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/packages/modules/NeuralNetworks/common/
DCpuExecutor.cpp85 bool setOutputShape(uint32_t index, const Shape& shape) override;
127 return getInputInfo(index)->shape(); in getInputShape()
143 return getOutputInfo(index)->shape(); in getOutputShape()
168 bool setInfoAndAllocateIfNeeded(RunTimeOperandInfo* info, const Shape& shape, int* result) { in setInfoAndAllocateIfNeeded() argument
172 if (info->type != shape.type) { in setInfoAndAllocateIfNeeded()
177 if (info->scale != shape.scale) { in setInfoAndAllocateIfNeeded()
182 if (info->zeroPoint != shape.offset) { in setInfoAndAllocateIfNeeded()
187 if (info->extraParams != shape.extraParams) { in setInfoAndAllocateIfNeeded()
194 auto combined = combineDimensions(shape.dimensions, info->dimensions); in setInfoAndAllocateIfNeeded()
201 info->type = shape.type; in setInfoAndAllocateIfNeeded()
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DIndexedShapeWrapper.cpp28 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()
DOperationsUtils.cpp134 uint32_t getNumberOfElements(const Shape& shape) { in getNumberOfElements() argument
136 for (size_t i = 0; i < shape.dimensions.size(); i++) { in getNumberOfElements()
137 count *= shape.dimensions[i]; in getNumberOfElements()
142 uint32_t getNumberOfElements(const Shape& shape, size_t firstAxisInclusive, in getNumberOfElements() argument
146 nnAssert(lastAxisExclusive <= shape.dimensions.size()); in getNumberOfElements()
149 count *= shape.dimensions[i]; in getNumberOfElements()
154 uint32_t getNumberOfDimensions(const Shape& shape) { in getNumberOfDimensions() argument
155 return shape.dimensions.size(); in getNumberOfDimensions()
158 uint32_t getSizeOfDimension(const Shape& shape, uint32_t dimensionIdx) { in getSizeOfDimension() argument
159 nnAssert(0 <= dimensionIdx && dimensionIdx < shape.dimensions.size()); in getSizeOfDimension()
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/packages/modules/NeuralNetworks/common/operations/
DBidirectionalSequenceLSTM.cpp336 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()
419 *fwOutputActivationState = fw_activation_state_->shape(); in Prepare()
420 *fwOutputCellState = fw_cell_state_->shape(); in Prepare()
421 *bwOutputActivationState = bw_activation_state_->shape(); in Prepare()
422 *bwOutputCellState = bw_cell_state_->shape(); in Prepare()
442 std::vector<uint32_t> fw_output_dims = input_->shape().dimensions; in Eval()
459 Shape bwInputShape = input_->shape(); in Eval()
463 bwInputShape = aux_input_->shape(); in Eval()
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DRNN.cpp68 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()
DSVDF.cpp95 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()
DQuantizedLSTMTest.cpp34 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()
DLogSoftmax.cpp42 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()
DQuantizedLSTM.cpp210 const std::vector<uint32_t> submatrixDims = submatrix->shape().dimensions; in assignWeightsSubmatrix()
332 *cellStateOutShape = prevCellState->shape(); in prepare()
333 *outputShape = prevOutput->shape(); in prepare()
412 GetBuffer<const uint8_t>(input_), convertShapeToDims(input_->shape()), in eval()
413 GetBuffer<const uint8_t>(prevOutput_), convertShapeToDims(prevOutput_->shape()), in eval()
416 convertShapeToDims(prevCellState_->shape()), in eval()
418 GetBuffer<int16_t>(cellStateOut_), convertShapeToDims(cellStateOut_->shape()), in eval()
419 GetBuffer<uint8_t>(output_), convertShapeToDims(output_->shape()), concatTemp.data(), in eval()
DEmbeddingLookup.cpp37 const int row_size = value_->shape().dimensions[0]; in Eval()
41 for (uint32_t i = 0; i < lookup_->shape().dimensions[0]; i++) { in Eval()
DHashtableLookup.cpp47 const int num_rows = value_->shape().dimensions[0]; in Eval()
52 for (int i = 0; i < static_cast<int>(lookup_->shape().dimensions[0]); i++) { in Eval()
/packages/modules/NeuralNetworks/common/include/
DCpuOperationUtils.h35 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()
43 dims.sizes[i] = static_cast<int>(getSizeOfDimension(shape, src)); in convertShapeToDims()
56 inline tflite::RuntimeShape convertShapeToTflshape(const Shape& shape) { in convertShapeToTflshape() argument
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()
166 return convertNchwToNhwc(mDataOriginal, shape, &mDataNhwc, &mShape); in initialize()
186 bool initialize(T* data, const Shape& shape) { in initialize() argument
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DOperationsUtils.h89 virtual bool setOutputShape(uint32_t index, const Shape& shape) = 0;
131 uint32_t getNumberOfElements(const Shape& shape);
132 uint32_t getNumberOfElements(const Shape& shape, size_t firstAxisInclusive,
135 uint32_t getNumberOfDimensions(const Shape& shape);
137 uint32_t getSizeOfDimension(const Shape& shape, uint32_t dimensionIdx);
139 uint32_t hasKnownRank(const Shape& shape);
144 inline bool handleNegativeAxis(const Shape& shape, int32_t* axis) { in handleNegativeAxis() argument
145 return handleNegativeAxis(getNumberOfDimensions(shape), axis); in handleNegativeAxis()
326 inline bool transposeFirstTwoDimensions(const T* buffer, const Shape& shape, T* transposedBuffer) { in transposeFirstTwoDimensions() argument
327 const int numDims = getNumberOfDimensions(shape); in transposeFirstTwoDimensions()
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DCpuExecutor.h76 Shape shape() const { in shape() function
276 return operand->shape().dimensions.size(); in NumDimensions()
280 return operand->shape().dimensions[i]; in SizeOfDimension()
/packages/modules/NeuralNetworks/tools/api/
Dtypes.spec425 * * 0: A 4-D tensor, of shape [batches, height, width, depth], specifying
454 * * 0: A 4-D tensor, of shape [batches, height, width, depth], specifying
478 * * 0: The output 4-D tensor, of shape
514 * * 0 ~ n-1: The list of n input tensors, of shape
536 * tensors. The output shape is [D0, D1, ..., sum(Daxis(i)), ..., Dm].
1119 * * 1: A 2-D tensor, specifying the weights, of shape
1122 * * 2: A 1-D tensor, of shape [num_units], specifying the bias. For input
1138 * * 0: The output tensor, of shape [batch_size, num_units]. %{BeforeNNAPILevel3For}
1163 * For example, if Values has shape of [40, 200, 300],
1164 * Keys should have a shape of [40]. If Lookups tensor has shape
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/packages/apps/ThemePicker/src/com/android/customization/model/theme/custom/
DColorOptionsProvider.java92 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()
DShapeOptionsProvider.java99 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()
/packages/apps/Test/connectivity/sl4n/rapidjson/doc/diagram/
Dmove2.dot19 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"]
Dmove3.dot20 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"]
Dsimpledom.dot13 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]
Dinsituparsing.dot13 node [shape=record, fontsize="8", margin="0.04", height=0.2, color=gray]
16 newjson [shape=plaintext, label=<
37 node [shape=Mrecord, style=filled, colorscheme=spectral7]
Dmove1.dot19 node [shape=Mrecord, style=filled, colorscheme=spectral7]
37 node [shape=Mrecord, style=filled, colorscheme=spectral7]
/packages/modules/NeuralNetworks/runtime/test/specs/V1_2/
Dsub_v1_2.mod.py37 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)
/packages/modules/NeuralNetworks/runtime/test/specs/V1_3/
Dsub_quant8_signed.mod.py86 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)
/packages/apps/Launcher3/src/com/android/launcher3/graphics/
DIconShape.java419 IconShape shape = getShapeDefinition(parser.getName(), a.getFloat(0, 1));
422 result.add(shape);
449 for (IconShape shape : getAllShapes(context)) {
451 shape.addToPath(shapePath, 0, 0, size / 2f);
458 closestShape = shape;

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