cuda stringlengths 84 3.33k | hip stringlengths 140 3.32k |
|---|---|
#include "caffe2/core/context_gpu.h"
#include "caffe2/operators/ceil_op.h"
#include "caffe2/utils/math.h"
namespace caffe2 {
template <typename T>
__global__ void CeilKernel(const int N, const T* X, T* Y) {
CUDA_1D_KERNEL_LOOP(i, N) {
Y[i] = std::ceil(X[i]);
}
}
template <>
bool CeilOp<float, CUDAContext>::... | // !!! This is a file automatically generated by hipify!!!
#include "hip/hip_runtime.h"
#include "caffe2/core/hip/context_gpu.h"
#include "caffe2/operators/ceil_op.h"
#include "caffe2/utils/math.h"
namespace caffe2 {
template <typename T>
__global__ void CeilKernel(const int N, const T* X, T* Y) {
HIP_1D_KERNEL_LO... |
#include "caffe2/core/context_gpu.h"
#include "caffe2/operators/clip_op.h"
namespace caffe2 {
namespace {
template <typename T>
__device__ T cuda_min(T x, T y);
template <typename T>
__device__ T cuda_max(T x, T y);
template <>
__device__ float cuda_min(float x, float y) { return fminf(x, y); }
template <>
__device_... | // !!! This is a file automatically generated by hipify!!!
#include "hip/hip_runtime.h"
#include "caffe2/core/hip/context_gpu.h"
#include "caffe2/operators/clip_op.h"
namespace caffe2 {
namespace {
template <typename T>
__device__ T hip_min(T x, T y);
template <typename T>
__device__ T hip_max(T x, T y);
template <>... |
#include "caffe2/core/context_gpu.h"
#include "caffe2/core/operator.h"
#include "caffe2/operators/no_default_engine_op.h"
namespace caffe2 {
// Communication operators do not have default engines.
REGISTER_CUDA_OPERATOR(CreateCommonWorld, NoDefaultEngineOp<CUDAContext>);
REGISTER_CUDA_OPERATOR(CloneCommonWorld, NoDef... | // !!! This is a file automatically generated by hipify!!!
#include "caffe2/core/hip/context_gpu.h"
#include "caffe2/core/operator.h"
#include "caffe2/operators/no_default_engine_op.h"
namespace caffe2 {
// Communication operators do not have default engines.
REGISTER_HIP_OPERATOR(CreateCommonWorld, NoDefaultEngineOp... |
#include "caffe2/core/context_gpu.h"
#include "caffe2/operators/concat_split_op.h"
namespace caffe2 {
REGISTER_CUDA_OPERATOR(Split, SplitOp<CUDAContext>);
REGISTER_CUDA_OPERATOR(Concat, ConcatOp<CUDAContext>);
// Backward compatibility settings
REGISTER_CUDA_OPERATOR(DepthSplit, SplitOp<CUDAContext>);
REGISTER_CUDA_... | // !!! This is a file automatically generated by hipify!!!
#include "caffe2/core/hip/context_gpu.h"
#include "caffe2/operators/concat_split_op.h"
namespace caffe2 {
REGISTER_HIP_OPERATOR(Split, SplitOp<HIPContext>);
REGISTER_HIP_OPERATOR(Concat, ConcatOp<HIPContext>);
// Backward compatibility settings
REGISTER_HIP_... |
#include "caffe2/operators/conv_op.h"
#include "caffe2/operators/conv_op_impl.h"
#include "caffe2/core/context_gpu.h"
namespace caffe2 {
REGISTER_CUDA_OPERATOR(Conv, ConvOp<float, CUDAContext>);
REGISTER_CUDA_OPERATOR(ConvGradient, ConvGradientOp<float, CUDAContext>);
REGISTER_CUDA_OPERATOR(Conv1D, ConvOp<float, CUD... | // !!! This is a file automatically generated by hipify!!!
#include "caffe2/operators/conv_op.h"
#include "caffe2/operators/conv_op_impl.h"
#include "caffe2/core/hip/context_gpu.h"
namespace caffe2 {
REGISTER_HIP_OPERATOR(Conv, ConvOp<float, HIPContext>);
REGISTER_HIP_OPERATOR(ConvGradient, ConvGradientOp<float, HIPC... |
#include "caffe2/core/context_gpu.h"
#include "caffe2/operators/conv_op_shared.h"
namespace caffe2 {
template <>
void createSharedBuffer<CUDAContext>(Workspace* ws) {
auto* mutexPtr = ws->CreateBlob("__CAFFE2_SHARED_CONV_BUFFER_CUDA_MUTEX__")
->GetMutable<std::unique_ptr<std::mutex>>();
mu... | // !!! This is a file automatically generated by hipify!!!
#include "caffe2/core/hip/context_gpu.h"
#include "caffe2/operators/conv_op_shared.h"
namespace caffe2 {
template <>
void createSharedBuffer<HIPContext>(Workspace* ws) {
auto* mutexPtr = ws->CreateBlob("__CAFFE2_SHARED_CONV_BUFFER_HIP_MUTEX__")
... |
#include "caffe2/core/context_gpu.h"
#include "caffe2/operators/conv_transpose_op.h"
#include "caffe2/operators/conv_transpose_op_impl.h"
namespace caffe2 {
REGISTER_CUDA_OPERATOR(ConvTranspose, ConvTransposeOp<float, CUDAContext>);
REGISTER_CUDA_OPERATOR(
ConvTransposeGradient,
ConvTransposeGradientOp<float,... | // !!! This is a file automatically generated by hipify!!!
#include "caffe2/core/hip/context_gpu.h"
#include "caffe2/operators/conv_transpose_op.h"
#include "caffe2/operators/conv_transpose_op_impl.h"
namespace caffe2 {
REGISTER_HIP_OPERATOR(ConvTranspose, ConvTransposeOp<float, HIPContext>);
REGISTER_HIP_OPERATOR(
... |
#include "caffe2/core/context_gpu.h"
#include "caffe2/operators/copy_op.h"
namespace caffe2 {
template <>
class CopyOnDeviceLikeOp<CUDAContext, CUDAContext, CUDAContext>
: public Operator<CUDAContext> {
public:
template <class... Args>
explicit CopyOnDeviceLikeOp(Args&&... args)
: Operator<CUDAContext... | // !!! This is a file automatically generated by hipify!!!
#include "caffe2/core/hip/context_gpu.h"
#include "caffe2/operators/copy_op.h"
namespace caffe2 {
template <>
class CopyOnDeviceLikeOp<HIPContext, HIPContext, HIPContext>
: public Operator<HIPContext> {
public:
template <class... Args>
explicit Copy... |
#include "caffe2/operators/cosh_op.h"
#include <c10/util/accumulate.h>
#include "caffe2/core/context_gpu.h"
#include <algorithm>
#include <functional>
namespace caffe2 {
namespace {
__global__ void CoshGradientCUDAKernel(
const int N,
const float* dY,
const float* X,
float* dX) {
CUDA_1D_KERNEL_... | // !!! This is a file automatically generated by hipify!!!
#include "hip/hip_runtime.h"
#include "caffe2/operators/cosh_op.h"
#include <c10/util/accumulate.h>
#include "caffe2/core/hip/context_gpu.h"
#include <algorithm>
#include <functional>
namespace caffe2 {
namespace {
__global__ void CoshGradientHIPKernel(
... |
#include "caffe2/core/context_gpu.h"
#include "caffe2/operators/cosine_embedding_criterion_op.h"
namespace caffe2 {
namespace {
__global__ void CECKernel(
const int N, const float* S, const int* Y, const float margin,
float* output) {
CUDA_1D_KERNEL_LOOP(i, N) {
output[i] = Y[i] == 1 ? (1. - S[i]) : f... | // !!! This is a file automatically generated by hipify!!!
#include "hip/hip_runtime.h"
#include "caffe2/core/hip/context_gpu.h"
#include "caffe2/operators/cosine_embedding_criterion_op.h"
namespace caffe2 {
namespace {
__global__ void CECKernel(
const int N, const float* S, const int* Y, const float margin,
... |
#define TORCH_ASSERT_NO_OPERATORS
#define _USE_MATH_DEFINES
#include <ATen/native/Activation.h>
#include <cmath>
#include <thrust/tuple.h>
#include <ATen/AccumulateType.h>
#include <ATen/Dispatch.h>
#include <ATen/core/TensorBase.h>
#include <c10/core/Scalar.h>
#include <c10/cuda/CUDAMathCompat.h>
#include <ATen/c... | // !!! This is a file automatically generated by hipify!!!
#define TORCH_ASSERT_NO_OPERATORS
#define _USE_MATH_DEFINES
#include <ATen/native/Activation.h>
#include <cmath>
#include <thrust/tuple.h>
#include <ATen/AccumulateType.h>
#include <ATen/Dispatch.h>
#include <ATen/core/TensorBase.h>
#include <c10/core/Scal... |
#define TORCH_ASSERT_NO_OPERATORS
#include <ATen/cuda/CUDAConfig.h>
#include <ATen/cuda/cub.cuh>
namespace at {
namespace cuda {
namespace cub {
template <typename key_t>
void radix_sort_keys(
const key_t* keys_in,
key_t* keys_out,
int64_t n,
bool descending,
int64_t begin_bit,
int64_t end_bi... | // !!! This is a file automatically generated by hipify!!!
#define TORCH_ASSERT_NO_OPERATORS
#include <ATen/hip\HIPConfig.h>
#include <ATen/hip\cub.cuh>
namespace at {
namespace hip {
namespace cub {
template <typename key_t>
void radix_sort_keys(
const key_t* keys_in,
key_t* keys_out,
int64_t n,
boo... |
#include "caffe2/operators/cos_op.h"
#include <algorithm>
#include <functional>
#include "caffe2/core/context_gpu.h"
namespace caffe2 {
namespace {
template <typename T>
__global__ void
CosGradientCUDAKernel(const int N, const T* dY, const T* X, T* dX) {
CUDA_1D_KERNEL_LOOP(i, N) {
#if __CUDA_ARCH__ >= 350
... | // !!! This is a file automatically generated by hipify!!!
#include "hip/hip_runtime.h"
#include "caffe2/operators/cos_op.h"
#include <algorithm>
#include <functional>
#include "caffe2/core/hip/context_gpu.h"
namespace caffe2 {
namespace {
template <typename T>
__global__ void
CosGradientHIPKernel(const int N, co... |
#include "caffe2/core/context_gpu.h"
#include "caffe2/operators/counter_ops.h"
namespace caffe2 {
REGISTER_CUDA_OPERATOR(CreateCounter, CreateCounterOp<int64_t, CUDAContext>);
REGISTER_CUDA_OPERATOR(ResetCounter, ResetCounterOp<int64_t, CUDAContext>);
REGISTER_CUDA_OPERATOR(CountDown, CountDownOp<int64_t, CUDAContext... | // !!! This is a file automatically generated by hipify!!!
#include "caffe2/core/hip/context_gpu.h"
#include "caffe2/operators/counter_ops.h"
namespace caffe2 {
REGISTER_HIP_OPERATOR(CreateCounter, CreateCounterOp<int64_t, HIPContext>);
REGISTER_HIP_OPERATOR(ResetCounter, ResetCounterOp<int64_t, HIPContext>);
REGISTE... |
#include "caffe2/operators/cube_op.h"
#include <algorithm>
#include <functional>
#include "caffe2/core/context_gpu.h"
namespace caffe2 {
namespace {
template <typename T>
__global__ void
CubeGradientCUDAKernel(const int N, const T* dY, const T* X, T* dX) {
CUDA_1D_KERNEL_LOOP(i, N) {
#if __CUDA_ARCH__ >= 350
... | // !!! This is a file automatically generated by hipify!!!
#include "hip/hip_runtime.h"
#include "caffe2/operators/cube_op.h"
#include <algorithm>
#include <functional>
#include "caffe2/core/hip/context_gpu.h"
namespace caffe2 {
namespace {
template <typename T>
__global__ void
CubeGradientHIPKernel(const int N, ... |
#include "caffe2/core/context_gpu.h"
#include "caffe2/operators/data_couple.h"
namespace caffe2 {
REGISTER_CUDA_OPERATOR(DataCouple, DataCoupleOp<CUDAContext>);
}
### | // !!! This is a file automatically generated by hipify!!!
#include "caffe2/core/hip/context_gpu.h"
#include "caffe2/operators/data_couple.h"
namespace caffe2 {
REGISTER_HIP_OPERATOR(DataCouple, DataCoupleOp<HIPContext>);
}
### |
#include "caffe2/operators/do_op.h"
#include "caffe2/core/context_gpu.h"
namespace caffe2 {
REGISTER_CUDA_OPERATOR(Do, DoOp<CUDAContext>);
} // namespace caffe2
### | // !!! This is a file automatically generated by hipify!!!
#include "caffe2/operators/do_op.h"
#include "caffe2/core/hip/context_gpu.h"
namespace caffe2 {
REGISTER_HIP_OPERATOR(Do, DoOp<HIPContext>);
} // namespace caffe2
### |
#include "caffe2/core/context_gpu.h"
#include "caffe2/operators/dropout_op.h"
namespace caffe2 {
namespace {
__global__ void DropoutKernel(
const int N, const float ratio, const float* Xdata, float* Ydata, bool* maskdata) {
const float scale = 1. / (1. - ratio);
CUDA_1D_KERNEL_LOOP(i, N) {
maskdata[i] = (Ydata[i... |
#include "hip/hip_runtime.h"
#include "caffe2/core/hip/context_gpu.h"
#include "caffe2/operators/dropout_op.h"
namespace caffe2 {
namespace {
__global__ void DropoutKernel(
const int N, const float ratio, const float* Xdata, float* Ydata, bool* maskdata) {
const float scale = 1. / (1. - ratio);
HIP_1D_KERNEL_LOOP... |
#include "caffe2/operators/elementwise_add_op.h"
#include "caffe2/core/context_gpu.h"
namespace caffe2 {
REGISTER_CUDA_OPERATOR(
Add,
BinaryElementwiseOp<NumericTypes, CUDAContext, AddFunctor<CUDAContext>>);
REGISTER_CUDA_OPERATOR(
AddGradient,
BinaryElementwiseGradientOp<
NumericTypes,
... | // !!! This is a file automatically generated by hipify!!!
#include "caffe2/operators/elementwise_add_op.h"
#include "caffe2/core/hip/context_gpu.h"
namespace caffe2 {
REGISTER_HIP_OPERATOR(
Add,
BinaryElementwiseOp<NumericTypes, HIPContext, AddFunctor<HIPContext>>);
REGISTER_HIP_OPERATOR(
AddGradient,
... |
#include "caffe2/operators/elementwise_op_test.h"
#include "caffe2/core/context_gpu.h"
#include "caffe2/core/flags.h"
C10_DECLARE_string(caffe_test_root);
template <>
void CopyVector<caffe2::CUDAContext>(const int N, const bool* x, bool* y) {
CUDA_CHECK(cudaMemcpy(y, x, N * sizeof(bool), cudaMemcpyHostToDevice));... | // !!! This is a file automatically generated by hipify!!!
#include "caffe2/operators/elementwise_op_test.h"
#include "caffe2/core/hip/context_gpu.h"
#include "caffe2/core/flags.h"
C10_DECLARE_string(caffe_test_root);
template <>
void CopyVector<caffe2::HIPContext>(const int N, const bool* x, bool* y) {
HIP_CHECK... |
#include "caffe2/operators/elementwise_sub_op.h"
#include "caffe2/core/context_gpu.h"
namespace caffe2 {
REGISTER_CUDA_OPERATOR(
Sub,
BinaryElementwiseOp<NumericTypes, CUDAContext, SubFunctor<CUDAContext>>);
REGISTER_CUDA_OPERATOR(
SubGradient,
BinaryElementwiseGradientOp<
NumericTypes,
... | // !!! This is a file automatically generated by hipify!!!
#include "caffe2/operators/elementwise_sub_op.h"
#include "caffe2/core/hip/context_gpu.h"
namespace caffe2 {
REGISTER_HIP_OPERATOR(
Sub,
BinaryElementwiseOp<NumericTypes, HIPContext, SubFunctor<HIPContext>>);
REGISTER_HIP_OPERATOR(
SubGradient,
... |
#include "caffe2/operators/elu_op.h"
#include <algorithm>
#include <functional>
#include "caffe2/core/context_gpu.h"
namespace caffe2 {
namespace {
template <typename T>
__global__ void EluCUDAKernel(const int N, const T alpha, const T* X, T* Y);
template <>
__global__ void
EluCUDAKernel<float>(const int N, cons... | // !!! This is a file automatically generated by hipify!!!
#include "hip/hip_runtime.h"
#include "caffe2/operators/elu_op.h"
#include <algorithm>
#include <functional>
#include "caffe2/core/hip/context_gpu.h"
namespace caffe2 {
namespace {
template <typename T>
__global__ void EluHIPKernel(const int N, const T al... |
#define TORCH_ASSERT_NO_OPERATORS
#define _USE_MATH_DEFINES
#include <ATen/native/Activation.h>
#include <cmath>
#include <thrust/tuple.h>
#include <ATen/AccumulateType.h>
#include <ATen/Dispatch.h>
#include <ATen/core/TensorBase.h>
#include <c10/core/Scalar.h>
#include <c10/cuda/CUDAMathCompat.h>
#include <ATen/c... | // !!! This is a file automatically generated by hipify!!!
#define TORCH_ASSERT_NO_OPERATORS
#define _USE_MATH_DEFINES
#include <ATen/native/Activation.h>
#include <cmath>
#include <thrust/tuple.h>
#include <ATen/AccumulateType.h>
#include <ATen/Dispatch.h>
#include <ATen/core/TensorBase.h>
#include <c10/core/Scal... |
#include "caffe2/operators/enforce_finite_op.h"
#include "caffe2/core/context_gpu.h"
namespace caffe2 {
template <>
template <typename T>
bool EnforceFiniteOp<CUDAContext>::DoRunWithType() {
buffer_.CopyFrom(Input(0)); // sync copy
EnforceOnCPU<T>(buffer_);
return true;
}
REGISTER_CUDA_OPERATOR(EnforceFinite... | // !!! This is a file automatically generated by hipify!!!
#include "caffe2/operators/enforce_finite_op.h"
#include "caffe2/core/hip/context_gpu.h"
namespace caffe2 {
template <>
template <typename T>
bool EnforceFiniteOp<HIPContext>::DoRunWithType() {
buffer_.CopyFrom(Input(0)); // sync copy
EnforceOnCPU<T>(bu... |
#include "caffe2/operators/ensure_cpu_output_op.h"
#include "caffe2/core/context_gpu.h"
namespace caffe2 {
// From CUDA Context, takes either CUDA or CPU tensor as input, and produce
// TensorCPU
REGISTER_CUDA_OPERATOR(EnsureCPUOutput, EnsureCPUOutputOp<CUDAContext>);
} // namespace caffe2
### | // !!! This is a file automatically generated by hipify!!!
#include "caffe2/operators/ensure_cpu_output_op.h"
#include "caffe2/core/hip/context_gpu.h"
namespace caffe2 {
// From HIP Context, takes either HIP or CPU tensor as input, and produce
// TensorCPU
REGISTER_HIP_OPERATOR(EnsureCPUOutput, EnsureCPUOutputOp<HIP... |
#include "caffe2/operators/erf_op.h"
#include <algorithm>
#include <functional>
#include "caffe2/core/context_gpu.h"
namespace caffe2 {
namespace {
__global__ void ErfGradientCUDAKernel(
const int N,
const float* dY,
const float* X,
float* dX) {
CUDA_1D_KERNEL_LOOP(i, N) {
#if __CUDA_ARCH__ >= 3... | // !!! This is a file automatically generated by hipify!!!
#include "hip/hip_runtime.h"
#include "caffe2/operators/erf_op.h"
#include <algorithm>
#include <functional>
#include "caffe2/core/hip/context_gpu.h"
namespace caffe2 {
namespace {
__global__ void ErfGradientHIPKernel(
const int N,
const float* dY... |
#include "caffe2/operators/expand_op.h"
#include "caffe2/core/context_gpu.h"
namespace caffe2 {
REGISTER_CUDA_OPERATOR(
Expand,
ExpandOp<
TensorTypes<std::int32_t, std::int64_t, float, double>,
CUDAContext>);
REGISTER_CUDA_OPERATOR(
ExpandGradient,
ExpandGradientOp<
TensorTyp... | // !!! This is a file automatically generated by hipify!!!
#include "caffe2/operators/expand_op.h"
#include "caffe2/core/hip/context_gpu.h"
namespace caffe2 {
REGISTER_HIP_OPERATOR(
Expand,
ExpandOp<
TensorTypes<std::int32_t, std::int64_t, float, double>,
HIPContext>);
REGISTER_HIP_OPERATOR(... |
#include "caffe2/core/context_gpu.h"
#include "caffe2/operators/expand_squeeze_dims_op.h"
namespace caffe2 {
REGISTER_CUDA_OPERATOR(Squeeze, SqueezeOp<CUDAContext>);
REGISTER_CUDA_OPERATOR(ExpandDims, ExpandDimsOp<CUDAContext>);
} // namespace caffe2
### | // !!! This is a file automatically generated by hipify!!!
#include "caffe2/core/hip/context_gpu.h"
#include "caffe2/operators/expand_squeeze_dims_op.h"
namespace caffe2 {
REGISTER_HIP_OPERATOR(Squeeze, SqueezeOp<HIPContext>);
REGISTER_HIP_OPERATOR(ExpandDims, ExpandDimsOp<HIPContext>);
} // namespace caffe2
### |
#include "caffe2/operators/exp_op.h"
#include "caffe2/core/context_gpu.h"
namespace caffe2 {
REGISTER_CUDA_OPERATOR(
Exp,
UnaryElementwiseOp<
TensorTypes<float>,
CUDAContext,
ExpFunctor<CUDAContext>>);
} // namespace caffe2
### | // !!! This is a file automatically generated by hipify!!!
#include "caffe2/operators/exp_op.h"
#include "caffe2/core/hip/context_gpu.h"
namespace caffe2 {
REGISTER_HIP_OPERATOR(
Exp,
UnaryElementwiseOp<
TensorTypes<float>,
HIPContext,
ExpFunctor<HIPContext>>);
} // namespace caffe2... |
#include <cmath>
#include "caffe2/core/context_gpu.h"
#include "caffe2/operators/filler_op.h"
#include "caffe2/operators/operator_fallback_gpu.h"
namespace caffe2 {
namespace {
__global__ void FillRangeKernel(const int n, float* data) {
CUDA_1D_KERNEL_LOOP(index, n) {
data[index] = index;
}
}
template <type... | // !!! This is a file automatically generated by hipify!!!
#include "hip/hip_runtime.h"
#include <cmath>
#include "caffe2/core/hip/context_gpu.h"
#include "caffe2/operators/filler_op.h"
#include "caffe2/operators/hip/operator_fallback_gpu.h"
namespace caffe2 {
namespace {
__global__ void FillRangeKernel(const int n,... |
#include <cub/block/block_reduce.cuh>
#include "caffe2/core/context_gpu.h"
#include "caffe2/operators/find_op.h"
#include "caffe2/utils/cub_namespace.cuh"
namespace caffe2 {
template <typename T>
__global__ void FindKernel(
int num_needles,
int idx_size,
const T* idx,
const T* needles,
int* out,
... | // !!! This is a file automatically generated by hipify!!!
#include "hip/hip_runtime.h"
#include <hipcub/hipcub.hpp>
#include "caffe2/core/hip/context_gpu.h"
#include "caffe2/operators/find_op.h"
#include "caffe2/utils/cub_namespace.cuh"
namespace caffe2 {
template <typename T>
__global__ void FindKernel(
int nu... |
#include "caffe2/core/context_gpu.h"
#include "caffe2/operators/floor_op.h"
#include "caffe2/utils/math.h"
namespace caffe2 {
template <typename T>
__global__ void FloorKernel(const int N, const T* X, T* Y) {
CUDA_1D_KERNEL_LOOP(i, N) {
Y[i] = std::floor(X[i]);
}
}
template <>
bool FloorOp<float, CUDAContex... | // !!! This is a file automatically generated by hipify!!!
#include "hip/hip_runtime.h"
#include "caffe2/core/hip/context_gpu.h"
#include "caffe2/operators/floor_op.h"
#include "caffe2/utils/math.h"
namespace caffe2 {
template <typename T>
__global__ void FloorKernel(const int N, const T* X, T* Y) {
HIP_1D_KERNEL_... |
#include "caffe2/core/context_gpu.h"
#include "caffe2/operators/free_op.h"
namespace caffe2 {
REGISTER_CUDA_OPERATOR(Free, FreeOp<CUDAContext>);
} // namespace caffe2
### | // !!! This is a file automatically generated by hipify!!!
#include "caffe2/core/hip/context_gpu.h"
#include "caffe2/operators/free_op.h"
namespace caffe2 {
REGISTER_HIP_OPERATOR(Free, FreeOp<HIPContext>);
} // namespace caffe2
### |
#define TORCH_ASSERT_NO_OPERATORS
#define _USE_MATH_DEFINES
#include <ATen/native/Activation.h>
#include <cmath>
#include <thrust/tuple.h>
#include <ATen/AccumulateType.h>
#include <ATen/Dispatch.h>
#include <ATen/core/TensorBase.h>
#include <c10/core/Scalar.h>
#include <c10/cuda/CUDAMathCompat.h>
#include <ATen/c... | // !!! This is a file automatically generated by hipify!!!
#define TORCH_ASSERT_NO_OPERATORS
#define _USE_MATH_DEFINES
#include <ATen/native/Activation.h>
#include <cmath>
#include <thrust/tuple.h>
#include <ATen/AccumulateType.h>
#include <ATen/Dispatch.h>
#include <ATen/core/TensorBase.h>
#include <c10/core/Scal... |
#include "caffe2/core/context_gpu.h"
#include "caffe2/operators/gather_op.h"
#include "caffe2/operators/gather_op.cuh"
namespace caffe2 {
template <>
bool GatherOp<CUDAContext>::RunOnDevice() {
return DispatchHelper<TensorTypes<int32_t, int64_t>>::call(
this, OperatorBase::Input<Tensor>(INDICES, CUDA));
}
t... | // !!! This is a file automatically generated by hipify!!!
#include "caffe2/core/hip/context_gpu.h"
#include "caffe2/operators/gather_op.h"
#include "caffe2/operators/hip/gather_op.cuh"
namespace caffe2 {
template <>
bool GatherOp<HIPContext>::RunOnDevice() {
return DispatchHelper<TensorTypes<int32_t, int64_t>>::c... |
#ifndef CAFFE2_OPERATORS_UTILS_NMS_GPU_H_
#define CAFFE2_OPERATORS_UTILS_NMS_GPU_H_
#include <vector>
#include "caffe2/core/context_gpu.h"
namespace caffe2 {
namespace utils {
// Computes Non-Maximum Suppression on the GPU
// Reject a bounding box if its region has an intersection-overunion (IoU)
// overlap wit... | // !!! This is a file automatically generated by hipify!!!
#ifndef CAFFE2_OPERATORS_UTILS_NMS_GPU_H_
#define CAFFE2_OPERATORS_UTILS_NMS_GPU_H_
#include <vector>
#include "caffe2/core/hip/context_gpu.h"
namespace caffe2 {
namespace utils {
// Computes Non-Maximum Suppression on the GPU
// Reject a bounding box if i... |
#include "caffe2/core/context_gpu.h"
#include "caffe2/operators/given_tensor_byte_string_to_uint8_fill_op.h"
namespace caffe2 {
REGISTER_CUDA_OPERATOR(
GivenTensorByteStringToUInt8Fill,
GivenTensorByteStringToUInt8FillOp<CUDAContext>);
}
### | // !!! This is a file automatically generated by hipify!!!
#include "caffe2/core/hip/context_gpu.h"
#include "caffe2/operators/given_tensor_byte_string_to_uint8_fill_op.h"
namespace caffe2 {
REGISTER_HIP_OPERATOR(
GivenTensorByteStringToUInt8Fill,
GivenTensorByteStringToUInt8FillOp<HIPContext>);
}
### |
#include "caffe2/core/context_gpu.h"
#include "caffe2/operators/given_tensor_fill_op.h"
namespace caffe2 {
REGISTER_CUDA_OPERATOR(GivenTensorFill, GivenTensorFillOp<float, CUDAContext>);
REGISTER_CUDA_OPERATOR(
GivenTensorDoubleFill,
GivenTensorFillOp<double, CUDAContext>);
REGISTER_CUDA_OPERATOR(
GivenT... | // !!! This is a file automatically generated by hipify!!!
#include "caffe2/core/hip/context_gpu.h"
#include "caffe2/operators/given_tensor_fill_op.h"
namespace caffe2 {
REGISTER_HIP_OPERATOR(GivenTensorFill, GivenTensorFillOp<float, HIPContext>);
REGISTER_HIP_OPERATOR(
GivenTensorDoubleFill,
GivenTensorFill... |
#include "caffe2/operators/glu_op.h"
#include "caffe2/core/context_gpu.h"
namespace caffe2 {
namespace {
__global__ void glu_kernel(
const int M,
const int split_dim_size,
const int N,
const float* Xdata,
float* Ydata) {
const int xOffset = 2 * split_dim_size * N;
const int yOffset = split_d... | // !!! This is a file automatically generated by hipify!!!
#include "hip/hip_runtime.h"
#include "caffe2/operators/glu_op.h"
#include "caffe2/core/hip/context_gpu.h"
namespace caffe2 {
namespace {
__global__ void glu_kernel(
const int M,
const int split_dim_size,
const int N,
const float* Xdata,
... |
#include "caffe2/operators/half_float_ops.h"
#include "caffe2/core/context_gpu.h"
#ifdef CAFFE_HAS_CUDA_FP16
namespace caffe2 {
namespace {
__global__ void FloatToHalfKernel(const int N, const float* X, half* Y) {
CUDA_1D_KERNEL_LOOP(i, N) {
Y[i] = __float2half(X[i]);
}
}
__global__ void HalfToFloatKernel(const in... |
#include "hip/hip_runtime.h"
#include "caffe2/operators/half_float_ops.h"
#include "caffe2/core/hip/context_gpu.h"
#ifdef CAFFE_HAS_HIP_FP16
namespace caffe2 {
namespace {
__global__ void FloatToHalfKernel(const int N, const float* X, half* Y) {
HIP_1D_KERNEL_LOOP(i, N) {
Y[i] = __float2half(X[i]);
}
}
__global__... |
#include "caffe2/operators/hard_sigmoid_op.h"
#include <algorithm>
#include <functional>
#include "caffe2/core/context_gpu.h"
namespace caffe2 {
namespace {
template <typename T>
__global__ void HardSigmoidCUDAKernel(
const int N,
const T alpha,
const T beta,
const T* X,
T* Y) {
CUDA_1D_KERN... | // !!! This is a file automatically generated by hipify!!!
#include "hip/hip_runtime.h"
#include "caffe2/operators/hard_sigmoid_op.h"
#include <algorithm>
#include <functional>
#include "caffe2/core/hip/context_gpu.h"
namespace caffe2 {
namespace {
template <typename T>
__global__ void HardSigmoidHIPKernel(
c... |
#include "caffe2/operators/if_op.h"
#include "caffe2/core/context_gpu.h"
namespace caffe2 {
REGISTER_CUDA_OPERATOR(If, IfOp<CUDAContext>);
} // namespace caffe2
### | // !!! This is a file automatically generated by hipify!!!
#include "caffe2/operators/if_op.h"
#include "caffe2/core/hip/context_gpu.h"
namespace caffe2 {
REGISTER_HIP_OPERATOR(If, IfOp<HIPContext>);
} // namespace caffe2
### |
#include "caffe2/core/context_gpu.h"
#include "caffe2/operators/im2col_op.h"
namespace caffe2 {
REGISTER_CUDA_OPERATOR(Im2Col, Im2ColOp<float, CUDAContext>);
REGISTER_CUDA_OPERATOR(Col2Im, Col2ImOp<float, CUDAContext>);
} // namespace caffe2
### | // !!! This is a file automatically generated by hipify!!!
#include "caffe2/core/hip/context_gpu.h"
#include "caffe2/operators/im2col_op.h"
namespace caffe2 {
REGISTER_HIP_OPERATOR(Im2Col, Im2ColOp<float, HIPContext>);
REGISTER_HIP_OPERATOR(Col2Im, Col2ImOp<float, HIPContext>);
} // namespace caffe2
### |
#include "caffe2/core/context_gpu.h"
#include "caffe2/operators/leaky_relu_op.h"
#include "caffe2/utils/math.h"
namespace caffe2 {
namespace {
template <typename T>
__global__ void LeakyReluKernel(const int N, const T alpha, const T* X, T* Y) {
CUDA_1D_KERNEL_LOOP(i, N) {
Y[i] = X[i] >= 0 ? X[i] : X[i] * alpha... | // !!! This is a file automatically generated by hipify!!!
#include "hip/hip_runtime.h"
#include "caffe2/core/hip/context_gpu.h"
#include "caffe2/operators/leaky_relu_op.h"
#include "caffe2/utils/math.h"
namespace caffe2 {
namespace {
template <typename T>
__global__ void LeakyReluKernel(const int N, const T alpha, ... |
#define TORCH_ASSERT_NO_OPERATORS
#define _USE_MATH_DEFINES
#include <ATen/native/Activation.h>
#include <cmath>
#include <thrust/tuple.h>
#include <ATen/AccumulateType.h>
#include <ATen/Dispatch.h>
#include <ATen/core/TensorBase.h>
#include <c10/core/Scalar.h>
#include <c10/cuda/CUDAMathCompat.h>
#include <ATen/c... | // !!! This is a file automatically generated by hipify!!!
#define TORCH_ASSERT_NO_OPERATORS
#define _USE_MATH_DEFINES
#include <ATen/native/Activation.h>
#include <cmath>
#include <thrust/tuple.h>
#include <ATen/AccumulateType.h>
#include <ATen/Dispatch.h>
#include <ATen/core/TensorBase.h>
#include <c10/core/Scal... |
#include "caffe2/operators/lengths_pad_op.h"
#include "caffe2/core/context_gpu.h"
namespace caffe2 {
REGISTER_CUDA_OPERATOR(LengthsPad, LengthsPadOp<CUDAContext>);
} // namespace caffe2
### | // !!! This is a file automatically generated by hipify!!!
#include "caffe2/operators/lengths_pad_op.h"
#include "caffe2/core/hip/context_gpu.h"
namespace caffe2 {
REGISTER_HIP_OPERATOR(LengthsPad, LengthsPadOp<HIPContext>);
} // namespace caffe2
### |
#include "caffe2/core/context_gpu.h"
#include "caffe2/operators/load_save_op.h"
namespace caffe2 {
template <>
void LoadOp<CUDAContext>::SetCurrentDevice(BlobProto* proto) {
if (proto->has_tensor()) {
proto->mutable_tensor()->clear_device_detail();
auto* device_detail = proto->mutable_tensor()->mutable_dev... | // !!! This is a file automatically generated by hipify!!!
#include "caffe2/core/hip/context_gpu.h"
#include "caffe2/operators/load_save_op.h"
namespace caffe2 {
template <>
void LoadOp<HIPContext>::SetCurrentDevice(BlobProto* proto) {
if (proto->has_tensor()) {
proto->mutable_tensor()->clear_device_detail();
... |
#include "caffe2/core/context_gpu.h"
#include "caffe2/operators/locally_connected_op.h"
#include "caffe2/operators/locally_connected_op_impl.h"
namespace caffe2 {
REGISTER_CUDA_OPERATOR(LC, LocallyConnectedOp<float, CUDAContext>);
REGISTER_CUDA_OPERATOR(
LCGradient,
LocallyConnectedGradientOp<float, CUDACont... | // !!! This is a file automatically generated by hipify!!!
#include "caffe2/core/hip/context_gpu.h"
#include "caffe2/operators/locally_connected_op.h"
#include "caffe2/operators/locally_connected_op_impl.h"
namespace caffe2 {
REGISTER_HIP_OPERATOR(LC, LocallyConnectedOp<float, HIPContext>);
REGISTER_HIP_OPERATOR(
... |
#include "caffe2/operators/log1p_op.h"
#include <algorithm>
#include <functional>
#include "caffe2/core/context_gpu.h"
namespace caffe2 {
namespace {
template <typename T>
__global__ void
Log1pGradientCUDAKernel(const int N, const T* dY, const T* X, T* dX) {
CUDA_1D_KERNEL_LOOP(i, N) {
#if __CUDA_ARCH__ >= 350
... | // !!! This is a file automatically generated by hipify!!!
#include "hip/hip_runtime.h"
#include "caffe2/operators/log1p_op.h"
#include <algorithm>
#include <functional>
#include "caffe2/core/hip/context_gpu.h"
namespace caffe2 {
namespace {
template <typename T>
__global__ void
Log1pGradientHIPKernel(const int N... |
#include "caffe2/operators/logit_op.h"
#include "caffe2/core/context_gpu.h"
namespace caffe2 {
namespace {
template <typename T>
__global__ void LogitKernel(const int N, const T* X, const float eps, T* Y) {
CUDA_1D_KERNEL_LOOP(i, N) {
Y[i] = fminf(X[i], (T(1) - eps));
Y[i] = fmaxf(Y[i], eps);
Y[i] = ... | // !!! This is a file automatically generated by hipify!!!
#include "hip/hip_runtime.h"
#include "caffe2/operators/logit_op.h"
#include "caffe2/core/hip/context_gpu.h"
namespace caffe2 {
namespace {
template <typename T>
__global__ void LogitKernel(const int N, const T* X, const float eps, T* Y) {
HIP_1D_KERNEL_... |
#include "caffe2/operators/log_op.h"
#include "caffe2/core/context_gpu.h"
namespace caffe2 {
REGISTER_CUDA_OPERATOR(
Log,
UnaryElementwiseOp<
TensorTypes<float>,
CUDAContext,
LogFunctor<CUDAContext>>);
} // namespace caffe2
### | // !!! This is a file automatically generated by hipify!!!
#include "caffe2/operators/log_op.h"
#include "caffe2/core/hip/context_gpu.h"
namespace caffe2 {
REGISTER_HIP_OPERATOR(
Log,
UnaryElementwiseOp<
TensorTypes<float>,
HIPContext,
LogFunctor<HIPContext>>);
} // namespace caffe2... |
#include "caffe2/core/context_gpu.h"
#include "caffe2/operators/loss_op.h"
namespace caffe2 {
REGISTER_CUDA_OPERATOR(AveragedLoss, AveragedLoss<float, CUDAContext>);
REGISTER_CUDA_OPERATOR(
AveragedLossGradient,
AveragedLossGradient<float, CUDAContext>);
} // namespace caffe2
### | // !!! This is a file automatically generated by hipify!!!
#include "caffe2/core/hip/context_gpu.h"
#include "caffe2/operators/loss_op.h"
namespace caffe2 {
REGISTER_HIP_OPERATOR(AveragedLoss, AveragedLoss<float, HIPContext>);
REGISTER_HIP_OPERATOR(
AveragedLossGradient,
AveragedLossGradient<float, HIPContext... |
#include "caffe2/core/context_gpu.h"
#include "caffe2/operators/lpnorm_op.h"
#include "caffe2/operators/operator_fallback_gpu.h"
namespace caffe2 {
REGISTER_CUDA_OPERATOR(LpNorm, GPUFallbackOp);
REGISTER_CUDA_OPERATOR(LpNormGradient, GPUFallbackOp);
} // namespace caffe2
### | // !!! This is a file automatically generated by hipify!!!
#include "caffe2/core/hip/context_gpu.h"
#include "caffe2/operators/lpnorm_op.h"
#include "caffe2/operators/hip/operator_fallback_gpu.h"
namespace caffe2 {
REGISTER_HIP_OPERATOR(LpNorm, GPUFallbackOp);
REGISTER_HIP_OPERATOR(LpNormGradient, GPUFallbackOp);
}... |
#include "caffe2/operators/matmul_op.h"
#include "caffe2/core/context_gpu.h"
namespace caffe2 {
REGISTER_CUDA_OPERATOR(MatMul, MatMulOp<float, CUDAContext>);
}
### | // !!! This is a file automatically generated by hipify!!!
#include "caffe2/operators/matmul_op.h"
#include "caffe2/core/hip/context_gpu.h"
namespace caffe2 {
REGISTER_HIP_OPERATOR(MatMul, MatMulOp<float, HIPContext>);
}
### |
#pragma once
#include <cfloat>
#include "caffe2/core/context.h"
#include "caffe2/core/context_gpu.h"
#include "caffe2/core/logging.h"
#include "caffe2/core/operator.h"
#include "caffe2/operators/conv_pool_op_base.h"
#include "caffe2/operators/pool_op.h"
#include "caffe2/utils/math.h"
namespace caffe2 {
class MaxPoo... | // !!! This is a file automatically generated by hipify!!!
#pragma once
#include <cfloat>
#include "caffe2/core/context.h"
#include "caffe2/core/hip/context_gpu.h"
#include "caffe2/core/logging.h"
#include "caffe2/core/operator.h"
#include "caffe2/operators/conv_pool_op_base.h"
#include "caffe2/operators/pool_op.h"
#... |
#define TORCH_ASSERT_NO_OPERATORS
#define _USE_MATH_DEFINES
#include <ATen/native/Activation.h>
#include <cmath>
#include <thrust/tuple.h>
#include <ATen/AccumulateType.h>
#include <ATen/Dispatch.h>
#include <ATen/core/TensorBase.h>
#include <c10/core/Scalar.h>
#include <c10/cuda/CUDAMathCompat.h>
#include <ATen/c... | // !!! This is a file automatically generated by hipify!!!
#define TORCH_ASSERT_NO_OPERATORS
#define _USE_MATH_DEFINES
#include <ATen/native/Activation.h>
#include <cmath>
#include <thrust/tuple.h>
#include <ATen/AccumulateType.h>
#include <ATen/Dispatch.h>
#include <ATen/core/TensorBase.h>
#include <c10/core/Scal... |
#include "caffe2/core/context_gpu.h"
#include "caffe2/operators/mean_op.h"
namespace caffe2 {
REGISTER_CUDA_OPERATOR(Mean, MeanOp<CUDAContext>);
REGISTER_CUDA_OPERATOR(MeanGradient, MeanGradientOp<CUDAContext>);
} // namespace caffe2
### | // !!! This is a file automatically generated by hipify!!!
#include "caffe2/core/hip/context_gpu.h"
#include "caffe2/operators/mean_op.h"
namespace caffe2 {
REGISTER_HIP_OPERATOR(Mean, MeanOp<HIPContext>);
REGISTER_HIP_OPERATOR(MeanGradient, MeanGradientOp<HIPContext>);
} // namespace caffe2
### |
#include "caffe2/core/context_gpu.h"
#include "caffe2/core/operator.h"
namespace caffe2 {
namespace {
class GetGPUMemoryUsageOp final : public Operator<CUDAContext> {
public:
template<class... Args> explicit GetGPUMemoryUsageOp(Args&&... args)
: Operator<CUDAContext>(std::forward<Args>(args)...) {}
~GetGP... | // !!! This is a file automatically generated by hipify!!!
#include "caffe2/core/hip/context_gpu.h"
#include "caffe2/core/operator.h"
namespace caffe2 {
namespace {
class GetGPUMemoryUsageOp final : public Operator<HIPContext> {
public:
template<class... Args> explicit GetGPUMemoryUsageOp(Args&&... args)
: ... |
#include "caffe2/operators/minmax_ops.h"
#include "caffe2/core/context_gpu.h"
#include "caffe2/utils/math.h"
namespace caffe2 {
namespace {
template <typename T>
__global__ void SelectGradientCUDAKernel(
const int N,
const T* dY,
const T* X,
const T* Y,
T* dX) {
const int i = blockIdx.x * CAF... | // !!! This is a file automatically generated by hipify!!!
#include "hip/hip_runtime.h"
#include "caffe2/operators/minmax_ops.h"
#include "caffe2/core/hip/context_gpu.h"
#include "caffe2/utils/math.h"
namespace caffe2 {
namespace {
template <typename T>
__global__ void SelectGradientHIPKernel(
const int N,
... |
#include "caffe2/operators/mod_op.h"
#include "caffe2/core/context_gpu.h"
namespace caffe2 {
namespace {
template <typename T>
__global__ void ModOpSimpleKernel(const int N, const int64_t divisor_,
const T* data_ptr, T* output_ptr) {
CUDA_1D_KERNEL_LOOP(i, N) {
output_ptr[i] = dat... | // !!! This is a file automatically generated by hipify!!!
#include "hip/hip_runtime.h"
#include "caffe2/operators/mod_op.h"
#include "caffe2/core/hip/context_gpu.h"
namespace caffe2 {
namespace {
template <typename T>
__global__ void ModOpSimpleKernel(const int N, const int64_t divisor_,
... |
#include "caffe2/core/context_gpu.h"
#include "caffe2/operators/multi_class_accuracy_op.h"
#include "caffe2/utils/GpuAtomics.cuh"
#include "caffe2/utils/math.h"
namespace caffe2 {
namespace {
__global__ void MultiClassAccuracyKernel(const int N, const int D, const float* Xdata,
const int* labeldata, float* accur... | // !!! This is a file automatically generated by hipify!!!
#include "hip/hip_runtime.h"
#include "caffe2/core/hip/context_gpu.h"
#include "caffe2/operators/multi_class_accuracy_op.h"
#include "caffe2/utils/hip/GpuAtomics.cuh"
#include "caffe2/utils/math.h"
namespace caffe2 {
namespace {
__global__ void MultiClassAcc... |
#include "caffe2/core/context_gpu.h"
#include "caffe2/operators/negate_gradient_op.h"
namespace caffe2 {
REGISTER_CUDA_OPERATOR(NegateGradient, NegateGradientOp<CUDAContext>)
} // namespace caffe2
### | // !!! This is a file automatically generated by hipify!!!
#include "caffe2/core/hip/context_gpu.h"
#include "caffe2/operators/negate_gradient_op.h"
namespace caffe2 {
REGISTER_HIP_OPERATOR(NegateGradient, NegateGradientOp<HIPContext>)
} // namespace caffe2
### |
#include "caffe2/operators/negative_op.h"
#include "caffe2/core/context_gpu.h"
namespace caffe2 {
REGISTER_CUDA_OPERATOR(
Negative,
UnaryElementwiseOp<
NumericTypes,
CUDAContext,
NegativeFunctor<CUDAContext>>);
} // namespace caffe2
### | // !!! This is a file automatically generated by hipify!!!
#include "caffe2/operators/negative_op.h"
#include "caffe2/core/hip/context_gpu.h"
namespace caffe2 {
REGISTER_HIP_OPERATOR(
Negative,
UnaryElementwiseOp<
NumericTypes,
HIPContext,
NegativeFunctor<HIPContext>>);
} // namespa... |
#include <cub/block/block_reduce.cuh>
#include "caffe2/core/context_gpu.h"
#include "caffe2/operators/one_hot_ops.h"
#include "caffe2/utils/cub_namespace.cuh"
namespace caffe2 {
__global__ void OneHotOpKernel(
const int64_t batch_size,
const int64_t index_size,
const int64_t* indices,
float* output)... | // !!! This is a file automatically generated by hipify!!!
#include "hip/hip_runtime.h"
#include <hipcub/hipcub.hpp>
#include "caffe2/core/hip/context_gpu.h"
#include "caffe2/operators/one_hot_ops.h"
#include "caffe2/utils/cub_namespace.cuh"
namespace caffe2 {
__global__ void OneHotOpKernel(
const int64_t batch... |
#ifndef CAFFE2_OPERATORS_OPERATOR_FALLBACK_H_
#define CAFFE2_OPERATORS_OPERATOR_FALLBACK_H_
#include "caffe2/core/common.h"
#include "caffe2/core/context.h"
#include "caffe2/core/context_gpu.h"
#include "caffe2/core/operator.h"
#include "caffe2/proto/caffe2_pb.h"
namespace caffe2 {
template <typename SkipOutputCopy>
... |
#ifndef CAFFE2_OPERATORS_OPERATOR_FALLBACK_H_
#define CAFFE2_OPERATORS_OPERATOR_FALLBACK_H_
#include "caffe2/core/common.h"
#include "caffe2/core/context.h"
#include "caffe2/core/hip/context_gpu.h"
#include "caffe2/core/operator.h"
#include "caffe2/proto/caffe2_pb.h"
namespace caffe2 {
template <typename SkipOutputC... |
#include <iostream>
#include "caffe2/core/operator.h"
#include "caffe2/operators/operator_fallback_gpu.h"
#include <gtest/gtest.h>
namespace caffe2 {
class IncrementByOneOp final : public Operator<CPUContext> {
public:
template <class... Args>
explicit IncrementByOneOp(Args&&... args)
: Operator<CPUContext>(std:... |
#include <iostream>
#include "caffe2/core/operator.h"
#include "caffe2/operators/hip/operator_fallback_gpu.h"
#include <gtest/gtest.h>
namespace caffe2 {
class IncrementByOneOp final : public Operator<CPUContext> {
public:
template <class... Args>
explicit IncrementByOneOp(Args&&... args)
: Operator<CPUContext>... |
#define TORCH_ASSERT_NO_OPERATORS
#define _USE_MATH_DEFINES
#include <ATen/native/Activation.h>
#include <cmath>
#include <thrust/tuple.h>
#include <ATen/AccumulateType.h>
#include <ATen/Dispatch.h>
#include <ATen/core/TensorBase.h>
#include <c10/core/Scalar.h>
#include <c10/cuda/CUDAMathCompat.h>
#include <ATen/c... | // !!! This is a file automatically generated by hipify!!!
#define TORCH_ASSERT_NO_OPERATORS
#define _USE_MATH_DEFINES
#include <ATen/native/Activation.h>
#include <cmath>
#include <thrust/tuple.h>
#include <ATen/AccumulateType.h>
#include <ATen/Dispatch.h>
#include <ATen/core/TensorBase.h>
#include <c10/core/Scal... |
#include "caffe2/operators/order_switch_ops.h"
#include "caffe2/core/context_gpu.h"
namespace caffe2 {
REGISTER_CUDA_OPERATOR(NHWC2NCHW, NHWC2NCHWOp<float, CUDAContext>);
REGISTER_CUDA_OPERATOR(NCHW2NHWC, NCHW2NHWCOp<float, CUDAContext>);
} // namespace caffe2
### | // !!! This is a file automatically generated by hipify!!!
#include "caffe2/operators/order_switch_ops.h"
#include "caffe2/core/hip/context_gpu.h"
namespace caffe2 {
REGISTER_HIP_OPERATOR(NHWC2NCHW, NHWC2NCHWOp<float, HIPContext>);
REGISTER_HIP_OPERATOR(NCHW2NHWC, NCHW2NHWCOp<float, HIPContext>);
} // namespace ca... |
#include "caffe2/core/context_gpu.h"
#include "caffe2/operators/perplexity_op.h"
#include "caffe2/utils/math.h"
#include <thrust/device_vector.h>
#include <thrust/transform_reduce.h>
#include <thrust/system/cuda/execution_policy.h>
namespace caffe2 {
struct perplexity_function
{
perplexity_function(float p) : pow(... | // !!! This is a file automatically generated by hipify!!!
#include "caffe2/core/hip/context_gpu.h"
#include "caffe2/operators/perplexity_op.h"
#include "caffe2/utils/math.h"
#include <thrust/device_vector.h>
#include <thrust/transform_reduce.h>
#include <thrust/system/hip/execution_policy.h>
namespace caffe2 {
stru... |
#include "caffe2/core/context_gpu.h"
#include "caffe2/operators/prepend_dim_op.h"
namespace caffe2 {
REGISTER_CUDA_OPERATOR(PrependDim, PrependDimOp<CUDAContext>);
REGISTER_CUDA_OPERATOR(MergeDim, MergeDimOp<CUDAContext>);
} // namespace caffe2
### | // !!! This is a file automatically generated by hipify!!!
#include "caffe2/core/hip/context_gpu.h"
#include "caffe2/operators/prepend_dim_op.h"
namespace caffe2 {
REGISTER_HIP_OPERATOR(PrependDim, PrependDimOp<HIPContext>);
REGISTER_HIP_OPERATOR(MergeDim, MergeDimOp<HIPContext>);
} // namespace caffe2
### |
#include "caffe2/operators/reciprocal_op.h"
#include <algorithm>
#include <functional>
#include "caffe2/core/context_gpu.h"
namespace caffe2 {
namespace {
template <typename T>
__global__ void
ReciprocalGradientCUDAKernel(const int N, const T* dY, const T* Y, T* dX) {
CUDA_1D_KERNEL_LOOP(i, N) {
#if __CUDA_ARCH... | // !!! This is a file automatically generated by hipify!!!
#include "hip/hip_runtime.h"
#include "caffe2/operators/reciprocal_op.h"
#include <algorithm>
#include <functional>
#include "caffe2/core/hip/context_gpu.h"
namespace caffe2 {
namespace {
template <typename T>
__global__ void
ReciprocalGradientHIPKernel(c... |
#include "caffe2/operators/relu_n_op.h"
#include <algorithm>
#include <functional>
#include "caffe2/core/context_gpu.h"
namespace caffe2 {
namespace {
template <typename T>
__global__ void
ReluNCUDAKernel(const int N, const T threshold, const T* X, T* Y) {
CUDA_1D_KERNEL_LOOP(i, N) {
#if __CUDA_ARCH__ >= 350
... | // !!! This is a file automatically generated by hipify!!!
#include "hip/hip_runtime.h"
#include "caffe2/operators/relu_n_op.h"
#include <algorithm>
#include <functional>
#include "caffe2/core/hip/context_gpu.h"
namespace caffe2 {
namespace {
template <typename T>
__global__ void
ReluNHIPKernel(const int N, const... |
#include "caffe2/core/context_gpu.h"
#include "caffe2/operators/replace_nan_op.h"
namespace caffe2 {
namespace {
template <typename T>
__global__ void
replace_nan_kernel(const T value, const int64_t size, const T* X, T* Y) {
CUDA_1D_KERNEL_LOOP(i, size) {
if (isnan(X[i])) {
Y[i] = value;
} else {
... | // !!! This is a file automatically generated by hipify!!!
#include "hip/hip_runtime.h"
#include "caffe2/core/hip/context_gpu.h"
#include "caffe2/operators/replace_nan_op.h"
namespace caffe2 {
namespace {
template <typename T>
__global__ void
replace_nan_kernel(const T value, const int64_t size, const T* X, T* Y) {
... |
#include "caffe2/core/context_gpu.h"
#include "caffe2/operators/reshape_op.h"
#include "caffe2/utils/math.h"
namespace caffe2 {
REGISTER_CUDA_OPERATOR(Reshape, ReshapeOp<float, CUDAContext>);
} // namespace caffe2
### | // !!! This is a file automatically generated by hipify!!!
#include "caffe2/core/hip/context_gpu.h"
#include "caffe2/operators/reshape_op.h"
#include "caffe2/utils/math.h"
namespace caffe2 {
REGISTER_HIP_OPERATOR(Reshape, ReshapeOp<float, HIPContext>);
} // namespace caffe2
### |
#include <iostream>
#include <gtest/gtest.h>
#include "caffe2/core/context.h"
#include "caffe2/core/context_gpu.h"
#include "caffe2/core/flags.h"
#include "caffe2/operators/reshape_op.h"
#include "caffe2/utils/math.h"
C10_DECLARE_string(caffe_test_root);
namespace caffe2 {
static void AddConstInput(
const vect... | // !!! This is a file automatically generated by hipify!!!
#include <iostream>
#include <gtest/gtest.h>
#include "caffe2/core/context.h"
#include "caffe2/core/hip/context_gpu.h"
#include "caffe2/core/flags.h"
#include "caffe2/operators/reshape_op.h"
#include "caffe2/utils/math.h"
C10_DECLARE_string(caffe_test_root);... |
#include "caffe2/core/context_gpu.h"
#include "caffe2/operators/reverse_packed_segs_op.h"
namespace caffe2 {
namespace {
template <typename T, typename LengthType>
__global__
void ReversePackedSegments_kernel(
size_t max_length,
size_t batch_size,
size_t block_size,
const LengthType* lengths... | // !!! This is a file automatically generated by hipify!!!
#include "hip/hip_runtime.h"
#include "caffe2/core/hip/context_gpu.h"
#include "caffe2/operators/reverse_packed_segs_op.h"
namespace caffe2 {
namespace {
template <typename T, typename LengthType>
__global__
void ReversePackedSegments_kernel(
size_t m... |
#include "caffe2/operators/rsqrt_op.h"
#include <algorithm>
#include <functional>
#include "caffe2/core/context_gpu.h"
#include "caffe2/utils/math.h"
namespace caffe2 {
namespace {
template <typename T>
__global__ void
RsqrtGradientCUDAKernel(const int size, const T* dY, const T* Y, T* dX) {
CUDA_1D_KERNEL_LOOP... | // !!! This is a file automatically generated by hipify!!!
#include "hip/hip_runtime.h"
#include "caffe2/operators/rsqrt_op.h"
#include <algorithm>
#include <functional>
#include "caffe2/core/hip/context_gpu.h"
#include "caffe2/utils/math.h"
namespace caffe2 {
namespace {
template <typename T>
__global__ void
Rsq... |
#define TORCH_ASSERT_NO_OPERATORS
#define _USE_MATH_DEFINES
#include <ATen/native/Activation.h>
#include <cmath>
#include <thrust/tuple.h>
#include <ATen/AccumulateType.h>
#include <ATen/Dispatch.h>
#include <ATen/core/TensorBase.h>
#include <c10/core/Scalar.h>
#include <c10/cuda/CUDAMathCompat.h>
#include <ATen/c... | // !!! This is a file automatically generated by hipify!!!
#define TORCH_ASSERT_NO_OPERATORS
#define _USE_MATH_DEFINES
#include <ATen/native/Activation.h>
#include <cmath>
#include <thrust/tuple.h>
#include <ATen/AccumulateType.h>
#include <ATen/Dispatch.h>
#include <ATen/core/TensorBase.h>
#include <c10/core/Scal... |
#include "caffe2/core/context_gpu.h"
#include "caffe2/operators/scale_op.h"
namespace caffe2 {
template <>
bool ScaleOp<CUDAContext>::RunOnDevice() {
return DispatchHelper<TensorTypes<at::Half, float>>::call(this, Input(0));
}
REGISTER_CUDA_OPERATOR(Scale, ScaleOp<CUDAContext>);
} // namespace caffe2
### | // !!! This is a file automatically generated by hipify!!!
#include "caffe2/core/hip/context_gpu.h"
#include "caffe2/operators/scale_op.h"
namespace caffe2 {
template <>
bool ScaleOp<HIPContext>::RunOnDevice() {
return DispatchHelper<TensorTypes<at::Half, float>>::call(this, Input(0));
}
REGISTER_HIP_OPERATOR(Sca... |
#include "caffe2/core/common_gpu.h"
#include "caffe2/core/context_gpu.h"
#include "caffe2/operators/selu_op.h"
namespace caffe2 {
namespace {
template <typename T>
__global__ void SeluKernel(const int N, const T* X, T* Y, T alpha_, T lambda_) {
CUDA_1D_KERNEL_LOOP(i, N) {
Y[i] = lambda_ * (X[i] > 0 ? X[i] : alp... | // !!! This is a file automatically generated by hipify!!!
#include "hip/hip_runtime.h"
#include "caffe2/core/hip/common_gpu.h"
#include "caffe2/core/hip/context_gpu.h"
#include "caffe2/operators/selu_op.h"
namespace caffe2 {
namespace {
template <typename T>
__global__ void SeluKernel(const int N, const T* X, T* Y, ... |
#include "caffe2/core/context_gpu.h"
#include "caffe2/operators/shape_op.h"
namespace caffe2 {
REGISTER_CUDA_OPERATOR(Shape, ShapeOp<CUDAContext>);
}
### | // !!! This is a file automatically generated by hipify!!!
#include "caffe2/core/hip/context_gpu.h"
#include "caffe2/operators/shape_op.h"
namespace caffe2 {
REGISTER_HIP_OPERATOR(Shape, ShapeOp<HIPContext>);
}
### |
#include "caffe2/operators/sigmoid_op.h"
#include <algorithm>
#include <functional>
#include "caffe2/core/context_gpu.h"
namespace caffe2 {
namespace {
template <typename T>
__global__ void SigmoidCUDAKernel(const int N, const T* X, T* Y);
template <>
__global__ void
SigmoidCUDAKernel<float>(const int N, const f... | // !!! This is a file automatically generated by hipify!!!
#include "hip/hip_runtime.h"
#include "caffe2/operators/sigmoid_op.h"
#include <algorithm>
#include <functional>
#include "caffe2/core/hip/context_gpu.h"
namespace caffe2 {
namespace {
template <typename T>
__global__ void SigmoidHIPKernel(const int N, co... |
#include "caffe2/operators/sinh_op.h"
#include <algorithm>
#include <functional>
#include "caffe2/core/context_gpu.h"
namespace caffe2 {
namespace {
__global__ void SinhGradientCUDAKernel(
const int N,
const float* dY,
const float* X,
float* dX) {
CUDA_1D_KERNEL_LOOP(i, N) {
#if __CUDA_ARCH__ >=... | // !!! This is a file automatically generated by hipify!!!
#include "hip/hip_runtime.h"
#include "caffe2/operators/sinh_op.h"
#include <algorithm>
#include <functional>
#include "caffe2/core/hip/context_gpu.h"
namespace caffe2 {
namespace {
__global__ void SinhGradientHIPKernel(
const int N,
const float* ... |
#include "caffe2/operators/sin_op.h"
#include <algorithm>
#include <functional>
#include "caffe2/core/context_gpu.h"
namespace caffe2 {
namespace {
template <typename T>
__global__ void
SinGradientCUDAKernel(const int N, const T* dY, const T* X, T* dX) {
CUDA_1D_KERNEL_LOOP(i, N) {
#if __CUDA_ARCH__ >= 350
... | // !!! This is a file automatically generated by hipify!!!
#include "hip/hip_runtime.h"
#include "caffe2/operators/sin_op.h"
#include <algorithm>
#include <functional>
#include "caffe2/core/hip/context_gpu.h"
namespace caffe2 {
namespace {
template <typename T>
__global__ void
SinGradientHIPKernel(const int N, co... |
#include "caffe2/core/context_gpu.h"
#include "caffe2/operators/softplus_op.h"
namespace caffe2 {
namespace {
template <typename T>
__global__ void SoftplusKernel(const int N, const T* X, T* Y) {
CUDA_1D_KERNEL_LOOP(i, N) {
Y[i] = log(exp(X[i]) + 1.0f);
}
}
template <typename T>
__global__ void
SoftplusGradi... | // !!! This is a file automatically generated by hipify!!!
#include "hip/hip_runtime.h"
#include "caffe2/core/hip/context_gpu.h"
#include "caffe2/operators/softplus_op.h"
namespace caffe2 {
namespace {
template <typename T>
__global__ void SoftplusKernel(const int N, const T* X, T* Y) {
HIP_1D_KERNEL_LOOP(i, N) {
... |
#include "caffe2/operators/softsign_op.h"
#include <algorithm>
#include <functional>
#include "caffe2/core/context_gpu.h"
namespace caffe2 {
namespace {
using c10::cuda::compat::abs;
template <typename T>
inline __host__ __device__ T SquareCUDA(const T x) {
return x * x;
}
template <typename T>
__global__ voi... | // !!! This is a file automatically generated by hipify!!!
#include "hip/hip_runtime.h"
#include "caffe2/operators/softsign_op.h"
#include <algorithm>
#include <functional>
#include "caffe2/core/hip/context_gpu.h"
namespace caffe2 {
namespace {
using c10::hip::compat::abs;
template <typename T>
inline __host__ _... |
#include "caffe2/core/context_gpu.h"
#include "caffe2/operators/operator_fallback_gpu.h"
#include "caffe2/operators/sparse_lp_regularizer_op.h"
namespace caffe2 {
REGISTER_CUDA_OPERATOR(SparseLpRegularizer, GPUFallbackOp);
}
### | // !!! This is a file automatically generated by hipify!!!
#include "caffe2/core/hip/context_gpu.h"
#include "caffe2/operators/hip/operator_fallback_gpu.h"
#include "caffe2/operators/sparse_lp_regularizer_op.h"
namespace caffe2 {
REGISTER_HIP_OPERATOR(SparseLpRegularizer, GPUFallbackOp);
}
### |
#include "caffe2/core/context_gpu.h"
#include "caffe2/operators/operator_fallback_gpu.h"
#include "caffe2/operators/sparse_normalize_op.h"
namespace caffe2 {
REGISTER_CUDA_OPERATOR(
SparseNormalize,
GPUFallbackOp);
}
### | // !!! This is a file automatically generated by hipify!!!
#include "caffe2/core/hip/context_gpu.h"
#include "caffe2/operators/hip/operator_fallback_gpu.h"
#include "caffe2/operators/sparse_normalize_op.h"
namespace caffe2 {
REGISTER_HIP_OPERATOR(
SparseNormalize,
GPUFallbackOp);
}
### |
#define TORCH_ASSERT_NO_OPERATORS
#define _USE_MATH_DEFINES
#include <ATen/native/Activation.h>
#include <cmath>
#include <thrust/tuple.h>
#include <ATen/AccumulateType.h>
#include <ATen/Dispatch.h>
#include <ATen/core/TensorBase.h>
#include <c10/core/Scalar.h>
#include <c10/cuda/CUDAMathCompat.h>
#include <ATen/c... | // !!! This is a file automatically generated by hipify!!!
#define TORCH_ASSERT_NO_OPERATORS
#define _USE_MATH_DEFINES
#include <ATen/native/Activation.h>
#include <cmath>
#include <thrust/tuple.h>
#include <ATen/AccumulateType.h>
#include <ATen/Dispatch.h>
#include <ATen/core/TensorBase.h>
#include <c10/core/Scal... |
#include "caffe2/operators/sparse_to_dense_op.h"
#include "caffe2/core/common_gpu.h"
#include "caffe2/core/context_gpu.h"
#include "caffe2/utils/GpuAtomics.cuh"
namespace caffe2 {
template <typename TInd, typename TData>
__global__ void SparseToDenseKernel(
size_t N, int64_t block_nitems, const TInd* indice... | // !!! This is a file automatically generated by hipify!!!
#include "hip/hip_runtime.h"
#include "caffe2/operators/sparse_to_dense_op.h"
#include "caffe2/core/hip/common_gpu.h"
#include "caffe2/core/hip/context_gpu.h"
#include "caffe2/utils/hip/GpuAtomics.cuh"
namespace caffe2 {
template <typename TInd, typename ... |
#include "caffe2/operators/spatial_batch_norm_op.h"
#include "caffe2/operators/spatial_batch_norm_op_impl.cuh"
namespace caffe2 {
REGISTER_CUDA_OPERATOR(SpatialBN, SpatialBNOp<CUDAContext>);
REGISTER_CUDA_OPERATOR(SpatialBNGradient, SpatialBNGradientOp<CUDAContext>);
} // namespace caffe2
### | // !!! This is a file automatically generated by hipify!!!
#include "caffe2/operators/spatial_batch_norm_op.h"
#include "caffe2/operators/hip/spatial_batch_norm_op_impl.cuh"
namespace caffe2 {
REGISTER_HIP_OPERATOR(SpatialBN, SpatialBNOp<HIPContext>);
REGISTER_HIP_OPERATOR(SpatialBNGradient, SpatialBNGradientOp<HIP... |
#include "caffe2/operators/sqrt_op.h"
#include "caffe2/core/context_gpu.h"
namespace caffe2 {
REGISTER_CUDA_OPERATOR(
Sqrt,
UnaryElementwiseOp<
TensorTypes<float>,
CUDAContext,
SqrtFunctor<CUDAContext>>);
} // namespace caffe2
### | // !!! This is a file automatically generated by hipify!!!
#include "caffe2/operators/sqrt_op.h"
#include "caffe2/core/hip/context_gpu.h"
namespace caffe2 {
REGISTER_HIP_OPERATOR(
Sqrt,
UnaryElementwiseOp<
TensorTypes<float>,
HIPContext,
SqrtFunctor<HIPContext>>);
} // namespace caf... |
#include "caffe2/operators/sqr_op.h"
#include "caffe2/core/context_gpu.h"
namespace caffe2 {
REGISTER_CUDA_OPERATOR(
Sqr,
UnaryElementwiseOp<
TensorTypes<float>,
CUDAContext,
SqrFunctor<CUDAContext>>);
} // namespace caffe2
### | // !!! This is a file automatically generated by hipify!!!
#include "caffe2/operators/sqr_op.h"
#include "caffe2/core/hip/context_gpu.h"
namespace caffe2 {
REGISTER_HIP_OPERATOR(
Sqr,
UnaryElementwiseOp<
TensorTypes<float>,
HIPContext,
SqrFunctor<HIPContext>>);
} // namespace caffe2... |
#include "caffe2/core/context_gpu.h"
#include "caffe2/operators/stop_gradient.h"
namespace caffe2 {
REGISTER_CUDA_OPERATOR(StopGradient, StopGradientOp<CUDAContext>);
} // namespace caffe2
### | // !!! This is a file automatically generated by hipify!!!
#include "caffe2/core/hip/context_gpu.h"
#include "caffe2/operators/stop_gradient.h"
namespace caffe2 {
REGISTER_HIP_OPERATOR(StopGradient, StopGradientOp<HIPContext>);
} // namespace caffe2
### |
/**
* Copyright (c) 2016-present, Facebook, Inc.
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable... | // !!! This is a file automatically generated by hipify!!!
#include "hip/hip_runtime.h"
/**
* Copyright (c) 2016-present, Facebook, Inc.
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
... |
#include <cuda.h>
#include <thrust/device_vector.h>
#include <thrust/transform_reduce.h>
#include <thrust/system/cuda/execution_policy.h>
#include "caffe2/operators/summarize_op.h"
#include "caffe2/core/context_gpu.h"
namespace caffe2 {
namespace {
template <typename T>
struct SummaryStatsData {
T n;
T min;
T max... |
#include <hip/hip_runtime.h>
#include <thrust/device_vector.h>
#include <thrust/transform_reduce.h>
#include <thrust/system/hip/execution_policy.h>
#include "caffe2/operators/summarize_op.h"
#include "caffe2/core/hip/context_gpu.h"
namespace caffe2 {
namespace {
template <typename T>
struct SummaryStatsData {
T n;... |
#include "caffe2/operators/swish_op.h"
#include "caffe2/core/context_gpu.h"
namespace caffe2 {
namespace {
template <typename T>
__global__ void SwishCUDAKernel(const int N, const T* X, T* Y) {
CUDA_1D_KERNEL_LOOP(i, N) {
#if __CUDA_ARCH__ >= 350
Y[i] = __ldg(X + i) / (T(1) + exp(-__ldg(X + i)));
#else
Y... |
#include "hip/hip_runtime.h"
#include "caffe2/operators/swish_op.h"
#include "caffe2/core/hip/context_gpu.h"
namespace caffe2 {
namespace {
template <typename T>
__global__ void SwishHIPKernel(const int N, const T* X, T* Y) {
HIP_1D_KERNEL_LOOP(i, N) {
#if __HIP_ARCH__ >= 350
Y[i] = __ldg(X + i) / (T(1) + exp(-__l... |
#include "caffe2/operators/tanh_op.h"
#include <algorithm>
#include <functional>
#include "caffe2/core/context_gpu.h"
namespace caffe2 {
namespace {
template <typename T>
__global__ void
TanhGradientCUDAKernel(const int N, const T* dY, const T* Y, T* dX) {
CUDA_1D_KERNEL_LOOP(i, N) {
#if __CUDA_ARCH__ >= 350
... | // !!! This is a file automatically generated by hipify!!!
#include "hip/hip_runtime.h"
#include "caffe2/operators/tanh_op.h"
#include <algorithm>
#include <functional>
#include "caffe2/core/hip/context_gpu.h"
namespace caffe2 {
namespace {
template <typename T>
__global__ void
TanhGradientHIPKernel(const int N, ... |
#include "caffe2/operators/tan_op.h"
#include <algorithm>
#include <functional>
#include "caffe2/core/context_gpu.h"
namespace caffe2 {
template <typename T>
inline __host__ __device__ T Square(const T& x) {
return x * x;
}
template <typename T>
__global__ void
TanGradientCUDAKernel(const int N, const T* dY, co... | // !!! This is a file automatically generated by hipify!!!
#include "hip/hip_runtime.h"
#include "caffe2/operators/tan_op.h"
#include <algorithm>
#include <functional>
#include "caffe2/core/hip/context_gpu.h"
namespace caffe2 {
template <typename T>
inline __host__ __device__ T Square(const T& x) {
return x * x;... |
#define TORCH_ASSERT_NO_OPERATORS
#define _USE_MATH_DEFINES
#include <ATen/native/Activation.h>
#include <cmath>
#include <thrust/tuple.h>
#include <ATen/AccumulateType.h>
#include <ATen/Dispatch.h>
#include <ATen/core/TensorBase.h>
#include <c10/core/Scalar.h>
#include <c10/cuda/CUDAMathCompat.h>
#include <ATen/c... | // !!! This is a file automatically generated by hipify!!!
#define TORCH_ASSERT_NO_OPERATORS
#define _USE_MATH_DEFINES
#include <ATen/native/Activation.h>
#include <cmath>
#include <thrust/tuple.h>
#include <ATen/AccumulateType.h>
#include <ATen/Dispatch.h>
#include <ATen/core/TensorBase.h>
#include <c10/core/Scal... |
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