Searched refs:time_steps (Results 1 – 11 of 11) sorted by relevance
| /external/libtextclassifier/native/tensorflow_models/seq_flow_lite/tflite_ops/ |
| D | layer_norm.cc | 172 int time_steps = static_cast<int>(GetNumberOfSteps(input) / num_features); in FlexibleLayerNorm() local
174 std::vector<float> sum_x(time_steps, 0.0f); in FlexibleLayerNorm()
175 std::vector<float> sum_xx(time_steps, 0.0f); in FlexibleLayerNorm()
193 std::vector<float> multiplier(time_steps, 1.0f); in FlexibleLayerNorm()
194 std::vector<float> bias(time_steps, 0.0f); in FlexibleLayerNorm()
197 for (int i = 0; i < time_steps; ++i) { in FlexibleLayerNorm()
236 const int time_steps = in DefaultLayerNormFloat() local
239 for (int i = 0; i < time_steps; ++i) { in DefaultLayerNormFloat()
264 const int time_steps = in DefaultLayerNorm() local
271 for (int i = 0; i < time_steps; ++i) { in DefaultLayerNorm()
|
| /external/tensorflow/tensorflow/lite/experimental/examples/lstm/ |
| D | bidirectional_sequence_rnn_test.py | 44 self.time_steps = 28
105 "float", [batch_size, self.time_steps, self.n_input],
110 sequence_length = [self.time_steps] * batch_size
125 rnn_inputs = tf.unstack(x, self.time_steps, 1)
174 batch_x = batch_x.reshape((self.batch_size, self.time_steps,
237 sample_input = np.reshape(b1, (1, self.time_steps, self.n_input))
|
| D | unidirectional_sequence_rnn_test.py | 43 self.time_steps = 28
91 "float", [None, self.time_steps, self.n_input], name="INPUT_IMAGE")
100 rnn_input = tf.unstack(x, self.time_steps, 1)
138 batch_x = batch_x.reshape((self.batch_size, self.time_steps,
189 sample_input = np.reshape(b1, (1, self.time_steps, self.n_input))
|
| D | bidirectional_sequence_lstm_test.py | 46 self.time_steps = 28
98 "float", [None, self.time_steps, self.n_input], name="INPUT_IMAGE")
113 lstm_input = tf.unstack(x, self.time_steps, 1)
153 batch_x = batch_x.reshape((self.batch_size, self.time_steps,
209 sample_input = np.reshape(b1, (1, self.time_steps, self.n_input))
|
| D | unidirectional_sequence_lstm_test.py | 46 self.time_steps = 28
95 "float", [None, self.time_steps, self.n_input], name="INPUT_IMAGE")
104 lstm_input = tf.unstack(x, self.time_steps, 1)
143 batch_x = batch_x.reshape((self.batch_size, self.time_steps,
194 sample_input = np.reshape(b1, (1, self.time_steps, self.n_input))
|
| /external/tensorflow/tensorflow/python/ops/ |
| D | rnn.py | 754 time_steps = input_shape[0]
792 max_sequence_length = time_steps
802 size=time_steps,
825 output_ta = tuple([0 for _ in range(time_steps.numpy())]
882 loop_bound = math_ops.minimum(time_steps,
886 loop_bound = time_steps
893 maximum_iterations=time_steps,
|
| /external/tensorflow/tensorflow/python/kernel_tests/ |
| D | rnn_cell_test.py | 1124 time_steps = 8
1130 input_values = np.random.randn(time_steps, batch_size, input_size).astype(
1134 sequence_length = np.random.randint(0, time_steps, size=batch_size)
1157 dtypes.float32, shape=(time_steps, batch_size, input_size))
1217 dtypes.float32, shape=(time_steps, batch_size, input_size))
1240 split_outputs_dynamic = array_ops.unstack(outputs_dynamic, time_steps)
1978 time_steps = 8
1983 input_values = np.random.randn(time_steps, batch_size, input_size)
1985 sequence_length = np.random.randint(0, time_steps, size=batch_size)
1989 dtypes.float32, shape=(time_steps, batch_size, input_size))
[all …]
|
| /external/tensorflow/tensorflow/python/profiler/ |
| D | model_analyzer_test.py | 639 time_steps = [2, 3]
647 pctx.add_auto_profiling('scope', time_opts, time_steps)
650 self._trainLoop(x, 10, time_dir, time_steps,
|
| /external/tensorflow/tensorflow/python/debug/lib/ |
| D | session_debug_testlib.py | 570 time_steps = 4
573 input_values = np.random.randn(time_steps, batch_size, input_size)
574 sequence_length = np.random.randint(0, time_steps, size=batch_size)
576 dtypes.float32, shape=(time_steps, batch_size, input_size))
|
| /external/tensorflow/tensorflow/python/keras/layers/ |
| D | gru_v2_test.py | 677 time_steps = 10
687 x = random_ops.random_uniform([1, time_steps, embedding_size])
|
| /external/tensorflow/tensorflow/python/keras/ |
| D | backend.py | 4325 time_steps = flatted_inputs[0].shape[0]
4361 if not time_steps:
4392 for i in range(time_steps):
4429 for i in range(time_steps):
4625 shape[0] = time_steps
|