fix: change model_dir to training job name if it is for tuning. #179
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laurenyu
reviewed
Apr 12, 2019
| @@ -192,6 +192,10 @@ def main(): | |||
| """ | |||
| hyperparameters = framework.env.read_hyperparameters() | |||
| env = framework.training_env(hyperparameters=hyperparameters) | |||
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| if '_tuning_objective_metric' in hyperparameters: | |||
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I'd add a comment similar to https://github.com/aws/sagemaker-tensorflow-container/blob/master/src/tf_container/train_entry_point.py#L118-L119 about why we have this logic
| @@ -192,6 +192,10 @@ def main(): | |||
| """ | |||
| hyperparameters = framework.env.read_hyperparameters() | |||
| env = framework.training_env(hyperparameters=hyperparameters) | |||
|
|
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| if '_tuning_objective_metric' in hyperparameters: | |||
| env.hyperparameters['model_dir'] = env.job_name | |||
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I think we should probably append env.job_name to the original model_dir rather than replacing the original value entirely. (the old version appended to checkpoint_path)
Elizaaaaa
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to Elizaaaaa/sagemaker-tensorflow-container
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Nov 4, 2019
Elizaaaaa
pushed a commit
to Elizaaaaa/sagemaker-tensorflow-container
that referenced
this pull request
Nov 4, 2019
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Issue #, if available:
Description of changes:
Change model_dir to training job name if this training job is part of tuning job.
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