/aosp12/packages/modules/NeuralNetworks/common/ |
H A D | CpuExecutor.cpp | 201 info->type = shape.type; in setInfoAndAllocateIfNeeded() 202 info->scale = shape.scale; in setInfoAndAllocateIfNeeded() 203 info->zeroPoint = shape.offset; in setInfoAndAllocateIfNeeded() 444 Shape inShape = from.shape(); in convertToNhwc() 950 success = embeddingLookupPrepare(values.shape(), lookups.shape(), &outputShape) && in executeOperation() 967 success = hashtableLookupPrepare(lookups.shape(), keys.shape(), values.shape(), in executeOperation() 1454 success = maximum_minimum::prepare(in1.shape(), in2.shape(), &outputShape) && in executeOperation() 1456 maximum_minimum::eval(in1.buffer, in1.shape(), in2.buffer, in2.shape(), in executeOperation() 1521 if (!groupedConvPrepare(input_tmp.shape(), filter.shape(), bias.shape(), padding_left, in executeOperation() 1642 success = pow::prepare(base.shape(), exponent.shape(), &outShape) && in executeOperation() [all …]
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H A D | IndexedShapeWrapper.cpp | 28 IndexedShapeWrapper::IndexedShapeWrapper(const Shape& wrapped_shape) : shape(&wrapped_shape) { in IndexedShapeWrapper() 29 strides.resize(shape->dimensions.size()); in IndexedShapeWrapper() 32 strides[i] = shape->dimensions[i + 1] * strides[i + 1]; in IndexedShapeWrapper() 41 if (index->at(i) < shape->dimensions[i] - 1) { in nextIndexInplace() 52 if (index->at(i) == shape->dimensions[i]) { in nextIndexInplace() 79 uint32_t currentDimSize = shape->dimensions[shape->dimensions.size() - i]; in broadcastedIndexToFlatIndex() 89 if (index.size() != shape->dimensions.size()) { in isValid() 92 << toString(shape->dimensions); in isValid() 96 if (index[i] >= shape->dimensions[i]) { in isValid() 98 << " is out of range for shape: " << toString(shape->dimensions); in isValid()
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/aosp12/packages/modules/NeuralNetworks/common/include/ |
H A D | CpuOperationUtils.h | 35 inline tflite::Dims<4> convertShapeToDims(const Shape& shape) { in convertShapeToDims() argument 36 CHECK_LE(shape.dimensions.size(), 4u); in convertShapeToDims() 41 int src = static_cast<int>(shape.dimensions.size()) - i - 1; in convertShapeToDims() 57 std::vector<int32_t> tflShapeDim(shape.dimensions.begin(), shape.dimensions.end()); in convertShapeToTflshape() 162 bool initialize(const T* data, const Shape& shape) { in initialize() argument 164 mShape = shape; in initialize() 186 bool initialize(T* data, const Shape& shape) { in initialize() argument 187 NN_RET_CHECK_EQ(getNumberOfDimensions(shape), 4); in initialize() 189 mShape = shape; in initialize() 191 const auto& dim = shape.dimensions; in initialize() [all …]
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H A D | OperationsUtils.h | 131 uint32_t getNumberOfElements(const Shape& shape); 135 uint32_t getNumberOfDimensions(const Shape& shape); 139 uint32_t hasKnownRank(const Shape& shape); 327 const int numDims = getNumberOfDimensions(shape); in transposeFirstTwoDimensions() 329 const int firstDim = getSizeOfDimension(shape, 0); in transposeFirstTwoDimensions() 330 const int secondDim = getSizeOfDimension(shape, 1); in transposeFirstTwoDimensions() 333 blockSize *= getSizeOfDimension(shape, i); in transposeFirstTwoDimensions() 348 NN_RET_CHECK(getNumberOfDimensions(shape) >= 2); in transposeFirstTwoDimensions() 349 *transposedShape = shape; in transposeFirstTwoDimensions() 350 transposedShape->dimensions[0] = shape.dimensions[1]; in transposeFirstTwoDimensions() [all …]
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/aosp12/packages/modules/NeuralNetworks/common/operations/ |
H A D | BidirectionalSequenceLSTM.cpp | 336 NN_CHECK_EQ(aux_input_->shape().dimensions[0], input_->shape().dimensions[0]); in Prepare() 337 NN_CHECK_EQ(aux_input_->shape().dimensions[1], input_->shape().dimensions[1]); in Prepare() 382 const Shape& inputShape = input_->shape(); in Prepare() 420 *fwOutputCellState = fw_cell_state_->shape(); in Prepare() 422 *bwOutputCellState = bw_cell_state_->shape(); in Prepare() 459 Shape bwInputShape = input_->shape(); in Eval() 463 bwInputShape = aux_input_->shape(); in Eval() 490 fw_input_to_output_weights_->shape(), in Eval() 542 bw_input_to_output_weights_->shape(), in Eval() 582 Shape bwInputShape = input_->shape(); in Eval() [all …]
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H A D | RNN.cpp | 68 const Shape& inputShape = input->shape(); in Prepare() 84 RNNStep<_Float16>(reinterpret_cast<_Float16*>(input_->buffer), input_->shape(), in Eval() 87 reinterpret_cast<_Float16*>(weights_->buffer), weights_->shape(), in Eval() 89 recurrent_weights_->shape(), activation_, in Eval() 92 sizeof(_Float16) * getNumberOfElements(output_->shape())); in Eval() 96 RNNStep<float>(reinterpret_cast<float*>(input_->buffer), input_->shape(), in Eval() 99 reinterpret_cast<float*>(weights_->buffer), weights_->shape(), in Eval() 101 recurrent_weights_->shape(), activation_, in Eval() 104 sizeof(float) * getNumberOfElements(output_->shape())); in Eval()
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H A D | SVDF.cpp | 95 const Shape& inputShape = input->shape(); in Prepare() 114 std::vector<float> inputDataFloat32(getNumberOfElements(input_->shape())); in Eval() 116 std::vector<float> inputStateDataFloat32(getNumberOfElements(state_in_->shape())); in Eval() 119 std::vector<float> biasDataFloat32(getNumberOfElements(bias_->shape())); in Eval() 125 getNumberOfElements(weights_feature_->shape())); in Eval() 128 std::vector<float> weightsTimeDataFloat32(getNumberOfElements(weights_time_->shape())); in Eval() 131 std::vector<float> outputDataFloat32(getNumberOfElements(output_->shape())); in Eval() 132 std::vector<float> outputStateDataFloat32(getNumberOfElements(state_out_->shape())); in Eval()
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H A D | LogSoftmax.cpp | 42 inline bool compute(const T* input, const Shape& shape, T beta, uint32_t axis, T* output) { in compute() argument 43 const uint32_t outerSize = getNumberOfElements(shape, 0, axis); in compute() 44 const uint32_t axisSize = getSizeOfDimension(shape, axis); in compute() 45 const uint32_t innerSize = getNumberOfElements(shape, axis + 1, getNumberOfDimensions(shape)); in compute()
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H A D | QuantizedLSTMTest.cpp | 34 std::vector<uint32_t> shape; member 38 OperandTypeParams(Type type, std::vector<uint32_t> shape, float scale, int32_t zeroPoint) in OperandTypeParams() 39 : type(type), shape(shape), scale(scale), zeroPoint(zeroPoint) {} in OperandTypeParams() 56 OperandType curType(curOTP.type, curOTP.shape, curOTP.scale, curOTP.zeroPoint); in QuantizedLSTMOpModel() 60 const uint32_t numBatches = inputOperandTypeParams[0].shape[0]; in QuantizedLSTMOpModel() 61 inputSize_ = inputOperandTypeParams[0].shape[0]; in QuantizedLSTMOpModel() 63 inputOperandTypeParams[QuantizedLSTMCell::kPrevCellStateTensor].shape[1]; in QuantizedLSTMOpModel() 188 for (int d : params.shape) { in initializeInputData()
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/aosp12/frameworks/av/services/camera/libcameraservice/tests/ |
H A D | DistortionMapperComp.py | 36 f.write('std::array<int32_t, %d> rawCoords = {\n' % (rawCoords.shape[0] * rawCoords.shape[1])) 37 for i in range(rawCoords.shape[0]): 41 f.write('std::array<int32_t, %d> expCoords = {\n' % (expCoords.shape[0] * expCoords.shape[2])) 42 for i in range(expCoords.shape[0]):
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/aosp12/hardware/interfaces/neuralnetworks/1.2/ |
H A D | types.hal | 812 * Keys should have a shape of [40]. If Lookups tensor has shape 829 * shape [ k ]. 1533 * shape of the output tensor. The number of elements implied by shape 1542 * * 0: The output tensor, of shape specified by the input shape. 1961 * shape is [1]. 2135 * shape is [1]. 2833 * * 2: A 2-D Tensor of shape [num_anchors, 4], specifying the shape of each 3028 * * 2: A 2-D Tensor of shape [num_anchors, 4], specifying the shape of each 3886 * shape is [1]. 3913 * shape is [1]. [all …]
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/aosp12/frameworks/base/graphics/java/android/graphics/drawable/shapes/ |
H A D | RoundRectShape.java | 135 final RoundRectShape shape = (RoundRectShape) super.clone(); in clone() local 136 shape.mOuterRadii = mOuterRadii != null ? mOuterRadii.clone() : null; in clone() 137 shape.mInnerRadii = mInnerRadii != null ? mInnerRadii.clone() : null; in clone() 138 shape.mInset = new RectF(mInset); in clone() 139 shape.mInnerRect = new RectF(mInnerRect); in clone() 140 shape.mPath = new Path(mPath); in clone() 141 return shape; in clone()
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H A D | Shape.java | 129 Shape shape = (Shape) o; in equals() local 130 return Float.compare(shape.mWidth, mWidth) == 0 in equals() 131 && Float.compare(shape.mHeight, mHeight) == 0; in equals()
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H A D | RectShape.java | 64 final RectShape shape = (RectShape) super.clone(); in clone() local 65 shape.mRect = new RectF(mRect); in clone() 66 return shape; in clone()
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H A D | PathShape.java | 75 final PathShape shape = (PathShape) super.clone(); in clone() local 76 shape.mPath = new Path(mPath); in clone() 77 return shape; in clone()
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/aosp12/hardware/interfaces/neuralnetworks/1.0/ |
H A D | types.hal | 188 * * 0: The output 4-D tensor, of shape 259 * * 1: A 4-D tensor, of shape 287 * * 1: A 4-D tensor, of shape 309 * * 0: The output 4-D tensor, of shape 490 * have shape of [3, 200, 300]. 593 * Keys should have a shape of [40]. If Lookups tensor has shape 610 * shape [ k ]. 1196 * shape of the output tensor. The number of elements implied by shape 1202 * of shape can be -1. 1205 * * 0: The output tensor, of shape specified by the input shape. [all …]
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/aosp12/hardware/interfaces/neuralnetworks/1.3/ |
H A D | types.hal | 801 * Keys should have a shape of [40]. If Lookups tensor has shape 818 * shape [ k ]. 1546 * shape of the output tensor. The number of elements implied by shape 1555 * * 0: The output tensor, of shape specified by the input shape. 2020 * shape is [1]. 2202 * shape is [1]. 3009 * * 2: A 2-D Tensor of shape [num_anchors, 4], specifying the shape of each 3210 * * 2: A 2-D Tensor of shape [num_anchors, 4], specifying the shape of each 4113 * shape is [1]. 4140 * shape is [1]. [all …]
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/aosp12/packages/apps/Test/connectivity/sl4n/rapidjson/doc/diagram/ |
H A D | move2.dot | 19 node [shape=Mrecord, style=filled, colorscheme=spectral7] 24 c13 [shape="none", label="...", style="solid"] 42 node [shape=Mrecord, style=filled, colorscheme=spectral7] 48 c23 [shape=none, label="...", style="solid"] 53 c33 [shape="none", label="...", style="solid"]
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H A D | move3.dot | 20 node [shape=Mrecord, style=filled, colorscheme=spectral7] 25 c13 [shape=none, label="...", style="solid"] 43 node [shape=Mrecord, style=filled, colorscheme=spectral7] 49 c23 [shape="none", label="...", style="solid"]
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H A D | simpledom.dot | 13 node [shape=record, fontsize="8", margin="0.04", height=0.2, color=gray] 19 node [shape="box", style="filled", fillcolor="gray95"] 30 node [shape=Mrecord, style=filled, colorscheme=spectral7]
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/aosp12/packages/modules/NeuralNetworks/tools/api/ |
H A D | types.spec | 1164 * Keys should have a shape of [40]. If Lookups tensor has shape 1181 * shape [ k ]. 2047 * shape of the output tensor. The number of elements implied by shape 2056 * * 0: The output tensor, of shape specified by the input shape. 2628 * shape is [1]. 3884 * * 2: A 2-D Tensor of shape [num_anchors, 4], specifying the shape of each 4106 * * 2: A 2-D Tensor of shape [num_anchors, 4], specifying the shape of each 5119 * shape is [1]. 5147 * shape is [1]. 5180 * shape is [1]. [all …]
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/aosp12/packages/apps/ThemePicker/src/com/android/customization/model/theme/custom/ |
H A D | ColorOptionsProvider.java | 92 Drawable shape = loadShape(shapePackage); in loadOptions() local 93 addDefault(previewIcons, shape); in loadOptions() 107 option.setShapeDrawable(shape); in loadOptions() 116 private void addDefault(List<Drawable> previewIcons, Drawable shape) { in addDefault() argument 139 option.setShapeDrawable(shape); in addDefault() 162 PathShape shape = new PathShape(PathParser.createPathFromPathData(path), in loadShape() local 164 shapeDrawable = new ShapeDrawable(shape); in loadShape()
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H A D | ShapeOptionsProvider.java | 99 PathShape shape = new PathShape(path, PATH_SIZE, PATH_SIZE); in createShapeDrawable() local 100 ShapeDrawable shapeDrawable = new ShapeDrawable(shape); in createShapeDrawable() 135 String shape = overlayRes.getString(overlayRes.getIdentifier(CONFIG_ICON_MASK, "string", in loadPath() local 138 if (!TextUtils.isEmpty(shape)) { in loadPath() 139 return PathParser.createPathFromPathData(shape); in loadPath()
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/aosp12/packages/modules/NeuralNetworks/runtime/test/specs/V1_2/ |
H A D | sub_v1_2.mod.py | 37 shape = "{2, 4, 16, 2}, 0.5, 0" variable 38 input0 = Input("input0", "TENSOR_QUANT8_ASYMM", shape) 39 input1 = Input("input1", "TENSOR_QUANT8_ASYMM", shape) 41 output0 = Output("output0", "TENSOR_QUANT8_ASYMM", shape)
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/aosp12/packages/modules/NeuralNetworks/runtime/test/specs/V1_3/ |
H A D | sub_quant8_signed.mod.py | 86 shape = "{2, 4, 16, 2}, 0.5, -128" variable 87 input0 = Input("input0", "TENSOR_QUANT8_ASYMM_SIGNED", shape) 88 input1 = Input("input1", "TENSOR_QUANT8_ASYMM_SIGNED", shape) 90 output0 = Output("output0", "TENSOR_QUANT8_ASYMM_SIGNED", shape)
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