repo stringlengths 1 152 ⌀ | file stringlengths 14 221 | code stringlengths 501 25k | file_length int64 501 25k | avg_line_length float64 20 99.5 | max_line_length int64 21 134 | extension_type stringclasses 2
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|---|---|---|---|---|---|---|
null | pytorch-main/aten/src/ATen/native/cpu/SoftmaxKernel.h | #pragma once
#include <ATen/native/DispatchStub.h>
#include <cstdint>
namespace at {
class Tensor;
namespace native {
using forward_fn = void (*)(const Tensor&, const Tensor&);
using backward_fn = void(*)(const Tensor &, const Tensor &, const Tensor&);
DECLARE_DISPATCH(forward_fn, softmax_lastdim_kernel);
DECLARE_... | 943 | 31.551724 | 83 | h |
null | pytorch-main/aten/src/ATen/native/cpu/WeightNormKernel.h | #pragma once
#include <ATen/native/DispatchStub.h>
#include <cstdint>
namespace at {
class TensorBase;
}
namespace at { namespace native {
using weight_norm_fn = void(*)(
TensorBase&, TensorBase&, const TensorBase&, const TensorBase&, int64_t);
using weight_norm_backward_fn = void(*)(
TensorBase&, TensorBase... | 565 | 25.952381 | 77 | h |
null | pytorch-main/aten/src/ATen/native/cpu/avx_mathfun.h | #pragma once
/*
AVX implementation of sin, cos, sincos, exp and log
Based on "sse_mathfun.h", by Julien Pommier
http://gruntthepeon.free.fr/ssemath/
Copyright (C) 2012 Giovanni Garberoglio
Interdisciplinary Laboratory for Computational Science (LISC)
Fondazione Bruno Kessler and University of Trento... | 17,448 | 32.363289 | 96 | h |
null | pytorch-main/aten/src/ATen/native/cpu/mixed_data_type.h | #pragma once
#include <ATen/core/Tensor.h>
namespace at { namespace native {
inline ScalarType first_type() {
return ScalarType::Undefined;
}
template <typename... Args>
inline ScalarType first_type(const Tensor& arg, const Args&... parameters) {
return arg.defined() ? arg.scalar_type() : first_type(parameters.... | 1,408 | 32.547619 | 108 | h |
null | pytorch-main/aten/src/ATen/native/cpu/moments_utils.h | #pragma once
#include <array>
#include <cstring>
#include <numeric>
#include <utility>
#include <vector>
#include <ATen/Parallel.h>
#include <ATen/OpMathType.h>
#include <ATen/cpu/vec/vec.h>
#include <ATen/native/cpu/utils.h>
#include <c10/util/SmallVector.h>
#include <c10/util/irange.h>
namespace at {
namespace nat... | 6,480 | 30.461165 | 91 | h |
null | pytorch-main/aten/src/ATen/native/cpu/utils.h | #pragma once
#include <ATen/Parallel.h>
#include <ATen/cpu/vec/vec.h>
#include <c10/util/llvmMathExtras.h>
#ifdef USE_FBGEMM
#include <fbgemm/Fbgemm.h>
#endif
namespace at {
namespace native {
inline namespace CPU_CAPABILITY {
template <typename T>
inline T data_index_init(T offset) {
return offset;
}
template ... | 5,775 | 31.632768 | 122 | h |
null | pytorch-main/aten/src/ATen/native/cpu/zmath.h | #pragma once
// Complex number math operations that act as no-ops for other dtypes.
#include <c10/util/complex.h>
#include <c10/util/math_compat.h>
#include <c10/util/MathConstants.h>
#include<ATen/NumericUtils.h>
namespace at { namespace native {
inline namespace CPU_CAPABILITY {
template <typename SCALAR_TYPE, typ... | 6,668 | 25.464286 | 93 | h |
null | pytorch-main/aten/src/ATen/native/cuda/Activation.h | #pragma once
#include <ATen/native/Activation.h>
#include <cstdint>
namespace at {
struct TensorIteratorBase;
class TensorBase;
}
namespace at { namespace native {
void launch_glu_backward_kernel(const TensorIteratorBase& iter,
int64_t gI_stride, int64_t I_stride);
void launch_log_si... | 548 | 25.142857 | 78 | h |
null | pytorch-main/aten/src/ATen/native/cuda/BinaryInternal.h | // DON'T include this except from Binary*.cu files. It should not leak into
// headers.
#pragma once
#define TORCH_ASSERT_NO_OPERATORS
#include <ATen/AccumulateType.h>
#include <ATen/Dispatch.h>
#include <ATen/native/BinaryOps.h>
#include <ATen/native/DispatchStub.h>
#include <ATen/native/TensorIterator.h>
#include <c1... | 1,237 | 24.265306 | 75 | h |
null | pytorch-main/aten/src/ATen/native/cuda/CompositeRandomAccessor.h | #pragma once
#include <ATen/native/CompositeRandomAccessorCommon.h>
#include <thrust/tuple.h>
namespace at { namespace native {
struct TupleInfoCPU {
template <typename ...Types>
using tuple = thrust::tuple<Types...>;
template <typename ...Types>
static constexpr auto tie(Types&... args) noexcept {
retu... | 929 | 24.833333 | 91 | h |
null | pytorch-main/aten/src/ATen/native/cuda/CuFFTPlanCache.h | #include <ATen/Config.h>
#include <ATen/core/DimVector.h>
#include <ATen/cuda/CUDAContext.h>
#include <ATen/native/cuda/CuFFTUtils.h>
#include <ATen/native/utils/ParamsHash.h>
#include <c10/util/accumulate.h>
#include <c10/util/irange.h>
#include <cufft.h>
#include <cufftXt.h>
#include <limits>
#include <list>
#inclu... | 19,257 | 35.131332 | 106 | h |
null | pytorch-main/aten/src/ATen/native/cuda/CuFFTUtils.h | #pragma once
#include <ATen/Config.h>
#include <string>
#include <stdexcept>
#include <sstream>
#include <cufft.h>
#include <cufftXt.h>
namespace at { namespace native {
// This means that max dim is 3 + 2 = 5 with batch dimension and possible
// complex dimension
constexpr int max_rank = 3;
static inline std::str... | 1,863 | 24.189189 | 73 | h |
null | pytorch-main/aten/src/ATen/native/cuda/Distributions.h | #pragma once
namespace at {
struct CUDAGeneratorImpl;
struct TensorIteratorBase;
class TensorBase;
namespace native {
void launch_poisson_cuda_kernel(
const TensorBase &ret, const TensorBase &lambda, CUDAGeneratorImpl *gen);
void launch_gamma_kernel(
const TensorBase &ret, const TensorBase &alpha, CUDAGener... | 641 | 23.692308 | 77 | h |
null | pytorch-main/aten/src/ATen/native/cuda/GridSampler.h | #pragma once
#include <array>
#include <cstdint>
namespace at {
class TensorBase;
}
namespace at {
namespace native {
void launch_grid_sampler_2d_forward_kernel(
const TensorBase &output, const TensorBase &input, const TensorBase &grid,
int64_t interpolation_mode, int64_t padding_mode, bool align_corners);
... | 1,157 | 34.090909 | 78 | h |
null | pytorch-main/aten/src/ATen/native/cuda/MiscUtils.h | #pragma once
#include <ATen/cuda/Exceptions.h>
#include <ATen/cuda/CUDAContext.h>
#include <ATen/cuda/CUDAConfig.h>
#include <ATen/cuda/PinnedMemoryAllocator.h>
namespace at {
namespace native {
static inline int cuda_int_cast(int64_t value, const char* varname) {
auto result = static_cast<int>(value);
TORCH_CHEC... | 958 | 28.060606 | 77 | h |
null | pytorch-main/aten/src/ATen/native/cuda/Resize.h | #pragma once
#include <ATen/EmptyTensor.h>
#include <ATen/native/ResizeCommon.h>
#include <c10/cuda/CUDAGuard.h>
namespace at { namespace native {
TORCH_CUDA_CPP_API void resize_bytes_cuda(StorageImpl* storage, size_t size_bytes);
static inline void maybe_resize_storage_cuda(TensorImpl* self, size_t new_size_bytes... | 1,771 | 27.580645 | 87 | h |
null | pytorch-main/aten/src/ATen/native/cuda/ScanKernels.h | #pragma once
#include <cstdint>
namespace at {
class TensorBase;
namespace native {
// NOTE: these functions require output tensors to be contiguous
void launch_cummax_cuda_kernel(const TensorBase& self, const TensorBase& values,
const TensorBase& indices, int64_t dim);
void launch_cum... | 779 | 40.052632 | 100 | h |
null | pytorch-main/aten/src/ATen/native/cuda/jit_utils.h | #pragma once
#include <string>
#include <sstream>
#include <unordered_map>
#include <vector>
#include <c10/util/irange.h>
#include <ATen/jit_macros.h>
#include <ATen/cuda/detail/LazyNVRTC.h>
namespace at { namespace cuda { namespace jit {
enum class BinaryFuncVariant {NoScalar, RhsScalar, LhsScalar};
struct NvrtcF... | 5,705 | 26.970588 | 93 | h |
null | pytorch-main/aten/src/ATen/native/cuda/thread_constants.h | #pragma once
#include <c10/macros/Macros.h>
// Marks a lambda as executable on both the host and device. The __host__
// attribute is important so that we can access static type information from
// the host, even if the function is typically only executed on the device.
#ifndef GPU_LAMBDA
#define GPU_LAMBDA __host__ _... | 611 | 25.608696 | 78 | h |
null | pytorch-main/aten/src/ATen/native/cuda/linalg/MagmaUtils.h | #pragma once
#include <ATen/cuda/CUDAConfig.h>
#if AT_MAGMA_ENABLED()
#include <magma_types.h>
#include <magma_v2.h>
#endif
namespace at {
namespace native {
#if AT_MAGMA_ENABLED()
// RAII for a MAGMA Queue
struct MAGMAQueue {
// Default constructor without a device will cause
// destroying a queue which has n... | 2,481 | 26.88764 | 91 | h |
null | pytorch-main/aten/src/ATen/native/cudnn/ConvShared.h | #pragma once
#include <ATen/core/Tensor.h>
#include <ATen/cudnn/cudnn-wrapper.h>
#include <ATen/cudnn/Descriptors.h>
#include <ATen/cudnn/Types.h>
#include <ATen/native/ConvUtils.h>
#if CUDNN_VERSION < 8000
#define AT_CUDNN_CONV_BIAS_RELU_FALLBACK
#endif
namespace at { namespace native {
// ------------------------... | 4,960 | 31.214286 | 89 | h |
null | pytorch-main/aten/src/ATen/native/cudnn/RNNUtils.h | #include <ATen/cudnn/cudnn-wrapper.h>
#include <ATen/cudnn/Descriptors.h>
#include <ATen/cudnn/Types.h>
#include <ATen/cudnn/Utils.h>
// Declares utilities used by RNN.cpp and also needed by external consumers
namespace at {
namespace native {
namespace cudnn_rnn {
TORCH_CUDA_CPP_API std::tuple<Tensor, std::vector<Te... | 834 | 25.935484 | 75 | h |
null | pytorch-main/aten/src/ATen/native/metal/MetalCommandBuffer.h | #import <MetalPerformanceShaders/MetalPerformanceShaders.h>
@protocol PTMetalCommandBuffer<NSObject>
@optional
- (void)beginSynchronization;
- (void)endSynchronization:(NSError*)error;
@end
@interface MetalCommandBuffer : NSObject
@property(nonatomic, strong, readonly) id<MTLCommandBuffer> buffer;
@property(nonatomic... | 651 | 28.636364 | 67 | h |
null | pytorch-main/aten/src/ATen/native/metal/MetalContext.h | #import <Foundation/Foundation.h>
#import <Metal/Metal.h>
#import <MetalPerformanceShaders/MetalPerformanceShaders.h>
#include <string>
API_AVAILABLE(ios(11.0), macos(10.13))
@interface MetalContext : NSObject
@property(nonatomic, strong, readonly) id<MTLDevice> device;
@property(nonatomic, strong, readonly) id<MTLCom... | 819 | 38.047619 | 82 | h |
null | pytorch-main/aten/src/ATen/native/metal/MetalConvParams.h | #ifndef MetalConvParams_h
#define MetalConvParams_h
#include <c10/util/ArrayRef.h>
namespace at {
namespace native {
namespace metal {
struct Conv2DParams final {
Conv2DParams() {}
Conv2DParams(
c10::IntArrayRef inputSizes,
c10::IntArrayRef weightSizes,
c10::IntArrayRef padding,
c10::IntA... | 1,304 | 23.166667 | 59 | h |
null | pytorch-main/aten/src/ATen/native/metal/MetalDevice.h | #ifndef PYTORCH_MOBILE_METAL_DEVICE_H_
#define PYTORCH_MOBILE_METAL_DEVICE_H_
#import <Metal/Metal.h>
#include <string>
namespace at {
namespace native {
namespace metal {
struct MetalDeviceInfo {
std::string name;
MTLLanguageVersion languageVersion;
};
static inline MetalDeviceInfo createDeviceInfo(id<MTLDevi... | 1,462 | 28.26 | 76 | h |
null | pytorch-main/aten/src/ATen/native/metal/MetalNeuronType.h | #ifndef MetalNeuronType_h
#define MetalNeuronType_h
#import <ATen/native/metal/mpscnn/MPSCNNNeuronOp.h>
#import <MetalPerformanceShaders/MetalPerformanceShaders.h>
#include <ATen/ATen.h>
namespace at {
namespace native {
namespace metal {
enum class NeuronType {
None,
Clamp,
Relu,
Sigmoid,
HardSigmoid,
... | 2,045 | 26.648649 | 84 | h |
null | pytorch-main/aten/src/ATen/native/metal/MetalPrepackOpContext.h | #pragma once
#include <ATen/Tensor.h>
#include <torch/custom_class.h>
namespace at {
namespace native {
namespace metal {
using SerializationTypeConv2dPrePack = std::tuple<
Tensor,
c10::optional<Tensor>,
std::vector<int64_t>,
std::vector<int64_t>,
std::vector<int64_t>,
int64_t,
c10::optio... | 4,687 | 22.093596 | 80 | h |
null | pytorch-main/aten/src/ATen/native/metal/MetalTensorImpl.h | #ifndef MetalTensorImpl_h
#define MetalTensorImpl_h
#include <ATen/OpaqueTensorImpl.h>
#include <ATen/WrapDimUtils.h>
#import <ATen/native/metal/MetalTensorImplStorage.h>
#import <ATen/native/metal/mpscnn/MPSImageWrapper.h>
namespace at {
template <typename OpaqueHandle>
struct TORCH_API MetalTensorImpl : public Opaq... | 1,290 | 23.826923 | 77 | h |
null | pytorch-main/aten/src/ATen/native/metal/MetalTensorImplStorage.h | #include <ATen/Tensor.h>
#include <c10/util/ArrayRef.h>
namespace at {
namespace native {
namespace metal {
class MPSImageWrapper;
class MetalTensorImplStorage final {
class Impl;
public:
MetalTensorImplStorage(){};
MetalTensorImplStorage(const std::vector<int64_t>& sizes);
MetalTensorImplStorage(
con... | 1,264 | 25.354167 | 77 | h |
null | pytorch-main/aten/src/ATen/native/metal/MetalTensorUtils.h | #include <ATen/Tensor.h>
#include <ATen/native/metal/MetalContext.h>
#include <ATen/native/metal/MetalCommandBuffer.h>
#include <ATen/native/metal/MetalTensorImpl.h>
#include <ATen/native/metal/MetalTensorImplStorage.h>
#if (defined(__ARM_NEON__) || defined(__ARM_NEON))
typedef float16_t fp16_t;
#else
typedef uint16_t... | 2,449 | 31.236842 | 80 | h |
null | pytorch-main/aten/src/ATen/native/metal/mpscnn/MPSCNNConvOp.h | #import <ATen/native/metal/MetalConvParams.h>
#import <ATen/native/metal/MetalNeuronType.h>
#import <ATen/native/metal/mpscnn/MPSCNNOp.h>
#import <Foundation/Foundation.h>
API_AVAILABLE(ios(11.0), macos(10.13))
@interface MPSCNNConvDataSource : NSObject<MPSCNNConvolutionDataSource>
@property(nonatomic, assign) void* w... | 791 | 30.68 | 71 | h |
null | pytorch-main/aten/src/ATen/native/metal/mpscnn/MPSCNNFullyConnectedOp.h | #import <ATen/native/metal/MetalConvParams.h>
#import <ATen/native/metal/MetalNeuronType.h>
#import <ATen/native/metal/mpscnn/MPSCNNConvOp.h>
#import <Foundation/Foundation.h>
using namespace at::native::metal;
API_AVAILABLE(ios(11.0), macos(10.13))
@interface MPSCNNFullyConnectedOp : NSObject<MPSCNNOp>
+ (MPSCNNFully... | 510 | 35.5 | 61 | h |
null | pytorch-main/aten/src/ATen/native/metal/mpscnn/MPSCNNNeuronOp.h | #import <MetalPerformanceShaders/MetalPerformanceShaders.h>
@interface MPSCNNNeuronOp : NSObject
+ (MPSCNNNeuronHardSigmoid*)hardSigmoid API_AVAILABLE(ios(11.0), macos(10.13));
+ (MPSCNNNeuronReLU*)relu;
+ (MPSCNNNeuronSigmoid*)sigmoid;
+ (MPSCNNNeuronTanH*)tanh;
@end
API_AVAILABLE(ios(11.3), macos(10.13), macCatal... | 563 | 25.857143 | 79 | h |
null | pytorch-main/aten/src/ATen/native/metal/mpscnn/MPSCNNOp.h | #import <Metal/Metal.h>
#import <MetalPerformanceShaders/MetalPerformanceShaders.h>
@protocol MPSCNNOp<NSObject>
@property(nonatomic, strong) MPSCNNKernel* kernel;
- (void)encode:(id<MTLCommandBuffer>)cb
sourceImage:(MPSImage*)src
destinationImage:(MPSImage*)dst;
@end
@protocol MPSCNNShaderOp<NSObject... | 503 | 23 | 67 | h |
null | pytorch-main/aten/src/ATen/native/metal/mpscnn/MPSCNNUtils.h | #import <Metal/Metal.h>
#import <MetalPerformanceShaders/MetalPerformanceShaders.h>
#include <string>
// This is a utility macro that can be used to throw an exception when a Metal
// API function produces a NSError. The exception will contain a message with
// useful info extracted from the NSError.
#define METAL_THR... | 3,051 | 38.128205 | 82 | h |
null | pytorch-main/aten/src/ATen/native/metal/mpscnn/MPSImageUtils.h | #import <ATen/Tensor.h>
#import <ATen/native/metal/MetalCommandBuffer.h>
#import <ATen/native/metal/MetalTensorImpl.h>
#import <ATen/native/metal/MetalTensorUtils.h>
#import <MetalPerformanceShaders/MetalPerformanceShaders.h>
namespace at {
namespace native {
namespace metal {
MPSImage* createStaticImage(IntArrayRef... | 2,464 | 31.012987 | 77 | h |
null | pytorch-main/aten/src/ATen/native/metal/mpscnn/MPSImageWrapper.h | #ifndef MPSImageWrapper_h
#define MPSImageWrapper_h
#import <ATen/native/metal/MetalCommandBuffer.h>
#import <MetalPerformanceShaders/MetalPerformanceShaders.h>
#include <c10/util/ArrayRef.h>
namespace at {
namespace native {
namespace metal {
class API_AVAILABLE(ios(11.0), macos(10.13)) MPSImageWrapper {
public:
... | 1,149 | 25.136364 | 62 | h |
null | pytorch-main/aten/src/ATen/native/metal/mpscnn/tests/MPSCNNTests.h | #ifndef MPSCNNTests_h
#define MPSCNNTests_h
bool test_synchronization();
bool test_copy_nchw_to_metal();
bool test_conv2d();
bool test_depthwiseConv();
bool test_max_pool2d();
bool test_max_pool2d_ceil();
bool test_max_pool2d_padding();
bool test_relu();
bool test_addmm();
bool test_add();
bool test_add_broadcast();
b... | 1,469 | 21.96875 | 38 | h |
null | pytorch-main/aten/src/ATen/native/metal/ops/MetalConvolution.h | #import <ATen/native/metal/MetalConvParams.h>
#import <ATen/native/metal/MetalPrepackOpContext.h>
#include <c10/util/ArrayRef.h>
namespace at {
namespace native {
namespace metal {
Tensor conv2d(
const Tensor& input,
const Tensor& weight,
const c10::optional<at::Tensor>& bias,
IntArrayRef stride,
... | 535 | 20.44 | 61 | h |
null | pytorch-main/aten/src/ATen/native/mkl/LinearAlgebra.h | #pragma once
#include <ATen/native/TransposeType.h>
#include <c10/util/complex.h>
namespace at {
namespace native {
void mkl_gemm_batched(
TransposeType trans_A, TransposeType trans_B,
int batch_size, int M, int N, int K, float alpha,
const float** A, int lda, const float** B, int ldb, float beta,
flo... | 1,180 | 34.787879 | 85 | h |
null | pytorch-main/aten/src/ATen/native/mkldnn/Common.h | #pragma once
#include <ATen/ATen.h>
#include <ATen/Config.h>
#if AT_MKLDNN_ENABLED()
#include <ideep/tensor.hpp>
namespace at {
namespace native {
namespace mkldnn {
struct ContextConv final {
ideep::tensor weight_packed_;
c10::optional<at::Tensor> at_bias_;
std::vector<int64_t> padding_;
std::vector<int64... | 1,000 | 20.297872 | 49 | h |
null | pytorch-main/aten/src/ATen/native/mkldnn/ConvPrepack.h | #pragma once
#include <ATen/Tensor.h>
#include <ATen/native/mkldnn/Common.h>
#include <ATen/native/mkldnn/OpContext.h>
#if AT_MKLDNN_ENABLED()
namespace at {
namespace native {
namespace mkldnn {
namespace internal {
namespace convolution {
c10::intrusive_ptr<mkldnn::ConvOpContext> createConvPrePackOpContext(
T... | 1,197 | 22.96 | 69 | h |
null | pytorch-main/aten/src/ATen/native/mkldnn/MKLDNNCommon.h | #pragma once
#include <ATen/core/Tensor.h>
#include <ATen/Config.h>
#if AT_MKLDNN_ENABLED()
#include <ideep.hpp>
namespace at { namespace native {
// Mapping ScalarType to ideep tensor data_type
TORCH_API ideep::tensor::data_type get_mkldnn_dtype(ScalarType type);
static inline ideep::tensor::data_type get_mkldnn_d... | 1,140 | 30.694444 | 124 | h |
null | pytorch-main/aten/src/ATen/native/mkldnn/Matmul.h | #pragma once
#include <ATen/core/Tensor.h>
#include <ATen/Config.h>
#include <ATen/native/LinearAlgebraUtils.h> // For TransposeType
namespace at { namespace native {
// result = beta * result + alpha * gemm(mat1, mat2)
TORCH_API void mkldnn_matmul(
const Tensor &mat1,
const Tensor &mat2,
co... | 846 | 23.2 | 84 | h |
null | pytorch-main/aten/src/ATen/native/mkldnn/OpContext.h | #pragma once
#include <ATen/Tensor.h>
#include <ATen/core/ivalue.h>
#include <ATen/native/mkldnn/Common.h>
#if AT_MKLDNN_ENABLED()
namespace at {
namespace native {
namespace mkldnn {
const static std::map<std::string, ideep::attr_t> fusion_attr_map = {
{"none", ideep::attr_t()},
{"relu", ideep::attr_t::fus... | 2,425 | 23.26 | 69 | h |
null | pytorch-main/aten/src/ATen/native/mkldnn/Utils.h | #pragma once
#include <ATen/Config.h>
#include <ATen/core/List.h>
#include <ATen/core/Tensor.h>
#include <c10/util/ArrayRef.h>
#include <cpuinfo.h>
#include <vector>
#if AT_MKLDNN_ENABLED()
#include <ideep/tensor.hpp>
#endif // AT_MKLDNN_ENABLED()
namespace at { namespace native {
std::tuple<Tensor, Tensor, Tensor>... | 2,388 | 26.147727 | 101 | h |
null | pytorch-main/aten/src/ATen/native/mps/MPSGraphVenturaOps.h | #pragma once
#include <MetalPerformanceShadersGraph/MetalPerformanceShadersGraph.h>
// TODO: Remove me when moved to MacOS 13
@interface MPSGraph (VenturaOps)
#if !defined(__MAC_13_0) && \
(!defined(MAC_OS_X_VERSION_13_0) || (MAC_OS_X_VERSION_MIN_REQUIRED < MAC_OS_X_VERSION_13_0))
typedef NS_ENUM(NSUInteger, MPS... | 9,522 | 64.675862 | 117 | h |
null | pytorch-main/aten/src/ATen/native/mps/OperationUtils.h | // Copyright © 2022 Apple Inc.
#pragma once
#define TORCH_ASSERT_ONLY_METHOD_OPERATORS
#include <ATen/Tensor.h>
#include <ATen/Utils.h>
#include <ATen/mps/MPSStream.h>
#include <ATen/native/mps/TensorFactory.h>
#include <c10/util/Optional.h>
#include <c10/core/ScalarType.h>
#include <torch/library.h>
#include <unord... | 11,499 | 33.743202 | 131 | h |
null | pytorch-main/aten/src/ATen/native/mps/TensorFactory.h | // Copyright © 2022 Apple Inc.
#define AT_DISPATCH_MPS_TYPES(TYPE, NAME, ...) \
AT_DISPATCH_SWITCH( \
TYPE, NAME, \
AT_DISPATCH_CASE(at::ScalarType::Float, __VA_ARGS__) ... | 758 | 57.384615 | 73 | h |
null | pytorch-main/aten/src/ATen/native/nested/NestedTensorMath.h | #pragma once
#include <ATen/core/ATen_fwd.h>
#include <ATen/NestedTensorImpl.h>
#include <c10/macros/Macros.h>
namespace at {
namespace native {
TORCH_API Tensor NestedTensor_to_padded_tensor_generic(
const Tensor& t,
double padding,
OptionalIntArrayRef output_size);
template <typename Func>
Tensor map_... | 2,676 | 32.4625 | 112 | h |
null | pytorch-main/aten/src/ATen/native/nested/NestedTensorTransformerFunctions.h | /**
* Transformer-specific NestedTensor utility functions.
*
* Not co-located with NestedTensor core code yet because they only
* support specific cases needed in transformers.
*/
#pragma once
#include <vector>
#include <c10/macros/Macros.h>
#include <c10/util/Optional.h>
namespace c10 {
class Scalar;
} // name... | 2,817 | 26.096154 | 119 | h |
null | pytorch-main/aten/src/ATen/native/nested/NestedTensorUtils.h | #pragma once
#include <ATen/Dispatch.h>
#include <ATen/NestedTensorImpl.h>
#include <ATen/Parallel.h>
#include <ATen/core/Tensor.h>
#include <c10/core/DispatchKeySet.h>
#include <c10/core/TensorImpl.h>
#include <c10/macros/Macros.h>
#include <c10/util/Exception.h>
#ifndef AT_PER_OPERATOR_HEADERS
#include <ATen/Funct... | 14,128 | 32.963942 | 106 | h |
null | pytorch-main/aten/src/ATen/native/quantized/AffineQuantizer.h | #pragma once
#include <ATen/core/Tensor.h>
#include <ATen/Dispatch.h>
#include <ATen/native/DispatchStub.h>
#include <ATen/native/quantized/AffineQuantizerBase.h>
namespace at {
namespace native {
Tensor& quantize_tensor_per_tensor_affine(
const Tensor& rtensor,
Tensor& qtensor,
double scale,
int64_t... | 3,654 | 26.900763 | 87 | h |
null | pytorch-main/aten/src/ATen/native/quantized/AffineQuantizerBase.h | #pragma once
#include <c10/macros/Export.h>
#include <c10/core/ScalarType.h>
namespace at {
namespace native {
// Quantize a float value into a uint value given scale and zero_point
template <typename T>
TORCH_API T quantize_val(double scale, int64_t zero_point, float value);
// TODO combine this with quantize_val on... | 1,460 | 29.4375 | 95 | h |
null | pytorch-main/aten/src/ATen/native/quantized/ConvUtils.h | #pragma once
#include <ATen/core/List.h>
#include <ATen/native/ConvUtils.h>
namespace at::native::quantized {
namespace {
// MakeConvOutputShape used from both CPU and CUDA libraries
// and exporting symbol from torch_cpu would probaby take more storage
// than duplicating implementation which likely be inlined away
t... | 2,239 | 34.555556 | 79 | h |
null | pytorch-main/aten/src/ATen/native/quantized/FakeQuantAffine.h | #pragma once
#include <ATen/core/Tensor.h>
#include <ATen/Dispatch.h>
#include <ATen/native/DispatchStub.h>
namespace at {
struct TensorIterator;
namespace native {
using fake_quant_tensor_cachemask_fn = void (*)(
Tensor& output,
Tensor& mask,
const Tensor& input,
float sc,
int64_t z_point,
... | 1,792 | 25.367647 | 113 | h |
null | pytorch-main/aten/src/ATen/native/quantized/PackedParams.h | #pragma once
#include <ATen/core/Tensor.h>
#include <ATen/core/ivalue.h>
struct LinearPackedParamsBase : public torch::jit::CustomClassHolder {
virtual at::Tensor apply(
at::Tensor input,
double output_scale,
int64_t output_zero_point) = 0;
virtual at::Tensor apply_relu(
at::Tensor input,
... | 4,739 | 31.027027 | 98 | h |
null | pytorch-main/aten/src/ATen/native/quantized/cpu/EmbeddingPackedParams.h | #pragma once
#include <ATen/core/Tensor.h>
#include <ATen/core/ivalue.h>
struct EmbeddingPackedParamsBase : public torch::jit::CustomClassHolder {
virtual at::Tensor embeddingbag_byte(
const at::Tensor& indices,
const c10::optional<at::Tensor>& offsets,
bool pruned_weights,
const c10::optional<at::T... | 921 | 29.733333 | 73 | h |
null | pytorch-main/aten/src/ATen/native/quantized/cpu/OnednnUtils.h | #pragma once
#include <ATen/Config.h>
#if AT_MKLDNN_ENABLED()
#include <ATen/Tensor.h>
#include <ATen/native/quantized/PackedParams.h>
#include <ideep.hpp>
#include <cpuinfo.h>
#include <c10/util/CallOnce.h>
using PrimitiveCacheKey = std::tuple<
double, // input_scale
int64_t, // input_zero_point
std::ve... | 11,394 | 26.130952 | 92 | h |
null | pytorch-main/aten/src/ATen/native/quantized/cpu/QnnpackUtils.h | #pragma once
#ifdef USE_PYTORCH_QNNPACK
#include <ATen/core/Tensor.h>
#include <c10/util/irange.h>
#include <pytorch_qnnpack.h>
#include <qnnpack_func.h>
#include <ATen/native/quantized/cpu/XnnpackUtils.h>
#include <ATen/native/quantized/PackedParams.h>
#include <ATen/native/utils/Factory.h>
#ifndef AT_PER_OPERATOR_H... | 17,723 | 32.568182 | 93 | h |
null | pytorch-main/aten/src/ATen/native/quantized/cpu/QuantUtils.h | #pragma once
#include <ATen/core/Tensor.h>
#include <ATen/core/List.h>
#include <ATen/TensorOperators.h>
#include <c10/util/irange.h>
#include <algorithm>
#include <cmath>
#ifndef AT_PER_OPERATOR_HEADERS
#include <ATen/Functions.h>
#include <ATen/NativeFunctions.h>
#else
#include <ATen/ops/quantize_per_tensor_native.... | 8,361 | 33.841667 | 88 | h |
null | pytorch-main/aten/src/ATen/native/quantized/cpu/QuantizedOps.h | #pragma once
#include <ATen/core/Tensor.h>
#include <ATen/core/IListRef.h>
#include <ATen/Dispatch.h>
#include <ATen/TensorIterator.h>
#include <ATen/native/Activation.h>
#include <ATen/native/DispatchStub.h>
namespace at {
namespace native {
using qrelu_fn = void (*)(const at::Tensor& /*qx*/, at::Tensor& /*qy*/);
us... | 7,861 | 29.355212 | 130 | h |
null | pytorch-main/aten/src/ATen/native/quantized/cpu/XnnpackUtils.h | #pragma once
#ifdef USE_XNNPACK
#include <cstdint>
#include <ATen/core/Tensor.h>
#include <ATen/native/xnnpack/Common.h>
using xnnpack_operator = at::native::xnnpack::Operator;
namespace at {
namespace native {
namespace xnnp_utils {
/*
* Return shape in the same order as the memory format
* e.g. channels_last w... | 12,149 | 41.78169 | 99 | h |
null | pytorch-main/aten/src/ATen/native/quantized/cpu/conv_serialization.h | #pragma once
#include <ATen/core/Tensor.h>
#include <ATen/core/List.h>
#include <ATen/native/quantized/cpu/fbgemm_utils.h>
#include <ATen/native/quantized/cpu/QnnpackUtils.h>
#include <ATen/native/quantized/cpu/OnednnUtils.h>
#include <c10/util/irange.h>
#include <cpuinfo.h>
#ifndef AT_PER_OPERATOR_HEADERS
#include <... | 12,861 | 29.406619 | 88 | h |
null | pytorch-main/aten/src/ATen/native/quantized/cpu/fbgemm_utils.h | #pragma once
#include <ATen/Tensor.h>
#include <ATen/native/quantized/PackedParams.h>
#include <ATen/native/quantized/cpu/EmbeddingPackedParams.h>
#include <c10/core/QScheme.h>
#include <c10/util/irange.h>
#ifdef USE_FBGEMM
#include <fbgemm/Fbgemm.h>
#include <fbgemm/FbgemmFP16.h>
#include <fbgemm/QuantUtils.h>
// T... | 11,912 | 27.915049 | 80 | h |
null | pytorch-main/aten/src/ATen/native/quantized/cpu/qembeddingbag.h | #pragma once
#include <ATen/core/Tensor.h>
#include <cstdint>
namespace at {
namespace native {
Tensor& embedding_bag_byte_rowwise_offsets_out(
Tensor& output,
const Tensor& weight,
const Tensor& indices,
const c10::optional<Tensor>& offsets_in,
const bool /* scale_grad_by_freq */,
const int64_... | 1,020 | 28.171429 | 83 | h |
null | pytorch-main/aten/src/ATen/native/quantized/cpu/qnnpack/deps/clog/include/clog.h | /*
* Copyright (c) Facebook, Inc. and its affiliates.
* All rights reserved.
*
* This source code is licensed under the BSD-style license found in the
* LICENSE file in the root directory of this source tree.
*/
#pragma once
#include <inttypes.h>
#include <stdarg.h>
#include <stdlib.h>
#define CLOG_NONE 0
#def... | 4,900 | 38.524194 | 75 | h |
null | pytorch-main/aten/src/ATen/native/quantized/cpu/qnnpack/deps/clog/src/clog.c | /*
* Copyright (c) Facebook, Inc. and its affiliates.
* All rights reserved.
*
* This source code is licensed under the BSD-style license found in the
* LICENSE file in the root directory of this source tree.
*/
#include <stdarg.h>
#include <stdio.h>
#include <stdlib.h>
#include <string.h>
#ifdef _WIN32
#include... | 15,834 | 29.161905 | 80 | c |
null | pytorch-main/aten/src/ATen/native/quantized/cpu/qnnpack/include/pack_block_sparse.h | /*
* Copyright (c) Facebook, Inc. and its affiliates.
* All rights reserved.
*
* This source code is licensed under the BSD-style license found in the
* LICENSE file in the root directory of this source tree.
*/
#pragma once
#include <cassert>
#include <cstdint>
#include <memory>
#include <vector>
#ifndef _WIN3... | 14,150 | 35.851563 | 80 | h |
null | pytorch-main/aten/src/ATen/native/quantized/cpu/qnnpack/include/pytorch_qnnpack.h | /*
* Copyright (c) Facebook, Inc. and its affiliates.
* All rights reserved.
*
* This source code is licensed under the BSD-style license found in the
* LICENSE file in the root directory of this source tree.
*/
#pragma once
#include <stdbool.h>
#include <stddef.h>
#include <stdint.h>
#include <pthreadpool.h>
... | 13,055 | 27.568928 | 77 | h |
null | pytorch-main/aten/src/ATen/native/quantized/cpu/qnnpack/include/qnnpack_func.h | #pragma once
#include <cstdlib>
#include <qnnpack/operator.h>
namespace qnnpack {
class PrePackConvWeights final {
public:
PrePackConvWeights(
const pytorch_qnnp_operator_t convolution,
const uint8_t* kernel_zero_points,
const uint8_t* kernel,
const int32_t* bias);
void* getPackedWeights... | 4,146 | 23.832335 | 68 | h |
null | pytorch-main/aten/src/ATen/native/quantized/cpu/qnnpack/src/add.c | /*
* Copyright (c) Facebook, Inc. and its affiliates.
* All rights reserved.
*
* This source code is licensed under the BSD-style license found in the
* LICENSE file in the root directory of this source tree.
*/
#include <assert.h>
#include <math.h>
#include <stddef.h>
#include <stdint.h>
#include <stdlib.h>
#i... | 4,530 | 27.142857 | 119 | c |
null | pytorch-main/aten/src/ATen/native/quantized/cpu/qnnpack/src/average-pooling.c | /*
* Copyright (c) Facebook, Inc. and its affiliates.
* All rights reserved.
*
* This source code is licensed under the BSD-style license found in the
* LICENSE file in the root directory of this source tree.
*/
#include <assert.h>
#include <math.h>
#include <stdbool.h>
#include <stddef.h>
#include <stdint.h>
#i... | 9,584 | 31.938144 | 108 | c |
null | pytorch-main/aten/src/ATen/native/quantized/cpu/qnnpack/src/channel-shuffle.c | /*
* Copyright (c) Facebook, Inc. and its affiliates.
* All rights reserved.
*
* This source code is licensed under the BSD-style license found in the
* LICENSE file in the root directory of this source tree.
*/
#include <assert.h>
#include <math.h>
#include <stddef.h>
#include <stdint.h>
#include <stdlib.h>
#i... | 2,998 | 28.401961 | 104 | c |
null | pytorch-main/aten/src/ATen/native/quantized/cpu/qnnpack/src/clamp.c | /*
* Copyright (c) Facebook, Inc. and its affiliates.
* All rights reserved.
*
* This source code is licensed under the BSD-style license found in the
* LICENSE file in the root directory of this source tree.
*/
#include <assert.h>
#include <math.h>
#include <stddef.h>
#include <stdint.h>
#include <stdlib.h>
#i... | 2,815 | 26.339806 | 97 | c |
null | pytorch-main/aten/src/ATen/native/quantized/cpu/qnnpack/src/deconvolution.c | /*
* Copyright (c) Facebook, Inc. and its affiliates.
* All rights reserved.
*
* This source code is licensed under the BSD-style license found in the
* LICENSE file in the root directory of this source tree.
*/
#include <assert.h>
#include <math.h>
#include <stdbool.h>
#include <stddef.h>
#include <stdint.h>
#i... | 10,140 | 32.69103 | 106 | c |
null | pytorch-main/aten/src/ATen/native/quantized/cpu/qnnpack/src/fully-connected-sparse.c | /*
* Copyright (c) Facebook, Inc. and its affiliates.
* All rights reserved.
*
* This source code is licensed under the BSD-style license found in the
* LICENSE file in the root directory of this source tree.
*/
#include <assert.h>
#include <math.h>
#include <stdbool.h>
#include <stddef.h>
#include <stdint.h>
#i... | 5,879 | 33.186047 | 120 | c |
null | pytorch-main/aten/src/ATen/native/quantized/cpu/qnnpack/src/fully-connected.c | /*
* Copyright (c) Facebook, Inc. and its affiliates.
* All rights reserved.
*
* This source code is licensed under the BSD-style license found in the
* LICENSE file in the root directory of this source tree.
*/
#include <assert.h>
#include <math.h>
#include <stdbool.h>
#include <stddef.h>
#include <stdint.h>
#i... | 4,827 | 28.987578 | 120 | c |
null | pytorch-main/aten/src/ATen/native/quantized/cpu/qnnpack/src/global-average-pooling.c | /*
* Copyright (c) Facebook, Inc. and its affiliates.
* All rights reserved.
*
* This source code is licensed under the BSD-style license found in the
* LICENSE file in the root directory of this source tree.
*/
#include <assert.h>
#include <math.h>
#include <stddef.h>
#include <stdint.h>
#include <stdlib.h>
#i... | 5,450 | 33.283019 | 117 | c |
null | pytorch-main/aten/src/ATen/native/quantized/cpu/qnnpack/src/hardsigmoid.c | /*
* Copyright (c) Facebook, Inc. and its affiliates.
* All rights reserved.
*
* This source code is licensed under the BSD-style license found in the
* LICENSE file in the root directory of this source tree.
*/
#include <assert.h>
#include <math.h>
#include <stddef.h>
#include <stdint.h>
#include <stdlib.h>
#i... | 5,005 | 29.339394 | 112 | c |
null | pytorch-main/aten/src/ATen/native/quantized/cpu/qnnpack/src/hardswish.c | /*
* Copyright (c) Facebook, Inc. and its affiliates.
* All rights reserved.
*
* This source code is licensed under the BSD-style license found in the
* LICENSE file in the root directory of this source tree.
*/
#include <assert.h>
#include <math.h>
#include <stddef.h>
#include <stdint.h>
#include <stdlib.h>
#i... | 4,420 | 28.871622 | 104 | c |
null | pytorch-main/aten/src/ATen/native/quantized/cpu/qnnpack/src/indirection.c | /*
* Copyright (c) Facebook, Inc. and its affiliates.
* All rights reserved.
*
* This source code is licensed under the BSD-style license found in the
* LICENSE file in the root directory of this source tree.
*/
#include <stddef.h>
#include <fxdiv.h>
#include <qnnpack/indirection.h>
#include <qnnpack/math.h>
#... | 21,849 | 43.320487 | 86 | c |
null | pytorch-main/aten/src/ATen/native/quantized/cpu/qnnpack/src/init.c | /*
* Copyright (c) Facebook, Inc. and its affiliates.
* All rights reserved.
*
* This source code is licensed under the BSD-style license found in the
* LICENSE file in the root directory of this source tree.
*/
#include <stdbool.h>
#include <stddef.h>
#include <stdint.h>
#ifdef _MSC_VER
#include <windows.h>
#e... | 13,994 | 35.350649 | 96 | c |
null | pytorch-main/aten/src/ATen/native/quantized/cpu/qnnpack/src/leaky-relu.c | /*
* Copyright (c) Facebook, Inc. and its affiliates.
* All rights reserved.
*
* This source code is licensed under the BSD-style license found in the
* LICENSE file in the root directory of this source tree.
*/
#include <assert.h>
#include <math.h>
#include <stddef.h>
#include <stdint.h>
#include <stdlib.h>
#i... | 5,225 | 29.741176 | 107 | c |
null | pytorch-main/aten/src/ATen/native/quantized/cpu/qnnpack/src/max-pooling.c | /*
* Copyright (c) Facebook, Inc. and its affiliates.
* All rights reserved.
*
* This source code is licensed under the BSD-style license found in the
* LICENSE file in the root directory of this source tree.
*/
#include <assert.h>
#include <math.h>
#include <stdbool.h>
#include <stddef.h>
#include <stdint.h>
#i... | 7,200 | 30.445415 | 104 | c |
null | pytorch-main/aten/src/ATen/native/quantized/cpu/qnnpack/src/operator-delete.c | /*
* Copyright (c) Facebook, Inc. and its affiliates.
* All rights reserved.
*
* This source code is licensed under the BSD-style license found in the
* LICENSE file in the root directory of this source tree.
*/
#include <stdlib.h>
#include <pytorch_qnnpack.h>
#include <qnnpack/operator.h>
enum pytorch_qnnp_st... | 646 | 22.107143 | 72 | c |
null | pytorch-main/aten/src/ATen/native/quantized/cpu/qnnpack/src/sigmoid.c | /*
* Copyright (c) Facebook, Inc. and its affiliates.
* All rights reserved.
*
* This source code is licensed under the BSD-style license found in the
* LICENSE file in the root directory of this source tree.
*/
#include <assert.h>
#include <math.h>
#include <stddef.h>
#include <stdint.h>
#include <stdlib.h>
#i... | 4,694 | 28.34375 | 108 | c |
null | pytorch-main/aten/src/ATen/native/quantized/cpu/qnnpack/src/softargmax.c | /*
* Copyright (c) Facebook, Inc. and its affiliates.
* All rights reserved.
*
* This source code is licensed under the BSD-style license found in the
* LICENSE file in the root directory of this source tree.
*/
#include <assert.h>
#include <math.h>
#include <stddef.h>
#include <stdint.h>
#include <stdlib.h>
#i... | 4,165 | 28.757143 | 112 | c |
null | pytorch-main/aten/src/ATen/native/quantized/cpu/qnnpack/src/tanh.c | /*
* Copyright (c) Facebook, Inc. and its affiliates.
* All rights reserved.
*
* This source code is licensed under the BSD-style license found in the
* LICENSE file in the root directory of this source tree.
*/
#include <assert.h>
#include <math.h>
#include <stddef.h>
#include <stdint.h>
#include <stdlib.h>
#i... | 4,708 | 28.067901 | 105 | c |
null | pytorch-main/aten/src/ATen/native/quantized/cpu/qnnpack/src/hgemm/8x8-neonfp16arith.c | /*
* Copyright (c) Facebook, Inc. and its affiliates.
* All rights reserved.
*
* This source code is licensed under the BSD-style license found in the
* LICENSE file in the root directory of this source tree.
*/
#include <arm_neon.h>
#include <qnnpack/hgemm.h>
void pytorch_hgemm_ukernel_8x8__neonfp16arith(
... | 14,917 | 39.210243 | 79 | c |
null | pytorch-main/aten/src/ATen/native/quantized/cpu/qnnpack/src/q8avgpool/mp8x9p8q-neon.c | /*
* Copyright (c) Facebook, Inc. and its affiliates.
* All rights reserved.
*
* This source code is licensed under the BSD-style license found in the
* LICENSE file in the root directory of this source tree.
*/
#include <assert.h>
#include <arm_neon.h>
#include <qnnpack/q8avgpool.h>
void pytorch_q8avgpool_uk... | 16,937 | 36.556541 | 80 | c |
null | pytorch-main/aten/src/ATen/native/quantized/cpu/qnnpack/src/q8avgpool/mp8x9p8q-sse2.c | /*
* Copyright (c) Facebook, Inc. and its affiliates.
* All rights reserved.
*
* This source code is licensed under the BSD-style license found in the
* LICENSE file in the root directory of this source tree.
*/
#include <assert.h>
#include <emmintrin.h>
#include <qnnpack/q8avgpool.h>
void pytorch_q8avgpool_u... | 19,158 | 39.591102 | 79 | c |
null | pytorch-main/aten/src/ATen/native/quantized/cpu/qnnpack/src/q8avgpool/up8x9-neon.c | /*
* Copyright (c) Facebook, Inc. and its affiliates.
* All rights reserved.
*
* This source code is licensed under the BSD-style license found in the
* LICENSE file in the root directory of this source tree.
*/
#include <assert.h>
#include <arm_neon.h>
#include <qnnpack/q8avgpool.h>
void pytorch_q8avgpool_uk... | 8,362 | 33.415638 | 79 | c |
null | pytorch-main/aten/src/ATen/native/quantized/cpu/qnnpack/src/q8avgpool/up8x9-sse2.c | /*
* Copyright (c) Facebook, Inc. and its affiliates.
* All rights reserved.
*
* This source code is licensed under the BSD-style license found in the
* LICENSE file in the root directory of this source tree.
*/
#include <assert.h>
#include <emmintrin.h>
#include <qnnpack/q8avgpool.h>
void pytorch_q8avgpool_u... | 8,457 | 34.687764 | 77 | c |
null | pytorch-main/aten/src/ATen/native/quantized/cpu/qnnpack/src/q8avgpool/up8xm-neon.c | /*
* Copyright (c) Facebook, Inc. and its affiliates.
* All rights reserved.
*
* This source code is licensed under the BSD-style license found in the
* LICENSE file in the root directory of this source tree.
*/
#include <assert.h>
#include <arm_neon.h>
#include <qnnpack/q8avgpool.h>
void pytorch_q8avgpool_uk... | 3,965 | 30.47619 | 79 | c |
null | pytorch-main/aten/src/ATen/native/quantized/cpu/qnnpack/src/q8avgpool/up8xm-sse2.c | /*
* Copyright (c) Facebook, Inc. and its affiliates.
* All rights reserved.
*
* This source code is licensed under the BSD-style license found in the
* LICENSE file in the root directory of this source tree.
*/
#include <assert.h>
#include <emmintrin.h>
#include <qnnpack/q8avgpool.h>
void pytorch_q8avgpool_u... | 3,032 | 28.446602 | 78 | c |
null | pytorch-main/aten/src/ATen/native/quantized/cpu/qnnpack/src/q8conv/4x4c2-sse2.c | /*
* Copyright (c) Facebook, Inc. and its affiliates.
* All rights reserved.
*
* This source code is licensed under the BSD-style license found in the
* LICENSE file in the root directory of this source tree.
*/
#include <immintrin.h>
#include <qnnpack/q8conv.h>
#include <requantization/runtime-sse2.h>
void py... | 13,622 | 36.736842 | 79 | c |
null | pytorch-main/aten/src/ATen/native/quantized/cpu/qnnpack/src/q8dwconv/mp8x27-sse2.c | /*
* Copyright (c) Facebook, Inc. and its affiliates.
* All rights reserved.
*
* This source code is licensed under the BSD-style license found in the
* LICENSE file in the root directory of this source tree.
*/
#include <immintrin.h>
#include <math.h>
#include <qnnpack/q8dwconv.h>
void pytorch_q8dwconv_ukerne... | 6,672 | 40.70625 | 79 | c |
null | pytorch-main/aten/src/ATen/native/quantized/cpu/qnnpack/src/q8dwconv/up8x9-sse2-per-channel.c | /*
* Copyright (c) Facebook, Inc. and its affiliates.
* All rights reserved.
*
* This source code is licensed under the BSD-style license found in the
* LICENSE file in the root directory of this source tree.
*/
#include <immintrin.h>
#include <qnnpack/q8dwconv.h>
#include <requantization/runtime-sse2.h>
void ... | 18,569 | 41.108844 | 91 | c |
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