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30 lines
1003 B
Python
30 lines
1003 B
Python
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# TRAINS - Example of manual model configuration
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#
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import torch
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from trains import Task
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task = Task.init(project_name='examples', task_name='Manual model configuration')
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# create a model
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model = torch.nn.Module
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# store dictionary of definition for a specific network design
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model_config_dict = {
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'value': 13.37,
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'dict': {'sub_value': 'string'},
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'list_of_ints': [1, 2, 3, 4],
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}
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task.set_model_config(config_dict=model_config_dict)
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# or read form a config file (this will override the previous configuration dictionary)
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# task.set_model_config(config_text='this is just a blob\nof text from a configuration file')
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# store the label enumeration the model is training for
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task.set_model_label_enumeration({'background': 0, 'cat': 1, 'dog': 2})
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print('Any model stored from this point onwards, will contain both model_config and label_enumeration')
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# storing the model, it will have the task network configuration and label enumeration
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torch.save(model, '/tmp/model')
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print('Model saved')
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