Command line arguments

Usage for model files being run with ExperimentBuilder.

usage: <model_file>.py [-h] [--model_kwargs MODEL_KWARGS] [--train] [--valid]
                       [--test] [--start_epoch START_EPOCH]
                       [--end_epoch END_EPOCH]
                       [--checkpoint_path CHECKPOINT_PATH]
                       [--ema_checkpoint_path EMA_CHECKPOINT_PATH]
                       [--batch_size BATCH_SIZE]
                       [--learning_rate LEARNING_RATE]
                       [--lr_schedule_name LR_SCHEDULE_NAME]
                       [--lr_schedule_kwargs LR_SCHEDULE_KWARGS]
                       [--weight_decay WEIGHT_DECAY] [--ema_decay EMA_DECAY]
                       [--num_data_threads NUM_DATA_THREADS]
                       [--model_checkpoint_interval MODEL_CHECKPOINT_INTERVAL]
                       [--train_output_interval TRAIN_OUTPUT_INTERVAL]
                       [--valid_output_interval VALID_OUTPUT_INTERVAL]
                       [--test_output_interval TEST_OUTPUT_INTERVAL]
                       [--data_root DATA_ROOT] [--train_dir TRAIN_DIR]
                       [--valid_dir VALID_DIR] [--test_dir TEST_DIR]
                       [--train_id_list TRAIN_ID_LIST]
                       [--valid_id_list VALID_ID_LIST]
                       [--test_id_list TEST_ID_LIST]
                       [--normalisation_dir NORMALISATION_DIR]
                       [--experiments_base EXPERIMENTS_BASE] --experiment_name
                       EXPERIMENT_NAME [--sample_rate SAMPLE_RATE]

Named Arguments

--model_kwargs

Settings for the model, a Python dictionary written in quotes.

Default: {}

--train

If True, model will be trained for –num_epochs on –train_id_list.

Default: True

--valid

If True, model will be evaluated on –valid_id_list every epoch.

Default: True

--test

If True, generation for –test_id_list will be performed after training.

Default: False

--start_epoch

The epoch number to start training at (will effect checkpoint saves).

Default: 1

--end_epoch

Epoch to end training at.

Default: 50

--checkpoint_path

If specified, the model will first load parameters from an existing checkpoint.

--ema_checkpoint_path

If specified, the EMA model will first load parameters from an existing checkpoint.

--batch_size

Batch size used for iteration over train/valid data.

Default: 32

--learning_rate

Learning rate for Adam optimiser to use during training.

Default: 0.01

--lr_schedule_name

Learning rate schedule to use during training.

Default: “constant”

--lr_schedule_kwargs

Settings for learning rate schedule, a Python dictionary written in quotes.

Default: {}

--weight_decay

L2 regularisation weight, default of 0 indication no L2 loss term.

Default: 0.0

--ema_decay

If not 0, track exponential moving average of model parameters, used for generation.

Default: 0.0

--num_data_threads

Number of threads used to load the data with.

Default: 1

--model_checkpoint_interval

The number of epochs to wait between saving the model.

Default: 1

--train_output_interval

The number of epochs to wait between generating output for training data.

Default: 10

--valid_output_interval

The number of epochs to wait between generating output for validation data.

Default: 10

--test_output_interval

The number of epochs to wait between generating output for test data.

Default: 10

--data_root

Base directory containing all data.

Default: “data”

--train_dir

Name of the sub-directory in –data_root containing training data.

Default: “train”

--valid_dir

Name of the sub-directory in –data_root containing validation data.

Default: “valid”

--test_dir

Name of the sub-directory in –data_root containing test data.

Default: “test”

--train_id_list

File name in –train_dir containing basenames of training samples.

Default: “train_file_id_list.scp”

--valid_id_list

File name in –valid_dir containing basenames of validation samples.

Default: “valid_file_id_list.scp”

--test_id_list

File name in –test_dir containing basenames of test files.

Default: “test_file_id_list.scp”

--normalisation_dir

Name of the sub-directory in –data_root containing normalisation data.

Default: “train”

--experiments_base

Base directory where all experiments direct their output.

Default: “experiments”

--experiment_name

Name of the sub-directory in –output_dir used for any output.

--sample_rate

Sample rate of the waveforms generated.

Default: 16000