chore: import upstream snapshot with attribution
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#!/bin/bash
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# Copyright (c) Facebook, Inc. and its affiliates.
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#
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# This source code is licensed under the MIT license found in the
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# LICENSE file in the root directory of this source tree.
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# data should be downloaded and processed with reprocess_RACE.py
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if [[ $# -ne 2 ]]; then
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echo "Run as following:"
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echo "./examples/roberta/preprocess_RACE.sh <race_data_folder> <output_folder>"
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exit 1
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fi
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RACE_DATA_FOLDER=$1
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OUT_DATA_FOLDER=$2
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# download bpe encoder.json, vocabulary and fairseq dictionary
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wget -N 'https://dl.fbaipublicfiles.com/fairseq/gpt2_bpe/encoder.json'
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wget -N 'https://dl.fbaipublicfiles.com/fairseq/gpt2_bpe/vocab.bpe'
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wget -N 'https://dl.fbaipublicfiles.com/fairseq/gpt2_bpe/dict.txt'
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SPLITS="train dev test-middle test-high"
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INPUT_TYPES="input0 input1 input2 input3 input4"
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for INPUT_TYPE in $INPUT_TYPES
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do
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for SPLIT in $SPLITS
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do
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echo "BPE encoding $SPLIT/$INPUT_TYPE"
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python -m examples.roberta.multiprocessing_bpe_encoder \
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--encoder-json encoder.json \
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--vocab-bpe vocab.bpe \
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--inputs "$RACE_DATA_FOLDER/$SPLIT.$INPUT_TYPE" \
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--outputs "$RACE_DATA_FOLDER/$SPLIT.$INPUT_TYPE.bpe" \
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--workers 10 \
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--keep-empty;
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done
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done
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for INPUT_TYPE in $INPUT_TYPES
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do
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LANG="input$INPUT_TYPE"
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fairseq-preprocess \
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--only-source \
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--trainpref "$RACE_DATA_FOLDER/train.$INPUT_TYPE.bpe" \
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--validpref "$RACE_DATA_FOLDER/dev.$INPUT_TYPE.bpe" \
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--testpref "$RACE_DATA_FOLDER/test-middle.$INPUT_TYPE.bpe,$RACE_DATA_FOLDER/test-high.$INPUT_TYPE.bpe" \
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--destdir "$OUT_DATA_FOLDER/$INPUT_TYPE" \
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--workers 10 \
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--srcdict dict.txt;
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done
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rm -rf "$OUT_DATA_FOLDER/label"
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mkdir -p "$OUT_DATA_FOLDER/label"
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cp "$RACE_DATA_FOLDER/train.label" "$OUT_DATA_FOLDER/label/"
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cp "$RACE_DATA_FOLDER/dev.label" "$OUT_DATA_FOLDER/label/valid.label"
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cp "$RACE_DATA_FOLDER/test-middle.label" "$OUT_DATA_FOLDER/label/test.label"
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cp "$RACE_DATA_FOLDER/test-high.label" "$OUT_DATA_FOLDER/label/test1.label"
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