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Add manual model tracking example
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@ -2,7 +2,7 @@
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#
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#
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import os
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import os
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from trains import Task
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from trains import Task, OutputModel
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task = Task.init(project_name='examples', task_name='Model configuration example')
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task = Task.init(project_name='examples', task_name='Model configuration example')
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@ -31,6 +31,9 @@ model_config_dict['value'] *= model_config_dict['new value']
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labels = {'background': 0, 'cat': 1, 'dog': 2}
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labels = {'background': 0, 'cat': 1, 'dog': 2}
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task.connect_label_enumeration(labels)
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task.connect_label_enumeration(labels)
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# Manually log a local model file
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OutputModel().update_weights('my_best_model.bin')
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# storing a model: Any saved model (keras / pytorch / tensorflow / etc.)
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# storing a model: Any saved model (keras / pytorch / tensorflow / etc.)
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# will have the task network configuration and label enumeration
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# will have the task network configuration and label enumeration
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print('Any model stored from this point onwards, will contain both model_config and label_enumeration')
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print('Any model stored from this point onwards, will contain both model_config and label_enumeration')
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