| #!/bin/bash |
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| if [[ $# -ne 2 ]]; then |
| echo "Run as following:" |
| echo "./examples/roberta/preprocess_RACE.sh <race_data_folder> <output_folder>" |
| exit 1 |
| fi |
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| RACE_DATA_FOLDER=$1 |
| OUT_DATA_FOLDER=$2 |
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| |
| wget -N 'https://dl.fbaipublicfiles.com/fairseq/gpt2_bpe/encoder.json' |
| wget -N 'https://dl.fbaipublicfiles.com/fairseq/gpt2_bpe/vocab.bpe' |
| wget -N 'https://dl.fbaipublicfiles.com/fairseq/gpt2_bpe/dict.txt' |
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| SPLITS="train dev test-middle test-high" |
| INPUT_TYPES="input0 input1 input2 input3 input4" |
| for INPUT_TYPE in $INPUT_TYPES |
| do |
| for SPLIT in $SPLITS |
| do |
| echo "BPE encoding $SPLIT/$INPUT_TYPE" |
| python -m examples.roberta.multiprocessing_bpe_encoder \ |
| --encoder-json encoder.json \ |
| --vocab-bpe vocab.bpe \ |
| --inputs "$RACE_DATA_FOLDER/$SPLIT.$INPUT_TYPE" \ |
| --outputs "$RACE_DATA_FOLDER/$SPLIT.$INPUT_TYPE.bpe" \ |
| --workers 10 \ |
| --keep-empty; |
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| done |
| done |
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| for INPUT_TYPE in $INPUT_TYPES |
| do |
| LANG="input$INPUT_TYPE" |
| fairseq-preprocess \ |
| --only-source \ |
| --trainpref "$RACE_DATA_FOLDER/train.$INPUT_TYPE.bpe" \ |
| --validpref "$RACE_DATA_FOLDER/dev.$INPUT_TYPE.bpe" \ |
| --testpref "$RACE_DATA_FOLDER/test-middle.$INPUT_TYPE.bpe,$RACE_DATA_FOLDER/test-high.$INPUT_TYPE.bpe" \ |
| --destdir "$OUT_DATA_FOLDER/$INPUT_TYPE" \ |
| --workers 10 \ |
| --srcdict dict.txt; |
| done |
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| rm -rf "$OUT_DATA_FOLDER/label" |
| mkdir -p "$OUT_DATA_FOLDER/label" |
| cp "$RACE_DATA_FOLDER/train.label" "$OUT_DATA_FOLDER/label/" |
| cp "$RACE_DATA_FOLDER/dev.label" "$OUT_DATA_FOLDER/label/valid.label" |
| cp "$RACE_DATA_FOLDER/test-middle.label" "$OUT_DATA_FOLDER/label/test.label" |
| cp "$RACE_DATA_FOLDER/test-high.label" "$OUT_DATA_FOLDER/label/test1.label" |
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