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56 lines
2.5 KiB
Markdown
56 lines
2.5 KiB
Markdown
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---
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title: Configuring Models
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---
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The [model_config.py](https://github.com/allegroai/clearml/blob/master/examples/reporting/model_config.py) example demonstrates
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configuring a model and defining label enumeration. Connect the configuration and label enumeration to a Task and, once
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connected, **ClearML** tracks any changes to them. When **ClearML** stores a model, in any framework, **ClearML** stores
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the configuration and label enumeration with it.
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When the script runs, it creates an experiment named `Model configuration example`, which is associated with the `examples` project.
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## Configuring models
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### Using a configuration file
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Connect a configuration file to a Task by calling the [Task.connect_configuration](../../references/sdk/task.md#connect_configuration)
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method with the file as an argument.
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# Connect a local configuration file
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config_file = os.path.join('data_samples', 'sample.json')
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config_file = task.connect_configuration(config_file)
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**ClearML** reports the configuration in the **ClearML Web UI**, experiment details, **CONFIGURATION** tab, **CONFIGURATION OBJECTS**
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area. See the image in the next section.
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### Configuration dictionary
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Connect a configuration dictionary to a Task by creating a dictionary, and then calling the [Task.connect_configuration](../../references/sdk/task.md#connect_configuration)
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method with the dictionary as an argument. After the configuration is connected, **ClearML** tracks changes to it.
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model_config_dict = {
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'value': 13.37,
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'dict': {'sub_value': 'string', 'sub_integer': 11},
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'list_of_ints': [1, 2, 3, 4],
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}
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model_config_dict = task.connect_configuration(model_config_dict)
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# We now update the dictionary after connecting it, and the changes will be tracked as well.
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model_config_dict['new value'] = 10
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model_config_dict['value'] *= model_config_dict['new value']
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**ClearML** reports the configuration in the **ClearML Web UI** **>** experiment details **>** **CONFIGURATION** tab **>**
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**CONFIGURATION OBJECTS** area.
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## Label enumeration
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Connect a label enumeration dictionary by creating the dictionary, and then calling the [Task.connect_label_enumeration](../../references/sdk/task.md#connect_label_enumeration)
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method with the dictionary as an argument.
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# store the label enumeration of the training model
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labels = {'background': 0, 'cat': 1, 'dog': 2}
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task.connect_label_enumeration(labels)
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