| /external/tensorflow/tensorflow/python/keras/engine/ |
| D | training_generator_v1.py | 44 steps_per_epoch=None, argument
125 steps_per_epoch = kwargs['steps']
134 if steps_per_epoch is None:
136 steps_per_epoch = training_utils_v1.infer_steps_for_dataset(
137 model, data, steps_per_epoch, epochs=epochs, steps_name=steps_name)
140 generator, steps_per_epoch = convert_to_generator_like(
142 steps_per_epoch=steps_per_epoch,
150 steps_per_epoch, validation_data, validation_steps, mode,
167 data, steps_per_epoch)
175 steps_per_epoch=steps_per_epoch,
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| D | training_arrays_v1.py | 59 steps_per_epoch=None, argument
127 steps_per_epoch = kwargs.pop('steps')
140 if steps_per_epoch is None:
142 steps_per_epoch = training_utils_v1.infer_steps_for_dataset(
143 model, inputs, steps_per_epoch, epochs=epochs, steps_name=steps_name)
153 use_steps = is_dataset or steps_per_epoch is not None
172 steps_per_epoch)
174 num_samples_or_steps = steps_per_epoch
223 steps_per_epoch=steps_per_epoch,
241 num_samples=None if steps_per_epoch else num_samples_or_steps,
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| D | training_distributed_v1.py | 129 steps_per_epoch=None, argument
167 iteration_value = min(steps_per_epoch,
209 steps_per_epoch=steps_per_epoch,
216 (steps_per_epoch //
218 if steps_per_epoch % current_strategy.extended.steps_per_run:
220 steps_per_epoch % current_strategy.extended.steps_per_run)
248 steps_per_epoch * epochs)
368 steps_per_epoch=steps,
510 steps_per_epoch=steps,
596 steps_per_epoch=None, argument
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| D | training_generator_test.py | 109 steps_per_epoch=5,
116 steps_per_epoch=5,
122 steps_per_epoch=5,
130 steps_per_epoch=5,
211 steps_per_epoch=5,
217 steps_per_epoch=5,
249 steps_per_epoch=5,
256 steps_per_epoch=5,
292 steps_per_epoch=2,
306 steps_per_epoch=5,
[all …]
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| D | training_dataset_test.py | 77 steps_per_epoch=2,
84 steps_per_epoch=2,
108 model.fit(dataset, epochs=1, steps_per_epoch=2, verbose=1)
116 steps_per_epoch=2,
126 steps_per_epoch=2,
138 steps_per_epoch=2,
145 model.fit(dataset, dataset, epochs=1, steps_per_epoch=2, verbose=0)
182 model.fit(dataset_tuple, epochs=1, steps_per_epoch=2, verbose=1)
197 model.fit(dataset_dict, epochs=1, steps_per_epoch=2, verbose=1)
226 model.fit(dataset, epochs=1, steps_per_epoch=2, verbose=1)
[all …]
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| D | data_adapter_test.py | 684 self.model.fit(self.generator_input, steps_per_epoch=10)
693 max_queue_size=10, steps_per_epoch=10)
697 max_queue_size=10, steps_per_epoch=10)
762 max_queue_size=10, steps_per_epoch=10)
766 max_queue_size=10, steps_per_epoch=10)
798 data, initial_epoch=0, epochs=2, steps_per_epoch=2)
826 data, initial_epoch=0, epochs=2, steps_per_epoch=4)
839 data, initial_epoch=0, epochs=2, steps_per_epoch=3)
856 filtered_ds, initial_epoch=0, epochs=2, steps_per_epoch=2)
893 ds, initial_epoch=0, epochs=2, steps_per_epoch=3)
[all …]
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| D | feature_columns_integration_test.py | 94 model.fit(ds, steps_per_epoch=1)
95 model.fit(ds, steps_per_epoch=1)
178 dnn_model.fit(ds, steps_per_epoch=1)
179 dnn_model.fit(ds, steps_per_epoch=1)
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| D | training_eager_test.py | 193 model.fit(dataset, steps_per_epoch=2, epochs=1, verbose=0,
196 model.fit(dataset, steps_per_epoch=2, epochs=1, verbose=0,
218 model.fit_generator(numpy_iterator(), steps_per_epoch=3, epochs=1)
299 history = model.fit(dataset, epochs=1, steps_per_epoch=10)
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| D | sequential_test.py | 140 steps_per_epoch = 10
160 model.fit(dataset, epochs=1, steps_per_epoch=steps_per_epoch)
184 model.fit(inputs, targets, epochs=10, steps_per_epoch=30)
203 steps_per_epoch=2,
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| D | data_adapter.py | 1108 steps_per_epoch=None, argument
1163 steps=steps_per_epoch,
1179 self._configure_dataset_and_inferred_steps(strategy, x, steps_per_epoch,
1187 def _configure_dataset_and_inferred_steps(self, strategy, x, steps_per_epoch, argument
1194 self._inferred_steps = self._infer_steps(steps_per_epoch, dataset)
1351 def _configure_dataset_and_inferred_steps(self, strategy, x, steps_per_epoch, argument
1362 if steps_per_epoch is None:
1365 self._inferred_steps = steps_per_epoch
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| D | training.py | 882 steps_per_epoch=None, argument
1107 steps_per_epoch=steps_per_epoch,
1176 steps_per_epoch=validation_steps,
1416 steps_per_epoch=steps,
1662 steps_per_epoch=steps,
1886 steps_per_epoch=None, argument
1910 steps_per_epoch=steps_per_epoch,
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| /external/tensorflow/tensorflow/python/keras/distribute/ |
| D | keras_utils_test.py | 94 steps_per_epoch = 5
100 steps_per_epoch=steps_per_epoch,
111 num_batch_call_per_epoch = steps_per_epoch // steps_per_run
112 if steps_per_epoch % steps_per_run:
115 num_batch_call_per_epoch = steps_per_epoch
259 steps_per_epoch=2,
270 steps_per_epoch=2,
390 hist = model.fit(x=dataset, epochs=1, steps_per_epoch=2)
431 model.fit(dataset, epochs=4, verbose=0, steps_per_epoch=10)
455 model.fit(dataset, epochs=1, steps_per_epoch=1)
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| D | multi_worker_callback_tf2_test.py | 120 steps_per_epoch=steps,
161 steps_per_epoch=steps,
205 steps_per_epoch=steps,
223 steps_per_epoch=steps,
262 steps_per_epoch=steps,
299 steps_per_epoch=steps,
322 steps_per_epoch=steps,
357 model.fit(x=train_ds, epochs=100, steps_per_epoch=steps, callbacks=cbks)
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| D | multi_worker_testing_utils.py | 28 def mnist_synthetic_dataset(batch_size, steps_per_epoch): argument
31 x_train = array_ops.ones([batch_size * steps_per_epoch, 28, 28, 1],
33 y_train = array_ops.ones([batch_size * steps_per_epoch, 1],
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| D | parameter_server_training_test.py | 277 steps_per_epoch=10, argument
293 steps_per_epoch=steps_per_epoch,
314 self._model_fit(steps_per_epoch=None)
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| D | distribute_strategy_test.py | 815 model.fit(inputs, epochs=1, steps_per_epoch=2)
905 steps_per_epoch=2,
912 steps_per_epoch=2,
943 steps_per_epoch=2,
953 dataset, epochs=1, steps_per_epoch=2, verbose=1, shuffle=False)
994 model.fit(dataset_tuple, epochs=1, steps_per_epoch=2, verbose=1)
1004 model.fit(dataset_dict, epochs=1, steps_per_epoch=2, verbose=1)
1240 model.fit(dataset, epochs=1, steps_per_epoch=2, verbose=1)
1258 model.fit(dataset, epochs=1, steps_per_epoch=2, verbose=1)
1292 model.fit(dataset, epochs=1, steps_per_epoch=2, verbose=0)
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| D | worker_training_state_test.py | 54 x=train_ds, epochs=2, steps_per_epoch=2, callbacks=callbacks_list)
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| /external/tensorflow/tensorflow/python/debug/examples/v1/ |
| D | debug_keras.py | 36 steps_per_epoch = 2
42 (xs, ys)).repeat(num_examples).batch(int(num_examples / steps_per_epoch))
64 model.fit(dataset, epochs=FLAGS.epochs, steps_per_epoch=steps_per_epoch)
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| /external/tensorflow/tensorflow/python/profiler/integration_test/ |
| D | mnist_testing_utils.py | 24 def mnist_synthetic_dataset(batch_size, steps_per_epoch): argument
27 x_train = tf.ones([batch_size * steps_per_epoch, 28, 28, 1],
29 y_train = tf.ones([batch_size * steps_per_epoch, 1], dtype=tf.dtypes.int32)
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| D | profiler_api_test.py | 89 model.fit(x=train_ds, epochs=2, steps_per_epoch=steps)
100 model.fit(x=train_ds, epochs=2, steps_per_epoch=steps)
158 model.fit(x=train_ds, epochs=2, steps_per_epoch=steps)
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| /external/tensorflow/tensorflow/python/keras/ |
| D | metrics_correctness_test.py | 300 custom_generator_multi_io(), steps_per_epoch=3, epochs=2)
309 steps_per_epoch=3,
318 steps_per_epoch=3,
521 self._custom_generator(), steps_per_epoch=2, epochs=2)
529 steps_per_epoch=2,
538 steps_per_epoch=2,
701 steps_per_epoch=3,
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| /external/tensorflow/tensorflow/python/keras/integration_test/ |
| D | multi_worker_tutorial_test.py | 162 steps_per_epoch=50,
183 loaded_model.fit(multi_worker_dataset, epochs=1, steps_per_epoch=1)
205 multi_worker_model.fit(multi_worker_dataset, epochs=1, steps_per_epoch=1)
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| /external/tensorflow/tensorflow/python/keras/tests/ |
| D | temporal_sample_weights_correctness_test.py | 422 steps_per_epoch=1,
435 steps_per_epoch=1,
449 steps_per_epoch=1,
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| D | automatic_outside_compilation_test.py | 197 steps_per_epoch=10,
227 steps_per_epoch=10,
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| /external/tensorflow/tensorflow/python/keras/utils/ |
| D | dataset_creator_test.py | 77 steps_per_epoch=10,
|