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74 lines
2.9 KiB
Markdown
74 lines
2.9 KiB
Markdown
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---
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title: Hyperparameters Reporting
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---
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The [hyper_parameters.py](https://github.com/allegroai/clearml/blob/master/examples/reporting/hyper_parameters.py) example
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script demonstrates:
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* **ClearML**'s automatic logging of `argparse` command line options and TensorFlow Definitions
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* Logging user-defined hyperparameters with a parameter dictionary and connecting the dictionary to a Task.
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Hyperparameters appear in the **web UI** in the experiment's page, under **CONFIGURATIONS** **>** **HYPER PARAMETERS**.
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Each type is in its own subsection. Parameters from older experiments are grouped together with the ``argparse`` command
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line options (in the **Args** subsection).
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When the script runs, it creates an experiment named `hyper-parameters example`, which is associated with the `examples` project.
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## argparse command line options
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If a code uses argparse and initializes a Task, **ClearML** automatically logs the argparse arguments.
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parser = ArgumentParser()
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parser.add_argument('--argparser_int_value', help='integer value', type=int, default=1)
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parser.add_argument('--argparser_disabled', action='store_true', default=False, help='disables something')
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parser.add_argument('--argparser_str_value', help='string value', default='a string')
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args = parser.parse_args()
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Command line options appears in **HYPER PARAMETERS** **>** **Args**.
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## TensorFlow Definitions
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**ClearML** automatically logs TensorFlow Definitions, whether they are defined before or after the Task is initialized.
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flags.DEFINE_string('echo', None, 'Text to echo.')
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flags.DEFINE_string('another_str', 'My string', 'A string', module_name='test')
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task = Task.init(project_name='examples', task_name='hyper-parameters example')
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flags.DEFINE_integer('echo3', 3, 'Text to echo.')
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flags.DEFINE_string('echo5', '5', 'Text to echo.', module_name='test')
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TensorFlow Definitions appear in **HYPER PARAMETERS** **>** **TF_DEFINE**.
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## Parameter dictionaries
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Connect a parameter dictionary to a Task by calling the [Task.connect](../../references/sdk/task.md#connect)
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method, and **ClearML** logs the parameters. **ClearML** also tracks changes to the parameters.
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parameters = {
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'list': [1, 2, 3],
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'dict': {'a': 1, 'b': 2},
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'tuple': (1, 2, 3),
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'int': 3,
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'float': 2.2,
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'string': 'my string',
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}
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parameters = task.connect(parameters)
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# adding new parameter after connect (will be logged as well)
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parameters['new_param'] = 'this is new'
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# changing the value of a parameter (new value will be stored instead of previous one)
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parameters['float'] = '9.9'
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Parameters from dictionaries connected to Tasks appear in **HYPER PARAMETERS** **>** **General**.
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