2fd98de56f
Currently train.py is overloaded with many independent features. Understanding the code and what will be the result of a training call requires untangling the entire script. It's also an error prone UX. This is a first step at separating independent parts into their own scripts.
32 lines
1.1 KiB
Bash
Executable File
32 lines
1.1 KiB
Bash
Executable File
#!/bin/sh
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set -xe
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ldc93s1_dir="./data/smoke_test"
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ldc93s1_csv="${ldc93s1_dir}/ldc93s1.csv"
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epoch_count=$1
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audio_sample_rate=$2
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if [ ! -f "${ldc93s1_dir}/ldc93s1.csv" ]; then
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echo "Downloading and preprocessing LDC93S1 example data, saving in ${ldc93s1_dir}."
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python -u bin/import_ldc93s1.py ${ldc93s1_dir}
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fi;
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# Force only one visible device because we have a single-sample dataset
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# and when trying to run on multiple devices (like GPUs), this will break
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export CUDA_VISIBLE_DEVICES=0
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python -u train.py --show_progressbar false --early_stop false \
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--train_files ${ldc93s1_csv} --train_batch_size 1 \
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--feature_cache '/tmp/ldc93s1_cache' \
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--dev_files ${ldc93s1_csv} --dev_batch_size 1 \
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--test_files ${ldc93s1_csv} --test_batch_size 1 \
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--n_hidden 100 --epochs $epoch_count \
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--max_to_keep 1 --checkpoint_dir '/tmp/ckpt_bytes' \
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--learning_rate 0.001 --dropout_rate 0.05 --export_dir '/tmp/train_bytes' \
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--scorer_path 'data/smoke_test/pruned_lm.bytes.scorer' \
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--audio_sample_rate ${audio_sample_rate} \
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--bytes_output_mode true \
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--export_tflite false
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