| /external/tensorflow/tensorflow/python/keras/benchmarks/keras_examples_benchmarks/ |
| D | reuters_mlp_benchmark_test.py | 39 self.epochs = 5
71 epochs=self.epochs,
88 epochs=self.epochs,
105 epochs=self.epochs,
127 epochs=self.epochs,
|
| D | mnist_conv_benchmark_test.py | 38 self.epochs = 15
71 epochs=self.epochs,
88 epochs=self.epochs,
105 epochs=self.epochs,
127 epochs=self.epochs,
|
| D | cifar10_cnn_benchmark_test.py | 34 self.epochs = 5
80 epochs=self.epochs,
97 epochs=self.epochs,
114 epochs=self.epochs,
136 epochs=self.epochs,
|
| D | mnist_conv_custom_training_benchmark_test.py | 36 self.epochs = 15
122 epochs=2, argument
152 for _ in range(epochs):
180 epochs=10, argument
229 total_num_examples = epochs * self.num_examples
241 epochs, distribution_strategy,
249 avg_epoch_time_list.append((end_time - t2) / epochs)
262 metrics.append({'name': 'epochs', 'value': epochs})
284 run_iters, self.epochs)
306 run_iters, self.epochs)
[all …]
|
| /external/libopus/training/ |
| D | rnn_train.py | 111 epochs=10, validation_data=(x_train, y_train))
117 epochs=50, initial_epoch=10)
127 epochs=100, initial_epoch=50)
133 epochs=150, initial_epoch=100)
139 epochs=200, initial_epoch=150)
145 epochs=201, initial_epoch=200)
151 epochs=202, initial_epoch=201, validation_data=(x_train, y_train))
157 epochs=203, initial_epoch=202, validation_data=(x_train, y_train))
163 epochs=204, initial_epoch=203, validation_data=(x_train, y_train))
169 epochs=205, initial_epoch=204, validation_data=(x_train, y_train))
[all …]
|
| /external/tensorflow/tensorflow/python/keras/utils/ |
| D | multi_gpu_utils_test.py | 61 epochs = 2
78 parallel_model.fit(x, y, epochs=epochs)
82 parallel_model.fit(x, y, epochs=epochs)
92 epochs = 2
115 parallel_model.fit([a_x, b_x], [a_y, b_y], epochs=epochs)
120 parallel_model.fit([a_x, b_x], [a_y, b_y], epochs=epochs)
140 parallel_model.fit(x, y, epochs=2)
145 parallel_model.fit(x, y, epochs=2)
149 parallel_model.fit(x, y, epochs=2)
153 parallel_model.fit(x, y, epochs=2)
[all …]
|
| /external/tensorflow/tensorflow/python/keras/distribute/ |
| D | keras_utils_test.py | 93 epochs = 2
99 epochs=epochs,
119 'on_batch_begin': epochs * num_batch_call_per_epoch,
120 'on_batch_end': epochs * num_batch_call_per_epoch,
121 'on_epoch_begin': epochs,
122 'on_epoch_end': epochs,
123 'on_test_batch_begin': epochs * validation_steps,
124 'on_test_batch_end': epochs * validation_steps,
125 'on_test_begin': epochs,
126 'on_test_end': epochs,
[all …]
|
| D | multi_worker_callback_tf2_test.py | 119 epochs=num_epoch,
160 epochs=num_epoch,
204 epochs=num_epoch,
222 epochs=num_epoch,
261 epochs=num_epoch,
298 epochs=num_epoch,
321 epochs=num_epoch,
357 model.fit(x=train_ds, epochs=100, steps_per_epoch=steps, callbacks=cbks)
|
| D | distribute_strategy_test.py | 492 epochs=1,
542 epochs=1,
635 model.fit(inputs, targets, epochs=1, batch_size=8, verbose=0)
815 model.fit(inputs, epochs=1, steps_per_epoch=2)
904 epochs=1,
911 epochs=1,
942 epochs=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)
[all …]
|
| D | keras_premade_models_test.py | 77 hist = model.fit(inputs, output, epochs=5)
79 hist = model.fit(get_dataset(), epochs=5)
95 hist = wide_deep_model.fit(inputs, output, epochs=5)
97 hist = wide_deep_model.fit(get_dataset(), epochs=5)
|
| /external/tensorflow/tensorflow/python/keras/engine/ |
| D | training_generator_v1.py | 45 epochs=1, argument
137 model, data, steps_per_epoch, epochs=epochs, steps_name=steps_name)
144 epochs=epochs - initial_epoch,
174 epochs=epochs,
200 for epoch in range(initial_epoch, epochs):
234 % (steps_name, steps_per_epoch * epochs))
247 'dataset.' % (steps_name, steps_per_epoch * epochs))
274 epochs=epochs,
325 if reset_dataset_after_each_epoch and epoch < epochs - 1:
428 epochs=1, argument
[all …]
|
| D | training_eager_test.py | 102 epochs=1,
108 epochs=1,
114 epochs=1, batch_size=2, verbose=0,
127 epochs=1,
131 epochs=1, batch_size=2, verbose=0,
135 epochs=1,
167 model.fit(inputs, targets, epochs=1, batch_size=2, verbose=0)
168 model.fit(inputs, targets, epochs=1, batch_size=3, verbose=0, shuffle=False)
169 model.fit(inputs, targets, epochs=1, batch_size=4, verbose=0,
189 model.fit(dataset, epochs=1, verbose=0)
[all …]
|
| D | training_generator_test.py | 110 epochs=1,
117 epochs=1,
123 epochs=1,
212 epochs=1,
218 epochs=1,
250 epochs=1,
257 epochs=1,
294 epochs=2)
307 epochs=1,
313 epochs=1,
[all …]
|
| D | training_dataset_test.py | 76 epochs=1,
83 epochs=1,
108 model.fit(dataset, epochs=1, steps_per_epoch=2, verbose=1)
115 epochs=1,
125 epochs=1,
137 epochs=1,
145 model.fit(dataset, dataset, epochs=1, steps_per_epoch=2, verbose=0)
149 model.fit(dataset, epochs=1, 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)
[all …]
|
| D | feature_columns_integration_test.py | 69 model.fit(x, y, epochs=1, batch_size=5)
70 model.fit(x, y, epochs=1, batch_size=5)
133 model.fit(ds, epochs=1)
134 model.fit(ds, epochs=1)
154 dnn_model.fit(x=x, y=y, epochs=1, batch_size=5)
155 dnn_model.fit(x=x, y=y, epochs=1, batch_size=5)
208 model.fit(*data, epochs=1)
243 model.fit(*data_list, epochs=1)
254 model.fit(*data_bloated_list, epochs=1)
266 model.fit(*data_dict, epochs=1)
[all …]
|
| D | training_arrays_v1.py | 51 epochs=1, argument
143 model, inputs, steps_per_epoch, epochs=epochs, steps_name=steps_name)
200 epochs=epochs,
222 epochs=epochs,
258 for epoch in range(initial_epoch, epochs):
309 % (steps_name, steps_per_epoch * epochs))
322 'dataset.' % (steps_name, steps_per_epoch * epochs))
434 if val_iterator and epoch < epochs - 1:
442 if reset_dataset_after_each_epoch and epoch < epochs - 1:
606 epochs=1, argument
[all …]
|
| D | training_test.py | 165 train_dataset, epochs=2, verbose=1, validation_data=val_dataset)
198 train_dataset, epochs=2, verbose=1, validation_data=val_dataset)
267 train_dataset, epochs=2, verbose=1, validation_data=val_dataset)
306 epochs=1,
311 epochs=1,
316 epochs=2,
326 epochs=1,
333 epochs=2,
340 epochs=2,
346 epochs=2,
[all …]
|
| D | training_distributed_v1.py | 125 epochs=100, argument
208 epochs=epochs,
227 for epoch in range(initial_epoch, epochs):
248 steps_per_epoch * epochs)
367 epochs=1,
509 epochs=1,
587 epochs=1, argument
621 epochs=epochs)
655 model, dataset, steps_per_epoch, epochs, steps_name='steps_per_epoch')
665 epochs=epochs,
[all …]
|
| /external/tensorflow/tensorflow/python/keras/wrappers/ |
| D | scikit_learn_test.py | 58 clf.fit(x_train, y_train, batch_size=BATCH_SIZE, epochs=EPOCHS)
94 reg.fit(x_train, y_train, batch_size=BATCH_SIZE, epochs=EPOCHS)
111 epochs=EPOCHS)
127 epochs=EPOCHS)
143 epochs=EPOCHS)
153 epochs=EPOCHS)
169 epochs=EPOCHS)
185 epochs=EPOCHS)
|
| /external/tensorflow/tensorflow/python/keras/ |
| D | callbacks_test.py | 170 epochs=5,
281 model.fit(dataset, epochs=2, steps_per_epoch=10)
309 epochs=1,
335 epochs=1)
350 model.fit(dataset, epochs=2, steps_per_epoch=10)
365 model.fit(training_dataset, epochs=2, validation_data=val_dataset)
380 model.fit(x, y, batch_size=10, epochs=2, validation_split=0.2)
411 x=training, validation_data=validation, epochs=2, steps_per_epoch=20)
496 epochs=1,
516 epochs=1,
[all …]
|
| D | callbacks_v1_test.py | 111 epochs=3,
121 epochs=2,
128 epochs=2,
139 epochs=2,
148 epochs=2,
156 data_generator(True), len(x_train), epochs=2, callbacks=cbks)
217 callbacks=callbacks_factory(histogram_freq=0), epochs=3)
222 callbacks=callbacks_factory(histogram_freq=1), epochs=2)
225 model.fit_generator(data_generator(True), len(x_train), epochs=2,
229 model.fit_generator(data_generator(True), len(x_train), epochs=2,
[all …]
|
| /external/tensorflow/tensorflow/python/keras/benchmarks/ |
| D | benchmark_util.py | 101 epochs=2, argument
160 total_num_examples = epochs * num_examples
183 model.fit(x=x, y=y, batch_size=batch_size, epochs=1)
190 epochs=epochs,
211 metrics.append({'name': 'epochs', 'value': epochs})
|
| /external/tensorflow/tensorflow/python/keras/premade/ |
| D | wide_deep_test.py | 55 wide_deep_model.fit(inputs, output, epochs=5)
76 wide_deep_model.fit(inputs, output, epochs=1)
95 wide_deep_model.fit(inputs, output, epochs=5)
134 wide_deep_model.fit(inputs, output, epochs=5)
158 model.fit([linear_input_np, dnn_input_np, input_b_np], output_np, epochs=5)
180 linear_model.fit(linear_inp, output, epochs=50)
181 dnn_model.fit(dnn_inp, output, epochs=50)
187 wide_deep_model.fit(inputs, output, epochs=50)
215 combined.fit(x={'symbol': data}, y=y, batch_size=32, epochs=10)
248 wide_deep_model.fit(x={'symbol': data}, y=y, batch_size=32, epochs=10)
|
| /external/zstd/lib/dictBuilder/ |
| D | cover.c | 659 COVER_epoch_info_t epochs; in COVER_computeEpochs() local
660 epochs.num = MAX(1, maxDictSize / k / passes); in COVER_computeEpochs()
661 epochs.size = nbDmers / epochs.num; in COVER_computeEpochs()
662 if (epochs.size >= minEpochSize) { in COVER_computeEpochs()
663 assert(epochs.size * epochs.num <= nbDmers); in COVER_computeEpochs()
664 return epochs; in COVER_computeEpochs()
666 epochs.size = MIN(minEpochSize, nbDmers); in COVER_computeEpochs()
667 epochs.num = nbDmers / epochs.size; in COVER_computeEpochs()
668 assert(epochs.size * epochs.num <= nbDmers); in COVER_computeEpochs()
669 return epochs; in COVER_computeEpochs()
[all …]
|
| /external/tensorflow/tensorflow/python/keras/tests/ |
| D | model_subclassing_compiled_test.py | 57 model.fit(x, y, epochs=2, batch_size=32, verbose=0)
78 model.fit([x1, x2], [y1, y2], epochs=2, batch_size=32, verbose=0)
100 model.fit(dataset, epochs=2, steps_per_epoch=10, verbose=0)
212 model.fit([x1, x2], [y1, y2], epochs=2, batch_size=32, verbose=0)
215 epochs=2, batch_size=32)
216 model.fit([x1, x2], [y1, y2], epochs=2, batch_size=32, verbose=0,
274 model.fit([x1, x2], [y1, y2], epochs=2, batch_size=32, verbose=0)
318 model.fit(x, y, epochs=2, batch_size=32, verbose=0)
342 model.fit(x, y, epochs=2, batch_size=32, verbose=0)
367 model.fit(x, y, epochs=2, batch_size=32, verbose=0)
[all …]
|