Hyperparameters Reporting

The example hyper_parameters.py demonstrates Trains automatic logging of argparse command line options and TensorFlow DEFINEs, and defining your own hyperparameters, using a parameter dictionary and connecting it to a Task. Parameters from older experiments are grouped together with the argparse command line options.

Hyperparameters appear in CONFIGURATIONS > HYPER PARAMETERS. Each type is in its own subsection.

When the script runs, it creates an experiment named hyper-parameters example, which is associated with the examples project.

argparse command line options

If code uses argparse and initialized a Task, Trains automatically logs the argparse arguments.

parser = ArgumentParser()
parser.add_argument('--argparser_int_value', help='integer value', type=int, default=1)
parser.add_argument('--argparser_disabled', action='store_true', default=False, help='disables something')
parser.add_argument('--argparser_str_value', help='string value', default='a string')

args = parser.parse_args()

Command line options appears in HYPER PARAMETERS > Args.

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TensorFlow DEFINEs

Trains automatically logs TensorFlow DEFINES, whether they are defined before or after the Task is initialized.

flags.DEFINE_string('echo', None, 'Text to echo.')
flags.DEFINE_string('another_str', 'My string', 'A string', module_name='test')

task = Task.init(project_name='examples', task_name='hyper-parameters example')

flags.DEFINE_integer('echo3', 3, 'Text to echo.')

flags.DEFINE_string('echo5', '5', 'Text to echo.', module_name='test')

TensorFlow DEFINEs appear in HYPER PARAMETERS > TF_DEFINE.

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Parameter dictionaries

Connect a parameter dictionary to a Task by calling the Task.connect method, and Trains logs the parameters. Trains also tracks changes to the parameters.

parameters = {
    'list': [1, 2, 3],
    'dict': {'a': 1, 'b': 2},
    'tuple': (1, 2, 3),
    'int': 3,
    'float': 2.2,
    'string': 'my string',
}

parameters = task.connect(parameters)

# adding new parameter after connect (will be logged as well)
parameters['new_param'] = 'this is new'

# changing the value of a parameter (new value will be stored instead of previous one)
parameters['float'] = '9.9'

Parameters from dictionaries connected to Tasks appear in HYPER PARAMETERS > General.

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