/frameworks/ml/nn/common/operations/ |
H A D | Reshape.cpp | 29 bool reshapeGeneric(const void* inputData, const Shape& inputShape, argument 31 size_t count = sizeOfData(inputShape.type, inputShape.dimensions); 36 bool resizeBilinearFloat32(const float* inputData, const Shape& inputShape, argument 47 inputData, convertShapeToDims(inputShape), 53 bool depthToSpaceGeneric(const uint8_t* inputData, const Shape& inputShape, argument 56 if (inputShape.type == OperandType::TENSOR_FLOAT32) { 59 convertShapeToDims(inputShape), 63 } else if (inputShape.type == OperandType::TENSOR_QUANT8_ASYMM) { 66 convertShapeToDims(inputShape), 77 spaceToDepthGeneric(const uint8_t* inputData, const Shape& inputShape, int32_t blockSize, uint8_t* outputData, const Shape& outputShape) argument [all...] |
H A D | Normalization.cpp | 25 bool l2normFloat32(const float* inputData, const Shape& inputShape, argument 28 inputData, convertShapeToDims(inputShape), 34 bool l2normQuant8(const uint8_t* inputData, const Shape& inputShape, argument 37 inputData, convertShapeToDims(inputShape), 38 inputShape.offset, 44 bool localResponseNormFloat32(const float* inputData, const Shape& inputShape, argument 48 inputData, convertShapeToDims(inputShape),
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H A D | Activation.cpp | 25 bool reluFloat32(const float* inputData, const Shape& inputShape, argument 27 int numElements = getNumberOfElements(inputShape); 34 bool relu1Float32(const float* inputData, const Shape& inputShape, argument 36 int numElements = getNumberOfElements(inputShape); 43 bool relu6Float32(const float* inputData, const Shape& inputShape, argument 45 int numElements = getNumberOfElements(inputShape); 52 bool tanhFloat32(const float* inputData, const Shape& inputShape, argument 54 int numElements = getNumberOfElements(inputShape); 61 bool logisticFloat32(const float* inputData, const Shape& inputShape, argument 63 int numElements = getNumberOfElements(inputShape); 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 | Pooling.cpp | 26 uint32_t height = getSizeOfDimension(inputShape, 1); \ 27 uint32_t width = getSizeOfDimension(inputShape, 2); \ 34 bool averagePoolFloat32(const float* inputData, const Shape& inputShape, argument 45 inputData, convertShapeToDims(inputShape), \ 56 bool averagePoolQuant8(const uint8_t* inputData, const Shape& inputShape, argument 74 inputData, convertShapeToDims(inputShape), \ 86 bool l2PoolFloat32(const float* inputData, const Shape& inputShape, argument 97 inputData, convertShapeToDims(inputShape), \ 108 bool maxPoolFloat32(const float* inputData, const Shape& inputShape, argument 119 inputData, convertShapeToDims(inputShape), \ 130 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 | FullyConnected.cpp | 25 bool fullyConnectedFloat32(const float* inputData, const Shape& inputShape, argument 33 inputData, convertShapeToDims(inputShape), \ 43 bool fullyConnectedQuant8(const uint8_t* inputData, const Shape& inputShape, argument 48 int32_t inputOffset = -inputShape.offset; 58 if (!GetQuantizedConvolutionMultipler(inputShape, weightsShape, biasShape, 74 inputData, convertShapeToDims(inputShape), inputOffset, \
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H A D | DepthwiseConv2D.cpp | 27 uint32_t height = getSizeOfDimension(inputShape, 1); \ 28 uint32_t width = getSizeOfDimension(inputShape, 2); \ 37 bool depthwiseConvFloat32(const float* inputData, const Shape& inputShape, argument 50 inputData, convertShapeToDims(inputShape), \ 64 bool depthwiseConvQuant8(const uint8_t* inputData, const Shape& inputShape, argument 82 if (!GetQuantizedConvolutionMultipler(inputShape, filterShape, biasShape, 92 uint32_t inputOffset = -inputShape.offset; 97 inputData, convertShapeToDims(inputShape), inputOffset, \
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H A D | Conv2D.cpp | 30 uint32_t height = getSizeOfDimension(inputShape, 1); \ 31 uint32_t width = getSizeOfDimension(inputShape, 2); \ 36 uint32_t inDepth = getSizeOfDimension(inputShape, 3); \ 63 bool convFloat32(const float* inputData, const Shape& inputShape, argument 76 inputData, convertShapeToDims(inputShape), \ 92 bool convQuant8(const uint8_t* inputData, const Shape& inputShape, argument 103 int32_t inputOffset = -inputShape.offset; 113 if (!GetQuantizedConvolutionMultipler(inputShape, filterShape, biasShape, 129 inputData, convertShapeToDims(inputShape), inputOffset, \
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H A D | SVDF.cpp | 91 const Shape &inputShape = input->shape(); local 92 stateShape->type = inputShape.type; 94 stateShape->offset = inputShape.offset; 95 stateShape->scale = inputShape.scale; 98 outputShape->type = inputShape.type; 100 outputShape->offset = inputShape.offset; 101 outputShape->scale = inputShape.scale;
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H A D | LSTM.cpp | 268 const Shape &inputShape = input->shape(); local 270 outputShape->type = inputShape.type; 272 outputShape->offset = inputShape.offset; 273 outputShape->scale = inputShape.scale; 275 outputStateShape->type = inputShape.type; 277 outputStateShape->offset = inputShape.offset; 278 outputStateShape->scale = inputShape.scale; 280 cellStateShape->type = inputShape.type; 282 cellStateShape->offset = inputShape.offset; 283 cellStateShape->scale = inputShape [all...] |
H A D | RNN.cpp | 67 const Shape &inputShape = input->shape(); local 70 hiddenStateShape->type = inputShape.type; 74 outputShape->type = inputShape.type;
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/frameworks/ml/nn/common/include/ |
H A D | Operations.h | 63 bool depthwiseConvFloat32(const float* inputData, const Shape& inputShape, 71 bool depthwiseConvQuant8(const uint8_t* inputData, const Shape& inputShape, 80 bool convFloat32(const float* inputData, const Shape& inputShape, 88 bool convQuant8(const uint8_t* inputData, const Shape& inputShape, 97 bool averagePoolFloat32(const float* inputData, const Shape& inputShape, 103 bool averagePoolQuant8(const uint8_t* inputData, const Shape& inputShape, 109 bool l2PoolFloat32(const float* inputData, const Shape& inputShape, 115 bool maxPoolFloat32(const float* inputData, const Shape& inputShape, 121 bool maxPoolQuant8(const uint8_t* inputData, const Shape& inputShape, 128 bool reluFloat32(const float* inputData, const Shape& inputShape, [all...] |
H A D | OperationsUtils.h | 86 bool GetQuantizedConvolutionMultipler(const Shape& inputShape,
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/frameworks/ml/nn/common/ |
H A D | CpuExecutor.cpp | 422 Shape inputShape = input.shape(); local 424 int32_t input_width = getSizeOfDimension(inputShape, 2); 425 int32_t input_height = getSizeOfDimension(inputShape, 1); 509 Shape inputShape = input.shape(); local 511 int32_t input_width = getSizeOfDimension(inputShape, 2); 512 int32_t input_height = getSizeOfDimension(inputShape, 1); 592 Shape inputShape = input.shape(); local 593 int32_t input_width = getSizeOfDimension(inputShape, 2); 594 int32_t input_height = getSizeOfDimension(inputShape, 1); 672 Shape inputShape local 736 Shape inputShape = input.shape(); local [all...] |
H A D | OperationsUtils.cpp | 110 bool GetQuantizedConvolutionMultipler(const Shape& inputShape, argument 115 const float input_product_scale = inputShape.scale * filterShape.scale;
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