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#! /usr/bin/bash
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pushd ../.. > /dev/null
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# download language model
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pushd models/lm > /dev/null
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sh download_lm_en.sh
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if [ $? -ne 0 ]; then
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exit 1
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fi
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popd > /dev/null
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# evaluate model
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CUDA_VISIBLE_DEVICES=0,1,2,3,4,5,6,7 \
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python -u test.py \
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--batch_size=128 \
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--trainer_count=8 \
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--beam_size=500 \
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--num_proc_bsearch=8 \
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--num_proc_data=4 \
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--num_conv_layers=2 \
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--num_rnn_layers=3 \
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--rnn_layer_size=2048 \
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--alpha=0.36 \
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--beta=0.25 \
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--cutoff_prob=0.99 \
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--use_gru=False \
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--use_gpu=True \
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--share_rnn_weights=True \
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--test_manifest='data/librispeech/manifest.test-clean' \
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--mean_std_path='data/librispeech/mean_std.npz' \
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--vocab_path='data/librispeech/vocab.txt' \
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--model_path='checkpoints/libri/params.latest.tar.gz' \
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--lang_model_path='models/lm/common_crawl_00.prune01111.trie.klm' \
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--decoding_method='ctc_beam_search' \
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--error_rate_type='wer' \
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--specgram_type='linear'
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if [ $? -ne 0 ]; then
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echo "Failed in evaluation!"
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exit 1
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fi
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exit 0
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