def _predict_input_fn(params):
     dataset = table_dataset_test_utils.create_random_dataset(
         num_examples=params["batch_size"],
         batch_size=params["batch_size"],
         repeat=True,
         generator_kwargs=generator_kwargs)
     return dataset.take(2)
예제 #2
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 def _input_fn(params):
     return table_dataset_test_utils.create_random_dataset(
         num_examples=params['batch_size'] * 2,
         batch_size=params['batch_size'],
         repeat=False,
         generator_kwargs=self._generator_kwargs(
             add_aggregation_function_id=do_model_aggregation,
             add_classification_labels=do_model_classification,
         ))
예제 #3
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 def _input_fn(params):
     return table_dataset_test_utils.create_random_dataset(
         num_examples=params['batch_size'] * 2,
         batch_size=params['batch_size'],
         repeat=False,
         generator_kwargs=self._generator_kwargs())
예제 #4
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 def _input_fn(params):
     return table_dataset_test_utils.create_random_dataset(
         num_examples=params["batch_size"],
         batch_size=params["batch_size"],
         repeat=False,
         generator_kwargs=generator_kwargs)