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test feature extractor speed
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@ -6,12 +6,12 @@ export PROTOCOL_BUFFERS_PYTHON_IMPLEMENTATION=python
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set -eou pipefail
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nj=15
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stage=0
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stop_stage=100
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stage=130
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stop_stage=130
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# Split L subset to this number of pieces
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# This is to avoid OOM during feature extraction.
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num_splits=1000
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num_splits=100
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# We assume dl_dir (download dir) contains the following
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# directories and files. If not, they will be downloaded
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@ -198,8 +198,8 @@ if [ $stage -le 130 ] && [ $stop_stage -ge 130 ]; then
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python3 ./local/compute_fbank_wenetspeech_splits.py \
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--training-subset L \
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--num-workers 20 \
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--batch-duration 600 \
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--num-workers 40 \
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--batch-duration 1600 \
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--start 0 \
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--num-mel-bins ${whisper_mel_bins} --whisper-fbank true \
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--num-splits $num_splits
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@ -210,6 +210,19 @@ if [ $stage -le 130 ] && [ $stop_stage -ge 130 ]; then
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fi
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fi
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if [ $stage -le 131 ] && [ $stop_stage -ge 131 ]; then
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log "Stage 131: test"
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python3 ./local/compute_fbank_wenetspeech_splits.py \
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--training-subset L \
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--num-workers 40 \
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--batch-duration 1600 \
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--start 99 \
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--num-mel-bins ${whisper_mel_bins} --whisper-fbank false \
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--num-splits $num_splits
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fi
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if [ $stage -le 14 ] && [ $stop_stage -ge 14 ]; then
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log "Stage 14: Compute fbank for musan"
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mkdir -p data/fbank
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