| /packages/modules/NeuralNetworks/common/operations/ |
| D | GroupedConv2D.cpp | 39 uint32_t filterWidth = getSizeOfDimension(filterShape, 2); \
72 for (uint32_t j = 0; j < filterWidth; j++) { in groupedConvFloat32()
80 i * filterWidth * filterDepth + j * filterDepth + k; in groupedConvFloat32()
91 filterBase += filterHeight * filterWidth * filterDepth; in groupedConvFloat32()
144 for (uint32_t j = 0; j < filterWidth; j++) { in groupedConvQuant8()
152 i * filterWidth * filterDepth + j * filterDepth + k; in groupedConvQuant8()
169 filterBase += filterHeight * filterWidth * filterDepth; in groupedConvQuant8()
248 for (uint32_t j = 0; j < filterWidth; j++) { in groupedConvQuant8PerChannel()
256 i * filterWidth * filterDepth + j * filterDepth + k; in groupedConvQuant8PerChannel()
273 filterBase += filterHeight * filterWidth * filterDepth; in groupedConvQuant8PerChannel()
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| D | TransposeConv2D.cpp | 76 int32_t filterWidth = getSizeOfDimension(filterShape, 2); in initialize() local
83 calculateExplicitPaddingTransposeConv(outputWidth, strideWidth, filterWidth, in initialize()
117 uint32_t filterWidth = getSizeOfDimension(filterShape, 2); \
149 for (uint32_t j = 0; j < filterWidth; j++, filterBase += inputDepth) { in transposeConvNhwc()
234 for (uint32_t j = 0; j < filterWidth; j++) { in transposeConvNhwc()
241 k * filterHeight * filterWidth * inputDepth + in transposeConvNhwc()
242 i * filterWidth * inputDepth + j * inputDepth + d; in transposeConvNhwc()
376 for (uint32_t j = 0; j < filterWidth; j++) { in transposeConvQuant8PerChannelNhwc()
383 k * filterHeight * filterWidth * inputDepth + in transposeConvQuant8PerChannelNhwc()
384 i * filterWidth * inputDepth + j * inputDepth + d; in transposeConvQuant8PerChannelNhwc()
[all …]
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| D | Conv2D.cpp | 137 uint32_t filterWidth = getSizeOfDimension(filterShape, 2); \
149 im2colDim.sizes[0] = (int)inDepth * filterHeight * filterWidth; \
367 uint32_t filterWidth = getSizeOfDimension(filterShape, 2); in convQuant8PerChannelNhwc() local
408 for (uint32_t j = 0; j < filterWidth; j++) { in convQuant8PerChannelNhwc()
418 i * filterWidth * filterDepth + j * filterDepth + k; in convQuant8PerChannelNhwc()
434 filterBase += filterHeight * filterWidth * filterDepth; in convQuant8PerChannelNhwc()
460 uint32_t filterWidth = getSizeOfDimension(filterShape, 2); in convQuant8PerChannelNhwc() local
666 uint32_t filterWidth = getSizeOfDimension(filter, 2); in prepare() local
675 int32_t effectiveFilterWidth = (filterWidth - 1) * param.dilation_width_factor + 1; in prepare()
683 computeOutSize(width, filterWidth, param.stride_width, param.dilation_width_factor, in prepare()
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| D | DepthwiseConv2D.cpp | 126 uint32_t filterWidth = getSizeOfDimension(filterShape, 2); \
294 uint32_t filterWidth = getSizeOfDimension(filterShape, 2); in depthwiseConvQuant8PerChannelNhwc() local
336 for (uint32_t j = 0; j < filterWidth; j++) { in depthwiseConvQuant8PerChannelNhwc()
345 i * filterWidth * filterDepth + j * filterDepth + oc; in depthwiseConvQuant8PerChannelNhwc()
551 uint32_t filterWidth = getSizeOfDimension(filter, 2); in prepare() local
554 int32_t effectiveFilterWidth = (filterWidth - 1) * param.dilation_width_factor + 1; in prepare()
565 computeOutSize(width, filterWidth, param.stride_width, param.dilation_width_factor, in prepare()
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| /packages/modules/NeuralNetworks/runtime/test/fuzzing/operation_signatures/ |
| D | Poolings.cpp | 34 auto filterWidth = op->inputs[7]->value<RandomVariable>(); in poolingExplicitOpConstructor() local
59 explicitPadding(op->inputs[0]->dimensions[widthIndex], filterWidth, strideWidth, /*dilation=*/1, in poolingExplicitOpConstructor()
73 auto filterWidth = op->inputs[4]->value<RandomVariable>(); in poolingImplicitOpConstructor() local
95 implicitPadding(op->inputs[0]->dimensions[widthIndex], filterWidth, strideWidth, in poolingImplicitOpConstructor()
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| /packages/modules/NeuralNetworks/common/ |
| D | OperationsUtils.cpp | 735 uint32_t filterWidth = getSizeOfDimension(filter, 2); in groupedConvPrepare() local
739 NN_RET_CHECK_GT(static_cast<int32_t>(filterWidth), padding_left); in groupedConvPrepare()
740 NN_RET_CHECK_GT(static_cast<int32_t>(filterWidth), padding_right); in groupedConvPrepare()
745 computeOutSize(width, filterWidth, stride_width, padding_left, padding_right); in groupedConvPrepare()
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| /packages/modules/NeuralNetworks/common/include/ |
| D | OperationsUtils.h | 222 int32_t strideHeight, int32_t filterWidth, in getPaddingScheme() argument
233 calculateExplicitPadding(inWidth, strideWidth, filterWidth, kPaddingSame, &expectedPaddingLeft, in getPaddingScheme()
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| /packages/modules/NeuralNetworks/runtime/test/ |
| D | TestValidateOperations.cpp | 1844 ANeuralNetworksOperandType filterWidth = scalar; in poolingOpTest() local
1850 strideHeight, filterWidth, filterHeight, activation}, in poolingOpTest()
1857 {input, padImplicit, strideWidth, strideHeight, filterWidth, filterHeight, activation}, in poolingOpTest()
1869 {input, padLeft, padRight, padTop, padBottom, strideWidth, strideHeight, filterWidth, in poolingOpTest()
1876 filterWidth, filterHeight, activation, layout}, in poolingOpTest()
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