/aosp12/frameworks/base/services/core/java/com/android/server/am/ |
H A D | LmkdStatsReporter.java | 55 final long pgFault = inputData.readLong(); in logKillOccurred() 56 final long pgMajFault = inputData.readLong(); in logKillOccurred() 57 final long rssInBytes = inputData.readLong(); in logKillOccurred() 61 final int uid = inputData.readInt(); in logKillOccurred() 62 final int oomScore = inputData.readInt(); in logKillOccurred() 63 final int minOomScore = inputData.readInt(); in logKillOccurred() 64 final int freeMemKb = inputData.readInt(); in logKillOccurred() 65 final int freeSwapKb = inputData.readInt(); in logKillOccurred() 66 final int killReason = inputData.readInt(); in logKillOccurred() 67 final int thrashing = inputData.readInt(); in logKillOccurred() [all …]
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/aosp12/packages/modules/NeuralNetworks/common/operations/ |
H A D | Reshape.cpp | 34 bool copyData(const void* inputData, const Shape& inputShape, void* outputData, in copyData() argument 38 memcpy(outputData, inputData, count); in copyData() 43 bool depthToSpaceGeneric(const T* inputData, const Shape& inputShape, int32_t blockSize, in depthToSpaceGeneric() argument 50 template bool depthToSpaceGeneric<float>(const float* inputData, const Shape& inputShape, 64 bool spaceToDepthGeneric(const T* inputData, const Shape& inputShape, int32_t blockSize, in spaceToDepthGeneric() argument 71 template bool spaceToDepthGeneric<float>(const float* inputData, const Shape& inputShape, 151 inputData + tflite::Offset(extInputShape, outB - leftBPadding, in padGeneric() 184 template bool padGeneric<float>(const float* inputData, const Shape& inputShape, 187 template bool padGeneric<_Float16>(const _Float16* inputData, const Shape& inputShape, 190 template bool padGeneric<uint8_t>(const uint8_t* inputData, const Shape& inputShape, [all …]
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H A D | Activation.cpp | 57 for (int i = 0; i < numElements; i++, inputData++, outputData++) { in reluFloat() 70 bool relu1Float(const T* inputData, const Shape& inputShape, T* outputData, in relu1Float() argument 80 bool relu6Float(const T* inputData, const Shape& inputShape, T* outputData, in relu6Float() argument 82 return reluFloat(inputData, inputShape, outputData, outputShape, 0.f, 6.f); in relu6Float() 93 for (int i = 0; i < numElements; i++, inputData++, outputData++) { in tanhFloat16() 103 for (int i = 0; i < numElements; i++, inputData++, outputData++) { in tanhFloat32() 104 *outputData = std::tanh(*inputData); in tanhFloat32() 110 bool logisticFloat(const T* inputData, const Shape& inputShape, T* outputData, in logisticFloat() argument 114 for (int i = 0; i < numElements; i++, inputData++, outputData++) { in logisticFloat() 134 for (int i = 0; i < numElements; i++, inputData++, outputData++) { in reluXQuant8() [all …]
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H A D | Split.cpp | 29 bool splitGeneric(const Scalar* inputData, const Shape& inputShape, int32_t axis, in splitGeneric() argument 43 const Scalar* inputPtr = inputData; in splitGeneric() 55 bool splitFloat16(const _Float16* inputData, const Shape& inputShape, int32_t axis, in splitFloat16() argument 59 return splitGeneric<_Float16>(inputData, inputShape, axis, outputDataPtrs, outputShapes); in splitFloat16() 62 bool splitFloat32(const float* inputData, const Shape& inputShape, int32_t axis, in splitFloat32() argument 66 return splitGeneric<float>(inputData, inputShape, axis, outputDataPtrs, outputShapes); in splitFloat32() 69 bool splitQuant8(const uint8_t* inputData, const Shape& inputShape, int32_t axis, in splitQuant8() argument 73 return splitGeneric<uint8_t>(inputData, inputShape, axis, outputDataPtrs, outputShapes); in splitQuant8() 76 bool splitQuant8Signed(const int8_t* inputData, const Shape& inputShape, int32_t axis, in splitQuant8Signed() argument 80 return splitGeneric<int8_t>(inputData, inputShape, axis, outputDataPtrs, outputShapes); in splitQuant8Signed() [all …]
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H A D | Pooling.cpp | 157 convertFloat16ToFloat32(inputData, &inputDataFloat32); in averagePoolNhwc() 187 bool l2PoolNhwc(const float* inputData, const Shape& inputShape, const PoolingParam& param, in l2PoolNhwc() argument 192 tflite::optimized_ops::L2Pool(op_params, convertShapeToTflshape(inputShape), inputData, in l2PoolNhwc() 203 convertFloat16ToFloat32(inputData, &inputDataFloat32); in l2PoolNhwc() 209 bool maxPoolNhwc(const float* inputData, const Shape& inputShape, const PoolingParam& param, in maxPoolNhwc() argument 214 tflite::optimized_ops::MaxPool(op_params, convertShapeToTflshape(inputShape), inputData, in maxPoolNhwc() 247 convertFloat16ToFloat32(inputData, &inputData_float32); in maxPoolNhwc() 255 bool averagePool(const T* inputData, const Shape& inputShape, const PoolingParam& param, in averagePool() argument 259 NN_RET_CHECK(input.initialize(inputData, inputShape)); in averagePool() 272 NN_RET_CHECK(input.initialize(inputData, inputShape)); in l2Pool() [all …]
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H A D | L2Normalization.cpp | 48 inline bool l2normFloat32Impl(const float* inputData, const Shape& inputShape, int32_t axis, in l2normFloat32Impl() argument 57 const float* inputBeg = inputData + outer * axisSize * innerSize; in l2normFloat32Impl() 84 const uint8_t* inputBeg = inputData + outer * axisSize * innerSize; in l2normQuant8Impl() 116 const int8_t* inputBeg = inputData + outer * axisSize * innerSize; in l2normQuant8SignedImpl() 151 return l2normFloat32Impl(inputData, inputShape, axis, outputData, outputShape); in l2normFloat32() 155 bool l2normFloat16(const _Float16* inputData, const Shape& inputShape, int32_t axis, in l2normFloat16() argument 159 convertFloat16ToFloat32(inputData, &inputDataFloat32); in l2normFloat16() 168 bool l2normQuant8(const uint8_t* inputData, const Shape& inputShape, int32_t axis, in l2normQuant8() argument 180 return l2normQuant8Impl(inputData, inputShape, axis, outputData, outputShape); in l2normQuant8() 184 bool l2normQuant8Signed(const int8_t* inputData, const Shape& inputShape, int32_t axis, in l2normQuant8Signed() argument [all …]
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H A D | SimpleMath.cpp | 33 bool meanFloat16(_Float16* inputData, const Shape& inputShape, const int32_t* axis, in meanFloat16() argument 38 convertFloat16ToFloat32(inputData, &inputDataFloat32); in meanFloat16() 48 bool meanGeneric(T* inputData, const Shape& inputShape, const int32_t* axis, const Shape& axisShape, in meanGeneric() argument 66 inputData, reinterpret_cast<const int*>(inputShape.dimensions.data()), in meanGeneric() 77 template bool meanGeneric<float, float>(float* inputData, const Shape& inputShape, 80 template bool meanGeneric<uint8_t, int32_t>(uint8_t* inputData, const Shape& inputShape, 84 template bool meanGeneric<int8_t, int32_t>(int8_t* inputData, const Shape& inputShape,
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H A 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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H A D | ArgMinMax.cpp | 29 static void argMinMaxImpl(const In* inputData, const Shape& inputShape, int32_t axis, bool isArgMin, in argMinMaxImpl() argument 37 auto minMaxValue = inputData[outer * axisSize * innerSize + inner]; in argMinMaxImpl() 40 const auto& value = inputData[(outer * axisSize + i) * innerSize + inner]; in argMinMaxImpl() 51 bool argMinMaxGeneric(const uint8_t* inputData, const Shape& inputShape, int32 axis, bool isArgMin, in argMinMaxGeneric() argument 59 argMinMaxImpl(reinterpret_cast<const dataType*>(inputData), inputShape, axis, isArgMin, \ in argMinMaxGeneric()
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H A D | Softmax.cpp | 53 inline bool softmaxSlowFloat32(const float* inputData, const Shape& inputShape, const float beta, in softmaxSlowFloat32() argument 61 const float* inputBeg = inputData + outer * axisSize * innerSize; in softmaxSlowFloat32() 85 bool softmaxFloat32(const float* inputData, const Shape& inputShape, const float beta, int32_t axis, in softmaxFloat32() argument 93 tflite::optimized_ops::Softmax(param, convertShapeToTflshape(inputShape), inputData, in softmaxFloat32() 97 return softmaxSlowFloat32(inputData, inputShape, beta, axis, outputData, outputShape); in softmaxFloat32() 101 bool softmaxFloat16(const _Float16* inputData, const Shape& inputShape, const float beta, in softmaxFloat16() argument 105 convertFloat16ToFloat32(inputData, &inputData_float32); in softmaxFloat16() 116 bool softmaxQuant8Impl(const T* inputData, const Shape& inputShape, const float beta, int32_t axis, in softmaxQuant8Impl() argument 136 const T* inputBeg = inputData + outer * axisSize * innerSize; in softmaxQuant8Impl() 203 bool softmaxQuant8(const T* inputData, const Shape& inputShape, const float beta, int32_t axis, in softmaxQuant8() argument [all …]
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H A D | LocalResponseNormalization.cpp | 51 inline bool localResponseNormFloat32Impl(const float* inputData, const Shape& inputShape, in localResponseNormFloat32Impl() argument 61 const float* inputBase = inputData + outer * axisSize * innerSize; in localResponseNormFloat32Impl() 82 bool localResponseNorm(const T* inputData, const Shape& inputShape, int32_t radius, T bias, T alpha, 86 bool localResponseNorm<float>(const float* inputData, const Shape& inputShape, int32_t radius, 98 param, convertShapeToTflshape(inputShape), inputData, 102 return localResponseNormFloat32Impl(inputData, inputShape, radius, bias, alpha, beta, axis, 108 bool localResponseNorm<_Float16>(const _Float16* inputData, const Shape& inputShape, int32_t radius, 113 convertFloat16ToFloat32(inputData, &inputDataFloat32);
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H A D | GroupedConv2D.cpp | 58 const float* inputBase = inputData; in groupedConvFloat32() 104 bool groupedConvQuant8(const T* inputData, const Shape& inputShape, const T* filterData, in groupedConvQuant8() argument 130 const T* inputBase = inputData; in groupedConvQuant8() 181 template bool groupedConvQuant8<int8_t>(const int8_t* inputData, const Shape& inputShape, 190 template bool groupedConvQuant8<uint8_t>(const uint8_t* inputData, const Shape& inputShape, 200 bool groupedConvQuant8PerChannel(const T* inputData, const Shape& inputShape, in groupedConvQuant8PerChannel() argument 234 const T* inputBase = inputData; in groupedConvQuant8PerChannel() 285 bool groupedConvFloat16(const _Float16* inputData, const Shape& inputShape, in groupedConvFloat16() argument 298 convertFloat16ToFloat32(inputData, &inputData_float32); in groupedConvFloat16() 312 const uint8_t* inputData, const Shape& inputShape, const int8_t* filterData, [all …]
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H A D | RNN.cpp | 116 bool RNN::RNNStep(const T* inputData, const Shape& inputShape, const T* hiddenStateInputData, in RNNStep() argument 124 return RNNStep<T>(inputData, inputShape, /*auxInputData=*/nullptr, /*auxInputShape=*/dummyShape, in RNNStep() 136 bool RNN::RNNStep(const T* inputData, const Shape& inputShape, const T* auxInputData, in RNNStep() argument 162 const T* input_ptr_batch = inputData + b * input_size; in RNNStep() 223 template bool RNN::RNNStep<_Float16>(const _Float16* inputData, const Shape& inputShape, 229 template bool RNN::RNNStep<_Float16>(const _Float16* inputData, const Shape& inputShape, 239 template bool RNN::RNNStep<float>(const float* inputData, const Shape& inputShape, 245 template bool RNN::RNNStep<float>(const float* inputData, const Shape& inputShape,
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H A D | InstanceNormalization.cpp | 49 inline bool instanceNormNhwc(const T* inputData, const Shape& inputShape, T gamma, T beta, in instanceNormNhwc() argument 64 T val = inputData[indexBase + (h * width + w) * depth]; in instanceNormNhwc() 73 T val = inputData[indexBase + (h * width + w) * depth] - mean; in instanceNormNhwc() 83 outputData[ind] = (inputData[ind] - mean) * gamma / sigma + beta; in instanceNormNhwc() 92 inline bool instanceNorm(const T* inputData, const Shape& inputShape, T gamma, T beta, T epsilon, in instanceNorm() argument 96 NN_RET_CHECK(input.initialize(inputData, inputShape)); in instanceNorm()
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H A D | FullyConnected.cpp | 56 bool fullyConnectedFloat32(const float* inputData, const Shape& inputShape, in fullyConnectedFloat32() argument 70 tflite::reference_ops::FullyConnected(inputData, convertShapeToDims(inputShape), in fullyConnectedFloat32() 77 tflite::optimized_ops::FullyConnected(inputData, convertShapeToDims(inputShape), in fullyConnectedFloat32() 86 bool fullyConnectedFloat16(const _Float16* inputData, const Shape& inputShape, in fullyConnectedFloat16() argument 92 convertFloat16ToFloat32(inputData, &inputDataFloat32); in fullyConnectedFloat16() 107 bool fullyConnectedQuant8(const uint8_t* inputData, const Shape& inputShape, in fullyConnectedQuant8() argument 138 tflite::optimized_ops::FullyConnected(inputData, convertShapeToDims(inputShape), inputOffset, in fullyConnectedQuant8() 148 bool fullyConnectedQuant8(const int8_t* inputData, const Shape& inputShape, in fullyConnectedQuant8() argument 177 params, convertShapeToTflshape(inputShape), inputData, in fullyConnectedQuant8()
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H A D | ResizeImageOps.cpp | 68 bool resizeNearestNeighbor(const T* inputData, const Shape& inputShape, bool alignCorners, in resizeNearestNeighbor() argument 98 std::copy_n(inputData + b * inHeight * inWidth * channels + in resizeNearestNeighbor() 111 bool resizeImageOpNhwc(OperationType opType, const T* inputData, const Shape& inputShape, in resizeImageOpNhwc() argument 126 convertShapeToTflshape(inputShape), inputData, convertShapeToTflshape(outDimShape), in resizeImageOpNhwc() 131 resizeNearestNeighbor(inputData, inputShape, alignCorners, halfPixelCenters, outputData, in resizeImageOpNhwc() 138 bool resizeImageOpNhwc<_Float16>(OperationType opType, const _Float16* inputData, 143 convertFloat16ToFloat32(inputData, &inputData_float32); 152 bool resizeImageOp(OperationType opType, const T* inputData, const Shape& inputShape, bool useNchw, in resizeImageOp() argument 157 NN_RET_CHECK(input.initialize(inputData, inputShape)); in resizeImageOp()
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H A 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() 90 bool eval(const uint8_t* inputData, const Shape& inputShape, const int32_t* multiples, in eval() argument 96 tileImpl(reinterpret_cast<const dataType*>(inputData), inputShape, multiples, \ in eval()
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H A D | Quantize.cpp | 40 bool quantizeToQuant8(const T* inputData, uint8_t* outputData, const Shape& outputShape) { in quantizeToQuant8() argument 45 0.0f, std::min<float>(255.0f, outputShape.offset + std::round(inputData[i] / in quantizeToQuant8() 52 bool quantizeToQuant8Signed(const T* inputData, int8_t* outputData, const Shape& outputShape) { in quantizeToQuant8Signed() argument 59 std::round(inputData[i] / outputShape.scale)))); in quantizeToQuant8Signed()
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/aosp12/packages/modules/NeuralNetworks/common/include/ |
H A D | Operations.h | 49 bool floorFloat16(const _Float16* inputData, _Float16* outputData, const Shape& shape); 50 bool floorFloat32(const float* inputData, float* outputData, const Shape& shape); 52 bool depthwiseConvFloat16(const _Float16* inputData, const Shape& inputShape, 66 bool depthwiseConvQuant8(const uint8_t* inputData, const Shape& inputShape, 73 bool depthwiseConvQuant8PerChannel(const uint8_t* inputData, const Shape& inputShape, 90 bool copyData(const void* inputData, const Shape& inputShape, void* outputData, 113 bool meanFloat16(_Float16* inputData, const Shape& inputShape, const int32_t* axis, 120 bool stridedSliceGeneric(const uint8_t* inputData, const Shape& inputShape, 128 bool splitFloat16(const _Float16* inputData, const Shape& inputShape, int32_t axis, 148 bool groupedConvFloat16(const _Float16* inputData, const Shape& inputShape, [all …]
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/aosp12/frameworks/base/startop/iorap/tests/src/com/google/android/startop/iorap/ |
H A D | ParcelablesTest.kt | 32 class ParcelablesTest<T : Parcelable>(private val inputData: InputData<T>) { 100 assertThat(inputData.valid).isEqualTo(inputData.valid) 101 assertThat(inputData.valid).isEqualTo(inputData.validCopy) 102 assertThat(inputData.valid).isNotEqualTo(inputData.validOther) 119 assertParcels(inputData.valid, inputData) 120 assertParcels(inputData.validCopy, inputData) 121 assertParcels(inputData.validOther, inputData)
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/aosp12/frameworks/base/core/java/com/android/internal/ml/clustering/ |
H A D | KMeans.java | 64 checkDataSetSanity(inputData); in predict() 65 int dimension = inputData[0].length; in predict() 79 converged = step(means, inputData); in predict() 115 public void checkDataSetSanity(float[][] inputData) { in checkDataSetSanity() argument 116 if (inputData == null) { in checkDataSetSanity() 118 } else if (inputData.length == 0) { in checkDataSetSanity() 120 } else if (inputData[0] == null) { in checkDataSetSanity() 124 final int dimension = inputData[0].length; in checkDataSetSanity() 125 final int length = inputData.length; in checkDataSetSanity() 127 if (inputData[i] == null || inputData[i].length != dimension) { in checkDataSetSanity() [all …]
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/aosp12/frameworks/base/packages/StatementService/src/com/android/statementservice/domain/worker/ |
H A D | CollectV1Worker.kt | 58 val inputData = params.inputData regex 59 val verificationId = inputData.getInt(VERIFICATION_ID_KEY, -1) 62 inputData.keyValueMap.entries.forEach { (key, _) -> 72 val packageName = inputData.getString(PACKAGE_NAME_KEY)
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H A D | SingleV2RequestWorker.kt | 58 val domainSetId = params.inputData.getString(DOMAIN_SET_ID_KEY)!!.let(UUID::fromString) 59 val packageName = params.inputData.getString(PACKAGE_NAME_KEY)!! 60 val host = params.inputData.getString(HOST_KEY)!!
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/aosp12/frameworks/base/packages/BackupEncryption/test/robolectric/src/com/android/server/backup/encryption/tasks/ |
H A D | EncryptedFullBackupDataProcessorTest.java | 120 byte[] inputData = Bytes.concat(TEST_DATA_1, TEST_DATA_2); in pushData_writesDataToTask() 122 mFullBackupDataProcessor.initiate(new ByteArrayInputStream(inputData)); in pushData_writesDataToTask() 161 byte[] inputData = Bytes.concat(TEST_DATA_1, TEST_DATA_2); in pushData_exceptionDuringUpload_returnsError() 163 mFullBackupDataProcessor.initiate(new ByteArrayInputStream(inputData)); in pushData_exceptionDuringUpload_returnsError() 176 byte[] inputData = Bytes.concat(TEST_DATA_1, TEST_DATA_2); in pushData_quotaExceptionDuringUpload_doesNotLogAndReturnsQuotaExceeded() 178 mFullBackupDataProcessor.initiate(new ByteArrayInputStream(inputData)); in pushData_quotaExceptionDuringUpload_doesNotLogAndReturnsQuotaExceeded() 193 byte[] inputData = Bytes.concat(TEST_DATA_1, TEST_DATA_2); in pushData_unexpectedEncryptedBackup_logs() 195 mFullBackupDataProcessor.initiate(new ByteArrayInputStream(inputData)); in pushData_unexpectedEncryptedBackup_logs() 207 byte[] inputData = Bytes.concat(TEST_DATA_1, TEST_DATA_2); in pushData_permanentExceptionDuringUpload_callsErrorCallback() 209 mFullBackupDataProcessor.initiate(new ByteArrayInputStream(inputData)); in pushData_permanentExceptionDuringUpload_callsErrorCallback()
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/aosp12/frameworks/av/media/libstagefright/codecs/m4v_h263/enc/ |
H A D | SoftMPEG4Encoder.cpp | 445 const uint8_t *inputData = NULL; in onQueueFilled() local 447 inputData = in onQueueFilled() 452 if (inputData == NULL) { in onQueueFilled() 459 inputData = (const uint8_t *)inHeader->pBuffer + inHeader->nOffset; in onQueueFilled() 462 inputData, mInputFrameData, mWidth, mHeight); in onQueueFilled() 463 inputData = mInputFrameData; in onQueueFilled() 467 CHECK(inputData != NULL); in onQueueFilled() 475 vin.yChan = (uint8_t *)inputData; in onQueueFilled()
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