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Searched refs:outputShape (Results 1 – 25 of 65) sorted by relevance

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/frameworks/ml/nn/common/operations/
DReshape.cpp35 const Shape& outputShape) { in copyData() argument
44 T* outputData, const Shape& outputShape) { in depthToSpaceGeneric() argument
47 outputData, convertShapeToDims(outputShape)); in depthToSpaceGeneric()
52 const Shape& outputShape);
55 const Shape& outputShape);
58 const Shape& outputShape);
61 const Shape& outputShape);
65 T* outputData, const Shape& outputShape) { in spaceToDepthGeneric() argument
68 outputData, convertShapeToDims(outputShape)); in spaceToDepthGeneric()
73 const Shape& outputShape);
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DActivation.cpp52 bool reluFloat(const T* inputData, const Shape& inputShape, T* outputData, const Shape& outputShape, in reluFloat() argument
63 const Shape& outputShape, float reluMin, float reluMax);
65 _Float16* outputData, const Shape& outputShape, float reluMin,
70 const Shape& outputShape) { in relu1Float() argument
71 return reluFloat(inputData, inputShape, outputData, outputShape, -1.f, 1.f); in relu1Float()
74 const Shape& outputShape);
76 _Float16* outputData, const Shape& outputShape);
80 const Shape& outputShape) { in relu6Float() argument
81 return reluFloat(inputData, inputShape, outputData, outputShape, 0.f, 6.f); in relu6Float()
84 const Shape& outputShape);
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DMaximumMinimum.cpp38 bool isMinimum, T* outputData, const Shape& outputShape) { in evalGeneric() argument
41 IndexedShapeWrapper outputShapeIndexed(outputShape); in evalGeneric()
43 std::vector<uint32_t> curIndex(outputShape.dimensions.size(), 0); in evalGeneric()
64 bool isMinimum, T* outputData, const Shape& outputShape) { in evalQuant8() argument
67 IndexedShapeWrapper outputShapeIndexed(outputShape); in evalQuant8()
69 std::vector<uint32_t> curIndex(outputShape.dimensions.size(), 0); in evalQuant8()
79 T aValue = requantize<T>(aData[aFlatIndex], aShape, outputShape); in evalQuant8()
80 T bValue = requantize<T>(bData[bFlatIndex], bShape, outputShape); in evalQuant8()
98 bool isMinimum, void* output, const Shape& outputShape) { in eval() argument
104 reinterpret_cast<_Float16*>(output), outputShape); in eval()
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DPooling.cpp140 float* outputData, const Shape& outputShape) { in averagePoolNhwc() argument
142 auto op_params = param.toTfliteParam(outputShape); in averagePoolNhwc()
145 convertShapeToTflshape(outputShape), outputData); in averagePoolNhwc()
150 _Float16* outputData, const Shape& outputShape) { in averagePoolNhwc() argument
153 std::vector<float> outputDataFloat32(getNumberOfElements(outputShape)); in averagePoolNhwc()
157 outputShape); in averagePoolNhwc()
163 uint8_t* outputData, const Shape& outputShape) { in averagePoolNhwc() argument
165 auto op_params = param.toTfliteParam(outputShape); in averagePoolNhwc()
168 convertShapeToTflshape(outputShape), outputData); in averagePoolNhwc()
173 int8_t* outputData, const Shape& outputShape) { in averagePoolNhwc() argument
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DSimpleMath.cpp35 const Shape& outputShape) { in meanFloat16() argument
40 std::vector<float> outputDataFloat32(getNumberOfElements(outputShape)); in meanFloat16()
42 outputDataFloat32.data(), outputShape); in meanFloat16()
49 bool keepDims, T* outputData, const Shape& outputShape) { in meanGeneric() argument
59 U* tempSumBuffer = new (std::nothrow) U[getNumberOfElements(outputShape)]; in meanGeneric()
68 reinterpret_cast<const int*>(outputShape.dimensions.data()), in meanGeneric()
69 getNumberOfDimensions(outputShape), axis, axisSize, keepDims, scratchBuffer, in meanGeneric()
79 float* outputData, const Shape& outputShape);
83 const Shape& outputShape);
87 const Shape& outputShape);
DFullyConnected.cpp58 float* outputData, const Shape& outputShape) { in fullyConnectedFloat32() argument
65 uint32_t batch_size = getSizeOfDimension(outputShape, 0); in fullyConnectedFloat32()
73 outputData, convertShapeToDims(outputShape)); in fullyConnectedFloat32()
80 outputData, convertShapeToDims(outputShape)); in fullyConnectedFloat32()
88 _Float16* outputData, const Shape& outputShape) { in fullyConnectedFloat16() argument
97 std::vector<float> outputDataFloat32(getNumberOfElements(outputShape)); in fullyConnectedFloat16()
100 outputDataFloat32.data(), outputShape); in fullyConnectedFloat16()
109 uint8_t* outputData, const Shape& outputShape) { in fullyConnectedQuant8() argument
113 int32_t outputOffset = outputShape.offset; in fullyConnectedQuant8()
121 NN_RET_CHECK(GetQuantizedConvolutionMultipler(inputShape, weightsShape, biasShape, outputShape, in fullyConnectedQuant8()
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DPow.cpp36 const Shape& exponentShape, T* outputData, const Shape& outputShape) { in evalGeneric() argument
39 IndexedShapeWrapper outputShapeIndexed(outputShape); in evalGeneric()
41 std::vector<uint32_t> curIndex(outputShape.dimensions.size(), 0); in evalGeneric()
71 const Shape& exponentShape, void* outputData, const Shape& outputShape) { in eval() argument
76 reinterpret_cast<_Float16*>(outputData), outputShape); in eval()
81 reinterpret_cast<float*>(outputData), outputShape); in eval()
DQuantize.cpp43 bool quantizeToQuant8(const T* inputData, uint8_t* outputData, const Shape& outputShape) { in quantizeToQuant8() argument
45 uint32_t size = getNumberOfElements(outputShape); in quantizeToQuant8()
48 0.0f, std::min<float>(255.0f, outputShape.offset + std::round(inputData[i] / in quantizeToQuant8()
49 outputShape.scale)))); in quantizeToQuant8()
55 bool quantizeToQuant8Signed(const T* inputData, int8_t* outputData, const Shape& outputShape) { in quantizeToQuant8Signed() argument
57 uint32_t size = getNumberOfElements(outputShape); in quantizeToQuant8Signed()
61 std::min<float>(127.0f, outputShape.offset + in quantizeToQuant8Signed()
62 std::round(inputData[i] / outputShape.scale)))); in quantizeToQuant8Signed()
DCast.cpp48 const Shape& outputShape) { in copyToTensor() argument
56 switch (outputShape.type) { in copyToTensor()
76 const Shape& outputShape) { in eval() argument
84 outputShape); \ in eval()
94 if (inputShape.type == outputShape.type) { in eval()
95 return copyData(inputData, inputShape, outputData, outputShape); in eval()
DConv2D.cpp137 uint32_t outHeight = getSizeOfDimension(outputShape, 1); \
138 uint32_t outWidth = getSizeOfDimension(outputShape, 2); \
145 im2colDim.sizes[3] = (int)getSizeOfDimension(outputShape, 0); \
146 im2colDim.sizes[2] = (int)getSizeOfDimension(outputShape, 1); \
147 im2colDim.sizes[1] = (int)getSizeOfDimension(outputShape, 2); \
198 float* outputData, const Shape& outputShape) { in convNhwc() argument
218 convertShapeToDims(outputShape), need_im2colData ? im2colData : nullptr, im2colDim); in convNhwc()
227 uint8_t* outputData, const Shape& outputShape) { in convNhwc() argument
234 int32_t outputOffset = outputShape.offset; in convNhwc()
242 NN_RET_CHECK(GetQuantizedConvolutionMultipler(inputShape, filterShape, biasShape, outputShape, in convNhwc()
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DGroupedConv2D.cpp41 uint32_t outputHeight = getSizeOfDimension(outputShape, 1); \
42 uint32_t outputWidth = getSizeOfDimension(outputShape, 2); \
43 uint32_t outputDepth = getSizeOfDimension(outputShape, 3); \
51 const Shape& outputShape) { in groupedConvFloat32() argument
109 const Shape& outputShape) { in groupedConvQuant8() argument
115 int32_t outputOffset = outputShape.offset; in groupedConvQuant8()
120 NN_RET_CHECK(GetQuantizedConvolutionMultipler(inputShape, filterShape, biasShape, outputShape, in groupedConvQuant8()
127 CalculateActivationRange<T>(activation, outputShape, &output_activation_min, in groupedConvQuant8()
188 const Shape& outputShape);
197 const Shape& outputShape);
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DL2Normalization.cpp48 float* outputData, const Shape& outputShape) { in l2normFloat32Impl() argument
76 uint8_t* outputData, const Shape& outputShape) { in l2normQuant8Impl() argument
108 int8_t* outputData, const Shape& outputShape) { in l2normQuant8SignedImpl() argument
139 const Shape& outputShape) { in l2normFloat32() argument
147 convertShapeToTflshape(outputShape), outputData); in l2normFloat32()
150 return l2normFloat32Impl(inputData, inputShape, axis, outputData, outputShape); in l2normFloat32()
155 _Float16* outputData, const Shape& outputShape) { in l2normFloat16() argument
159 std::vector<float> outputDataFloat32(getNumberOfElements(outputShape)); in l2normFloat16()
161 l2normFloat32(inputDataFloat32.data(), inputShape, axis, outputDataFloat32.data(), outputShape); in l2normFloat16()
168 uint8_t* outputData, const Shape& outputShape) { in l2normQuant8() argument
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DConcatenation.cpp50 const Shape& outputShape) { in concatenation() argument
61 getNumberOfDimensions(outputShape) - axis - 1, inputDataPtrs.data(), in concatenation()
62 inputDimsPtr.data(), num_inputs, outputData, convertShapeToDims(outputShape)); in concatenation()
70 uint8_t* outputData, const Shape& outputShape) { in concatenation() argument
86 getNumberOfDimensions(outputShape) - axis - 1, inputDataPtrs.data(), in concatenation()
88 convertShapeToDims(outputShape), outputShape.offset, outputShape.scale); in concatenation()
129 Shape outputShape(context->getOutputShape(kOutputTensor)); in concatenation() local
130 outputShape.offset += 128; in concatenation()
132 output_uint8.data(), outputShape)); in concatenation()
DSoftmax.cpp52 int32_t axis, float* outputData, const Shape& outputShape) { in softmaxSlowFloat32() argument
84 float* outputData, const Shape& outputShape) { in softmaxFloat32() argument
92 convertShapeToTflshape(outputShape), outputData); in softmaxFloat32()
95 return softmaxSlowFloat32(inputData, inputShape, beta, axis, outputData, outputShape); in softmaxFloat32()
100 int32_t axis, _Float16* outputData, const Shape& outputShape) { in softmaxFloat16() argument
104 std::vector<float> outputData_float32(getNumberOfElements(outputShape)); in softmaxFloat16()
107 outputShape); in softmaxFloat16()
116 T* outputData, const Shape& outputShape) { in softmaxQuant8Impl() argument
202 T* outputData, const Shape& outputShape) { in softmaxQuant8() argument
206 if ((inputShape.type == OperandType::TENSOR_QUANT8_ASYMM && outputShape.offset != 0) || in softmaxQuant8()
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DPRelu.cpp48 const Shape& outputShape) { in eval() argument
51 IndexedShapeWrapper outputShapeIndexed(outputShape); in eval()
52 std::vector<uint32_t> curIndex(outputShape.dimensions.size(), 0); in eval()
71 T* outputData, const Shape& outputShape) { in evalQuant8() argument
74 const int32_t output_offset = outputShape.offset; in evalQuant8()
76 const double real_multiplier_pos = aShape.scale / outputShape.scale; in evalQuant8()
77 const double real_multiplier_neg = input_product_scale / outputShape.scale; in evalQuant8()
98 aData, aShape, bData, bShape, outputData, outputShape); in evalQuant8()
DDepthwiseConv2D.cpp125 uint32_t outHeight = getSizeOfDimension(outputShape, 1); \
126 uint32_t outWidth = getSizeOfDimension(outputShape, 2); \
137 const Shape& outputShape) { in depthwiseConvNhwc() argument
160 convertShapeToTflshape(outputShape), outputData); in depthwiseConvNhwc()
171 _Float16* outputData, const Shape& outputShape) { in depthwiseConvNhwc() argument
180 std::vector<float> outputDataFloat32(getNumberOfElements(outputShape)); in depthwiseConvNhwc()
185 outputShape); in depthwiseConvNhwc()
197 const Shape& outputShape) { in depthwiseConvNhwc() argument
208 NN_RET_CHECK(GetQuantizedConvolutionMultipler(inputShape, filterShape, biasShape, outputShape, in depthwiseConvNhwc()
213 CalculateActivationRangeUint8(activation, outputShape, &output_activation_min, in depthwiseConvNhwc()
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DResizeImageOps.cpp67 bool halfPixelCenters, T* outputData, const Shape& outputShape) { in resizeNearestNeighbor() argument
72 const int outHeight = getSizeOfDimension(outputShape, 1); in resizeNearestNeighbor()
73 const int outWidth = getSizeOfDimension(outputShape, 2); in resizeNearestNeighbor()
111 const Shape& outputShape) { in resizeImageOpNhwc() argument
113 int32_t height = static_cast<int32_t>(getSizeOfDimension(outputShape, 1)); in resizeImageOpNhwc()
114 int32_t width = static_cast<int32_t>(getSizeOfDimension(outputShape, 2)); in resizeImageOpNhwc()
125 outDimData, convertShapeToTflshape(outputShape), outputData); in resizeImageOpNhwc()
130 outputShape); in resizeImageOpNhwc()
138 _Float16* outputData, const Shape& outputShape) { in resizeImageOpNhwc() argument
142 std::vector<float> outputData_float32(getNumberOfElements(outputShape)); in resizeImageOpNhwc()
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DTransposeConv2D.cpp117 uint32_t outputHeight = getSizeOfDimension(outputShape, 1); \
118 uint32_t outputWidth = getSizeOfDimension(outputShape, 2); \
119 uint32_t outputDepth = getSizeOfDimension(outputShape, 3); \
128 const Shape& outputShape) { in transposeConvNhwc() argument
135 memset(outputData, 0, getNumberOfElements(outputShape) * sizeof(float)); in transposeConvNhwc()
184 const TransposeConv2dParam& param, T* outputData, const Shape& outputShape) { in transposeConvNhwc() argument
190 uint32_t tempBufferByteSize = getNumberOfElements(outputShape) * sizeof(int32_t); in transposeConvNhwc()
204 int32_t outputOffset = outputShape.offset; in transposeConvNhwc()
209 NN_RET_CHECK(GetQuantizedConvolutionMultipler(inputShape, filterShape, biasShape, outputShape, in transposeConvNhwc()
216 CalculateActivationRange<T>(activation, outputShape, &outputActivationMin, in transposeConvNhwc()
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DReduce.cpp55 const Shape outputShape = context->getOutputShape(kOutputTensor); in compute() local
64 reinterpret_cast<const int32_t*>(outputShape.dimensions.data()), in compute()
65 outputShape.dimensions.size(), context->getInputBuffer<int32_t>(kInputAxes), numAxes, in compute()
145 Shape outputShape = inputShape; in prepare() local
146 outputShape.dimensions.clear(); in prepare()
151 outputShape.dimensions.push_back(1); in prepare()
154 outputShape.dimensions.push_back(getSizeOfDimension(inputShape, axis)); in prepare()
159 if (outputShape.dimensions.empty()) { in prepare()
160 outputShape.dimensions.push_back(1); in prepare()
163 return context->setOutputShape(kOutputTensor, outputShape); in prepare()
DSlice.cpp54 T* outputData, const Shape& outputShape) { in evalGeneric() argument
55 const int outputSize = getNumberOfElements(outputShape); in evalGeneric()
56 const IndexedShapeWrapper indexedOutput = IndexedShapeWrapper(outputShape); in evalGeneric()
58 std::vector<uint32_t> outputIndex(getNumberOfDimensions(outputShape), 0); in evalGeneric()
121 Shape outputShape = context->getOutputShape(kOutputTensor); in prepare() local
122 outputShape.dimensions.resize(n_dims); in prepare()
132 outputShape.dimensions[i] = sliceSize; in prepare()
134 return context->setOutputShape(kOutputTensor, outputShape); in prepare()
DLocalResponseNormalization.cpp53 const Shape& outputShape) { in localResponseNormFloat32Impl() argument
82 T beta, int32_t axis, T* outputData, const Shape& outputShape);
87 const Shape& outputShape) { in localResponseNorm() argument
97 convertShapeToTflshape(outputShape), outputData); in localResponseNorm()
101 outputData, outputShape); in localResponseNorm()
108 _Float16* outputData, const Shape& outputShape) { in localResponseNorm() argument
112 std::vector<float> outputDataFloat32(getNumberOfElements(outputShape)); in localResponseNorm()
115 outputDataFloat32.data(), outputShape); in localResponseNorm()
DMultinomial.cpp64 Shape* outputShape) { in Prepare() argument
76 outputShape->type = OperandType::TENSOR_INT32; in Prepare()
77 outputShape->dimensions = {batch_size, sample_count}; in Prepare()
78 outputShape->offset = inputShape.offset; in Prepare()
79 outputShape->scale = inputShape.scale; in Prepare()
DLSHProjection.cpp46 Shape* outputShape) { in Prepare() argument
70 outputShape->dimensions = {SizeOfDimension(hash, 0)}; in Prepare()
77 outputShape->dimensions = {SizeOfDimension(hash, 0) * SizeOfDimension(hash, 1)}; in Prepare()
84 outputShape->type = OperandType::TENSOR_INT32; in Prepare()
85 outputShape->offset = 0; in Prepare()
86 outputShape->scale = 0.f; in Prepare()
/frameworks/ml/nn/common/include/
DOperations.h54 _Float16* outputData, const Shape& outputShape);
61 const Shape& outputShape);
68 uint8_t* outputData, const Shape& outputShape);
77 const Shape& outputShape);
81 _Float16* outputData, const Shape& outputShape);
84 const Shape& outputShape);
87 const Shape& outputShape);
91 T* outputData, const Shape& outputShape);
94 T* outputData, const Shape& outputShape);
98 T* outputData, const Shape& outputShape);
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/frameworks/ml/nn/common/
DOperationsUtils.cpp50 void CalculateActivationRangeImpl(int32_t activation, const Shape& outputShape, int32_t qmin, in CalculateActivationRangeImpl() argument
52 const auto scale = outputShape.scale; in CalculateActivationRangeImpl()
53 const auto zero_point = outputShape.offset; in CalculateActivationRangeImpl()
259 const Shape& biasShape, const Shape& outputShape, in GetQuantizedConvolutionMultipler() argument
269 *multiplier = input_product_scale / outputShape.scale; in GetQuantizedConvolutionMultipler()
273 void CalculateActivationRangeUint8(int32_t activation, const Shape& outputShape, int32_t* act_min, in CalculateActivationRangeUint8() argument
278 CalculateActivationRangeImpl(activation, outputShape, qmin, qmax, act_min, act_max); in CalculateActivationRangeUint8()
281 void CalculateActivationRangeInt8(int32_t activation, const Shape& outputShape, int32_t* act_min, in CalculateActivationRangeInt8() argument
286 CalculateActivationRangeImpl(activation, outputShape, qmin, qmax, act_min, act_max); in CalculateActivationRangeInt8()
462 bool embeddingLookupPrepare(const Shape& valueShape, const Shape& lookupShape, Shape* outputShape) { in embeddingLookupPrepare() argument
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