@@ -301,7 +301,7 @@ def end_trial(self, trial_id: Text, status: Text = "COMPLETED"):
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def get_best_trials (self , num_trials : int = 1 ) -> List [trial_module .Trial ]:
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"""Returns the trials with the best objective values found so far.
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- Arguments :
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+ Args :
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num_trials: positive int, number of trials to return.
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Returns:
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List of KerasTuner Trials.
@@ -509,7 +509,7 @@ def run_trial(self, trial, *fit_args, **fit_kwargs):
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This method is called during `search` to evaluate a set of
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hyperparameters using AI Platform training.
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- Arguments :
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+ Args :
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trial: A `Trial` instance that contains the information
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needed to run this trial. `Hyperparameters` can be accessed
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via `trial.hyperparameters`.
@@ -643,7 +643,7 @@ def run_trial(self, trial, *fit_args, **fit_kwargs):
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def _get_job_spec_from_config (self , job_id : Text ) -> Dict [Text , Any ]:
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"""Creates a request dictionary for the CAIP training service.
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- Arguments :
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+ Args :
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job_id: Job name that will be used for AIP training
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Returns:
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An AI Platform Training job spec.
@@ -688,7 +688,7 @@ def _get_remote_training_metrics(
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All complete epochs metrics (including the last epoch if applicable) are
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returned as training_metrics.
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- Arguments :
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+ Args :
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log_reader: An instance of tensorboard DirectoryWatcher that is
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pointing to the tensorboard logs directory.
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partial_epoch_metrics: Any incomplete epoch metrics from previous
@@ -749,7 +749,7 @@ def _add_logging(self, callbacks, trial):
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TensorBoard callback to pass back the epoch related metrics from
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remote execution.
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- Arguments :
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+ Args :
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callbacks: List of callbacks passed in to the search function.
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trial: A `Trial` instance.
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Raises:
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