chore: import upstream snapshot with attribution
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#!/bin/bash
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# Copyright 2020 Google and DeepMind.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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REPO=$PWD
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MODEL=${1:-bert-base-multilingual-cased}
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DATA_DIR=${2:-"$REPO/download/"}
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TASK='udpos'
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MAXL=128
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LANGS='af,ar,bg,de,el,en,es,et,eu,fa,fi,fr,he,hi,hu,id,it,ja,kk,ko,mr,nl,pt,ru,ta,te,th,tl,tr,ur,vi,yo,zh'
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LC=""
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if [ $MODEL == "bert-base-multilingual-cased" ]; then
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MODEL_TYPE="bert"
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elif [ $MODEL == "xlm-mlm-100-1280" ] || [ $MODEL == "xlm-mlm-tlm-xnli15-1024" ]; then
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MODEL_TYPE="xlm"
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LC=" --do_lower_case"
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elif [ $MODEL == "xlm-roberta-large" ] || [ $MODEL == "xlm-roberta-base" ]; then
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MODEL_TYPE="xlmr"
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fi
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SAVE_DIR="$DATA_DIR/${TASK}/udpos_processed_maxlen${MAXL}"
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mkdir -p $SAVE_DIR
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python3 $REPO/utils_preprocess.py \
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--data_dir $DATA_DIR/${TASK}/ \
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--task udpos_tokenize \
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--model_name_or_path $MODEL \
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--model_type $MODEL_TYPE \
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--max_len $MAXL \
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--output_dir $SAVE_DIR \
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--languages $LANGS $LC >> $SAVE_DIR/process.log
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if [ ! -f $SAVE_DIR/labels.txt ]; then
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echo "create label"
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cat $SAVE_DIR/*/*.${MODEL} | cut -f 2 | grep -v "^$" | sort | uniq > $SAVE_DIR/labels.txt
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fi
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