hookeai.miscellaneous.pruning.pruning_dataset.set_pruning_step_dir

set_pruning_step_dir(prun_datasets_dir, train_dataset, val_dataset, test_dataset, dataset_basename='ss_paths_dataset')

Setup pruning iteration directory.

Parameters:

• prun_datasets_dir (str) – Pruned data sets directory.

• train_dataset (torch.utils.data.Dataset) – Time series training data set. Each sample is stored as a dictionary where each feature (key, str) data is a torch.Tensor(2d) of shape (sequence_length, n_features).

• val_dataset (torch.utils.data.Dataset) – Time series validation data set. Each sample is stored as a dictionary where each feature (key, str) data is a torch.Tensor(2d) of shape (sequence_length, n_features).

• test_dataset (torch.utils.data.Dataset) – Time series testing data set. Each sample is stored as a dictionary where each feature (key, str) data is a torch.Tensor(2d) of shape (sequence_length, n_features).

• dataset_basename (str, defaut='ss_paths_dataset') – Data set file base name.

Returns:

• pruning_step_dir (str) – Pruning step directory.

• model_directory (str) – Directory where model is stored.

• train_dataset_file_path (str) – Training data set file path.

• val_dataset_file_path (str) – Validation data set file path.

• test_dataset_file_path (str) – Testing data set file path.

• prediction_subdir (str) – Directory where samples predictions results files are stored.