hyperparam_reporter

class aitoolbox.experiment.result_reporting.hyperparam_reporter.HyperParamSourceReporter(project_name, experiment_name, experiment_timestamp, local_model_result_folder_path)[source]

Bases: object

Writer of selected hyperparameters to human-readable text file on disk

Parameters:
  • project_name (str) – root name of the project

  • experiment_name (str) – name of the particular experiment

  • experiment_timestamp (str) – time stamp of the training start

  • local_model_result_folder_path (str) – root local path where project folder will be created

save_hyperparams_to_text_file(hyperparams, sort_names=False)[source]

Save hyperparameters dict into text file on disk

Parameters:
  • hyperparams (dict) – hyper-parameters listed in the dict

  • sort_names (bool) – should presented hyper-param names be listed alphabetically

Returns:

path to the saved hyper-param text file

Return type:

str

copy_to_cloud_storage(local_hyperparams_file_path, cloud_saver, file_name=None)[source]

Copy saved text local file into cloud storage

Parameters:
Returns:

path where the file was saved in the cloud storage

Return type:

str

save_experiment_python_file(hyperparams)[source]

Saves the python experiment file to the project folder

Python experiment file is file in which the main training procedure is defined. File from which the TrainLoop is executed

Parameters:

hyperparams (dict) – hyper-parameters listed in the dict. In order for this function to work, the dict needs to include experiment_file_path key.

Returns:

path to the saved main python experiment file

Return type:

str

save_experiment_source_files(hyperparams)[source]

Saves all the experiment source files into single source code zip

Parameters:

hyperparams (dict) – hyper-parameters listed in the dict. In order for this function to work, the dict needs to include source_dirs_paths key.

Returns:

path to the saved experiment source code zip

Return type:

str