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#!/bin/bash
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Support paddle 2.x (#538)
* 2.x model
* model test pass
* fix data
* fix soundfile with flac support
* one thread dataloader test pass
* export feasture size
add trainer and utils
add setup model and dataloader
update travis using Bionic dist
* add venv; test under venv
* fix unittest; train and valid
* add train and config
* add config and train script
* fix ctc cuda memcopy error
* fix imports
* fix train valid log
* fix dataset batch shuffle shift start from 1
fix rank_zero_only decreator error
close tensorboard when train over
add decoding config and code
* test process can run
* test with decoding
* test and infer with decoding
* fix infer
* fix ctc loss
lr schedule
sortagrad
logger
* aishell egs
* refactor train
add aishell egs
* fix dataset batch shuffle and add batch sampler log
print model parameter
* fix model and ctc
* sequence_mask make all inputs zeros, which cause grad be zero, this is a bug of LessThanOp
add grad clip by global norm
add model train test notebook
* ctc loss
remove run prefix
using ord value as text id
* using unk when training
compute_loss need text ids
ord id using in test mode, which compute wer/cer
* fix tester
* add lr_deacy
refactor code
* fix tools
* fix ci
add tune
fix gru model bugs
add dataset and model test
* fix decoding
* refactor repo
fix decoding
* fix musan and rir dataset
* refactor io, loss, conv, rnn, gradclip, model, utils
* fix ci and import
* refactor model
add export jit model
* add deploy bin and test it
* rm uselss egs
* add layer tools
* refactor socket server
new model from pretrain
* remve useless
* fix instability loss and grad nan or inf for librispeech training
* fix sampler
* fix libri train.sh
* fix doc
* add license on cpp
* fix doc
* fix libri script
* fix install
* clip 5 wer 7.39, clip 400 wer 7.54, 1.8 clip 400 baseline 7.49
4 years ago
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if [ $# != 1 ];then
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echo "usage: tune ckpt_path"
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exit 1
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fi
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# grid-search for hyper-parameters in language model
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python3 -u ${BIN_DIR}/tune.py \
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--device 'gpu' \
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--nproc 1 \
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--config conf/deepspeech2.yaml \
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--num_batches=-1 \
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--batch_size=128 \
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--beam_size=500 \
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--num_proc_bsearch=12 \
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--num_alphas=45 \
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--num_betas=8 \
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--alpha_from=1.0 \
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--alpha_to=3.2 \
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--beta_from=0.1 \
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--beta_to=0.45 \
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--cutoff_prob=1.0 \
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--cutoff_top_n=40 \
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--checkpoint_path ${1}
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if [ $? -ne 0 ]; then
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echo "Failed in tuning!"
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exit 1
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fi
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exit 0
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