/external/v8/src/inspector/ |
string-16.h | 25 : m_impl(other.m_impl), hash_code(other.hash_code) {} 27 : m_impl(std::move(other.m_impl)), hash_code(other.hash_code) {} 28 String16(const UChar* characters, size_t size) : m_impl(characters, size) {} 30 : m_impl(characters) {} 34 m_impl.resize(size); 35 for (size_t i = 0; i < size; ++i) m_impl[i] = characters[i]; 37 explicit String16(const std::basic_string<UChar>& impl) : m_impl(impl) {} 40 m_impl = other.m_impl 111 std::basic_string<UChar> m_impl; member in class:v8_inspector::String16 [all...] |
/external/eigen/unsupported/Eigen/CXX11/src/Tensor/ |
TensorBroadcasting.h | 116 : m_broadcast(op.broadcast()),m_impl(op.expression(), device) 122 const InputDimensions& input_dims = m_impl.dimensions(); 149 m_impl.evalSubExprsIfNeeded(NULL); 154 m_impl.cleanup(); 160 return m_impl.coeff(0); 177 eigen_assert(idx < m_impl.dimensions()[i]); 181 eigen_assert(idx % m_impl.dimensions()[i] == 0); 183 inputIndex += (idx % m_impl.dimensions()[i]) * m_inputStrides[i]; 189 eigen_assert(index < m_impl.dimensions()[0]); 193 eigen_assert(index % m_impl.dimensions()[0] == 0) [all...] |
TensorConversion.h | 56 : m_impl(impl) {} 60 return internal::pcast<SrcPacket, TgtPacket>(m_impl.template packet<LoadMode>(index)); 64 const TensorEvaluator& m_impl; member in struct:Eigen::PacketConverter 72 : m_impl(impl) {} 78 SrcPacket src1 = m_impl.template packet<LoadMode>(index); 79 SrcPacket src2 = m_impl.template packet<LoadMode>(index + SrcPacketSize); 85 const TensorEvaluator& m_impl; member in struct:Eigen::PacketConverter 92 : m_impl(impl) {} 98 SrcPacket src1 = m_impl.template packet<LoadMode>(index); 99 SrcPacket src2 = m_impl.template packet<LoadMode>(index + SrcPacketSize) 107 const TensorEvaluator& m_impl; member in struct:Eigen::PacketConverter 140 const TensorEvaluator& m_impl; member in struct:Eigen::PacketConverter 274 TensorEvaluator<ArgType, Device> m_impl; member in struct:Eigen::TensorEvaluator [all...] |
TensorLayoutSwap.h | 127 : m_impl(op.expression(), device) 130 m_dimensions[i] = m_impl.dimensions()[NumDims-1-i]; 141 return m_impl.evalSubExprsIfNeeded(data); 144 m_impl.cleanup(); 149 return m_impl.coeff(index); 155 return m_impl.template packet<LoadMode>(index); 159 return m_impl.costPerCoeff(vectorized); 162 EIGEN_DEVICE_FUNC Scalar* data() const { return m_impl.data(); } 164 const TensorEvaluator<ArgType, Device>& impl() const { return m_impl; } 167 TensorEvaluator<ArgType, Device> m_impl; member in struct:Eigen::TensorEvaluator [all...] |
TensorArgMax.h | 96 : m_impl(op.expression(), device) { } 99 return m_impl.dimensions(); 103 m_impl.evalSubExprsIfNeeded(NULL); 107 m_impl.cleanup(); 112 return CoeffReturnType(index, m_impl.coeff(index)); 117 return m_impl.costPerCoeff(vectorized) + TensorOpCost(0, 0, 1); 123 TensorEvaluator<ArgType, Device> m_impl; member in struct:Eigen::TensorEvaluator 224 m_impl(op.expression().index_tuples().reduce(op.reduce_dims(), op.reduce_op()), device), 239 return m_impl.dimensions(); 243 m_impl.evalSubExprsIfNeeded(NULL) [all...] |
TensorEvalTo.h | 112 : m_impl(op.expression(), device), m_device(device), 125 EIGEN_DEVICE_FUNC const Dimensions& dimensions() const { return m_impl.dimensions(); } 130 return m_impl.evalSubExprsIfNeeded(m_buffer); 134 m_buffer[i] = m_impl.coeff(i); 137 internal::pstoret<CoeffReturnType, PacketReturnType, Aligned>(m_buffer + i, m_impl.template packet<TensorEvaluator<ArgType, Device>::IsAligned ? Aligned : Unaligned>(i)); 141 m_impl.cleanup(); 158 return m_impl.costPerCoeff(vectorized) + 166 const TensorEvaluator<ArgType, Device>& impl() const { return m_impl; } 171 TensorEvaluator<ArgType, Device> m_impl; member in struct:Eigen::TensorEvaluator
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TensorMorphing.h | 113 : m_impl(op.expression(), device), m_dimensions(op.dimensions()) 117 eigen_assert(internal::array_prod(m_impl.dimensions()) == internal::array_prod(op.dimensions())); 128 return m_impl.evalSubExprsIfNeeded(data); 131 m_impl.cleanup(); 136 return m_impl.coeff(index); 142 return m_impl.template packet<LoadMode>(index); 146 return m_impl.costPerCoeff(vectorized); 149 EIGEN_DEVICE_FUNC Scalar* data() const { return const_cast<Scalar*>(m_impl.data()); } 151 EIGEN_DEVICE_FUNC const TensorEvaluator<ArgType, Device>& impl() const { return m_impl; } 154 TensorEvaluator<ArgType, Device> m_impl; member in struct:Eigen::TensorEvaluator 522 TensorEvaluator<ArgType, Device> m_impl; member in struct:Eigen::TensorEvaluator 841 TensorEvaluator<ArgType, Device> m_impl; member in struct:Eigen::TensorEvaluator [all...] |
TensorStriding.h | 120 : m_impl(op.expression(), device) 122 m_dimensions = m_impl.dimensions(); 127 const typename TensorEvaluator<ArgType, Device>::Dimensions& input_dims = m_impl.dimensions(); 152 m_impl.evalSubExprsIfNeeded(NULL); 156 m_impl.cleanup(); 161 return m_impl.coeff(srcCoeff(index)); 196 PacketReturnType rslt = m_impl.template packet<Unaligned>(inputIndices[0]); 201 values[0] = m_impl.coeff(inputIndices[0]); 202 values[PacketSize-1] = m_impl.coeff(inputIndices[1]); 220 return m_impl.costPerCoeff(vectorized && m_inputStrides[innerDim] == 1) 252 TensorEvaluator<ArgType, Device> m_impl; member in struct:Eigen::TensorEvaluator [all...] |
TensorInflation.h | 99 : m_impl(op.expression(), device), m_strides(op.strides()) 101 m_dimensions = m_impl.dimensions(); 112 const typename TensorEvaluator<ArgType, Device>::Dimensions& input_dims = m_impl.dimensions(); 133 m_impl.evalSubExprsIfNeeded(NULL); 137 m_impl.cleanup(); 181 return m_impl.coeff(inputIndex); 207 const double input_size = m_impl.dimensions().TotalSize(); 211 return m_impl.costPerCoeff(vectorized) + 222 TensorEvaluator<ArgType, Device> m_impl; member in namespace:Eigen
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TensorReverse.h | 122 : m_impl(op.expression(), device), m_reverse(op.reverse()) 128 m_dimensions = m_impl.dimensions(); 146 m_impl.evalSubExprsIfNeeded(NULL); 150 m_impl.cleanup(); 191 return m_impl.coeff(reverseIndex(index)); 221 return m_impl.costPerCoeff(vectorized) + 230 TensorEvaluator<ArgType, Device> m_impl; member in namespace:Eigen 267 return this->m_impl.coeffRef(this->reverseIndex(index));
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TensorScan.h | 106 : m_impl(op.expression(), device), 110 m_size(m_impl.dimensions()[op.axis()]), 119 const Dimensions& dims = m_impl.dimensions(); 132 return m_impl.dimensions(); 152 return m_impl; 160 m_impl.evalSubExprsIfNeeded(NULL); 197 m_impl.cleanup(); 201 TensorEvaluator<ArgType, Device> m_impl; member in struct:Eigen::TensorEvaluator
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TensorShuffling.h | 120 : m_impl(op.expression(), device) 122 const typename TensorEvaluator<ArgType, Device>::Dimensions& input_dims = m_impl.dimensions(); 154 m_impl.evalSubExprsIfNeeded(NULL); 158 m_impl.cleanup(); 163 return m_impl.coeff(srcCoeff(index)); 184 return m_impl.costPerCoeff(vectorized) + 213 TensorEvaluator<ArgType, Device> m_impl; member in struct:Eigen::TensorEvaluator 245 return this->m_impl.coeffRef(this->srcCoeff(index));
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TensorChipping.h | 153 : m_impl(op.expression(), device), m_dim(op.dim()), m_device(device) 158 const typename TensorEvaluator<ArgType, Device>::Dimensions& input_dims = m_impl.dimensions(); 189 m_impl.evalSubExprsIfNeeded(NULL); 194 m_impl.cleanup(); 199 return m_impl.coeff(srcCoeff(index)); 215 values[i] = m_impl.coeff(inputIndex); 224 return m_impl.template packet<LoadMode>(index + m_inputOffset); 230 return m_impl.template packet<LoadMode>(inputIndex); 262 return m_impl.costPerCoeff(vectorized) + 267 CoeffReturnType* result = const_cast<CoeffReturnType*>(m_impl.data()) 304 TensorEvaluator<ArgType, Device> m_impl; member in struct:Eigen::TensorEvaluator [all...] |
TensorPatch.h | 102 : m_impl(op.expression(), device) 105 const typename TensorEvaluator<ArgType, Device>::Dimensions& input_dims = m_impl.dimensions(); 147 m_impl.evalSubExprsIfNeeded(NULL); 152 m_impl.cleanup(); 181 return m_impl.coeff(inputIndex); 233 PacketReturnType rslt = m_impl.template packet<Unaligned>(inputIndices[0]); 238 values[0] = m_impl.coeff(inputIndices[0]); 239 values[PacketSize-1] = m_impl.coeff(inputIndices[1]); 252 return m_impl.costPerCoeff(vectorized) + 264 TensorEvaluator<ArgType, Device> m_impl; member in struct:Eigen::TensorEvaluator [all...] |
TensorForcedEval.h | 111 : m_impl(op.expression(), device), m_op(op.expression()), m_device(device), m_buffer(NULL) 114 EIGEN_DEVICE_FUNC const Dimensions& dimensions() const { return m_impl.dimensions(); } 117 const Index numValues = internal::array_prod(m_impl.dimensions()); 154 const TensorEvaluator<ArgType, Device>& impl() { return m_impl; } 158 TensorEvaluator<ArgType, Device> m_impl; member in struct:Eigen::TensorEvaluator
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TensorRef.h | 48 TensorLazyEvaluatorReadOnly(const Expr& expr, const Device& device) : m_impl(expr, device), m_dummy(Scalar(0)) { 49 m_dims = m_impl.dimensions(); 50 m_impl.evalSubExprsIfNeeded(NULL); 53 m_impl.cleanup(); 60 return m_impl.data(); 64 return m_impl.coeff(index); 72 TensorEvaluator<Expr, Device> m_impl; member in class:Eigen::internal::TensorLazyEvaluatorReadOnly 89 return this->m_impl.coeffRef(index);
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TensorPadding.h | 104 : m_impl(op.expression(), device), m_padding(op.padding()), m_paddingValue(op.padding_value()) 112 m_dimensions = m_impl.dimensions(); 116 const typename TensorEvaluator<ArgType, Device>::Dimensions& input_dims = m_impl.dimensions(); 139 m_impl.evalSubExprsIfNeeded(NULL); 143 m_impl.cleanup(); 177 return m_impl.coeff(inputIndex); 190 TensorOpCost cost = m_impl.costPerCoeff(vectorized); 239 const double in = static_cast<double>(m_impl.dimensions()[i]); 309 return m_impl.template packet<Unaligned>(inputIndex); 367 return m_impl.template packet<Unaligned>(inputIndex) 386 TensorEvaluator<ArgType, Device> m_impl; member in namespace:Eigen [all...] |
TensorReductionCuda.h | 165 typename Self::CoeffReturnType val = input.m_impl.coeff(index); 195 half last = input.m_impl.coeff(num_coeffs-1); 228 half last = input.m_impl.coeff(num_coeffs-1); 241 half2 val = input.m_impl.template packet<Unaligned>(index); 361 const Index num_coeffs = array_prod(self.m_impl.dimensions()); 413 const Type val = input.m_impl.coeff(row * num_coeffs_to_reduce + col); 422 reducer.reduce(input.m_impl.coeff(row * num_coeffs_to_reduce + col), &reduced_val); 491 const half2 val1 = input.m_impl.template packet<Unaligned>(row * num_coeffs_to_reduce + col); 493 const half2 val2 = input.m_impl.template packet<Unaligned>((row+1) * num_coeffs_to_reduce + col); 498 const half last1 = input.m_impl.coeff(row * num_coeffs_to_reduce + col) [all...] |
TensorImagePatch.h | 175 : m_impl(op.expression(), device) 181 const typename TensorEvaluator<ArgType, Device>::Dimensions& input_dims = m_impl.dimensions(); 316 m_impl.evalSubExprsIfNeeded(NULL); 321 m_impl.cleanup(); 359 return m_impl.coeff(inputIndex); 414 return m_impl.template packet<Unaligned>(inputIndex); 423 const TensorEvaluator<ArgType, Device>& impl() const { return m_impl; } 444 return m_impl.costPerCoeff(vectorized) + 503 TensorEvaluator<ArgType, Device> m_impl; member in struct:Eigen::TensorEvaluator
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TensorReduction.h | 144 reducer.reduce(self.m_impl.coeff(input), accum); 151 reducer.reduce(self.m_impl.coeff(index), accum); 160 reducer.reduce(self.m_impl.coeff(firstIndex + j), &accum); 173 reducer.reducePacket(self.m_impl.template packet<Unaligned>(firstIndex + j), &p); 177 reducer.reduce(self.m_impl.coeff(firstIndex + j), &accum); 206 reducer.reducePacket(self.m_impl.template packet<Unaligned>(input), accum); 223 const typename Self::Index num_coeffs = array_prod(self.m_impl.dimensions()); 253 const Index num_coeffs = array_prod(self.m_impl.dimensions()); 259 self.m_impl.costPerCoeff(Vectorizable) + 412 : m_impl(op.expression(), device), m_reducer(op.reducer()), m_result(NULL), m_device(device), m_xpr_dims(op (…) 757 TensorEvaluator<ArgType, Device> m_impl; member in struct:Eigen::TensorEvaluator [all...] |
/external/deqp/external/vulkancts/framework/vulkan/ |
vkPrograms.hpp | 82 explicit Iterator (const IteratorImpl& i) : m_impl(i) {} 84 Iterator& operator++ (void) { ++m_impl; return *this; } 87 const std::string& getName (void) const { return m_impl->first; } 88 const Program& getProgram (void) const { return *m_impl->second; } 90 bool operator== (const Iterator& other) const { return m_impl == other.m_impl; } 91 bool operator!= (const Iterator& other) const { return m_impl != other.m_impl; } 95 IteratorImpl m_impl; member in class:vk::ProgramCollection::Iterator
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/external/mdnsresponder/mDNSWindows/DLL.NET/ |
dnssd_NET.cpp | 63 m_impl = new ServiceRefImpl(this); 80 check( m_impl != NULL ); 82 m_impl->SetupEvents(); 101 m_impl->ProcessingThread(); 113 check(m_impl != NULL); 125 m_impl->Dispose(); 126 m_impl = NULL; 149 if ((m_callback != NULL) && (m_impl != NULL)) 172 if ((m_callback != NULL) && (m_impl != NULL)) 196 if ((m_callback != NULL) && (m_impl != NULL) [all...] |
dnssd_NET.h | 164 m_impl = new RecordRefImpl; 165 m_impl->m_ref = NULL; 170 delete m_impl; 180 RecordRefImpl * m_impl; member in class:Apple::DNSSD::RecordRef 415 ServiceRefImpl * m_impl; member in class:Apple::DNSSD::ServiceRef 455 m_impl = new TextRecordImpl(); 456 TXTRecordCreate(&m_impl->m_ref, 0, NULL); 461 TXTRecordDeallocate(&m_impl->m_ref); 462 delete m_impl; 472 TextRecordImpl * m_impl; member in class:Apple::DNSSD::TextRecord [all...] |
/external/deqp/framework/platform/android/ |
tcuAndroidInternals.cpp | 242 , m_impl (DE_NULL) 248 m_impl = createGraphicBuffer(m_functions, m_baseFunctions, width, height, format, usage); 253 if (m_impl && m_baseFunctions.decRef) 255 m_baseFunctions.decRef(getAndroidNativeBase(m_impl)); 256 m_impl = DE_NULL; 262 return m_functions.lock(m_impl, usage, vaddr); 267 return m_functions.unlock(m_impl); 272 return m_functions.getNativeBuffer(m_impl);
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tcuAndroidInternals.hpp | 181 android::GraphicBuffer* m_impl; member in class:tcu::Android::internal::GraphicBuffer
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