blob: f5235a8e1770b7d48f3c5b7dd15b33c8fe3064cb [file]
// Ternary and higher-order pointwise operations
#define TORCH_ASSERT_ONLY_METHOD_OPERATORS
#include <ATen/native/PointwiseOps.h>
#include <ATen/core/Tensor.h>
#include <ATen/TensorMeta.h>
#ifndef AT_PER_OPERATOR_HEADERS
#include <ATen/NativeFunctions.h>
#else
#include <ATen/ops/addcdiv_native.h>
#include <ATen/ops/addcmul_native.h>
#endif
namespace at::meta {
TORCH_META_FUNC(addcmul)
(const Tensor& self,
const Tensor& tensor1,
const Tensor& tensor2,
const Scalar& value) {
build_ternary_op(maybe_get_output(), self, tensor1, tensor2);
}
TORCH_META_FUNC(addcdiv)
(const Tensor& self,
const Tensor& tensor1,
const Tensor& tensor2,
const Scalar& value) {
if (isIntegralType(tensor1.scalar_type(), /*includeBool=*/true) &&
isIntegralType(tensor2.scalar_type(), /*includeBool=*/true)) {
TORCH_CHECK(
false,
"Integer division with addcdiv is no longer supported, and in a future ",
"release addcdiv will perform a true division of tensor1 and tensor2. ",
"The historic addcdiv behavior can be implemented as ",
"(input + value * torch.trunc(tensor1 / tensor2)).to(input.dtype) ",
"for integer inputs and as ",
"(input + value * tensor1 / tensor2) for float inputs. ",
"The future addcdiv behavior is just the latter implementation: ",
"(input + value * tensor1 / tensor2), for all dtypes.");
}
build_ternary_op(maybe_get_output(), self, tensor1, tensor2);
}
} // namespace at::meta
namespace at::native {
TORCH_IMPL_FUNC(addcmul_out)
(const Tensor& self,
const Tensor& tensor1,
const Tensor& tensor2,
const Scalar& value,
const Tensor& result) {
addcmul_stub(device_type(), *this, value);
}
TORCH_IMPL_FUNC(addcdiv_out)
(const Tensor& self,
const Tensor& tensor1,
const Tensor& tensor2,
const Scalar& value,
const Tensor& result) {
addcdiv_stub(device_type(), *this, value);
}
DEFINE_DISPATCH(addcmul_stub);
DEFINE_DISPATCH(addcdiv_stub);
} // namespace at::native