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Reuben Morais 2fd98de56f Split train.py into separate modules 
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.
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compare_samples.py
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data_set_tool.py
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graphdef_binary_to_text.py
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import_aidatatang.py
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import_aishell.py
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import_ccpmf.py
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import_cv2.py
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import_cv.py
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import_fisher.py
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import_freestmandarin.py
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import_gram_vaani.py
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import_librivox.py
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import_lingua_libre.py
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import_mls_english.py
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import_primewords.py
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import_slr57.py
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import_swb.py
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import_ted.py
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import_timit.py
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import_tuda.py
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import_vctk.py
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import_voxforge.py
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ops_in_graph.py
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play.py
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README.rst
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run-ci-graph_augmentations.sh
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run-ci-ldc93s1_checkpoint_bytes.sh
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run-ci-ldc93s1_checkpoint.sh
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run-ci-ldc93s1_new_bytes_tflite.sh
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run-ci-ldc93s1_new_metrics.sh
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run-ci-ldc93s1_new_sdb_csv.sh
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run-ci-ldc93s1_new_sdb.sh
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run-ci-ldc93s1_new.sh
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run-ci-ldc93s1_singleshotinference.sh
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run-ci-ldc93s1_tflite.sh
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run-ci-sample_augmentations.sh
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run-ci-transfer.sh
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run-ldc93s1.py
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run-ldc93s1.sh
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README.rst 

Utility scripts
===============

This folder contains scripts that can be used to do training on the various included importers from the command line. This is useful to be able to run training without a browser open, or unattended on a remote machine. They should be run from the base directory of the repository. Note that the default settings assume a very well-specified machine. In the situation that out-of-memory errors occur, you may find decreasing the values of ``--train_batch_size``\ , ``--dev_batch_size`` and ``--test_batch_size`` will allow you to continue, at the expense of speed.