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utils.h
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/
utils.h
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#include "paddle/phi/backends/cpu/cpu_context.h"
#include "paddle/phi/backends/gpu/gpu_context.h"
#include "paddle/phi/core/kernel_registry.h"
#include "paddle/phi/kernels/copy_kernel.h"
#include "paddle/phi/kernels/empty_kernel.h"
#define DEFINE_SPARSE_UNARY_KERNEL(dense_kernel_func) \
namespace phi { \
namespace sparse { \
\
template <typename T, typename Context> \
void SparseCoo##dense_kernel_func(const Context& dev_ctx, \
const SparseCooTensor& x, \
SparseCooTensor* out) { \
DenseTensor non_zero_indices = \
phi::EmptyLike<T, Context>(dev_ctx, x.non_zero_indices()); \
DenseTensor non_zero_elements = \
phi::EmptyLike<T, Context>(dev_ctx, x.non_zero_elements()); \
phi::Copy(dev_ctx, \
x.non_zero_indices(), \
dev_ctx.GetPlace(), \
false, \
&non_zero_indices); \
phi::dense_kernel_func<T, Context>( \
dev_ctx, x.non_zero_elements(), &non_zero_elements); \
out->SetMember(non_zero_indices, non_zero_elements, x.dims(), true); \
} \
\
template <typename T, typename Context> \
void SparseCsr##dense_kernel_func(const Context& dev_ctx, \
const SparseCsrTensor& x, \
SparseCsrTensor* out) { \
DenseTensor non_zero_crows = \
phi::EmptyLike<T, Context>(dev_ctx, x.non_zero_crows()); \
DenseTensor non_zero_cols = \
phi::EmptyLike<T, Context>(dev_ctx, x.non_zero_cols()); \
DenseTensor non_zero_elements = \
phi::EmptyLike<T, Context>(dev_ctx, x.non_zero_elements()); \
phi::Copy(dev_ctx, \
x.non_zero_crows(), \
dev_ctx.GetPlace(), \
false, \
&non_zero_crows); \
phi::Copy(dev_ctx, \
x.non_zero_cols(), \
dev_ctx.GetPlace(), \
false, \
&non_zero_cols); \
phi::dense_kernel_func<T, Context>( \
dev_ctx, x.non_zero_elements(), &non_zero_elements); \
out->SetMember( \
non_zero_crows, non_zero_cols, non_zero_elements, x.dims()); \
} \
} \
}
#define DEFINE_SPARSE_UNARY_GRAD_KERNEL(dense_kernel_func) \
namespace phi { \
namespace sparse { \
\
template <typename T, typename Context> \
void SparseCoo##dense_kernel_func(const Context& dev_ctx, \
const SparseCooTensor& x, \
const SparseCooTensor& out_grad, \
SparseCooTensor* x_grad) { \
DenseTensor non_zero_indices = \
phi::EmptyLike<T, Context>(dev_ctx, x.non_zero_indices()); \
DenseTensor non_zero_elements = \
phi::EmptyLike<T, Context>(dev_ctx, x.non_zero_elements()); \
phi::Copy(dev_ctx, \
x.non_zero_indices(), \
dev_ctx.GetPlace(), \
false, \
&non_zero_indices); \
phi::dense_kernel_func<T, Context>(dev_ctx, \
x.non_zero_elements(), \
out_grad.non_zero_elements(), \
&non_zero_elements); \
x_grad->SetMember(non_zero_indices, non_zero_elements, x.dims(), true); \
} \
\
template <typename T, typename Context> \
void SparseCsr##dense_kernel_func(const Context& dev_ctx, \
const SparseCsrTensor& x, \
const SparseCsrTensor& out_grad, \
SparseCsrTensor* out) { \
DenseTensor non_zero_crows = \
phi::EmptyLike<T, Context>(dev_ctx, x.non_zero_crows()); \
DenseTensor non_zero_cols = \
phi::EmptyLike<T, Context>(dev_ctx, x.non_zero_cols()); \
DenseTensor non_zero_elements = \
phi::EmptyLike<T, Context>(dev_ctx, x.non_zero_elements()); \
phi::Copy(dev_ctx, \
x.non_zero_crows(), \
dev_ctx.GetPlace(), \
false, \
&non_zero_crows); \
phi::Copy(dev_ctx, \
x.non_zero_cols(), \
dev_ctx.GetPlace(), \
false, \
&non_zero_cols); \
phi::dense_kernel_func<T, Context>(dev_ctx, \
x.non_zero_elements(), \
out_grad.non_zero_elements(), \
&non_zero_elements); \
out->SetMember( \
non_zero_crows, non_zero_cols, non_zero_elements, x.dims()); \
} \
} \
}
#define REGISTER_CPU_SPARSE_UNARY_KERNEL(kernel_name, dense_kernel_func) \
PD_REGISTER_KERNEL(sparse_coo_##kernel_name, \
CPU, \
ALL_LAYOUT, \
phi::sparse::SparseCoo##dense_kernel_func, \
float, \
double) { \
kernel->InputAt(0).SetDataLayout(phi::DataLayout::SPARSE_COO); \
} \
PD_REGISTER_KERNEL(sparse_csr_##kernel_name, \
CPU, \
ALL_LAYOUT, \
phi::sparse::SparseCsr##dense_kernel_func, \
float, \
double) { \
kernel->InputAt(0).SetDataLayout(phi::DataLayout::SPARSE_CSR); \
}
#if defined(PADDLE_WITH_CUDA) || defined(PADDLE_WITH_HIP)
#define REGISTER_GPU_SPARSE_UNARY_KERNEL(kernel_name, dense_kernel_func) \
PD_REGISTER_KERNEL(sparse_coo_##kernel_name, \
GPU, \
ALL_LAYOUT, \
phi::sparse::SparseCoo##dense_kernel_func, \
float, \
double, \
phi::dtype::float16) { \
kernel->InputAt(0).SetDataLayout(phi::DataLayout::SPARSE_COO); \
} \
\
PD_REGISTER_KERNEL(sparse_csr_##kernel_name, \
GPU, \
ALL_LAYOUT, \
phi::sparse::SparseCsr##dense_kernel_func, \
float, \
double, \
phi::dtype::float16) { \
kernel->InputAt(0).SetDataLayout(phi::DataLayout::SPARSE_CSR); \
}
#else
// This macro definition is empty when GPU is disabled
#define REGISTER_GPU_SPARSE_UNARY_KERNEL(sparse_kernel_name, dense_kernel_func)
#endif
#define REGISTER_SPARSE_UNARY_KERNEL(kernel_name, dense_kernel_func) \
REGISTER_CPU_SPARSE_UNARY_KERNEL(kernel_name, dense_kernel_func) \
REGISTER_GPU_SPARSE_UNARY_KERNEL(kernel_name, dense_kernel_func)
#define DEFINE_AND_REGISTER_SPARSE_UNARY_KERNEL(kernel_name, \
dense_kernel_func) \
DEFINE_SPARSE_UNARY_KERNEL(dense_kernel_func) \
REGISTER_SPARSE_UNARY_KERNEL(kernel_name, dense_kernel_func)
#define DEFINE_AND_REGISTER_SPARSE_UNARY_GRAD_KERNEL(kernel_name, \
dense_kernel_func) \
DEFINE_SPARSE_UNARY_GRAD_KERNEL(dense_kernel_func) \
REGISTER_SPARSE_UNARY_KERNEL(kernel_name, dense_kernel_func)