| /frameworks/ml/nn/common/operations/ |
| D | GroupedConv2D.cpp | 35 uint32_t filterWidth = getSizeOfDimension(filterShape, 2); \
68 for (uint32_t j = 0; j < filterWidth; j++) { in groupedConvFloat32()
76 i * filterWidth * filterDepth + j * filterDepth + k; in groupedConvFloat32()
87 filterBase += filterHeight * filterWidth * filterDepth; in groupedConvFloat32()
139 for (uint32_t j = 0; j < filterWidth; j++) { in groupedConvQuant8()
147 i * filterWidth * filterDepth + j * filterDepth + k; in groupedConvQuant8()
164 filterBase += filterHeight * filterWidth * filterDepth; in groupedConvQuant8()
225 for (uint32_t j = 0; j < filterWidth; j++) { in groupedConvQuant8PerChannel()
233 i * filterWidth * filterDepth + j * filterDepth + k; in groupedConvQuant8PerChannel()
250 filterBase += filterHeight * filterWidth * filterDepth; in groupedConvQuant8PerChannel()
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| D | TransposeConv2D.cpp | 66 int32_t filterWidth = getSizeOfDimension(filterShape, 2); in initialize() local
73 calculateExplicitPaddingTransposeConv(outputWidth, strideWidth, filterWidth, in initialize()
106 uint32_t filterWidth = getSizeOfDimension(filterShape, 2); \
138 for (uint32_t j = 0; j < filterWidth; j++, filterBase += inputDepth) { in transposeConvNhwc()
223 for (uint32_t j = 0; j < filterWidth; j++) { in transposeConvNhwc()
230 k * filterHeight * filterWidth * inputDepth + in transposeConvNhwc()
231 i * filterWidth * inputDepth + j * inputDepth + d; in transposeConvNhwc()
364 for (uint32_t j = 0; j < filterWidth; j++) { in transposeConvQuant8PerChannelNhwc()
371 k * filterHeight * filterWidth * inputDepth + in transposeConvQuant8PerChannelNhwc()
372 i * filterWidth * inputDepth + j * inputDepth + d; in transposeConvQuant8PerChannelNhwc()
[all …]
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| D | DepthwiseConv2D.cpp | 58 uint32_t filterWidth = getSizeOfDimension(filterShape, 2); \
166 uint32_t filterWidth = getSizeOfDimension(filterShape, 2); in depthwiseConvQuant8PerChannel() local
208 for (uint32_t j = 0; j < filterWidth; j++) { in depthwiseConvQuant8PerChannel()
217 i * filterWidth * filterDepth + j * filterDepth + oc; in depthwiseConvQuant8PerChannel()
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| D | Conv2D.cpp | 123 uint32_t filterWidth = getSizeOfDimension(filterShape, 2); \
135 im2colDim.sizes[0] = (int)inDepth * filterHeight * filterWidth; \
297 uint32_t filterWidth = getSizeOfDimension(filterShape, 2); in convQuant8PerChannelNhwc() local
338 for (uint32_t j = 0; j < filterWidth; j++) { in convQuant8PerChannelNhwc()
348 i * filterWidth * filterDepth + j * filterDepth + k; in convQuant8PerChannelNhwc()
364 filterBase += filterHeight * filterWidth * filterDepth; in convQuant8PerChannelNhwc()
517 uint32_t filterWidth = getSizeOfDimension(filter, 2); in prepare() local
526 int32_t effectiveFilterWidth = (filterWidth - 1) * param.dilation_width_factor + 1; in prepare()
534 computeOutSize(width, filterWidth, param.stride_width, param.dilation_width_factor, in prepare()
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| /frameworks/ml/nn/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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| /frameworks/ml/nn/common/ |
| D | OperationsUtils.cpp | 375 uint32_t filterWidth = getSizeOfDimension(filter, 2); in depthwiseConvPrepare() local
380 int32_t effectiveFilterWidth = (filterWidth - 1) * dilation_width_factor + 1; in depthwiseConvPrepare()
387 uint32_t outWidth = computeOutSize(width, filterWidth, stride_width, dilation_width_factor, in depthwiseConvPrepare()
892 uint32_t filterWidth = getSizeOfDimension(filter, 2); in groupedConvPrepare() local
896 NN_RET_CHECK_GT(static_cast<int32_t>(filterWidth), padding_left); in groupedConvPrepare()
897 NN_RET_CHECK_GT(static_cast<int32_t>(filterWidth), padding_right); in groupedConvPrepare()
902 computeOutSize(width, filterWidth, stride_width, padding_left, padding_right); in groupedConvPrepare()
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| /frameworks/ml/nn/common/include/ |
| D | OperationsUtils.h | 235 int32_t filterWidth, int32_t filterHeight, in getPaddingScheme() argument
245 calculateExplicitPadding(inWidth, strideWidth, filterWidth, kPaddingSame, in getPaddingScheme()
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| /frameworks/ml/nn/runtime/test/ |
| D | TestValidateOperations.cpp | 1010 ANeuralNetworksOperandType filterWidth = scalar; in poolingOpTest() local
1016 strideHeight, filterWidth, filterHeight, activation}, in poolingOpTest()
1023 {input, padImplicit, strideWidth, strideHeight, filterWidth, filterHeight, activation}, in poolingOpTest()
1035 {input, padLeft, padRight, padTop, padBottom, strideWidth, strideHeight, filterWidth, in poolingOpTest()
1042 filterWidth, filterHeight, activation, layout}, in poolingOpTest()
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