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When no `type` keyword argument is passed to the `add_argument` method of an `argparse.ArgumentParser`, the type will be `str` by default and therefore this does not need to be specified. |
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| .. | ||
| benchmark_nc.py | ||
| benchmark_plotter.py | ||
| enqueue.sh | ||
| gpu_usage_chart | ||
| gpu_usage_plot | ||
| import_cv.py | ||
| import_fisher.py | ||
| import_ldc93s1.py | ||
| import_librivox.py | ||
| import_swb.py | ||
| import_ted.py | ||
| import_timit.py | ||
| import_voxforge.py | ||
| job-template.sbatch | ||
| README.md | ||
| run-cluster.sh | ||
| run-fisher.sh | ||
| run-ldc93s1.sh | ||
| run-librivox.sh | ||
| run-swb.sh | ||
| run-tc-ldc93s1.sh | ||
| run-ted.sh | ||
| run-timit.sh | ||
| run-wer-automation.sh | ||
| update-website.sh | ||
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.