Searched refs:sequence_input (Results 1 – 2 of 2) sorted by relevance
| /external/tensorflow/tensorflow/python/feature_column/ |
| D | sequence_feature_column.py | 41 def concatenate_context_input(context_input, sequence_input): argument
62 sequence_input,
65 data=[array_ops.shape(sequence_input)])
67 sequence_input,
70 sequence_input.dtype))
83 padded_length = array_ops.shape(sequence_input)[1]
87 return array_ops.concat([sequence_input, tiled_context_input], 2)
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| /external/tensorflow/tensorflow/python/keras/engine/ |
| D | data_adapter_test.py | 90 self.sequence_input = TestSequence(batch_size=self.batch_size,
125 self.assertFalse(self.adapter_cls.can_handle(self.sequence_input))
257 self.assertFalse(self.adapter_cls.can_handle(self.sequence_input))
428 self.assertFalse(self.adapter_cls.can_handle(self.sequence_input))
633 self.assertFalse(self.adapter_cls.can_handle(self.sequence_input))
676 self.assertFalse(self.adapter_cls.can_handle(self.sequence_input))
745 self.assertTrue(self.adapter_cls.can_handle(self.sequence_input))
753 self.model.fit(self.sequence_input)
761 self.model.fit(self.sequence_input, workers=1, use_multiprocessing=True,
765 self.model.fit(self.sequence_input, workers=1, use_multiprocessing=True,
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