/frameworks/ml/nn/runtime/test/specs/V1_2/ |
D | bidirectional_sequence_rnn.mod.py | 84 input_size = 8 variable 210 num_batches, max_time, input_size)), 212 fw_num_units, input_size)), 220 bw_num_units, input_size)), 260 max_time, num_batches, input_size)), 262 fw_num_units, input_size)), 270 bw_num_units, input_size)), 292 [num_batches, max_time, input_size]), 313 max_time, num_batches, input_size)), 315 fw_num_units, input_size)), [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 41 input_size]).transpose([1, 0, 2]).flatten().tolist() 46 input_size = 8 variable 142 num_batches, max_time, input_size)), 144 num_units, input_size)), 164 max_time, num_batches, input_size)), 166 num_units, input_size)), 177 input_size),
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D | rnn_float16.mod.py | 19 input_size = 8 variable 23 input = Input("input", "TENSOR_FLOAT16", "{%d, %d}" % (batches, input_size)) 24 weights = Input("weights", "TENSOR_FLOAT16", "{%d, %d}" % (units, input_size)) 184 input_sequence_size = int(len(test_inputs) / input_size / batches) 189 input_begin = i * input_size 190 input_end = input_begin + input_size
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D | svdf_bias_present_float16.mod.py | 21 input_size = 3 variable 26 input = Input("input", "TENSOR_FLOAT16", "{%d, %d}" % (batches, input_size)) 27 weights_feature = Input("weights_feature", "TENSOR_FLOAT16", "{%d, %d}" % (features, input_size)) 132 batch_start = i * input_size * batches 133 batch_end = batch_start + input_size * batches
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D | svdf_float16.mod.py | 21 input_size = 3 variable 26 input = Input("input", "TENSOR_FLOAT16", "{%d, %d}" % (batches, input_size)) 27 weights_feature = Input("weights_feature", "TENSOR_FLOAT16", "{%d, %d}" % (features, input_size)) 132 batch_start = i * input_size * batches 133 batch_end = batch_start + input_size * batches
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D | svdf_state_float16.mod.py | 19 input_size = 3 variable 24 input = Input("input", "TENSOR_FLOAT16", "{%d, %d}" % (batches, input_size)) 25 weights_feature = Input("weights_feature", "TENSOR_FLOAT16", "{%d, %d}" % (units, input_size))
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/frameworks/ml/nn/runtime/test/specs/V1_3/ |
D | bidirectional_sequence_rnn_state_output.mod.py | 92 input_size = 8 variable 221 "{{ {}, {}, {} }}".format(num_batches, max_time, input_size)), 223 "{{ {}, {} }}".format(fw_num_units, input_size)), 231 "{{ {}, {} }}".format(bw_num_units, input_size)), 277 "{{ {}, {}, {} }}".format(max_time, num_batches, input_size)), 279 "{{ {}, {} }}".format(fw_num_units, input_size)), 287 "{{ {}, {} }}".format(bw_num_units, input_size)), 313 [num_batches, max_time, input_size]), 336 "{{ {}, {}, {} }}".format(max_time, num_batches, input_size)), 338 "{{ {}, {} }}".format(fw_num_units, input_size)), [all …]
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D | bidirectional_sequence_rnn_1_3.mod.py | 90 input_size = 8 variable 216 "{{ {}, {}, {} }}".format(num_batches, max_time, input_size)), 218 "{{ {}, {} }}".format(fw_num_units, input_size)), 226 "{{ {}, {} }}".format(bw_num_units, input_size)), 235 "{{ {}, {}, {} }}".format(num_batches, max_time, input_size)), 248 fw_weights_data=[0] * fw_num_units * input_size, 266 "{{ {}, {}, {} }}".format(max_time, num_batches, input_size)), 268 "{{ {}, {} }}".format(fw_num_units, input_size)), 276 "{{ {}, {} }}".format(bw_num_units, input_size)), 285 "{{ {}, {}, {} }}".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 49 input_size = 8 variable 180 "{{{}, {}, {}}}".format(num_batches, max_time, input_size)), 182 "{{{}, {}}}".format(num_units, input_size)), 206 "{{{}, {}, {}}}".format(max_time, num_batches, input_size)), 208 "{{{}, {}}}".format(num_units, input_size)), 221 input_size),
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D | qlstm_noprojection.mod.py | 23 input_size = 5 variable 27 InputType = ("TENSOR_QUANT8_ASYMM_SIGNED", [batch_size, input_size], 0.0078125, 0) 30 InputWeightsType = ("TENSOR_QUANT8_SYMM", [num_units, input_size], 0.00784314, 0)
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/frameworks/ml/nn/runtime/test/specs/V1_1/ |
D | rnn_relaxed.mod.py | 19 input_size = 8 variable 23 input = Input("input", "TENSOR_FLOAT32", "{%d, %d}" % (batches, input_size)) 24 weights = Input("weights", "TENSOR_FLOAT32", "{%d, %d}" % (units, input_size)) 185 input_sequence_size = int(len(test_inputs) / input_size / batches) 190 input_begin = i * input_size 191 input_end = input_begin + input_size
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D | svdf2_relaxed.mod.py | 21 input_size = 3 variable 26 input = Input("input", "TENSOR_FLOAT32", "{%d, %d}" % (batches, input_size)) 27 weights_feature = Input("weights_feature", "TENSOR_FLOAT32", "{%d, %d}" % (features, input_size)) 148 batch_start = i * input_size * batches 149 batch_end = batch_start + input_size * batches
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D | svdf_relaxed.mod.py | 21 input_size = 3 variable 26 input = Input("input", "TENSOR_FLOAT32", "{%d, %d}" % (batches, input_size)) 27 weights_feature = Input("weights_feature", "TENSOR_FLOAT32", "{%d, %d}" % (features, input_size)) 133 batch_start = i * input_size * batches 134 batch_end = batch_start + input_size * batches
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D | svdf_bias_present_relaxed.mod.py | 21 input_size = 3 variable 26 input = Input("input", "TENSOR_FLOAT32", "{%d, %d}" % (batches, input_size)) 27 weights_feature = Input("weights_feature", "TENSOR_FLOAT32", "{%d, %d}" % (features, input_size)) 133 batch_start = i * input_size * batches 134 batch_end = batch_start + input_size * batches
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D | rnn_state_relaxed.mod.py | 19 input_size = 8 variable 23 input = Input("input", "TENSOR_FLOAT32", "{%d, %d}" % (batches, input_size)) 24 weights = Input("weights", "TENSOR_FLOAT32", "{%d, %d}" % (units, input_size))
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D | svdf_state_relaxed.mod.py | 19 input_size = 3 variable 24 input = Input("input", "TENSOR_FLOAT32", "{%d, %d}" % (batches, input_size)) 25 weights_feature = Input("weights_feature", "TENSOR_FLOAT32", "{%d, %d}" % (units, input_size))
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/frameworks/ml/nn/runtime/test/specs/V1_0/ |
D | rnn.mod.py | 19 input_size = 8 variable 23 input = Input("input", "TENSOR_FLOAT32", "{%d, %d}" % (batches, input_size)) 24 weights = Input("weights", "TENSOR_FLOAT32", "{%d, %d}" % (units, input_size)) 184 input_sequence_size = int(len(test_inputs) / input_size / batches) 189 input_begin = i * input_size 190 input_end = input_begin + input_size
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D | svdf.mod.py | 21 input_size = 3 variable 26 input = Input("input", "TENSOR_FLOAT32", "{%d, %d}" % (batches, input_size)) 27 weights_feature = Input("weights_feature", "TENSOR_FLOAT32", "{%d, %d}" % (features, input_size)) 132 batch_start = i * input_size * batches 133 batch_end = batch_start + input_size * batches
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D | svdf_bias_present.mod.py | 21 input_size = 3 variable 26 input = Input("input", "TENSOR_FLOAT32", "{%d, %d}" % (batches, input_size)) 27 weights_feature = Input("weights_feature", "TENSOR_FLOAT32", "{%d, %d}" % (features, input_size)) 132 batch_start = i * input_size * batches 133 batch_end = batch_start + input_size * batches
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D | svdf2.mod.py | 21 input_size = 3 variable 26 input = Input("input", "TENSOR_FLOAT32", "{%d, %d}" % (batches, input_size)) 27 weights_feature = Input("weights_feature", "TENSOR_FLOAT32", "{%d, %d}" % (features, input_size)) 147 batch_start = i * input_size * batches 148 batch_end = batch_start + input_size * batches
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D | rnn_state.mod.py | 19 input_size = 8 variable 23 input = Input("input", "TENSOR_FLOAT32", "{%d, %d}" % (batches, input_size)) 24 weights = Input("weights", "TENSOR_FLOAT32", "{%d, %d}" % (units, input_size))
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D | svdf_state.mod.py | 19 input_size = 3 variable 24 input = Input("input", "TENSOR_FLOAT32", "{%d, %d}" % (batches, input_size)) 25 weights_feature = Input("weights_feature", "TENSOR_FLOAT32", "{%d, %d}" % (units, input_size))
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/frameworks/av/media/libaudioprocessing/tests/fuzzer/ |
D | libaudioprocessing_resampler_fuzzer.cpp | 158 size_t input_size = size - metadata_size; in LLVMFuzzerTestOneInput() local 159 uint8_t input_data[input_size]; in LLVMFuzzerTestOneInput() 160 memcpy(input_data, &data[metadata_size], input_size); in LLVMFuzzerTestOneInput() 162 size_t input_frames = input_size / input_frame_size; in LLVMFuzzerTestOneInput()
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/frameworks/ml/nn/common/operations/ |
D | RNNTest.cpp | 187 uint32_t input_size() const { return input_size_; } in input_size() function in android::nn::wrapper::BasicRNNOpModel 283 sizeof(rnn_input) / sizeof(float) / (rnn.input_size() * rnn.num_batches()); in TEST() 286 float* batch_start = rnn_input + i * rnn.input_size(); in TEST() 287 float* batch_end = batch_start + rnn.input_size(); in TEST() 289 rnn.SetInput(rnn.input_size(), batch_start, batch_end); in TEST()
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/frameworks/av/media/libaudioprocessing/tests/ |
D | test-resampler.cpp | 209 size_t input_size; in main() local 219 input_size = info.frames * info.channels * sizeof(short); in main() 220 input_vaddr = malloc(input_size); in main() 231 input_size = channels * sizeof(int16_t) * input_frames; in main() 232 input_vaddr = malloc(input_size); in main() 244 size_t input_frames = input_size / input_framesize; in main() 251 input_size = input_frames * input_framesize; in main() 252 new_vaddr = malloc(input_size); in main()
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