/external/v8/src/compiler/x64/ |
D | unwinding-info-writer-x64.cc | 20 const BlockInitialState* initial_state = in BeginInstructionBlock() local 22 if (initial_state) { in BeginInstructionBlock() 23 if (initial_state->register_ != eh_frame_writer_.base_register() && in BeginInstructionBlock() 24 initial_state->offset_ != eh_frame_writer_.base_offset()) { in BeginInstructionBlock() 26 eh_frame_writer_.SetBaseAddressRegisterAndOffset(initial_state->register_, in BeginInstructionBlock() 27 initial_state->offset_); in BeginInstructionBlock() 28 } else if (initial_state->register_ != eh_frame_writer_.base_register()) { in BeginInstructionBlock() 30 eh_frame_writer_.SetBaseAddressRegister(initial_state->register_); in BeginInstructionBlock() 31 } else if (initial_state->offset_ != eh_frame_writer_.base_offset()) { in BeginInstructionBlock() 33 eh_frame_writer_.SetBaseAddressOffset(initial_state->offset_); in BeginInstructionBlock() [all …]
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/external/tensorflow/tensorflow/contrib/rnn/python/ops/ |
D | fused_rnn_cell.py | 47 initial_state=None, argument 97 initial_state=None, argument 109 initial_state=initial_state, 122 initial_state=initial_state, 172 initial_state=None, argument 179 initial_state=initial_state,
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/external/tensorflow/tensorflow/python/keras/layers/ |
D | lstm_test.py | 164 initial_state = [keras.Input((units,)) for _ in range(num_states)] 166 if len(initial_state) == 1: 167 output = layer(inputs, initial_state=initial_state[0]) 169 output = layer(inputs, initial_state=initial_state) 170 assert initial_state[0] in layer._inbound_nodes[0].input_tensors 172 model = keras.models.Model([inputs] + initial_state, output) 178 initial_state = [np.random.random((num_samples, units)) 181 model.train_on_batch([inputs] + initial_state, targets) 192 initial_state = [keras.backend.random_normal_variable( 196 output = layer(inputs, initial_state=initial_state) [all …]
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D | recurrent_v2.py | 211 def call(self, inputs, mask=None, training=None, initial_state=None): argument 213 inputs, initial_state, _ = self._process_inputs(inputs, initial_state, None) 231 initial_state, 243 inputs, initial_state, training) 261 def _defun_gru_call(self, inputs, initial_state, training): argument 281 init_h=initial_state[0], 289 init_h=initial_state[0], 306 init_h=initial_state[0], 314 function.register(defun_cudnn_gru, inputs, initial_state[0], 582 def call(self, inputs, mask=None, training=None, initial_state=None): argument [all …]
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D | convolutional_recurrent.py | 280 initial_state = K.zeros_like(inputs) 282 initial_state = K.sum(initial_state, axis=1) 285 initial_state = self.cell.input_conv(initial_state, 290 return [initial_state for _ in self.cell.state_size] 292 return [initial_state] 294 def __call__(self, inputs, initial_state=None, constants=None, **kwargs): argument 295 inputs, initial_state, constants = _standardize_args( 296 inputs, initial_state, constants, self._num_constants) 298 if initial_state is None and constants is None: 307 if initial_state is not None: [all …]
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D | wrappers.py | 435 def __call__(self, inputs, initial_state=None, constants=None, **kwargs): argument 437 inputs, initial_state, constants = _standardize_args( 438 inputs, initial_state, constants, self._num_constants) 442 initial_state = inputs[1:] 445 if initial_state is None and constants is None: 451 if initial_state is not None: 453 num_states = len(initial_state) 459 'Found: ' + str(initial_state)) 461 kwargs['initial_state'] = initial_state 462 additional_inputs += initial_state [all …]
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D | lstm_v2_test.py | 136 initial_state = [keras.Input((units,)) for _ in range(num_states)] 138 if len(initial_state) == 1: 139 output = layer(inputs, initial_state=initial_state[0]) 141 output = layer(inputs, initial_state=initial_state) 142 assert initial_state[0] in layer._inbound_nodes[0].input_tensors 144 model = keras.models.Model([inputs] + initial_state, output) 150 initial_state = [ 154 model.train_on_batch([inputs] + initial_state, targets) 165 initial_state = [ 170 output = layer(inputs, initial_state=initial_state) [all …]
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D | cudnn_recurrent.py | 84 def call(self, inputs, mask=None, training=None, initial_state=None): argument 94 initial_state = inputs[1:] 96 elif initial_state is not None: 99 initial_state = self.states 101 initial_state = self.get_initial_state(inputs) 103 if len(initial_state) != len(self.states): 105 ' states but was passed ' + str(len(initial_state)) + 111 output, states = self._process_batch(inputs, initial_state) 272 def _process_batch(self, inputs, initial_state): argument 275 input_h = initial_state[0] [all …]
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D | recurrent.py | 627 def __call__(self, inputs, initial_state=None, constants=None, **kwargs): argument 628 inputs, initial_state, constants = _standardize_args(inputs, 629 initial_state, 638 if initial_state is None and constants is None: 647 if initial_state is not None: 648 additional_inputs += initial_state 650 InputSpec(shape=K.int_shape(state)) for state in initial_state 686 if initial_state is not None: 687 kwargs['initial_state'] = initial_state 696 initial_state=None, argument [all …]
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D | cudnn_recurrent_test.py | 135 initial_state = [keras.Input((units,)) for _ in range(num_states)] 137 if len(initial_state) == 1: 138 output = layer(inputs, initial_state=initial_state[0]) 140 output = layer(inputs, initial_state=initial_state) 141 self.assertIn(initial_state[0], layer._inbound_nodes[0].input_tensors) 143 model = keras.models.Model([inputs] + initial_state, output) 149 initial_state = [ 153 model.fit([inputs] + initial_state, targets)
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/external/tensorflow/tensorflow/contrib/recurrent/python/ops/ |
D | functional_rnn.py | 60 def __init__(self, rnn_cell, seq_inputs, initial_state): argument 61 assert initial_state is not None 64 input_dtypes = [seq_inputs.dtype] + _GetDTypesFromStructure(initial_state) 68 input_structure = (like_inputs_t, initial_state) 74 _SetShapeFromTemplate(state0, initial_state) 140 self._state_template = initial_state 278 initial_state=None, argument 291 if initial_state is None: 292 initial_state = cell.zero_state(batch_size, dtype) 293 func_cell = _FunctionalRnnCell(cell, inputs, initial_state) [all …]
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/external/v8/src/compiler/arm/ |
D | unwinding-info-writer-arm.cc | 20 const BlockInitialState* initial_state = in BeginInstructionBlock() local 22 if (initial_state) { in BeginInstructionBlock() 23 if (initial_state->saved_lr_ != saved_lr_) { in BeginInstructionBlock() 25 if (initial_state->saved_lr_) { in BeginInstructionBlock() 30 saved_lr_ = initial_state->saved_lr_; in BeginInstructionBlock()
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/external/v8/src/compiler/arm64/ |
D | unwinding-info-writer-arm64.cc | 20 const BlockInitialState* initial_state = in BeginInstructionBlock() local 22 if (initial_state) { in BeginInstructionBlock() 23 if (initial_state->saved_lr_ != saved_lr_) { in BeginInstructionBlock() 25 if (initial_state->saved_lr_) { in BeginInstructionBlock() 31 saved_lr_ = initial_state->saved_lr_; in BeginInstructionBlock()
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/external/tensorflow/tensorflow/contrib/crf/python/ops/ |
D | crf.py | 212 initial_state=first_input, 554 initial_state = array_ops.slice(potentials, [0, 0, 0], [-1, 1, -1]) 555 initial_state = array_ops.squeeze(initial_state, axis=[1]) # [B, O] 565 initial_state=initial_state, 573 initial_state = math_ops.cast(math_ops.argmax(last_score, axis=1), # [B] 575 initial_state = array_ops.expand_dims(initial_state, axis=-1) # [B, 1] 580 initial_state=initial_state, 584 decode_tags = array_ops.concat([initial_state, decode_tags], # [B, T]
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/external/tensorflow/tensorflow/contrib/seq2seq/python/kernel_tests/ |
D | basic_decoder_v2_test.py | 65 initial_state = cell.zero_state(dtype=dtypes.float32, 75 initial_state=initial_state, 144 initial_state = cell.zero_state( 153 initial_state=initial_state) 221 initial_state = cell.zero_state( 229 initial_state=initial_state) 295 initial_state = cell.zero_state( 302 initial_state=initial_state) 396 initial_state = cell.zero_state( 407 initial_state=initial_state, [all …]
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D | decoder_v2_test.py | 63 initial_state = cell.zero_state( 66 input_t, initial_state=initial_state, sequence_length=sequence_length) 136 inputs, initial_state=zero_state, sequence_length=sequence_length) 142 initial_state=zero_state)
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/external/tensorflow/tensorflow/contrib/learn/python/learn/ops/ |
D | seq2seq_ops.py | 99 def rnn_decoder(decoder_inputs, initial_state, cell, scope=None): argument 113 states, sampling_states = [initial_state], [initial_state] 115 with ops.name_scope("training", values=[decoder_inputs, initial_state]): 122 with ops.name_scope("sampling", values=[initial_state]):
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/external/tensorflow/tensorflow/python/data/experimental/ops/ |
D | scan_ops.py | 34 def __init__(self, input_dataset, initial_state, scan_func): argument 41 self._initial_state = nest.pack_sequence_as(initial_state, [ 45 for i, t in enumerate(nest.flatten(initial_state)) 150 def scan(initial_state, scan_func): argument 171 return _ScanDataset(dataset, initial_state, scan_func)
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/external/toolchain-utils/automation/common/ |
D | state_machine.py | 21 def __init__(self, initial_state): argument 22 assert initial_state in self.state_machine,\ 25 self._state = initial_state
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/external/tensorflow/tensorflow/python/ops/ |
D | rnn.py | 441 initial_state=initial_state_fw, dtype=dtype, 473 initial_state=initial_state_bw, dtype=dtype, 491 def dynamic_rnn(cell, inputs, sequence_length=None, initial_state=None, argument 636 if initial_state is not None: 637 state = initial_state 685 initial_state, argument 724 state = initial_state 1087 (elements_finished, next_input, initial_state, emit_structure, 1109 nest.assert_same_structure(initial_state, cell.state_size) 1110 state = initial_state [all …]
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/external/tensorflow/tensorflow/contrib/cudnn_rnn/python/layers/ |
D | cudnn_rnn.py | 379 initial_state=None, argument 414 if initial_state is not None and not isinstance(initial_state, tuple): 416 initial_state) 421 if initial_state is None: 422 initial_state = self._zero_state(batch_size) 424 h, c = initial_state # pylint:disable=unbalanced-tuple-unpacking,unpacking-non-sequence 426 h, = initial_state # pylint:disable=unbalanced-tuple-unpacking,unpacking-non-sequence
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/external/tensorflow/tensorflow/contrib/seq2seq/python/ops/ |
D | basic_decoder.py | 49 def __init__(self, cell, helper, initial_state, output_layer=None): argument 73 self._initial_state = initial_state 182 def initialize(self, inputs, initial_state=None, **kwargs): argument 186 self._cell_dtype = nest.flatten(initial_state)[0].dtype 187 return self.sampler.initialize(inputs, **kwargs) + (initial_state,)
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D | decoder.py | 169 def call(self, inputs, initial_state=None, **kwargs): argument 171 init_kwargs["initial_state"] = initial_state 196 def initialize(self, inputs, initial_state=None, **kwargs): argument 334 initial_finished, initial_inputs, initial_state = decoder.initialize() 339 initial_finished, initial_inputs, initial_state = decoder.initialize( 448 initial_state,
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/external/tensorflow/tensorflow/lite/experimental/examples/lstm/ |
D | rnn.py | 45 initial_state=None, argument 230 if initial_state is not None: 231 state = initial_state 374 initial_state=initial_state_fw, 413 initial_state=initial_state_bw,
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/external/tensorflow/tensorflow/contrib/cudnn_rnn/python/kernel_tests/ |
D | cudnn_rnn_test.py | 132 self._inputs, initial_state=self._initial_state, training=training) 145 def initial_state(self): member in CudnnTestModel 180 initial_state = (input_h, input_c) 182 initial_state = (input_h,) 183 return inputs, initial_state 196 initial_state = (input_h, input_c) 198 initial_state = (input_h,) 199 return initial_state 212 inputs_t, initial_state=initial_state_t, training=training) 215 def Feed(self, sess, inputs, initial_state=None, return_sum=True): argument [all …]
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