| /packages/modules/NeuralNetworks/common/cpu_operations/ |
| D | Reshape.cpp | 40 bool copyData(const void* inputData, const Shape& inputShape, void* outputData, in copyData() argument
44 memcpy(outputData, inputData, count); in copyData()
50 T* outputData, const Shape& outputShape) { in depthToSpaceGeneric() argument
53 outputData, convertShapeToDims(outputShape)); in depthToSpaceGeneric()
57 int32_t blockSize, float* outputData,
60 int32_t blockSize, _Float16* outputData,
63 int32_t blockSize, uint8_t* outputData,
66 int32_t blockSize, int8_t* outputData,
71 T* outputData, const Shape& outputShape) { in spaceToDepthGeneric() argument
74 outputData, convertShapeToDims(outputShape)); in spaceToDepthGeneric()
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| D | Activation.cpp | 54 bool reluFloat(const T* inputData, const Shape& inputShape, T* outputData, in reluFloat() argument
59 for (int i = 0; i < numElements; i++, inputData++, outputData++) { in reluFloat()
60 *outputData = static_cast<T>( in reluFloat()
65 template bool reluFloat<float>(const float* inputData, const Shape& inputShape, float* outputData,
68 _Float16* outputData, const Shape& outputShape, float reluMin,
72 bool relu1Float(const T* inputData, const Shape& inputShape, T* outputData, in relu1Float() argument
74 return reluFloat(inputData, inputShape, outputData, outputShape, -1.f, 1.f); in relu1Float()
76 template bool relu1Float<float>(const float* inputData, const Shape& inputShape, float* outputData,
79 _Float16* outputData, const Shape& outputShape);
82 bool relu6Float(const T* inputData, const Shape& inputShape, T* outputData, in relu6Float() argument
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| D | Pooling.cpp | 144 float* outputData, const Shape& outputShape) { in averagePoolNhwc() argument
149 convertShapeToTflshape(outputShape), outputData); in averagePoolNhwc()
154 _Float16* outputData, const Shape& outputShape) { in averagePoolNhwc() argument
162 convertFloat32ToFloat16(outputDataFloat32, outputData); in averagePoolNhwc()
167 uint8_t* outputData, const Shape& outputShape) { in averagePoolNhwc() argument
172 convertShapeToTflshape(outputShape), outputData); in averagePoolNhwc()
177 int8_t* outputData, const Shape& outputShape) { in averagePoolNhwc() argument
185 outputData); in averagePoolNhwc()
190 float* outputData, const Shape& outputShape) { in l2PoolNhwc() argument
195 convertShapeToTflshape(outputShape), outputData); in l2PoolNhwc()
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| D | L2Normalization.cpp | 47 float* outputData, const Shape& /*outputShape*/) { in l2normFloat32Impl() argument
57 float* outputBeg = outputData + outer * axisSize * innerSize; in l2normFloat32Impl()
75 uint8_t* outputData, const Shape& /*outputShape*/) { in l2normQuant8Impl() argument
84 uint8_t* outputBeg = outputData + outer * axisSize * innerSize; in l2normQuant8Impl()
107 int8_t* outputData, const Shape& /*outputShape*/) { in l2normQuant8SignedImpl() argument
116 int8_t* outputBeg = outputData + outer * axisSize * innerSize; in l2normQuant8SignedImpl()
137 bool l2normFloat32(const float* inputData, const Shape& inputShape, int32_t axis, float* outputData, in l2normFloat32() argument
146 convertShapeToTflshape(outputShape), outputData); in l2normFloat32()
149 return l2normFloat32Impl(inputData, inputShape, axis, outputData, outputShape); in l2normFloat32()
154 _Float16* outputData, const Shape& outputShape) { in l2normFloat16() argument
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| D | SimpleMath.cpp | 40 const Shape& axisShape, bool keepDims, _Float16* outputData, in meanFloat16() argument
49 convertFloat32ToFloat16(outputDataFloat32, outputData); in meanFloat16()
55 bool keepDims, T* outputData, const Shape& outputShape) { in meanGeneric() argument
73 getNumberOfDimensions(inputShape), outputData, in meanGeneric()
85 float* outputData, const Shape& outputShape);
88 bool keepDims, uint8_t* outputData,
92 bool keepDims, int8_t* outputData,
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| D | LocalResponseNormalization.cpp | 47 int32_t axis, float* outputData, in localResponseNormFloat32Impl() argument
56 float* outputBase = outputData + outer * axisSize * innerSize; in localResponseNormFloat32Impl()
77 T beta, int32_t axis, T* outputData, const Shape& outputShape);
81 float bias, float alpha, float beta, int32_t axis, float* outputData, in localResponseNorm() argument
93 convertShapeToTflshape(outputShape), outputData); in localResponseNorm()
97 outputData, outputShape); in localResponseNorm()
104 _Float16* outputData, const Shape& outputShape) { in localResponseNorm() argument
112 convertFloat32ToFloat16(outputDataFloat32, outputData); in localResponseNorm()
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| D | Softmax.cpp | 51 int32_t axis, float* outputData, const Shape& /*outputShape*/) { in softmaxSlowFloat32() argument
60 float* outputBeg = outputData + outer * axisSize * innerSize; in softmaxSlowFloat32()
83 float* outputData, const Shape& outputShape) { in softmaxFloat32() argument
91 convertShapeToTflshape(outputShape), outputData); in softmaxFloat32()
94 return softmaxSlowFloat32(inputData, inputShape, beta, axis, outputData, outputShape); in softmaxFloat32()
99 int32_t axis, _Float16* outputData, const Shape& outputShape) { in softmaxFloat16() argument
107 convertFloat32ToFloat16(outputData_float32, outputData); in softmaxFloat16()
115 T* outputData, const Shape& /*outputShape*/) { in softmaxQuant8Impl() argument
135 T* outputBeg = outputData + outer * axisSize * innerSize; in softmaxQuant8Impl()
201 T* outputData, const Shape& outputShape) { in softmaxQuant8() argument
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| D | Pow.cpp | 35 const Shape& exponentShape, T* outputData, const Shape& outputShape) { in evalGeneric() argument
50 outputData[outputFlatIndex] = std::pow(static_cast<float>(baseData[baseFlatIndex]), in evalGeneric()
70 const Shape& exponentShape, void* outputData, const Shape& outputShape) { in eval() argument
75 reinterpret_cast<_Float16*>(outputData), outputShape); in eval()
80 reinterpret_cast<float*>(outputData), outputShape); in eval()
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| D | Cast.cpp | 44 bool copyToTensor(const FromT* inputData, int numElements, uint8_t* outputData, in copyToTensor() argument
49 copyCast(inputData, reinterpret_cast<dataType*>(outputData), numElements); \ in copyToTensor()
72 bool eval(const uint8_t* inputData, const Shape& inputShape, uint8_t* outputData, in eval() argument
80 copyToTensor(reinterpret_cast<const dataType*>(inputData), numElements, outputData, \ in eval()
92 return copyData(inputData, inputShape, outputData, outputShape); in eval()
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| D | FullyConnected.cpp | 55 float* outputData, const Shape& outputShape) { in fullyConnectedFloat32() argument
70 outputData, convertShapeToDims(outputShape)); in fullyConnectedFloat32()
77 outputData, convertShapeToDims(outputShape)); in fullyConnectedFloat32()
85 _Float16* outputData, const Shape& outputShape) { in fullyConnectedFloat16() argument
98 convertFloat32ToFloat16(outputDataFloat32, outputData); in fullyConnectedFloat16()
106 uint8_t* outputData, const Shape& outputShape) { in fullyConnectedQuant8() argument
138 outputActivationMin, outputActivationMax, outputData, in fullyConnectedQuant8()
147 int8_t* outputData, const Shape& outputShape) { in fullyConnectedQuant8() argument
175 biasData, convertShapeToTflshape(outputShape), outputData); in fullyConnectedQuant8()
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| D | ResizeImageOps.cpp | 62 bool halfPixelCenters, T* outputData, const Shape& outputShape) { in resizeNearestNeighbor() argument
94 outputData + b * outHeight * outWidth * channels + in resizeNearestNeighbor()
105 bool alignCorners, bool halfPixelCenters, T* outputData, in resizeImageOpNhwc() argument
120 outDimData, convertShapeToTflshape(outputShape), outputData); in resizeImageOpNhwc()
124 resizeNearestNeighbor(inputData, inputShape, alignCorners, halfPixelCenters, outputData, in resizeImageOpNhwc()
133 _Float16* outputData, const Shape& outputShape) { in resizeImageOpNhwc() argument
140 convertFloat32ToFloat16(outputData_float32, outputData); in resizeImageOpNhwc()
146 bool alignCorners, bool halfPixelCenters, T* outputData, in resizeImageOp() argument
151 NN_RET_CHECK(output.initialize(outputData, outputShape)); in resizeImageOp()
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| D | GroupedConv2D.cpp | 54 int32_t numGroups, int32_t activation, float* outputData, in groupedConvFloat32() argument
63 float* outPtr = outputData; in groupedConvFloat32()
112 int32_t numGroups, int32_t activation, T* outputData, in groupedConvQuant8() argument
135 T* outPtr = outputData; in groupedConvQuant8()
191 int32_t numGroups, int32_t activation, int8_t* outputData,
200 int32_t numGroups, int32_t activation, uint8_t* outputData,
211 T* outputData, const Shape& outputShape) { in groupedConvQuant8PerChannel() argument
240 T* outPtr = outputData; in groupedConvQuant8PerChannel()
295 int32_t activation, _Float16* outputData, const Shape& outputShape) { in groupedConvFloat16() argument
311 convertFloat32ToFloat16(outputData_float32, outputData); in groupedConvFloat16()
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| D | RNN.cpp | 119 const int32_t activation, T* outputData) { in RNNStep() argument
128 /*outputBatchStride=*/numUnits, /*outputBatchOffset=*/0, outputData); in RNNStep()
141 const uint32_t outputBatchStride, const uint32_t outputBatchOffset, T* outputData, in RNNStep() argument
168 T* output_ptr_batch = outputData + b * outputBatchStride + outputBatchOffset; in RNNStep()
228 _Float16* outputData);
237 const uint32_t outputBatchOffset, _Float16* outputData,
244 float* outputData);
253 float* outputData, float* hiddenStateOutput);
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| D | ArgMinMax.cpp | 32 Out* outputData, const Shape& /*outputShape*/) { in argMinMaxImpl() argument
48 outputData[outer * innerSize + inner] = minMaxIndex; in argMinMaxImpl()
54 uint8_t* outputData, const Shape& outputShape) { in argMinMaxGeneric() argument
62 reinterpret_cast<int32_t*>(outputData), outputShape); \ in argMinMaxGeneric()
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| D | TransposeConv2D.cpp | 124 const TransposeConv2dParam& param, float* outputData, in transposeConvNhwc() argument
132 memset(outputData, 0, getNumberOfElements(outputShape) * sizeof(float)); in transposeConvNhwc()
135 float* outputBase = outputData; in transposeConvNhwc()
167 float* outPtr = outputData; in transposeConvNhwc()
181 const TransposeConv2dParam& param, T* outputData, const Shape& outputShape) { in transposeConvNhwc() argument
259 T* outPtr = outputData; in transposeConvNhwc()
276 const TransposeConv2dParam& param, _Float16* outputData, in transposeConvNhwc() argument
291 convertFloat32ToFloat16(outputData_float32, outputData); in transposeConvNhwc()
299 const TransposeConv2dParam& param, T_Input* outputData, in transposeConv() argument
304 NN_RET_CHECK(output.initialize(outputData, outputShape)); in transposeConv()
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| D | Quantize.cpp | 36 bool quantizeToQuant8(const T* inputData, uint8_t* outputData, const Shape& outputShape) { in quantizeToQuant8() argument
40 outputData[i] = static_cast<uint8_t>(std::max<float>( in quantizeToQuant8()
49 bool quantizeToQuant8Signed(const T* inputData, int8_t* outputData, const Shape& outputShape) { in quantizeToQuant8Signed() argument
53 outputData[i] = static_cast<int8_t>(std::max<float>( in quantizeToQuant8Signed()
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| D | RoiPooling.cpp | 45 T_Input* outputData, const Shape& outputShape) { in roiPoolingNhwc() argument
61 T_Input* outPtr = outputData; in roiPoolingNhwc()
134 bool useNchw, T_Input* outputData, const Shape& outputShape) { in roiPooling() argument
138 NN_RET_CHECK(output.initialize(outputData, outputShape)); in roiPooling()
151 float widthStride, bool useNchw, uint8_t* outputData, in roiPooling() argument
156 batchSplitShape, heightStride, widthStride, useNchw, outputData, in roiPooling()
166 float widthStride, bool useNchw, int8_t* outputData, in roiPooling() argument
171 batchSplitShape, heightStride, widthStride, useNchw, outputData, in roiPooling()
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| D | Tile.cpp | 69 void tileImpl(const T* inputData, const Shape& inputShape, const int32_t* multiples, T* outputData, in tileImpl() argument
71 TileOneDimension(inputShape, inputData, multiples, outputData, 0); in tileImpl()
91 uint8_t* outputData, const Shape& outputShape) { in eval() argument
97 reinterpret_cast<dataType*>(outputData), outputShape); \ in eval()
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| /packages/apps/Camera2/src/com/android/camera/app/ |
| D | MemoryQuery.java | 104 HashMap outputData = new HashMap(); in queryMemory() local
105 outputData.put(KEY_TIMESTAMP, new Long(timestamp)); in queryMemory()
106 outputData.put(KEY_MEMORY_AVAILABLE, new Long(availMem)); in queryMemory()
107 outputData.put(KEY_TOTAL_MEMORY, new Long(totalMem)); in queryMemory()
108 outputData.put(KEY_TOTAL_PSS, new Long(totalPSS)); in queryMemory()
109 outputData.put(KEY_LAST_TRIM_LEVEL, new Integer(info.lastTrimLevel)); in queryMemory()
110 outputData.put(KEY_TOTAL_PRIVATE_DIRTY, new Long(totalPrivateDirty)); in queryMemory()
111 outputData.put(KEY_TOTAL_SHARED_DIRTY, new Long(totalSharedDirty)); in queryMemory()
112 outputData.put(KEY_MEMORY_CLASS, new Long(memoryClass)); in queryMemory()
113 outputData.put(KEY_LARGE_MEMORY_CLASS, new Long(largeMemoryClass)); in queryMemory()
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| /packages/modules/NeuralNetworks/common/include/ |
| D | Operations.h | 32 bool floorFloat16(const _Float16* inputData, _Float16* outputData, const Shape& shape);
33 bool floorFloat32(const float* inputData, float* outputData, const Shape& shape);
41 _Float16* outputData, const Shape& outputShape);
47 int32_t depthMultiplier, int32_t activation, float* outputData,
55 uint8_t* outputData, const Shape& outputShape);
63 int32_t depthMultiplier, int32_t activation, uint8_t* outputData,
68 _Float16* outputData, const Shape& outputShape);
70 float bias, float alpha, float beta, int32_t axis, float* outputData,
73 bool copyData(const void* inputData, const Shape& inputShape, void* outputData,
78 T* outputData, const Shape& outputShape);
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| /packages/modules/OnDevicePersonalization/tests/cts/endtoend/src/com/android/ondevicepersonalization/cts/e2e/ |
| D | InferenceInputTest.java | 50 HashMap<Integer, Object> outputData = new HashMap<>(); in buildInput_success() local
51 outputData.put(0, new float[1]); in buildInput_success()
61 new InferenceOutput.Builder().setDataOutputs(outputData).build()) in buildInput_success()
74 HashMap<Integer, Object> outputData = new HashMap<>(); in buildInputWithSetters() local
75 outputData.put(0, new float[1]); in buildInputWithSetters()
85 new InferenceOutput.Builder().setDataOutputs(outputData).build()) in buildInputWithSetters()
90 new InferenceOutput.Builder().setDataOutputs(outputData).build()) in buildInputWithSetters()
102 HashMap<Integer, Object> outputData = new HashMap<>(); in buildInput_batchNotSet_success() local
103 outputData.put(0, new float[1]); in buildInput_batchNotSet_success()
113 new InferenceOutput.Builder().setDataOutputs(outputData).build()) in buildInput_batchNotSet_success()
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| D | InferenceOutputTest.java | 33 HashMap<Integer, Object> outputData = new HashMap<>(); in build_success() local
34 outputData.put(0, new float[] {1.0f}); in build_success()
35 InferenceOutput output = new InferenceOutput.Builder().setDataOutputs(outputData).build(); in build_success()
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| /packages/modules/OnDevicePersonalization/tests/frameworktests/src/android/adservices/ondevicepersonalization/ |
| D | InferenceInputTest.java | 58 HashMap<Integer, Object> outputData = new HashMap<>(); in buildInferenceInput_reusable() local
59 outputData.put(0, new float[1]); in buildInferenceInput_reusable()
69 new InferenceOutput.Builder().setDataOutputs(outputData).build()) in buildInferenceInput_reusable()
78 HashMap<Integer, Object> outputData = new HashMap<>(); in buildInput_success() local
79 outputData.put(0, new float[1]); in buildInput_success()
89 new InferenceOutput.Builder().setDataOutputs(outputData).build()) in buildInput_success()
102 HashMap<Integer, Object> outputData = new HashMap<>(); in buildInput_batchNotSet_success() local
103 outputData.put(0, new float[1]); in buildInput_batchNotSet_success()
113 new InferenceOutput.Builder().setDataOutputs(outputData).build()) in buildInput_batchNotSet_success()
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| D | ModelManagerTest.java | 68 HashMap<Integer, Object> outputData = new HashMap<>(); in runInference_success() local
69 outputData.put(0, new float[1]); in runInference_success()
76 new InferenceOutput.Builder().setDataOutputs(outputData).build()) in runInference_success()
91 HashMap<Integer, Object> outputData = new HashMap<>(); in runInference_error() local
92 outputData.put(0, new float[1]); in runInference_error()
100 new InferenceOutput.Builder().setDataOutputs(outputData).build()) in runInference_error()
121 HashMap<Integer, Object> outputData = new HashMap<>(); in runInference_resultMissingInferenceOutput() local
122 outputData.put(0, new float[1]); in runInference_resultMissingInferenceOutput()
130 new InferenceOutput.Builder().setDataOutputs(outputData).build()) in runInference_resultMissingInferenceOutput()
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| /packages/modules/NeuralNetworks/runtime/test/specs/experimental/ |
| D | densify_8.mod.py | 26 outputData = [0.0] * 210 variable
27 outputData[22] = 11.0
28 outputData[51] = 13.0
29 outputData[80] = 17.0
30 outputData[129] = 19.0
32 outputData}
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