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CatKernel.cpp
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CatKernel.cpp
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#define TORCH_ASSERT_ONLY_METHOD_OPERATORS
#include <ATen/core/Tensor.h>
#include <ATen/Dispatch.h>
#include <ATen/native/cpu/CatKernel.h>
#include <ATen/cpu/vec/functional.h>
#include <ATen/cpu/vec/vec.h>
#include <c10/util/irange.h>
namespace at::native {
namespace {
struct InputMeta {
void* data_ptr;
int64_t inner_size;
InputMeta(const Tensor& t, int64_t dim, int64_t inner)
: data_ptr(t.data_ptr())
, inner_size(t.sizes()[dim] * inner) {}
};
template <typename scalar_t>
void cat_serial_kernel_impl(const Tensor& result, const MaterializedITensorListRef& tensors, int64_t dim) {
TORCH_INTERNAL_ASSERT_DEBUG_ONLY(
dim >= 0 && dim < result.dim(), "dim out of range in cat_serial_kernel_impl");
int64_t outer = result.numel() / (result.sizes()[dim] * result.strides()[dim]);
scalar_t* result_data = result.data_ptr<scalar_t>();
int64_t ninputs = static_cast<int64_t>(tensors.size());
std::vector<InputMeta> inputs;
inputs.reserve(ninputs);
for (const Tensor& tensor : tensors) {
inputs.emplace_back(tensor, dim, result.strides()[dim]);
}
using Vec = vec::Vectorized<scalar_t>;
scalar_t* result_ptr = result_data;
for (const auto i : c10::irange(outer)) {
for (const auto j : c10::irange(ninputs)) {
int64_t local_inner = inputs[j].inner_size;
scalar_t* input_ptr = (scalar_t*)(inputs[j].data_ptr) + i * local_inner;
int64_t d = 0;
for (; d < local_inner - (local_inner % Vec::size()); d += Vec::size()) {
Vec in_vec = Vec::loadu(input_ptr + d);
in_vec.store(result_ptr + d);
}
#if !defined(_MSC_VER) && !defined(COMPILING_FOR_MIN_SIZE)
# pragma unroll
#endif
for (; d < local_inner; d++) {
result_ptr[d] = input_ptr[d];
}
result_ptr += local_inner;
}
}
}
void cat_serial_kernel(const Tensor& result, const MaterializedITensorListRef& tensors, int64_t dim) {
AT_DISPATCH_FLOATING_TYPES_AND2(kBFloat16, kHalf, result.scalar_type(), "cat_serial_kernel", [&]() {
cat_serial_kernel_impl<scalar_t>(result, tensors, dim);
});
}
} // anonymous namespace
REGISTER_DISPATCH(cat_serial_stub, &cat_serial_kernel);
} // at::native