbForm=Fin
+havias	haver	Mood=Ind|Number=Sing|Person=2|Tense=Imp|VerbForm=Fin
+havida	haver	Gender=Fem|Number=Sing|VerbForm=Part
+havidas	haver	Gender=Fem|Number=Plur|VerbForm=Part
+havido	haver	Gender=Masc|Number=Sing|VerbForm=Part
+havidos	haver	Gender=Masc|Number=Plur|VerbForm=Part
+havíamos	haver	Mood=Ind|Number=Plur|Person=1|Tense=Imp|VerbForm=Fin
+havíeis	haver	Mood=Ind|Number=Plur|Person=2|Tense=Imp|VerbForm=Fin
+hei	haver	Mood=Ind|Number=Sing|Person=1|Tense=Pres|VerbForm=Fin
+houve	haver	Mood=Ind|Number=Sing|Person=1|Tense=Past|VerbForm=Fin
+houve	haver	Mood=Ind|Number=Sing|Person=3|Tense=Past|VerbForm=Fin
+houvemos	haver	Mood=Ind|Number=Plur|Person=1|Tense=Past|VerbForm=Fin
+houver	haver	Mood=Sub|Number=Sing|Person=1|Tense=Fut|VerbForm=Fin
+houver	haver	Mood=Sub|Number=Sing|Person=3|Tense=Fut|VerbForm=Fin
+houvera	haver	Mood=Ind|Number=Sing|Person=1|Tense=Pqp|VerbForm=Fin
+houvera	haver	Mood=Ind|Number=Sing|Person=3|Tense=Pqp|VerbForm=Fin
+houveram	haver	Mood=Ind|Number=Plur|Person=3|Tense=Past|VerbForm=Fin
+houveram	haver	Mood=Ind|Number=Plur|Person=3|Tense=Pqp|VerbForm=Fin
+houveras	haver	Mood=Ind|Number=Sing|Person=2|Tense=Pqp|VerbForm=Fin
+houverdes	haver	Mood=Sub|Number=Plur|Person=2|Tense=Fut|VerbForm=Fin
+houverem	haver	Mood=Sub|Number=Plur|Person=3|Tense=Fut|VerbForm=Fin
+houveres	haver	Mood=Sub|Number=Sing|Person=2|Tense=Fut|VerbForm=Fin
+houvermos	haver	Mood=Sub|Number=Plur|Person=1|Tense=Fut|VerbForm=Fin
+houvesse	haver	Mood=Sub|Number=Sing|Person=1|Tense=Past|VerbForm=Fin
+houvesse	haver	Mood=Sub|Number=Sing|Person=3|Tense=Past|VerbForm=Fin
+houvessem	haver	Mood=Sub|Number=Plur|Person=3|Tense=Past|VerbForm=Fin
+houvesses	haver	Mood=Sub|Number=Sing|Person=2|Tense=Past|VerbForm=Fin
+houveste	haver	Mood=Ind|Number=Sing|Person=2|Tense=Past|VerbForm=Fin
+houvestes	haver	Mood=Ind|Number=Plur|Person=2|Tense=Past|VerbForm=Fin
+houvéramos	haver	Mood=Ind|Number=Plur|Person=1|Tense=Pqp|VerbForm=Fin
+houvéreis	haver	Mood=Ind|Number=Plur|Person=2|Tense=Pqp|VerbForm=Fin
+houvésseis	haver	Mood=Sub|Number=Plur|Person=2|Tense=Past|VerbForm=Fin
+houvéssemos	haver	Mood=Sub|Number=Plur|Person=1|Tense=Past|VerbForm=Fin
+há	haver	Mood=Imp|Number=Sing|Person=2|VerbForm=Fin
+há	haver	Mood=Ind|Number=Sing|Person=3|Tense=Pres|VerbForm=Fin
+hás	haver	Mood=Ind|Number=Sing|Person=2|Tense=Pres|VerbForm=Fin
+hão	haver	Mood=Ind|Number=Plur|Person=3|Tense=Pres|VerbForm=Fin
+ia	ir	Mood=Ind|Number=Sing|Person=1|Tense=Imp|VerbForm=Fin
+ia	ir	Mood=Ind|Number=Sing|Person=3|Tense=Imp|VerbForm=Fin
+iam	ir	Mood=Ind|Number=Plur|Person=3|Tense=Imp|VerbForm=Fin
+ias	ir	Mood=Ind|Number=Sing|Person=2|Tense=Imp|VerbForm=Fin
+ida	ir	Gender=Fem|Number=Sing|VerbForm=Part
+idas	ir	Gender=Fem|Number=Plur|VerbForm=Part
+ide	ir	Mood=Imp|Number=Plur|Person=2|VerbForm=Fin
+ides	ir	Mood=Ind|Number=Plur|Person=2|Tense=Pres|VerbForm=Fin
+ido	ir	Gender=Masc|Number=Sing|VerbForm=Part
+idos	ir	Gender=Masc|Number=Plur|VerbForm=Part
+indo	ir	VerbForm=Ger
+ir	ir	Number=Sing|Person=1|VerbForm=Inf
+ir	ir	Number=Sing|Person=3|VerbForm=Inf
+ir	ir	VerbForm=Inf
+irdes	ir	Number=Plur|Person=2|VerbForm=Inf
+irei	ir	Mood=Ind|Number=Sing|Person=1|Tense=Fut|VerbForm=Fin
+ireis	ir	Mood=Ind|Number=Plur|Person=2|Tense=Fut|VerbForm=Fin
+irem	ir	Number=Plur|Person=3|VerbForm=Inf
+iremos	ir	Mood=Ind|Number=Plur|Person=1|Tense=Fut|VerbForm=Fin
+ires	ir	Number=Sing|Person=2|VerbForm=Inf
+iria	ir	Mood=Cnd|Number=Sing|Person=1|VerbForm=Fin
+iria	ir	Mood=Cnd|Number=Sing|Person=3|VerbForm=Fin
+iriam	ir	Mood=Cnd|Number=Plur|Person=3|VerbForm=Fin
+irias	ir	Mood=Cnd|Number=Sing|Person=2|VerbForm=Fin
+irmos	ir	Number=Plur|Person=1|VerbForm=Inf
+irá	ir	Mood=Ind|Number=Sing|Person=3|Tense=Fut|VerbForm=Fin
+irás	ir	Mood=Ind|Number=Sing|Person=2|Tense=Fut|VerbForm=Fin
+irão	ir	Mood=Ind|Number=Plur|Person=3|Tense=Fut|VerbForm=Fin
+iríamos	ir	Mood=Cnd|Number=Plur|Person=1|VerbForm=Fin
+iríeis	ir	Mood=Cnd|Number=Plur|Person=2|VerbForm=Fin
+sede	ser	Mood=Imp|Number=Plur|Person=2|VerbForm=Fin
+seja	ser	Mood=Imp|Number=Sing|Person=3|VerbForm=Fin
+seja	ser	Mood=Sub|Number=Sing|Person=1|Tense=Pres|VerbForm=Fin
+seja	ser	Mood=Sub|Number=Sing|Person=3|Tense=Pres|VerbForm=Fin
+sejais	ser	Mood=Sub|Number=Plur|Person=2|Tense=Pres|VerbForm=Fin
+sejam	ser	Mood=Imp|Number=Plur|Person=3|VerbForm=Fin
+sejam	ser	Mood=Sub|Number=Plur|Person=3|Tense=Pres|VerbForm=Fin
+sejamos	ser	Mood=Imp|Number=Plur|Person=1|VerbForm=Fin
+sejamos	ser	Mood=Sub|Number=Plur|Person=1|Tense=Pres|VerbForm=Fin
+sejas	ser	Mood=Sub|Number=Sing|Person=2|Tense=Pres|VerbForm=Fin
+sendo	ser	VerbForm=Ger
+ser	ser	Number=Sing|Person=1|VerbForm=Inf
+ser	ser	Number=Sing|Person=3|VerbForm=Inf
+ser	ser	VerbForm=Inf
+serdes	ser	Number=Plur|Person=2|VerbForm=Inf
+serei	ser	Mood=Ind|Number=Sing|Person=1|Tense=Fut|VerbForm=Fin
+sereis	ser	Mood=Ind|Number=Plur|Person=2|Tense=Fut|VerbForm=Fin
+serem	ser	Number=Plur|Person=3|VerbForm=Inf
+seremos	ser	Mood=Ind|Number=Plur|Person=1|Tense=Fut|VerbForm=Fin
+seres	ser	Number=Sing|Person=2|VerbForm=Inf
+seria	ser	Mood=Cnd|Number=Sing|Person=1|VerbForm=Fin
+seria	ser	Mood=Cnd|Number=Sing|Person=3|VerbForm=Fin
+seriam	ser	Mood=Cnd|Number=Plur|Person=3|VerbForm=Fin
+serias	ser	Mood=Cnd|Number=Sing|Person=2|VerbForm=Fin
+sermos	ser	Number=Plur|Person=1|VerbForm=Inf
+será	ser	Mood=Ind|Number=Sing|Person=3|Tense=Fut|VerbForm=Fin
+serás	ser	Mood=Ind|Number=Sing|Person=2|Tense=Fut|VerbForm=Fin
+serão	ser	Mood=Ind|Number=Plur|Person=3|Tense=Fut|VerbForm=Fin
+seríamos	ser	Mood=Cnd|Number=Plur|Person=1|VerbForm=Fin
+seríeis	ser	Mood=Cnd|Number=Plur|Person=2|VerbForm=Fin
+sida	ser	Gender=Fem|Number=Sing|VerbForm=Part
+sidas	ser	Gender=Fem|Number=Plur|VerbForm=Part
+sido	ser	Gender=Masc|Number=Sing|VerbForm=Part
+sidos	ser	Gender=Masc|Number=Plur|VerbForm=Part
+sois	ser	Mood=Ind|Number=Plur|Person=2|Tense=Pres|VerbForm=Fin
+somos	ser	Mood=Ind|Number=Plur|Person=1|Tense=Pres|VerbForm=Fin
+sou	ser	Mood=Ind|Number=Sing|Person=1|Tense=Pres|VerbForm=Fin
+são	ser	Mood=Ind|Number=Plur|Person=3|Tense=Pres|VerbForm=Fin
+sê	ser	Mood=Imp|Number=Sing|Person=2|VerbForm=Fin
+tamos	estar	Abbr=Yes|Mood=Ind|Number=Plur|Person=1|Tense=Pres|VerbForm=Fin
+tava	estar	Abbr=Yes|Mood=Ind|Number=Sing|Person=3|Tense=Imp|VerbForm=Fin
+tavam	estar	Abbr=Yes|Mood=Ind|Number=Plur|Person=3|Tense=Imp|VerbForm=Fin
+tem	ter	Mood=Imp|Number=Sing|Person=2|VerbForm=Fin
+tem	ter	Mood=Ind|Number=Sing|Person=3|Tense=Pres|VerbForm=Fin
+temos	ter	Mood=Ind|Number=Plur|Person=1|Tense=Pres|VerbForm=Fin
+tende	ter	Mood=Imp|Number=Plur|Person=2|VerbForm=Fin
+tendes	ter	Mood=Ind|Number=Plur|Person=2|Tense=Pres|VerbForm=Fin
+tendo	ter	VerbForm=Ger
+tenha	ter	Mood=Imp|Number=Sing|Person=3|VerbForm=Fin
+tenha	ter	Mood=Sub|Number=Sing|Person=1|Tense=Pres|VerbForm=Fin
+tenha	ter	Mood=Sub|Number=Sing|Person=3|Tense=Pres|VerbForm=Fin
+tenhais	ter	Mood=Sub|Number=Plur|Person=2|Tense=Pres|VerbForm=Fin
+tenham	ter	Mood=Imp|Number=Plur|Person=3|VerbForm=Fin
+tenham	ter	Mood=Sub|Number=Plur|Person=3|Tense=Pres|VerbForm=Fin
+tenhamos	ter	Mood=Imp|Number=Plur|Person=1|VerbForm=Fin
+tenhamos	ter	Mood=Sub|Number=Plur|Person=1|Tense=Pres|VerbForm=Fin
+tenhas	ter	Mood=Sub|Number=Sing|Person=2|Tense=Pres|VerbForm=Fin
+tenho	ter	Mood=Ind|Number=Sing|Person=1|Tense=Pres|VerbForm=Fin
+tens	ter	Mood=Ind|Number=Sing|Person=2|Tense=Pres|VerbForm=Fin
+ter	ter	Number=Sing|Person=1|VerbForm=Inf
+ter	ter	Number=Sing|Person=3|VerbForm=Inf
+ter	ter	VerbForm=Inf
+terdes	ter	Number=Plur|Person=2|VerbForm=Inf
+terei	ter	Mood=Ind|Number=Sing|Person=1|Tense=Fut|VerbForm=Fin
+tereis	ter	Mood=Ind|Number=Plur|Person=2|Tense=Fut|VerbForm=Fin
+terem	ter	Number=Plur|Person=3|VerbForm=Inf
+teremos	ter	Mood=Ind|Number=Plur|Person=1|Tense=Fut|VerbForm=Fin
+teres	ter	Number=Sing|Person=2|VerbForm=Inf
+teria	ter	Mood=Cnd|Number=Sing|Person=1|VerbForm=Fin
+teria	ter	Mood=Cnd|Number=Sing|Person=3|VerbForm=Fin
+teriam	ter	Mood=Cnd|Number=Plur|Person=3|VerbForm=Fin
+terias	ter	Mood=Cnd|Number=Sing|Person=2|VerbForm=Fin
+termos	ter	Number=Plur|Person=1|VerbForm=Inf
+terá	ter	Mood=Ind|Number=Sing|Person=3|Tense=Fut|VerbForm=Fin
+terás	ter	Mood=Ind|Number=Sing|Person=2|Tense=Fut|VerbForm=Fin
+terão	ter	Mood=Ind|Number=Plur|Person=3|Tense=Fut|VerbForm=Fin
+teríamos	ter	Mood=Cnd|Number=Plur|Person=1|VerbForm=Fin
+teríeis	ter	Mood=Cnd|Number=Plur|Person=2|VerbForm=Fin
+teve	ter	Mood=Ind|Number=Sing|Person=3|Tense=Past|VerbForm=Fin
+tida	ter	Gender=Fem|Number=Sing|VerbForm=Part
+tidas	ter	Gender=Fem|Number=Plur|VerbForm=Part
+tido	ter	Gender=Masc|Number=Sing|VerbForm=Part
+tidos	ter	Gender=Masc|Number=Plur|VerbForm=Part
+tinha	ter	Mood=Ind|Number=Sing|Person=1|Tense=Imp|VerbForm=Fin
+tinha	ter	Mood=Ind|Number=Sing|Person=3|Tense=Imp|VerbForm=Fin
+tinham	ter	Mood=Ind|Number=Plur|Person=3|Tense=Imp|VerbForm=Fin
+tinhas:	ter	Mood=Ind|Number=Sing|Person=2|Tense=Imp|VerbForm=Fin
+tive	ter	Mood=Ind|Number=Sing|Person=1|Tense=Past|VerbForm=Fin
+tivemos	ter	Mood=Ind|Number=Plur|Person=1|Tense=Past|VerbForm=Fin
+tiver	ter	Mood=Sub|Number=Sing|Person=1|Tense=Fut|VerbForm=Fin
+tiver	ter	Mood=Sub|Number=Sing|Person=3|Tense=Fut|VerbForm=Fin
+tivera	ter	Mood=Ind|Number=Sing|Person=1|Tense=Pqp|VerbForm=Fin
+tivera	ter	Mood=Ind|Number=Sing|Person=3|Tense=Pqp|VerbForm=Fin
+tiveram	ter	Mood=Ind|Number=Plur|Person=3|Tense=Past|VerbForm=Fin
+tiveram	ter	Mood=Ind|Number=Plur|Person=3|Tense=Pqp|VerbForm=Fin
+tiveras	ter	Mood=Ind|Number=Sing|Person=2|Tense=Pqp|VerbForm=Fin
+tiverdes	ter	Mood=Sub|Number=Plur|Person=2|Tense=Fut|VerbForm=Fin
+tiverem	ter	Mood=Sub|Number=Plur|Person=3|Tense=Fut|VerbForm=Fin
+tiveres	ter	Mood=Sub|Number=Sing|Person=2|Tense=Fut|VerbForm=Fin
+tivermos	ter	Mood=Sub|Number=Plur|Person=1|Tense=Fut|VerbForm=Fin
+tivesse	ter	Mood=Sub|Number=Sing|Person=1|Tense=Past|VerbForm=Fin
+tivesse	ter	Mood=Sub|Number=Sing|Person=3|Tense=Past|VerbForm=Fin
+tivessem	ter	Mood=Sub|Number=Plur|Person=3|Tense=Past|VerbForm=Fin
+tivesses	ter	Mood=Sub|Number=Sing|Person=2|Tense=Past|VerbForm=Fin
+tiveste	ter	Mood=Ind|Number=Sing|Person=2|Tense=Past|VerbForm=Fin
+tivestes	ter	Mood=Ind|Number=Plur|Person=2|Tense=Past|VerbForm=Fin
+tivéramos	ter	Mood=Ind|Number=Plur|Person=1|Tense=Pqp|VerbForm=Fin
+tivéreis	ter	Mood=Ind|Number=Plur|Person=2|Tense=Pqp|VerbForm=Fin
+tivésseis	ter	Mood=Sub|Number=Plur|Person=2|Tense=Past|VerbForm=Fin
+tivéssemos	ter	Mood=Sub|Number=Plur|Person=1|Tense=Past|VerbForm=Fin
+tá	estar	Abbr=Yes|Mood=Ind|Number=Sing|Person=3|Tense=Pres|VerbForm=Fin
+tão	estar	Abbr=Yes|Abbr=Yes|Mood=Ind|Number=Plur|Person=3|Tense=Pres|VerbForm=Fin
+têm	ter	Mood=Ind|Number=Plur|Person=3|Tense=Pres|VerbForm=Fin
+tínhamos	ter	Mood=Ind|Number=Plur|Person=1|Tense=Imp|VerbForm=Fin
+tínheis	ter	Mood=Ind|Number=Plur|Person=2|Tense=Imp|VerbForm=Fin
+tô	estar	Abbr=Yes|Mood=Ind|Number=Sing|Person=1|Tense=Pres|VerbForm=Fin
+vades	ir	Mood=Sub|Number=Plur|Person=2|Tense=Pres|VerbForm=Fin
+vai	ir	Mood=Imp|Number=Sing|Person=2|VerbForm=Fin
+vai	ir	Mood=Ind|Number=Sing|Person=3|Tense=Pres|VerbForm=Fin
+vais	ir	Mood=Ind|Number=Sing|Person=2|Tense=Pres|VerbForm=Fin
+vamo	ir	Abbr=Yes|Mood=Imp|Number=Plur|Person=1|VerbForm=Fin
+vamo	ir	Abbr=Yes|Mood=Ind|Number=Plur|Person=1|Tense=Pres|VerbForm=Fin
+vamo	ir	Abbr=Yes|Mood=Sub|Number=Plur|Person=1|Tense=Pres|VerbForm=Fin
+vamos	ir	Mood=Imp|Number=Plur|Person=1|VerbForm=Fin
+vamos	ir	Mood=Ind|Number=Plur|Person=1|Tense=Pres|VerbForm=Fin
+vamos	ir	Mood=Sub|Number=Plur|Person=1|Tense=Pres|VerbForm=Fin
+veio	vir	Mood=Ind|Number=Sing|Person=3|Tense=Past|VerbForm=Fin
+vem	vir	Mood=Imp|Number=Sing|Person=2|VerbForm=Fin
+vem	vir	Mood=Ind|Number=Sing|Person=3|Tense=Pres|VerbForm=Fin
+venha	vir	Mood=Imp|Number=Sing|Person=3|VerbForm=Fin
+venha	vir	Mood=Sub|Number=Sing|Person=1|Tense=Pres|VerbForm=Fin
+venha	vir	Mood=Sub|Number=Sing|Person=3|Tense=Pres|VerbForm=Fin
+venhais	vir	Mood=Sub|Number=Plur|Person=2|Tense=Pres|VerbForm=Fin
+venham	vir	Mood=Imp|Number=Plur|Person=3|VerbForm=Fin
+venham	vir	Mood=Sub|Number=Plur|Person=3|Tense=Pres|VerbForm=Fin
+venhamos	vir	Mood=Imp|Number=Plur|Person=1|VerbForm=Fin
+venhamos	vir	Mood=Sub|Number=Plur|Person=1|Tense=Pres|VerbForm=Fin
+venhas	vir	Mood=Sub|Number=Sing|Person=2|Tense=Pres|VerbForm=Fin
+venho	vir	Mood=Ind|Number=Sing|Person=1|Tense=Pres|VerbForm=Fin
+vens:	vir	Mood=Ind|Number=Sing|Person=2|Tense=Pres|VerbForm=Fin
+viemos	vir	Mood=Ind|Number=Plur|Person=1|Tense=Past|VerbForm=Fin
+vier	vir	Mood=Sub|Number=Sing|Person=1|Tense=Fut|VerbForm=Fin
+vier	vir	Mood=Sub|Number=Sing|Person=3|Tense=Fut|VerbForm=Fin
+viera	vir	Mood=Ind|Number=Sing|Person=1|Tense=Pqp|VerbForm=Fin
+viera	vir	Mood=Ind|Number=Sing|Person=3|Tense=Pqp|VerbForm=Fin
+vieram	vir	Mood=Ind|Number=Plur|Person=3|Tense=Past|VerbForm=Fin
+vieram	vir	Mood=Ind|Number=Plur|Person=3|Tense=Pqp|VerbForm=Fin
+vieras	vir	Mood=Ind|Number=Sing|Person=2|Tense=Pqp|VerbForm=Fin
+vierdes	vir	Mood=Sub|Number=Plur|Person=2|Tense=Fut|VerbForm=Fin
+vierem	vir	Mood=Sub|Number=Plur|Person=3|Tense=Fut|VerbForm=Fin
+vieres	vir	Mood=Sub|Number=Sing|Person=2|Tense=Fut|VerbForm=Fin
+viermos	vir	Mood=Sub|Number=Plur|Person=1|Tense=Fut|VerbForm=Fin
+viesse	vir	Mood=Sub|Number=Sing|Person=1|Tense=Past|VerbForm=Fin
+viesse	vir	Mood=Sub|Number=Sing|Person=3|Tense=Past|VerbForm=Fin
+viessem	vir	Mood=Sub|Number=Plur|Person=3|Tense=Past|VerbForm=Fin
+viesses	vir	Mood=Sub|Number=Sing|Person=2|Tense=Past|VerbForm=Fin
+vieste	vir	Mood=Ind|Number=Sing|Person=2|Tense=Past|VerbForm=Fin
+viestes	vir	Mood=Ind|Number=Plur|Person=2|Tense=Past|VerbForm=Fin
+vim	vir	Mood=Ind|Number=Sing|Person=1|Tense=Past|VerbForm=Fin
+vimos	vir	Mood=Ind|Number=Plur|Person=1|Tense=Pres|VerbForm=Fin
+vinda	vir	Gender=Fem|Number=Sing|VerbForm=Part
+vindas	vir	Gender=Fem|Number=Plur|VerbForm=Part
+vinde	vir	Mood=Imp|Number=Plur|Person=2|VerbForm=Fin
+vindes	vir	Mood=Ind|Number=Plur|Person=2|Tense=Pres|VerbForm=Fin
+vindo	vir	Gender=Masc|Number=Sing|VerbForm=Part
+vindo	vir	VerbForm=Ger
+vindos	vir	Gender=Masc|Number=Plur|VerbForm=Part
+vinha	vir	Mood=Ind|Number=Sing|Person=1|Tense=Imp|VerbForm=Fin
+vinha	vir	Mood=Ind|Number=Sing|Person=3|Tense=Imp|VerbForm=Fin
+vinham	vir	Mood=Ind|Number=Plur|Person=3|Tense=Imp|VerbForm=Fin
+vinhas:	vir	Mood=Ind|Number=Sing|Person=2|Tense=Imp|VerbForm=Fin
+vir	vir	Number=Sing|Person=1|VerbForm=Inf
+vir	vir	Number=Sing|Person=3|VerbForm=Inf
+vir	vir	VerbForm=Inf
+virdes	vir	Number=Plur|Person=2|VerbForm=Inf
+virei	vir	Mood=Ind|Number=Sing|Person=1|Tense=Fut|VerbForm=Fin
+vireis	vir	Mood=Ind|Number=Plur|Person=2|Tense=Fut|VerbForm=Fin
+virem	vir	Number=Plur|Person=3|VerbForm=Inf
+viremos	vir	Mood=Ind|Number=Plur|Person=1|Tense=Fut|VerbForm=Fin
+vires	vir	Number=Sing|Person=2|VerbForm=Inf
+viria	vir	Mood=Cnd|Number=Sing|Person=1|VerbForm=Fin
+viria	vir	Mood=Cnd|Number=Sing|Person=3|VerbForm=Fin
+viriam	vir	Mood=Cnd|Number=Plur|Person=3|VerbForm=Fin
+virias	vir	Mood=Cnd|Number=Sing|Person=2|VerbForm=Fin
+virmos	vir	Number=Plur|Person=1|VerbForm=Inf
+virá	vir	Mood=Ind|Number=Sing|Person=3|Tense=Fut|VerbForm=Fin
+virás	vir	Mood=Ind|Number=Sing|Person=2|Tense=Fut|VerbForm=Fin
+virão	vir	Mood=Ind|Number=Plur|Person=3|Tense=Fut|VerbForm=Fin
+viríamos	vir	Mood=Cnd|Number=Plur|Person=1|VerbForm=Fin
+viríeis	vir	Mood=Cnd|Number=Plur|Person=2|VerbForm=Fin
+viéramos	vir	Mood=Ind|Number=Plur|Person=1|Tense=Pqp|VerbForm=Fin
+viéreis	vir	Mood=Ind|Number=Plur|Person=2|Tense=Pqp|VerbForm=Fin
+viésseis	vir	Mood=Sub|Number=Plur|Person=2|Tense=Past|VerbForm=Fin
+viéssemos	vir	Mood=Sub|Number=Plur|Person=1|Tense=Past|VerbForm=Fin
+vou	ir	Mood=Ind|Number=Sing|Person=1|Tense=Pres|VerbForm=Fin
+vá	ir	Mood=Imp|Number=Sing|Person=3|VerbForm=Fin
+vá	ir	Mood=Sub|Number=Sing|Person=1|Tense=Pres|VerbForm=Fin
+vá	ir	Mood=Sub|Number=Sing|Person=3|Tense=Pres|VerbForm=Fin
+vás	ir	Mood=Sub|Number=Sing|Person=2|Tense=Pres|VerbForm=Fin
+vão	ir	Mood=Imp|Number=Plur|Person=3|VerbForm=Fin
+vão	ir	Mood=Ind|Number=Plur|Person=3|Tense=Pres|VerbForm=Fin
+vão	ir	Mood=Sub|Number=Plur|Person=3|Tense=Pres|VerbForm=Fin
+vêm	vir	Mood=Ind|Number=Plur|Person=3|Tense=Pres|VerbForm=Fin
+vínhamos	vir	Mood=Ind|Number=Plur|Person=1|Tense=Imp|VerbForm=Fin
+vínheis	vir	Mood=Ind|Number=Plur|Person=2|Tense=Imp|VerbForm=Fin
+é	ser	Mood=Ind|Number=Sing|Person=3|Tense=Pres|VerbForm=Fin
+éramos	ser	Mood=Ind|Number=Plur|Person=1|Tense=Imp|VerbForm=Fin
+éreis	ser	Mood=Ind|Number=Plur|Person=2|Tense=Imp|VerbForm=Fin
+és	ser	Mood=Ind|Number=Sing|Person=2|Tense=Pres|VerbForm=Fin
+íamos	ir	Mood=Ind|Number=Plur|Person=1|Tense=Imp|VerbForm=Fin
+íeis	ir	Mood=Ind|Number=Plur|Person=2|Tense=Imp|VerbForm=Fin

src/portTokenizer/CCONJ.tsv

@@ -0,0 +1,25 @@
+como	como	_
+contudo	contudo	_
+e	e	_
+enquanto	enquanto	_
+entretanto	entretanto	_
+então	então	_
+já	já	_
+logo	logo	_
+mas	mas	_
+nem	nem	_
+ora	ora	_
+ou	ou	_
+pois	pois	_
+porquanto	porquanto	_
+porque	porque	_
+portanto	portanto	_
+porém	porém	_
+quando	quando	_
+quanto	quanto	_
+que	que	_
+quer	quer	_
+seja	seja	_
+senão	senão	_
+tanto	tanto	_
+todavia	todavia	_