| /aosp_15_r20/external/tensorflow/tensorflow/python/keras/engine/ |
| H A D | training_generator_v1.py | 559 validation_split=0., argument
573 y, sample_weight, validation_split=validation_split)
649 validation_split=0., argument
662 validation_split)
729 validation_split=0., argument
750 validation_split=validation_split,
757 elif validation_split and 0. < validation_split < 1.:
761 x, y, sample_weights, validation_split))
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| H A D | training_distributed_v1.py | 585 validation_split=0., argument
606 validation_split=validation_split)
614 validation_split=validation_split,
624 validation_split=validation_split,
641 validation_split=validation_split,
644 elif validation_split:
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| H A D | training_arrays_v1.py | 606 validation_split=0., argument
628 validation_split=validation_split,
634 elif validation_split and 0. < validation_split < 1.:
637 x, y, sample_weights, validation_split)
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| H A D | training_utils_v1.py | 1235 def validate_dataset_input(x, y, sample_weight, validation_split=None): argument
1266 if validation_split is not None and validation_split != 0.0:
1270 'Received: x=%s, validation_split=%f' % (x, validation_split))
1292 validation_split=None): argument
1302 if validation_split:
1838 def split_training_and_validation_data(x, y, sample_weights, validation_split): argument
1844 split_at = int(x[0].shape[0] * (1. - validation_split))
1846 split_at = int(len(x[0]) * (1. - validation_split))
1927 validation_split=0., argument
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| H A D | training_v1.py | 622 validation_split=0., argument
801 validation_split=validation_split,
2108 validation_split=0, argument
2210 validation_split)
2222 validation_split=0, argument
2288 validation_split)
2299 validation_split)
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| H A D | data_adapter.py | 1466 def train_validation_split(arrays, validation_split): argument
1503 split_at = int(math.floor(batch_dim * (1. - validation_split)))
1511 batch_dim=batch_dim, validation_split=validation_split))
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| H A D | training.py | 887 validation_split=0., argument
1119 if validation_split:
1124 (x, y, sample_weight), validation_split=validation_split))
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| /aosp_15_r20/external/libopus/dnn/training_tf2/ |
| H A D | pade.py | 59 model.fit([x, x2in], yout, batch_size=1, epochs=500000, validation_split=0.0)
62 model.fit([x, x2in], yout, batch_size=1, epochs=50000, validation_split=0.0)
65 model.fit([x, x2in], yout, batch_size=1, epochs=50000, validation_split=0.0)
68 model.fit([x, x2in], yout, batch_size=1, epochs=50000, validation_split=0.0)
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| H A D | train_rdovae.py | 151 …ures, features, features], batch_size=batch_size, epochs=nb_epochs, validation_split=0.0, callback…
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| H A D | train_plc.py | 197 model.fit(loader, epochs=nb_epochs, validation_split=0.0, callbacks=callbacks)
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| H A D | train_lpcnet.py | 214 model.fit(loader, epochs=nb_epochs, validation_split=0.0, callbacks=callbacks)
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| /aosp_15_r20/external/tensorflow/tensorflow/python/keras/distribute/ |
| H A D | distributed_training_utils_v1.py | 433 validation_split=0.): argument
438 if validation_split and 0. < validation_split < 1.:
439 num_samples = int(num_samples * (1 - validation_split))
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| /aosp_15_r20/external/rnnoise/training/ |
| H A D | rnn_train.py | 115 validation_split=0.1)
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| /aosp_15_r20/external/tensorflow/tensorflow/lite/python/ |
| H A D | util_test.py | 258 validation_split=0.1,
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| /aosp_15_r20/external/tensorflow/ |
| H A D | RELEASE.md | 70 …irectory`, and `audio_dataset_from_directory`, to be used with the `validation_split` argument, fo…
|