/external/tensorflow/tensorflow/contrib/recurrent/python/kernel_tests/ |
D | functional_rnn_test.py | 64 def _CreateInputs(self, time_major=False): argument 65 if time_major: 107 time_major=None, argument 116 time_major=time_major, 125 time_major=time_major, 148 is_dynamic, time_major=None, is_bidirectional=False): argument 167 fn, cell, tf_inputs, tf_slen, is_bidirectional, time_major=time_major) 217 time_major = True 218 np_inputs, np_slen = self._CreateInputs(time_major=True) 221 _, func_rnn = self._RunRnn(*(args + [False]), time_major=time_major) [all …]
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/external/tensorflow/tensorflow/python/keras/layers/ |
D | recurrent_v2.py | 172 time_major=False, argument 202 time_major=time_major, 219 timesteps = input_shape[0] if self.time_major else input_shape[1] 237 time_major=self.time_major, 267 inputs = K.reverse(inputs, 0 if self.time_major else 1) 285 time_major=self.time_major) 295 time_major=self.time_major) 312 time_major=self.time_major) 316 self.cell.bias, self.time_major) 322 recurrent_activation, time_major): argument [all …]
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D | cudnn_recurrent.py | 61 time_major=False, argument 70 self.time_major = time_major 130 'time_major': self.time_major, 273 if not self.time_major: 308 if self.time_major: 466 if not self.time_major: 507 if self.time_major:
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/external/tensorflow/tensorflow/contrib/cudnn_rnn/python/kernel_tests/ |
D | cudnn_rnn_ops_test.py | 72 time_major=True, argument 90 if time_major else [batch_size, time, input_size]) 135 time_major=time_major, 144 initial_h_op, axis=(0 if time_major else 1)) 146 initial_c_op, axis=(0 if time_major else 1)) 153 time_major=time_major, 159 c=array_ops.squeeze(cu_c_op, axis=0 if time_major else 1), 160 h=array_ops.squeeze(cu_h_op, axis=0 if time_major else 1)) 172 cu_hgrad_op = array_ops.squeeze(cu_hgrad_op, axis=0 if time_major else 1) 174 cu_cgrad_op = array_ops.squeeze(cu_cgrad_op, axis=0 if time_major else 1) [all …]
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/external/tensorflow/tensorflow/contrib/seq2seq/python/kernel_tests/ |
D | decoder_v2_test.py | 38 def _testDecodeRNN(self, time_major, maximum_iterations=None): argument 48 if time_major: 56 sampler = sampler_py.TrainingSampler(time_major=time_major) 60 output_time_major=time_major, 69 if time_major: 104 self._testDecodeRNN(time_major=False) 107 self._testDecodeRNN(time_major=True) 110 self._testDecodeRNN(time_major=True, maximum_iterations=0) 113 self._testDecodeRNN(time_major=True, maximum_iterations=1)
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D | decoder_test.py | 37 def _testDynamicDecodeRNN(self, time_major, maximum_iterations=None): argument 47 if time_major: 55 inputs, sequence_length, time_major=time_major) 63 decoder.dynamic_decode(my_decoder, output_time_major=time_major, 67 if time_major: 108 self._testDynamicDecodeRNN(time_major=False) 111 self._testDynamicDecodeRNN(time_major=True) 114 self._testDynamicDecodeRNN(time_major=True, maximum_iterations=0) 117 self._testDynamicDecodeRNN(time_major=True, maximum_iterations=1)
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D | beam_search_decoder_test.py | 478 def _testDynamicDecodeRNN(self, time_major, has_attention, argument 539 bsd, output_time_major=time_major, maximum_iterations=max_out)) 542 if time_major: 577 self._testDynamicDecodeRNN(time_major=False, has_attention=False) 580 self._testDynamicDecodeRNN(time_major=False, has_attention=True) 584 time_major=False, 592 def _testDynamicDecodeRNN(self, time_major, has_attention, argument 646 output_time_major=time_major, 656 if time_major: 691 self._testDynamicDecodeRNN(time_major=False, has_attention=False) [all …]
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/external/tensorflow/tensorflow/lite/kernels/ |
D | unidirectional_sequence_rnn.cc | 70 const bool time_major = params->time_major; in Prepare() local 72 (time_major) ? input->dims->data[1] : input->dims->data[0]; in Prepare() 74 (time_major) ? input->dims->data[0] : input->dims->data[1]; in Prepare() 93 output_size_array->data[0] = (time_major) ? max_time : batch_size; in Prepare() 94 output_size_array->data[1] = (time_major) ? batch_size : max_time; in Prepare() 155 const bool time_major = params->time_major; in EvalFloat() local 157 (time_major) ? input->dims->data[1] : input->dims->data[0]; in EvalFloat() 159 (time_major) ? input->dims->data[0] : input->dims->data[1]; in EvalFloat() 167 if (time_major) { in EvalFloat() 210 const bool time_major = params->time_major; in EvalHybrid() local [all …]
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D | bidirectional_sequence_rnn.cc | 131 const bool time_major = params->time_major; in Prepare() local 133 (time_major) ? input->dims->data[1] : input->dims->data[0]; in Prepare() 135 (time_major) ? input->dims->data[0] : input->dims->data[1]; in Prepare() 263 fw_output_size_array->data[0] = (time_major) ? max_time : batch_size; in Prepare() 264 fw_output_size_array->data[1] = (time_major) ? batch_size : max_time; in Prepare() 295 const bool time_major = params->time_major; in EvalFloat() local 297 (time_major) ? input->dims->data[1] : input->dims->data[0]; in EvalFloat() 299 (time_major) ? input->dims->data[0] : input->dims->data[1]; in EvalFloat() 324 if (time_major) { in EvalFloat() 429 const bool time_major = params->time_major; in EvalHybrid() local [all …]
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D | unidirectional_sequence_rnn_test.cc | 175 int batches, int sequence_len, int units, int size, bool time_major, in UnidirectionalRNNOpModel() argument 190 CreateSequenceRNNOptions(builder_, time_major, in UnidirectionalRNNOpModel() 193 if (time_major) { in UnidirectionalRNNOpModel() 251 int size, bool time_major, in HybridUnidirectionalRNNOpModel() argument 253 : UnidirectionalRNNOpModel(batches, sequence_len, units, size, time_major, in HybridUnidirectionalRNNOpModel()
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D | bidirectional_sequence_lstm.cc | 401 const bool time_major = params->time_major; in Prepare() local 402 const int max_time = time_major ? input->dims->data[0] : input->dims->data[1]; in Prepare() 403 const int n_batch = time_major ? input->dims->data[1] : input->dims->data[0]; in Prepare() 504 fw_output_size->data[0] = time_major ? max_time : n_batch; in Prepare() 505 fw_output_size->data[1] = time_major ? n_batch : max_time; in Prepare() 564 bw_output_size->data[0] = time_major ? max_time : n_batch; in Prepare() 565 bw_output_size->data[1] = time_major ? n_batch : max_time; in Prepare() 888 const bool time_major = params->time_major; in Eval() local 927 /*forward_sequence=*/true, time_major, /*output_offset=*/0, in Eval() 947 /*forward_sequence=*/false, time_major, bw_output_offset, in Eval()
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D | unidirectional_sequence_lstm.cc | 266 const bool time_major = params->time_major; in Prepare() local 267 const int n_batch = time_major ? input->dims->data[1] : input->dims->data[0]; in Prepare() 441 const bool time_major = params->time_major; in Eval() local 516 projection_bias, &lstm_params, /*forward_sequence=*/true, time_major, in Eval() 548 projection_bias, &lstm_params, /*forward_sequence=*/true, time_major, in Eval()
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/external/tensorflow/tensorflow/lite/experimental/examples/lstm/ |
D | rnn.py | 49 time_major=True, argument 161 assert time_major 212 if not time_major: 271 if not time_major: 288 time_major=False, argument 378 time_major=time_major, 382 if not time_major: 417 time_major=time_major,
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/external/tensorflow/tensorflow/core/api_def/base_api/ |
D | api_def_CudnnRNNV3.pbtxt | 19 input: If time_major is true, this is a 3-D tensor with the shape of 20 [seq_length, batch_size, input_size]. If time_major is false, the shape is 22 input_h: If time_major is true, this is a 3-D tensor with the shape of 23 [num_layer * dir, batch_size, num_units]. If time_major is false, the shape 32 output: If time_major is true, this is a 3-D tensor with the shape of 33 [seq_length, batch_size, dir * num_units]. If time_major is false, the 39 time_major: Indicates whether the input/output format is time major or batch
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D | api_def_CudnnRNNBackpropV3.pbtxt | 19 input: If time_major is true, this is a 3-D tensor with the shape of 20 [seq_length, batch_size, input_size]. If time_major is false, the shape is 22 input_h: If time_major is true, this is a 3-D tensor with the shape of 23 [num_layer * dir, batch_size, num_units]. If time_major is false, the shape 32 output: If time_major is true, this is a 3-D tensor with the shape of 33 [seq_length, batch_size, dir * num_units]. If time_major is false, the 42 time_major: Indicates whether the input/output format is time major or batch
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/external/tensorflow/tensorflow/contrib/recurrent/python/ops/ |
D | functional_rnn.py | 280 time_major=False, argument 286 if not time_major: 317 if time_major: 329 time_major=False, argument 394 time_major=time_major, scope=fw_scope, use_tpu=use_tpu) 396 if not time_major: 427 time_major=time_major,
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/external/tensorflow/tensorflow/contrib/cudnn_rnn/python/ops/ |
D | cudnn_rnn_ops.py | 959 time_major=True, argument 1028 args["time_major"] = time_major 1030 elif time_major is False: 1035 args["time_major"] = time_major 1050 time_major=True, argument 1096 sequence_lengths, time_major, input_mode, direction, 1106 time_major=True, argument 1153 time_major, input_mode, direction, dropout, seed, name) 1162 time_major=True, argument 1206 sequence_lengths, time_major, input_mode, [all …]
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/external/tensorflow/tensorflow/core/kernels/ |
D | cudnn_rnn_ops.cc | 562 const CudnnModelTypes& model_types, bool time_major, in ExtractForwardInput() argument 576 if (time_major) { in ExtractForwardInput() 593 if (time_major) { in ExtractForwardInput() 602 if (time_major) { in ExtractForwardInput() 625 if (time_major) { in ExtractForwardInput() 639 const CudnnModelTypes& model_types, bool time_major, in ExtractForwardInput() argument 645 return ExtractForwardInput(context, model_types, time_major, input, input_h, in ExtractForwardInput() 655 const absl::Span<const int>& seq_lengths, bool time_major) { in CreateForwardAndBackwardIODescriptors() argument 665 if (time_major) { in CreateForwardAndBackwardIODescriptors() 668 input_shape.dim_size(2), seq_lengths, time_major, data_type); in CreateForwardAndBackwardIODescriptors() [all …]
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/external/tensorflow/tensorflow/lite/c/ |
D | builtin_op_data.h | 113 bool time_major; member 118 bool time_major; member 213 bool time_major; member 228 bool time_major; member
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/external/tensorflow/tensorflow/contrib/seq2seq/python/ops/ |
D | sampler.py | 192 def __init__(self, time_major=False): argument 202 self.time_major = time_major 233 if not self.time_major: 290 time_major=False, argument 323 self).__init__(time_major=time_major) 384 time_major=False, argument 412 super(ScheduledOutputTrainingSampler, self).__init__(time_major=time_major) 422 if not self.time_major:
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D | helper.py | 233 def __init__(self, inputs, sequence_length, time_major=False, name=None): argument 249 if not time_major: 323 time_major=False, seed=None, scheduling_seed=None, name=None): argument 361 time_major=time_major, 423 time_major=False, seed=None, next_inputs_fn=None, argument 465 if not time_major: 480 time_major=time_major,
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/external/tensorflow/tensorflow/lite/core/api/ |
D | flatbuffer_conversions.cc | 243 params->time_major = sequence_rnn_params->time_major(); in ParseOpData() 255 params->time_major = bidi_sequence_rnn_params->time_major(); in ParseOpData() 412 params->time_major = seq_lstm_params->time_major(); in ParseOpData() 427 params->time_major = bidi_lstm_params->time_major(); in ParseOpData()
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/external/tensorflow/tensorflow/contrib/rnn/python/ops/ |
D | rnn.py | 133 time_major=False, argument 239 time_major=time_major)
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/external/tensorflow/tensorflow/contrib/rnn/python/kernel_tests/ |
D | gru_ops_test.py | 54 cell, x, time_major=True, dtype=dtypes.float32) 121 time_major=True, 134 time_major=True, 247 time_major=True, 265 time_major=True, 366 time_major=True, 386 time_major=True, 438 time_major=True, 451 time_major=True,
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/external/tensorflow/tensorflow/contrib/cudnn_rnn/python/layers/ |
D | cudnn_rnn.py | 381 time_major=True, argument 434 inputs, h, c, self.kernel, sequence_lengths, time_major, training) 498 def _forward(self, inputs, h, c, opaque_params, sequence_lengths, time_major, argument 508 time_major=time_major,
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