/frameworks/ml/nn/common/operations/ |
H A D | Concatenation.cpp | 27 float* outputData, const Shape& outputShape) { 37 getNumberOfDimensions(outputShape) - axis - 1, 39 outputData, convertShapeToDims(outputShape)); 46 uint8_t* outputData, const Shape& outputShape) { 56 getNumberOfDimensions(outputShape) - axis - 1, 58 outputData, convertShapeToDims(outputShape)); 25 concatenationFloat32(const std::vector<const float*>& inputDataPtrs, const std::vector<Shape>& inputShapes, int32_t axis, float* outputData, const Shape& outputShape) argument 44 concatenationQuant8(const std::vector<const uint8_t*>& inputDataPtrs, const std::vector<Shape>& inputShapes, int32_t axis, uint8_t* outputData, const Shape& outputShape) argument
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H A D | Normalization.cpp | 26 float* outputData, const Shape& outputShape) { 29 outputData, convertShapeToDims(outputShape)); 35 uint8_t* outputData, const Shape& outputShape) { 39 outputData, convertShapeToDims(outputShape)); 46 float* outputData, const Shape& outputShape) { 50 outputData, convertShapeToDims(outputShape)); 25 l2normFloat32(const float* inputData, const Shape& inputShape, float* outputData, const Shape& outputShape) argument 34 l2normQuant8(const uint8_t* inputData, const Shape& inputShape, uint8_t* outputData, const Shape& outputShape) argument 44 localResponseNormFloat32(const float* inputData, const Shape& inputShape, int32_t radius, float bias, float alpha, float beta, float* outputData, const Shape& outputShape) argument
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H A D | FullyConnected.cpp | 35 float* outputData, const Shape& outputShape) { 42 uint32_t batch_size = getSizeOfDimension(outputShape, 0); 50 outputData, convertShapeToDims(outputShape)); 57 outputData, convertShapeToDims(outputShape)); 66 uint8_t* outputData, const Shape& outputShape) { 69 int32_t outputOffset = outputShape.offset; 78 outputShape, &real_multiplier) || 83 CalculateActivationRangeUint8(activation, outputShape, 100 outputData, convertShapeToDims(outputShape), &gemm_context); 31 fullyConnectedFloat32(const float* inputData, const Shape& inputShape, const float* weightsData, const Shape& weightsShape, const float* biasData, const Shape& biasShape, int32_t activation, float* outputData, const Shape& outputShape) argument 62 fullyConnectedQuant8(const uint8_t* inputData, const Shape& inputShape, const uint8_t* weightsData, const Shape& weightsShape, const int32_t* biasData, const Shape& biasShape, int32_t activation, uint8_t* outputData, const Shape& outputShape) argument
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H A D | LSHProjection.cpp | 40 Shape *outputShape) { 58 outputShape->dimensions = { SizeOfDimension(hash, 0) }; 65 outputShape->dimensions = { SizeOfDimension(hash, 0) * SizeOfDimension(hash, 1) }; 72 outputShape->type = OperandType::TENSOR_INT32; 73 outputShape->offset = 0; 74 outputShape->scale = 0.f; 38 Prepare(const Operation &operation, std::vector<RunTimeOperandInfo>& operands, Shape *outputShape) argument
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H A D | Pooling.cpp | 28 uint32_t outHeight = getSizeOfDimension(outputShape, 1); \ 29 uint32_t outWidth = getSizeOfDimension(outputShape, 2); \ 39 float* outputData, const Shape& outputShape) { 52 outputData, convertShapeToDims(outputShape)); 62 uint8_t* outputData, const Shape& outputShape) { 69 CalculateActivationRangeUint8(activation, outputShape, 78 outputData, convertShapeToDims(outputShape)); 88 float* outputData, const Shape& outputShape) { 101 outputData, convertShapeToDims(outputShape)); 111 float* outputData, const Shape& outputShape) { 34 averagePoolFloat32(const float* inputData, const Shape& inputShape, int32_t padding_left, int32_t padding_right, int32_t padding_top, int32_t padding_bottom, int32_t stride_width, int32_t stride_height, int32_t filter_width, int32_t filter_height, int32_t activation, float* outputData, const Shape& outputShape) argument 57 averagePoolQuant8(const uint8_t* inputData, const Shape& inputShape, int32_t padding_left, int32_t padding_right, int32_t padding_top, int32_t padding_bottom, int32_t stride_width, int32_t stride_height, int32_t filter_width, int32_t filter_height, int32_t activation, uint8_t* outputData, const Shape& outputShape) argument 83 l2PoolFloat32(const float* inputData, const Shape& inputShape, int32_t padding_left, int32_t padding_right, int32_t padding_top, int32_t padding_bottom, int32_t stride_width, int32_t stride_height, int32_t filter_width, int32_t filter_height, int32_t activation, float* outputData, const Shape& outputShape) argument 106 maxPoolFloat32(const float* inputData, const Shape& inputShape, int32_t padding_left, int32_t padding_right, int32_t padding_top, int32_t padding_bottom, int32_t stride_width, int32_t stride_height, int32_t filter_width, int32_t filter_height, int32_t activation, float* outputData, const Shape& outputShape) argument 129 maxPoolQuant8(const uint8_t* inputData, const Shape& inputShape, int32_t padding_left, int32_t padding_right, int32_t padding_top, int32_t padding_bottom, int32_t stride_width, int32_t stride_height, int32_t filter_width, int32_t filter_height, int32_t activation, uint8_t* outputData, const Shape& outputShape) argument [all...] |
H A D | RNN.cpp | 43 Shape *outputShape) { 74 outputShape->type = inputShape.type; 75 outputShape->dimensions = { batch_size, num_units }; 40 Prepare(const Operation &operation, std::vector<RunTimeOperandInfo> &operands, Shape *hiddenStateShape, Shape *outputShape) argument
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H A D | StridedSlice.cpp | 33 uint8_t* outputData, const Shape& outputShape) { 79 convertShapeToDims(outputShape)); 87 convertShapeToDims(outputShape)); 29 stridedSliceGeneric(const uint8_t* inputData, const Shape& inputShape, const int32_t* beginData, const int32_t* endData, const int32_t* stridesData, int32_t beginMask, int32_t endMask, int32_t shrinkAxisMask, uint8_t* outputData, const Shape& outputShape) argument
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H A D | Activation.cpp | 26 float* outputData, const Shape& outputShape) { 35 float* outputData, const Shape& outputShape) { 44 float* outputData, const Shape& outputShape) { 53 float* outputData, const Shape& outputShape) { 62 float* outputData, const Shape& outputShape) { 72 float* outputData, const Shape& outputShape) { 109 uint8_t* outputData, const Shape& outputShape) { 115 uint8_t* outputData, const Shape& outputShape) { 121 uint8_t* outputData, const Shape& outputShape) { 129 uint8_t* outputData, const Shape& outputShape) { 25 reluFloat32(const float* inputData, const Shape& inputShape, float* outputData, const Shape& outputShape) argument 34 relu1Float32(const float* inputData, const Shape& inputShape, float* outputData, const Shape& outputShape) argument 43 relu6Float32(const float* inputData, const Shape& inputShape, float* outputData, const Shape& outputShape) argument 52 tanhFloat32(const float* inputData, const Shape& inputShape, float* outputData, const Shape& outputShape) argument 61 logisticFloat32(const float* inputData, const Shape& inputShape, float* outputData, const Shape& outputShape) argument 70 softmaxFloat32(const float* inputData, const Shape& inputShape, const float beta, float* outputData, const Shape& outputShape) argument 108 reluQuant8(const uint8_t* inputData, const Shape& inputShape, uint8_t* outputData, const Shape& outputShape) argument 114 relu1Quant8(const uint8_t* inputData, const Shape& inputShape, uint8_t* outputData, const Shape& outputShape) argument 120 relu6Quant8(const uint8_t* inputData, const Shape& inputShape, uint8_t* outputData, const Shape& outputShape) argument 128 logisticQuant8(const uint8_t* inputData, const Shape& inputShape, uint8_t* outputData, const Shape& outputShape) argument 161 softmaxQuant8(const uint8_t* inputData, const Shape& inputShape, const float beta, uint8_t* outputData, const Shape& outputShape) argument [all...] |
H A D | Conv2D.cpp | 39 uint32_t outHeight = getSizeOfDimension(outputShape, 1); \ 40 uint32_t outWidth = getSizeOfDimension(outputShape, 2); \ 47 im2colDim.sizes[3] = (int)getSizeOfDimension(outputShape, 0); \ 48 im2colDim.sizes[2] = (int)getSizeOfDimension(outputShape, 1); \ 49 im2colDim.sizes[1] = (int)getSizeOfDimension(outputShape, 2); \ 86 float* outputData, const Shape& outputShape) { 102 outputData, convertShapeToDims(outputShape), 114 uint8_t* outputData, const Shape& outputShape) { 120 int32_t outputOffset = outputShape.offset; 129 outputShape, 79 convFloat32(const float* inputData, const Shape& inputShape, const float* filterData, const Shape& filterShape, const float* biasData, const Shape& biasShape, int32_t padding_left, int32_t padding_right, int32_t padding_top, int32_t padding_bottom, int32_t stride_width, int32_t stride_height, int32_t activation, float* outputData, const Shape& outputShape) argument 107 convQuant8(const uint8_t* inputData, const Shape& inputShape, const uint8_t* filterData, const Shape& filterShape, const int32_t* biasData, const Shape& biasShape, int32_t padding_left, int32_t padding_right, int32_t padding_top, int32_t padding_bottom, int32_t stride_width, int32_t stride_height, int32_t activation, uint8_t* outputData, const Shape& outputShape) argument [all...] |
H A D | DepthwiseConv2D.cpp | 31 uint32_t outHeight = getSizeOfDimension(outputShape, 1); \ 32 uint32_t outWidth = getSizeOfDimension(outputShape, 2); \ 44 float* outputData, const Shape& outputShape) { 59 outputData, convertShapeToDims(outputShape)); 72 uint8_t* outputData, const Shape& outputShape) { 84 outputShape, &real_multiplier) || 89 CalculateActivationRangeUint8(activation, outputShape, 95 uint32_t outputOffset = outputShape.offset; 105 outputData, convertShapeToDims(outputShape)); 37 depthwiseConvFloat32(const float* inputData, const Shape& inputShape, const float* filterData, const Shape& filterShape, const float* biasData, const Shape& biasShape, int32_t padding_left, int32_t padding_right, int32_t padding_top, int32_t padding_bottom, int32_t stride_width, int32_t stride_height, int32_t depth_multiplier, int32_t activation, float* outputData, const Shape& outputShape) argument 65 depthwiseConvQuant8(const uint8_t* inputData, const Shape& inputShape, const uint8_t* filterData, const Shape& filterShape, const int32_t* biasData, const Shape& biasShape, int32_t padding_left, int32_t padding_right, int32_t padding_top, int32_t padding_bottom, int32_t stride_width, int32_t stride_height, int32_t depth_multiplier, int32_t activation, uint8_t* outputData, const Shape& outputShape) argument
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H A D | Reshape.cpp | 31 void* outputData, const Shape& outputShape) { 38 float* outputData, const Shape& outputShape) { 39 int32_t height = (int32_t) getSizeOfDimension(outputShape, 1); 40 int32_t width = (int32_t) getSizeOfDimension(outputShape, 2); 50 outputData, convertShapeToDims(outputShape)); 56 uint8_t* outputData, const Shape& outputShape) { 63 convertShapeToDims(outputShape)); 70 convertShapeToDims(outputShape)); 80 uint8_t* outputData, const Shape& outputShape) { 87 convertShapeToDims(outputShape)); 30 reshapeGeneric(const void* inputData, const Shape& inputShape, void* outputData, const Shape& outputShape) argument 37 resizeBilinearFloat32(const float* inputData, const Shape& inputShape, float* outputData, const Shape& outputShape) argument 54 depthToSpaceGeneric(const uint8_t* inputData, const Shape& inputShape, int32_t blockSize, uint8_t* outputData, const Shape& outputShape) argument 78 spaceToDepthGeneric(const uint8_t* inputData, const Shape& inputShape, int32_t blockSize, uint8_t* outputData, const Shape& outputShape) argument 102 padGeneric(const uint8_t* inputData, const Shape& inputShape, const int32_t* paddings, uint8_t* outputData, const Shape& outputShape) argument 136 batchToSpaceGeneric(const uint8_t* inputData, const Shape& inputShape, const int32_t* blockSize, uint8_t* outputData, const Shape& outputShape) argument 162 spaceToBatchGeneric(const uint8_t* inputData, const Shape& inputShape, const int32_t* blockSize, const int32_t* padding, const Shape& paddingShape, uint8_t* outputData, const Shape& outputShape) argument 191 squeezeGeneric(const void* inputData, const Shape& inputShape, void* outputData, const Shape& outputShape) argument 198 transposeGeneric(const uint8_t* inputData, const Shape& inputShape, const int32_t* perm, const Shape& permShape, uint8_t* outputData, const Shape& outputShape) argument [all...] |
H A D | SVDF.cpp | 58 Shape *outputShape) { 97 outputShape->type = inputShape.type; 98 outputShape->dimensions = { batch_size, num_units }; 99 outputShape->offset = inputShape.offset; 100 outputShape->scale = inputShape.scale; 55 Prepare(const Operation &operation, std::vector<RunTimeOperandInfo> &operands, Shape *stateShape, Shape *outputShape) argument
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H A D | LSTM.cpp | 235 Shape *outputShape) { 270 outputShape->type = inputShape.type; 271 outputShape->dimensions = { n_batch, n_output }; 272 outputShape->offset = inputShape.offset; 273 outputShape->scale = inputShape.scale; 230 Prepare(const Operation &operation, std::vector<RunTimeOperandInfo> &operands, Shape *scratchShape, Shape *outputStateShape, Shape *cellStateShape, Shape *outputShape) argument
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H A D | SimpleMath.cpp | 281 uint8_t* outputData, const Shape& outputShape) { 296 reinterpret_cast<const int*>(outputShape.dimensions.data()), 297 getNumberOfDimensions(outputShape), 305 reinterpret_cast<const int*>(outputShape.dimensions.data()), 306 getNumberOfDimensions(outputShape), 279 meanGeneric(const uint8_t* inputData, const Shape& inputShape, const int32_t* axis, const Shape& axisShape, bool keepDims, uint8_t* outputData, const Shape& outputShape) argument
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/frameworks/ml/nn/common/ |
H A D | CpuExecutor.cpp | 1216 Shape outputShape; local 1219 success = embeddingLookupPrepare(values.shape(), lookups.shape(), &outputShape) && 1220 setInfoAndAllocateIfNeeded(&output, outputShape) && 1236 Shape outputShape, hitShape; local 1240 &outputShape, &hitShape) && 1241 setInfoAndAllocateIfNeeded(&output, outputShape) && 1249 Shape outputShape; local 1253 &outputShape) && 1254 setInfoAndAllocateIfNeeded(&output, outputShape) && 1267 Shape scratchShape, outputStateShape, cellStateShape, outputShape; local 1285 Shape hiddenStateShape, outputShape; local 1300 Shape stateShape, outputShape; local [all...] |
H A D | OperationsUtils.cpp | 113 const Shape& outputShape, 117 const float output_scale = outputShape.scale; 129 const Shape& outputShape, 135 const auto scale = outputShape.scale; 136 const auto zero_point = outputShape.offset; 521 Shape *outputShape) { 530 outputShape->type = valueShape.type; 531 outputShape->dimensions = { lookups, columns }; 533 outputShape->dimensions.push_back(getSizeOfDimension(valueShape, i)); 535 outputShape 110 GetQuantizedConvolutionMultipler(const Shape& inputShape, const Shape& filterShape, const Shape& biasShape, const Shape& outputShape, float* multiplier) argument 519 embeddingLookupPrepare(const Shape &valueShape, const Shape &lookupShape, Shape *outputShape) argument 541 hashtableLookupPrepare(const Shape &lookupShape, const Shape &keyShape, const Shape &valueShape, Shape *outputShape, Shape *hitShape) argument [all...] |