| /packages/apps/LegacyCamera/jni/ |
| D | feature_mos_jni.cpp | 587 int* dims = new int[2]; in Java_com_android_camera_panorama_Mosaic_getFinalMosaic() local
598 dims[0] = width; in Java_com_android_camera_panorama_Mosaic_getFinalMosaic()
599 dims[1] = height; in Java_com_android_camera_panorama_Mosaic_getFinalMosaic()
610 env->SetIntArrayRegion(bytes, imageSize, 2, (jint*) dims); in Java_com_android_camera_panorama_Mosaic_getFinalMosaic()
612 delete[] dims; in Java_com_android_camera_panorama_Mosaic_getFinalMosaic()
642 unsigned char* dims = new unsigned char[8]; in Java_com_android_camera_panorama_Mosaic_getFinalMosaicNV21() local
644 dims[0] = (unsigned char)(width >> 24); in Java_com_android_camera_panorama_Mosaic_getFinalMosaicNV21()
645 dims[1] = (unsigned char)(width >> 16); in Java_com_android_camera_panorama_Mosaic_getFinalMosaicNV21()
646 dims[2] = (unsigned char)(width >> 8); in Java_com_android_camera_panorama_Mosaic_getFinalMosaicNV21()
647 dims[3] = (unsigned char)width; in Java_com_android_camera_panorama_Mosaic_getFinalMosaicNV21()
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| /packages/modules/NeuralNetworks/runtime/test/ |
| D | TestOperandExtraParams.cpp | 46 static uint32_t dims[4] = {1, 2, 3, CHANNEL_DIM_SIZE}; in createOperand() local
68 .dimensions = dims, in createOperand()
74 .dimensions = dims, in createOperand()
80 .dimensions = dims, in createOperand()
86 .dimensions = dims, in createOperand()
92 .dimensions = dims, in createOperand()
98 .dimensions = dims, in createOperand()
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| D | GeneratedTestUtils.cpp | 45 auto dims = op.dimensions; in getOperandType() local
47 dims.assign(dims.size(), 0); in getOperandType()
51 static_cast<Type>(op.type), dims, in getOperandType()
54 return OperandType(static_cast<Type>(op.type), dims, op.scale, op.zeroPoint); in getOperandType()
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| D | TestValidation.cpp | 2434 uint32_t rank, dims[4], expectedRank = 1, expectedDims = 2; in TEST_F() local
2438 EXPECT_EQ(ANeuralNetworksExecution_getOutputOperandDimensions(execution, 0, dims), in TEST_F()
2448 EXPECT_EQ(ANeuralNetworksExecution_getOutputOperandDimensions(nullptr, 0, dims), in TEST_F()
2460 EXPECT_EQ(ANeuralNetworksExecution_getOutputOperandDimensions(execution, -1, dims), in TEST_F()
2462 EXPECT_EQ(ANeuralNetworksExecution_getOutputOperandDimensions(execution, 999, dims), in TEST_F()
2467 EXPECT_EQ(ANeuralNetworksExecution_getOutputOperandDimensions(execution, 0, dims), in TEST_F()
2470 EXPECT_EQ(dims[0], expectedDims); in TEST_F()
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| /packages/modules/NeuralNetworks/common/include/ |
| D | CpuOperationUtils.h | 37 tflite::Dims<4> dims; in convertShapeToDims() local
43 dims.sizes[i] = static_cast<int>(getSizeOfDimension(shape, src)); in convertShapeToDims()
45 dims.sizes[i] = 1; in convertShapeToDims()
49 dims.strides[0] = 1; in convertShapeToDims()
51 dims.strides[i] = dims.strides[i - 1] * dims.sizes[i - 1]; in convertShapeToDims()
53 return dims; in convertShapeToDims()
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| /packages/modules/StatsD/statsd/src/ |
| D | stats_log_util.cpp | 105 void writeDimensionToProtoHelper(const std::vector<FieldValue>& dims, size_t* index, int depth, in writeDimensionToProtoHelper() argument
108 size_t count = dims.size(); in writeDimensionToProtoHelper()
110 const auto& dim = dims[*index]; in writeDimensionToProtoHelper()
162 writeDimensionToProtoHelper(dims, index, valueDepth, dim.mField.getPrefix(valueDepth), in writeDimensionToProtoHelper()
173 void writeDimensionLeafToProtoHelper(const std::vector<FieldValue>& dims, in writeDimensionLeafToProtoHelper() argument
177 size_t count = dims.size(); in writeDimensionLeafToProtoHelper()
179 const auto& dim = dims[*index]; in writeDimensionLeafToProtoHelper()
222 writeDimensionLeafToProtoHelper(dims, dimensionLeafField, in writeDimensionLeafToProtoHelper()
338 void writeFieldValueTreeToStreamHelper(int tagId, const std::vector<FieldValue>& dims, in writeFieldValueTreeToStreamHelper() argument
341 size_t count = dims.size(); in writeFieldValueTreeToStreamHelper()
[all …]
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| D | HashableDimensionKey.cpp | 42 const vector<FieldValue>& dims, in populateStatsDimensionsValueParcelChildren() argument
49 while (index < dims.size()) { in populateStatsDimensionsValueParcelChildren()
50 const FieldValue& dim = dims[index]; in populateStatsDimensionsValueParcelChildren()
87 dim.mField.getPrefix(childDepth + 1), dims, in populateStatsDimensionsValueParcelChildren()
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| /packages/modules/NeuralNetworks/common/types/operations/src/ |
| D | Cast.cpp | 60 auto getNumberOfElements = [](const std::vector<uint32_t>& dims) { in validate() argument
61 if (dims.empty()) { in validate()
64 return std::accumulate(dims.begin(), dims.end(), 1, std::multiplies<>()); in validate()
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| /packages/modules/NeuralNetworks/common/cpu_operations/ |
| D | Fill.cpp | 48 const int32_t* dims = context->getInputBuffer<int32_t>(kDimsTensor); in prepare() local
50 outputShape.dimensions[i] = dims[i]; in prepare()
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| D | LSHProjectionTest.cpp | 62 auto multiAll = [](const std::vector<uint32_t>& dims) -> uint32_t { in LSHProjectionOpModel() argument
64 for (uint32_t d : dims) { in LSHProjectionOpModel()
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| D | EmbeddingLookupTest.cpp | 77 auto multiAll = [](const std::vector<uint32_t>& dims) -> uint32_t { in EmbeddingLookupOpModel() argument
79 for (uint32_t d : dims) { in EmbeddingLookupOpModel()
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| D | HashtableLookupTest.cpp | 91 auto multiAll = [](const std::vector<uint32_t>& dims) -> uint32_t { in HashtableLookupOpModel() argument
93 for (uint32_t d : dims) { in HashtableLookupOpModel()
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| D | SVDFTest.cpp | 218 auto multiAll = [](const std::vector<uint32_t>& dims) -> uint32_t { in SVDFOpModel() argument
220 for (uint32_t d : dims) { in SVDFOpModel()
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| D | LayerNormLSTMTest.cpp | 152 auto multiAll = [](const std::vector<uint32_t>& dims) -> uint32_t { in LayerNormLSTMOpModel() argument
154 for (uint32_t d : dims) { in LayerNormLSTMOpModel()
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| D | LSTMTest.cpp | 141 auto multiAll = [](const std::vector<uint32_t>& dims) -> uint32_t { in LSTMOpModel() argument
143 for (uint32_t d : dims) { in LSTMOpModel()
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| /packages/modules/NeuralNetworks/runtime/test/android_fuzzing/ |
| D | FuzzTest.cpp | 42 const auto& dims = op.dimensions; in getOperandType() local
45 static_cast<Type>(op.type), dims, in getOperandType()
48 return OperandType(static_cast<Type>(op.type), dims, op.scale, op.zeroPoint); in getOperandType()
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| /packages/modules/NeuralNetworks/tools/test_generator/ |
| D | README.md | 287 AxisConverter(origin, origin, dim, drop[0:(dim-i)]).Identify(op_list) for i in dims])
288 example.AddDims(dims, *op_list)
292 example.AddAllDims(dims, *op_list)
298 example.AddAllDimsAndPositiveAxis(dims, *op_list)
304 example.AddAllDimsAndAxis(dims, *op_list)
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| D | test_generator.py | 1165 def AddDims(self, dims, *args, includeDefault=True, defaultName=None): argument
1167 dims = [dims] if type(dims) is int else list(dims)
1170 var = [AxisConverter(origin, origin, dim, drop[0:(dim-i)]).Identify(args) for i in dims]
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| /packages/modules/StatsD/tests/src/android/cts/statsd/validation/ |
| D | ValidationTests.java | 267 List<DimensionsValue> dims = data.getDimensionLeafValuesInWhatList(); in getStatsdWakelockData() local
268 assertThat(dims).hasSize(2); in getStatsdWakelockData()
273 for (DimensionsValue dim : dims) { in getStatsdWakelockData()
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| /packages/modules/NeuralNetworks/tools/api/ |
| D | OperationTypes.t | 51 * To encode a conceptual n-dimensional dense tensor with dims [D0, ..., Dn-1], potentially with
52 * a k-dimensional block (0 <= k <= n) with dims [Dn, ..., Dn+k-1], the format specifies:
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| /packages/modules/NeuralNetworks/runtime/ |
| D | ExecutionBuilder.cpp | 536 const auto& dims = mOutputs[index].dimensions(); in getOutputOperandDimensions() local
537 if (dims.empty()) { in getOutputOperandDimensions()
542 std::copy(dims.begin(), dims.end(), dimensions); in getOutputOperandDimensions()
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| /packages/modules/NeuralNetworks/runtime/test/fuzzing/ |
| D | RandomVariable.h | 251 void addDimensionProd(const std::vector<RandomVariable>& dims);
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| D | RandomVariable.cpp | 1035 void RandomVariableNetwork::addDimensionProd(const std::vector<RandomVariable>& dims) { in addDimensionProd() argument
1036 if (dims.size() <= 1) return; in addDimensionProd()
1038 for (const auto& dim : dims) order.push_back(dim.get()); in addDimensionProd()
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| /packages/modules/NeuralNetworks/common/ |
| D | LegacyUtils.cpp | 1392 auto getNumberOfElements = [](const std::vector<uint32_t>& dims) { in validateOperation() argument
1393 if (dims.size() == 0) { in validateOperation()
1396 return std::accumulate(dims.begin(), dims.end(), 1, std::multiplies<>()); in validateOperation()
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| /packages/modules/NeuralNetworks/driver/sample_hidl/ |
| D | SampleDriverFloatXNNPACK.cpp | 239 std::vector<size_t> dims(operands[tensors[t]].dimensions.size()); in Create() local
240 for (size_t i = 0; i < dims.size(); i++) { in Create()
241 dims[i] = operands[tensors[t]].dimensions[i]; in Create()
245 subgraph.get(), xnn_datatype_fp32, dims.size(), dims.data(), data, in Create()
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