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Searched refs:initial_state (Results 1 – 25 of 146) sorted by relevance

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/external/v8/src/compiler/x64/
Dunwinding-info-writer-x64.cc20 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 …]
/external/tensorflow/tensorflow/contrib/rnn/python/ops/
Dfused_rnn_cell.py47 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,
/external/tensorflow/tensorflow/python/keras/layers/
Dlstm_test.py164 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 …]
Drecurrent_v2.py211 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
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Dconvolutional_recurrent.py280 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:
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Dwrappers.py435 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 …]
Dlstm_v2_test.py136 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 …]
Dcudnn_recurrent.py84 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 …]
Drecurrent.py627 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 …]
Dcudnn_recurrent_test.py135 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)
/external/tensorflow/tensorflow/contrib/recurrent/python/ops/
Dfunctional_rnn.py60 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)
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/external/v8/src/compiler/arm/
Dunwinding-info-writer-arm.cc20 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()
/external/v8/src/compiler/arm64/
Dunwinding-info-writer-arm64.cc20 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()
/external/tensorflow/tensorflow/contrib/crf/python/ops/
Dcrf.py212 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]
/external/tensorflow/tensorflow/contrib/seq2seq/python/kernel_tests/
Dbasic_decoder_v2_test.py65 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 …]
Ddecoder_v2_test.py63 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)
/external/tensorflow/tensorflow/contrib/learn/python/learn/ops/
Dseq2seq_ops.py99 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]):
/external/tensorflow/tensorflow/python/data/experimental/ops/
Dscan_ops.py34 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)
/external/toolchain-utils/automation/common/
Dstate_machine.py21 def __init__(self, initial_state): argument
22 assert initial_state in self.state_machine,\
25 self._state = initial_state
/external/tensorflow/tensorflow/python/ops/
Drnn.py441 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
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/external/tensorflow/tensorflow/contrib/cudnn_rnn/python/layers/
Dcudnn_rnn.py379 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
/external/tensorflow/tensorflow/contrib/seq2seq/python/ops/
Dbasic_decoder.py49 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,)
Ddecoder.py169 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,
/external/tensorflow/tensorflow/lite/experimental/examples/lstm/
Drnn.py45 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,
/external/tensorflow/tensorflow/contrib/cudnn_rnn/python/kernel_tests/
Dcudnn_rnn_test.py132 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
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