| /frameworks/ml/nn/runtime/test/specs/V1_3/ |
| D | bidirectional_sequence_rnn_state_output.mod.py | 90 num_batches = 2 variable
221 "{{ {}, {}, {} }}".format(num_batches, max_time, input_size)),
229 "{{ {}, {} }}".format(num_batches, fw_num_units)),
237 "{{ {}, {} }}".format(num_batches, bw_num_units)),
246 "{{ {}, {}, {} }}".format(num_batches, max_time, fw_num_units)),
249 "{{ {}, {}, {} }}".format(num_batches, max_time, bw_num_units)),
252 "{{ {}, {} }}".format(num_batches, fw_num_units)),
255 "{{ {}, {} }}".format(num_batches, bw_num_units)),
260 fw_hidden_state_data=[0] * num_batches * fw_num_units,
264 bw_hidden_state_data=[0] * num_batches * bw_num_units,
[all …]
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| D | bidirectional_sequence_rnn_1_3.mod.py | 88 num_batches = 2 variable
216 "{{ {}, {}, {} }}".format(num_batches, max_time, input_size)),
224 "{{ {}, {} }}".format(num_batches, fw_num_units)),
232 "{{ {}, {} }}".format(num_batches, bw_num_units)),
235 "{{ {}, {}, {} }}".format(num_batches, max_time, input_size)),
240 "{{ {}, {}, {} }}".format(num_batches, max_time, fw_num_units)),
243 "{{ {}, {}, {} }}".format(num_batches, max_time, bw_num_units)),
251 fw_hidden_state_data=[0] * num_batches * fw_num_units,
255 bw_hidden_state_data=[0] * num_batches * bw_num_units,
266 "{{ {}, {}, {} }}".format(max_time, num_batches, input_size)),
[all …]
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| D | unidirectional_sequence_rnn.mod.py | 42 def convert_to_time_major(tensor, num_batches, max_time, input_size): argument
43 return np.array(tensor).reshape([num_batches, max_time, input_size
47 num_batches = 2 variable
180 "{{{}, {}, {}}}".format(num_batches, max_time, input_size)),
187 "{{{}, {}}}".format(num_batches, num_units)),
189 "{{{}, {}, {}}}".format(num_batches, max_time, num_units)),
191 "{{{}, {}}}".format(num_batches, num_units)),
198 hidden_state_data=[0] * num_batches * num_units,
206 "{{{}, {}, {}}}".format(max_time, num_batches, input_size)),
213 "{{{}, {}}}".format(num_batches, num_units)),
[all …]
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| /frameworks/ml/nn/runtime/test/specs/V1_2/ |
| D | bidirectional_sequence_rnn.mod.py | 82 num_batches = 2 variable
210 num_batches, max_time, input_size)),
218 "{{ {}, {} }}".format(num_batches, fw_num_units)),
226 "{{ {}, {} }}".format(num_batches, bw_num_units)),
234 num_batches, max_time, fw_num_units)),
237 num_batches, max_time, bw_num_units)),
245 fw_hidden_state_data=[0] * num_batches * fw_num_units,
249 bw_hidden_state_data=[0] * num_batches * bw_num_units,
260 max_time, num_batches, input_size)),
268 "{{ {}, {} }}".format(num_batches, fw_num_units)),
[all …]
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| D | unidirectional_sequence_rnn.mod.py | 39 def convert_to_time_major(tensor, num_batches, max_time, input_size): argument
40 return np.array(tensor).reshape([num_batches, max_time,
44 num_batches = 2 variable
142 num_batches, max_time, input_size)),
149 num_batches, num_units)),
151 num_batches, max_time, num_units)),
158 hidden_state_data=[0] * num_batches * num_units,
164 max_time, num_batches, input_size)),
171 num_batches, num_units)),
173 max_time, num_batches, num_units)),
[all …]
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| /frameworks/ml/nn/common/operations/ |
| D | SVDFTest.cpp | 295 int num_batches() const { return batches_; } in num_batches() function in android::nn::wrapper::SVDFOpModel
336 const int svdf_num_batches = svdf.num_batches(); in TEST()
395 const int svdf_num_batches = svdf.num_batches(); in TEST()
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| D | RNNTest.cpp | 189 uint32_t num_batches() const { return batches_; } in num_batches() function in android::nn::wrapper::BasicRNNOpModel
283 sizeof(rnn_input) / sizeof(float) / (rnn.input_size() * rnn.num_batches()); in TEST()
|