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Searched refs:batch_size (Results 1 – 19 of 19) sorted by relevance

/aosp12/packages/modules/NeuralNetworks/common/operations/
H A DSVDF.cpp81 const uint32_t batch_size = SizeOfDimension(input, 0); in Prepare() local
97 stateShape->dimensions = {batch_size, memory_size * num_filters}; in Prepare()
103 outputShape->dimensions = {batch_size, num_units}; in Prepare()
168 const int batch_size = SizeOfDimension(input_, 0); in EvalFloat32() local
176 for (int b = 0; b < batch_size; b++) { in EvalFloat32()
185 float scratch[batch_size * num_filters]; in EvalFloat32()
186 std::fill_n(scratch, batch_size * num_filters, 0.0f); in EvalFloat32()
192 for (int i = 0; i < batch_size * num_filters; ++i) { in EvalFloat32()
198 for (int b = 0; b < batch_size; b++) { in EvalFloat32()
214 tflite::tensor_utils::ApplyActivationToVector(outputData, batch_size * num_units, in EvalFloat32()
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H A DMultinomial.cpp74 const uint32_t batch_size = SizeOfDimension(input, 0); in Prepare() local
79 outputShape->dimensions = {batch_size, sample_count}; in Prepare()
108 const int batch_size = SizeOfDimension(input_, 0); in EvalFloat32() local
120 random_generator.ReserveRandomOutputs(batch_size * sample_count_aligned, 256); in EvalFloat32()
123 for (uint64_t b = 0; b < batch_size; ++b) { in EvalFloat32()
H A DFullyConnected.cpp66 uint32_t batch_size = getSizeOfDimension(outputShape, 0); in fullyConnectedFloat32() local
68 if (batch_size * batch_size == input_n_elements) { in fullyConnectedFloat32()
206 uint32_t batch_size = input_size == 0 ? 0 : input_n_elements / input_size; in validateShapes() local
207 if (batch_size != 0) { in validateShapes()
208 NN_RET_CHECK_EQ(input_size * batch_size, input_n_elements); in validateShapes()
218 output->dimensions = {batch_size, num_units}; in validateShapes()
H A DRNN.cpp61 const uint32_t batch_size = SizeOfDimension(input, 0); in Prepare() local
72 hiddenStateShape->dimensions = {batch_size, num_units}; in Prepare()
76 outputShape->dimensions = {batch_size, num_units}; in Prepare()
145 const uint32_t batch_size = inputShape.dimensions[0]; in RNNStep() local
160 for (uint32_t b = 0; b < batch_size; b++) { in RNNStep()
H A DMultinomialTest.cpp39 MultinomialOpModel(uint32_t batch_size, uint32_t class_size, uint32_t sample_size) in MultinomialOpModel() argument
40 : batch_size_(batch_size), class_size_(class_size), sample_size_(sample_size) { in MultinomialOpModel()
/aosp12/packages/modules/NeuralNetworks/runtime/test/specs/V1_3/
H A Dqlstm_projection.mod.py22 batch_size = 2 variable
27 InputType = ("TENSOR_QUANT8_ASYMM_SIGNED", [batch_size, input_size], 0.0078125, 0)
58 OutputStateType = ("TENSOR_QUANT8_ASYMM_SIGNED", [batch_size, output_size], 3.05176e-05, 0)
59 CellStateType = ("TENSOR_QUANT16_SYMM", [batch_size, num_units], 3.05176e-05, 0)
134 output_state_in: [ 0 for _ in range(batch_size * output_size) ],
135 cell_state_in: [ 0 for _ in range(batch_size * num_units) ],
191 output_state_in: [ 0 for _ in range(batch_size * output_size) ],
192 cell_state_in: [ 0 for _ in range(batch_size * num_units) ],
H A Dqlstm_noprojection.mod.py22 batch_size = 2 variable
27 InputType = ("TENSOR_QUANT8_ASYMM_SIGNED", [batch_size, input_size], 0.0078125, 0)
58 OutputStateType = ("TENSOR_QUANT8_ASYMM_SIGNED", [batch_size, output_size], 3.05176e-05, 0)
59 CellStateType = ("TENSOR_QUANT16_SYMM", [batch_size, num_units], 3.05176e-05, 0)
128 output_state_in: [ 0 for _ in range(batch_size * output_size) ],
129 cell_state_in: [ 0 for _ in range(batch_size * num_units) ],
/aosp12/system/bt/gd/l2cap/classic/cert/
H A Dl2cap_performance_test.py57 def _basic_mode_tx_fixed_interval(self, mtu, interval=timedelta(seconds=10), batch_size=20): argument
69 for _ in range(batch_size):
71 packets_sent += batch_size
72 … assertThat(cert_channel).emits(L2capMatchers.Data(b'a' * mtu), at_least_times=batch_size)
/aosp12/hardware/interfaces/neuralnetworks/1.0/
H A Dtypes.hal930 * A 2-D tensor of shape [batch_size, input_size], where “batch_size”
971 * A 2-D tensor of shape [batch_size, output_size].
973 * A 2-D tensor of shape [batch_size, num_units].
993 * [batch_size, num_units * 4] without CIFG.
995 * A 2-D tensor of shape [batch_size, output_size].
997 * A 2-D tensor of shape [batch_size, num_units].
1261 * A 2-D tensor of shape [batch_size, input_size], where “batch_size”
1273 * A 2-D tensor of shape [batch_size, num_units].
1281 * A 2-D tensor of shape [batch_size, num_units].
1405 * A 2-D tensor of shape [batch_size, input_size], where “batch_size”
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/aosp12/hardware/google/camera/devices/EmulatedCamera/hwl/
H A DJpegCompressor.cpp348 const uint32_t batch_size = DCTSIZE * max_vsamp_factor; in CompressYUV420Frame() local
354 jpeg_write_raw_data(cinfo.get(), planes, batch_size); in CompressYUV420Frame()
/aosp12/hardware/qcom/msm8996/kernel-headers/media/
H A Dmsmb_pproc.h70 uint32_t batch_size; member
/aosp12/hardware/qcom/msm8996/original-kernel-headers/media/
H A Dmsmb_pproc.h53 uint32_t batch_size; member
/aosp12/hardware/interfaces/neuralnetworks/1.3/
H A Dtypes.hal1215 * A 2-D tensor of shape [batch_size, input_size], where “batch_size”
1258 * A 2-D tensor of shape [batch_size, num_units].
1305 * [batch_size, num_units * 4] without CIFG.
1309 * A 2-D tensor of shape [batch_size, num_units].
1668 * A 2-D tensor of shape [batch_size, input_size], where “batch_size”
1680 * A 2-D tensor of shape [batch_size, num_units].
1688 * A 2-D tensor of shape [batch_size, num_units].
1836 * A 2-D tensor of shape [batch_size, input_size], where “batch_size”
1862 * [batch_size, num_units].
2640 * [max_time, batch_size, fw_output_size]
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/aosp12/hardware/interfaces/neuralnetworks/1.2/
H A Dtypes.hal1216 * A 2-D tensor of shape [batch_size, input_size], where “batch_size”
1259 * A 2-D tensor of shape [batch_size, num_units].
1306 * [batch_size, num_units * 4] without CIFG.
1310 * A 2-D tensor of shape [batch_size, num_units].
1630 * A 2-D tensor of shape [batch_size, input_size], where “batch_size”
1642 * A 2-D tensor of shape [batch_size, num_units].
1792 * A 2-D tensor of shape [batch_size, input_size], where “batch_size”
1818 * [batch_size, num_units].
2458 * A 3-D tensor of shape [max_time, batch_size, input_size], where “batch_size”
2537 * [max_time, batch_size, fw_output_size]
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/aosp12/hardware/qcom/msm8994/kernel-headers/media/
H A Dmsmb_pproc.h189 uint32_t batch_size; member
/aosp12/hardware/qcom/msm8994/original-kernel-headers/media/
H A Dmsmb_pproc.h187 uint32_t batch_size; member
/aosp12/packages/modules/NeuralNetworks/tools/api/
H A Dtypes.spec1651 * A 2-D tensor of shape [batch_size, input_size], where “batch_size”
1692 * A 2-D tensor of shape [batch_size, output_size].
1694 * A 2-D tensor of shape [batch_size, num_units].
1745 * [batch_size, num_units * 4] without CIFG.
1747 * A 2-D tensor of shape [batch_size, output_size].
1749 * A 2-D tensor of shape [batch_size, num_units].
2196 * A 2-D tensor of shape [batch_size, input_size], where “batch_size”
2208 * A 2-D tensor of shape [batch_size, num_units].
2216 * A 2-D tensor of shape [batch_size, num_units].
2400 * A 2-D tensor of shape [batch_size, input_size], where “batch_size”
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/aosp12/hardware/qcom/camera/msm8998/QCamera2/stack/common/
H A Dcam_types.h1846 uint8_t batch_size; member
/aosp12/hardware/qcom/camera/msm8998/QCamera2/HAL/
H A DQCameraParameters.cpp13714 stream_config_info.batch_size = getBufBatchCount(); in setStreamConfigure()
13723 stream_config_info.batch_size); in setStreamConfigure()