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ForeachBinaryOpScalarList.cu
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ForeachBinaryOpScalarList.cu
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#define TORCH_ASSERT_ONLY_METHOD_OPERATORS
#include <ATen/Dispatch.h>
#include <ATen/native/BinaryOps.h>
#include <ATen/native/ForeachUtils.h>
#include <ATen/native/cuda/ForeachFunctors.cuh>
#include <ATen/native/cuda/ForeachMinMaxFunctors.cuh>
#ifndef AT_PER_OPERATOR_HEADERS
#include <ATen/NativeFunctions.h>
#else
#include <ATen/ops/_foreach_add_native.h>
#include <ATen/ops/_foreach_clamp_max_native.h>
#include <ATen/ops/_foreach_clamp_min_native.h>
#include <ATen/ops/_foreach_div_native.h>
#include <ATen/ops/_foreach_mul_native.h>
#include <ATen/ops/_foreach_pow_native.h>
#include <ATen/ops/_foreach_sub_native.h>
#include <ATen/ops/empty_like_native.h>
#endif
namespace at::native {
template <typename T, template <class> class Op>
std::vector<Tensor> foreach_binary_op(
TensorList tensors,
at::ArrayRef<Scalar> scalars) {
std::vector<std::vector<at::Tensor>> tensor_lists;
std::vector<at::Tensor> vec_res;
vec_res.reserve(tensors.size());
for (const auto& t : tensors) {
vec_res.emplace_back(at::native::empty_like(t));
}
tensor_lists.emplace_back(tensors.vec());
tensor_lists.emplace_back(vec_res);
using opmath_t = at::opmath_type<T>;
multi_tensor_apply<2, opmath_t>(
tensor_lists,
scalars,
BinaryOpScalarListFunctor<
T,
/* depth */ 2,
/* r_args_depth */ 1,
/* res_arg_index */ 1>(),
Op<opmath_t>());
return tensor_lists[1];
}
template <typename T, template <class> class Op>
void foreach_binary_op_(TensorList tensors, at::ArrayRef<Scalar> scalars) {
std::vector<std::vector<at::Tensor>> tensor_lists;
tensor_lists.emplace_back(tensors.vec());
using opmath_t = at::opmath_type<T>;
multi_tensor_apply<1, opmath_t>(
tensor_lists,
scalars,
BinaryOpScalarListFunctor<
T,
/* depth */ 1,
/* r_args_depth */ 1,
/* res_arg_index */ 0>(),
Op<opmath_t>());
increment_version(tensors);
}
template <template <class> class Op>
std::vector<Tensor> all_types_complex_bool_half_bfloat16(
TensorList tensors,
at::ArrayRef<Scalar> scalars) {
return AT_DISPATCH_ALL_TYPES_AND_COMPLEX_AND3(
kBool,
kHalf,
kBFloat16,
tensors[0].scalar_type(),
"foreach_binary_op_scalarlist_cuda",
[&]() { return foreach_binary_op<scalar_t, Op>(tensors, scalars); });
}
template <template <class> class Op>
void all_types_complex_bool_half_bfloat16_(
TensorList tensors,
at::ArrayRef<Scalar> scalars) {
AT_DISPATCH_ALL_TYPES_AND_COMPLEX_AND3(
kBool,
kHalf,
kBFloat16,
tensors[0].scalar_type(),
"foreach_binary_op_scalarlist_cuda_",
[&]() { foreach_binary_op_<scalar_t, Op>(tensors, scalars); });
}
template <template <class> class Op>
std::vector<Tensor> all_types_half_bfloat16(
TensorList tensors,
at::ArrayRef<Scalar> scalars) {
return AT_DISPATCH_ALL_TYPES_AND2(
kHalf,
kBFloat16,
tensors[0].scalar_type(),
"foreach_binary_op_scalarlist_cuda",
[&]() { return foreach_binary_op<scalar_t, Op>(tensors, scalars); });
}
template <template <class> class Op>
void all_types_half_bfloat16_(
TensorList tensors,
at::ArrayRef<Scalar> scalars) {
AT_DISPATCH_ALL_TYPES_AND2(
kHalf,
kBFloat16,
tensors[0].scalar_type(),
"foreach_binary_op_scalarlist_cuda_",
[&]() { foreach_binary_op_<scalar_t, Op>(tensors, scalars); });
}
template <template <class> class Op>
std::vector<Tensor> all_types_complex_half_bfloat16(
TensorList tensors,
at::ArrayRef<Scalar> scalars) {
return AT_DISPATCH_ALL_TYPES_AND_COMPLEX_AND2(
kHalf,
kBFloat16,
tensors[0].scalar_type(),
"foreach_binary_op_scalarlist_cuda",
[&]() { return foreach_binary_op<scalar_t, Op>(tensors, scalars); });
}
template <template <class> class Op>
void all_types_complex_half_bfloat16_(
TensorList tensors,
at::ArrayRef<Scalar> scalars) {
AT_DISPATCH_ALL_TYPES_AND_COMPLEX_AND2(
kHalf,
kBFloat16,
tensors[0].scalar_type(),
"foreach_binary_op_scalarlist_cuda_",
[&]() { foreach_binary_op_<scalar_t, Op>(tensors, scalars); });
}
#define FOREACH_BINARY_OP_SCALARLIST(FUNCTION, NAME, OP, DIV_OP) \
void foreach_tensor_##NAME##_scalarlist_kernel_cuda_( \
TensorList tensors, at::ArrayRef<Scalar> scalars) { \
check_foreach_api_restrictions(tensors, scalars); \
if (!can_use_fast_route(tensors, scalars, DIV_OP)) { \
return at::native::foreach_tensor_##NAME##_scalarlist_kernel_slow_( \
tensors, scalars); \
} \
\
FUNCTION##_<OP>(tensors, scalars); \
} \
\
std::vector<Tensor> foreach_tensor_##NAME##_scalarlist_kernel_cuda( \
TensorList tensors, at::ArrayRef<Scalar> scalars) { \
check_foreach_api_restrictions(tensors, scalars); \
if (!can_use_fast_route(tensors, scalars, DIV_OP)) { \
return at::native::foreach_tensor_##NAME##_scalarlist_kernel_slow( \
tensors, scalars); \
} \
\
return FUNCTION<OP>(tensors, scalars); \
}
FOREACH_BINARY_OP_SCALARLIST(
all_types_complex_bool_half_bfloat16,
add,
std::plus,
/*div_op*/ false);
FOREACH_BINARY_OP_SCALARLIST(
all_types_complex_bool_half_bfloat16,
mul,
std::multiplies,
/*div_op*/ false);
FOREACH_BINARY_OP_SCALARLIST(
all_types_complex_bool_half_bfloat16,
div,
std::divides,
/*div_op*/ true);
// See [Why is foreach_pow's division_op=true?]
FOREACH_BINARY_OP_SCALARLIST(
all_types_complex_half_bfloat16,
pow,
power_functor,
/*div_op*/ true);
// This does not use FOREACH_BINARY_OP_SCALARLIST because
// In the case of subtraction, we dont allow scalar to be boolean following the
// torch.sub logic
void foreach_tensor_sub_scalarlist_kernel_cuda_(
TensorList tensors,
at::ArrayRef<Scalar> scalars) {
check_foreach_api_restrictions(tensors, scalars);
for (const auto i : c10::irange(tensors.size())) {
sub_check(tensors[i], scalars[i]);
}
if (!can_use_fast_route({tensors}, scalars)) {
return at::native::foreach_tensor_sub_scalarlist_kernel_slow_(
tensors, scalars);
}
AT_DISPATCH_ALL_TYPES_AND_COMPLEX_AND3(
kBool,
kHalf,
kBFloat16,
tensors[0].scalar_type(),
"foreach_binary_op_scalarlist_cuda_",
[&]() { foreach_binary_op_<scalar_t, std::minus>(tensors, scalars); });
}
std::vector<Tensor> foreach_tensor_sub_scalarlist_kernel_cuda(
TensorList tensors,
at::ArrayRef<Scalar> scalars) {
check_foreach_api_restrictions(tensors, scalars);
for (const auto i : c10::irange(tensors.size())) {
sub_check(tensors[i], scalars[i]);
}
if (!can_use_fast_route({tensors}, scalars)) {
return at::native::foreach_tensor_sub_scalarlist_kernel_slow(
tensors, scalars);
}
return AT_DISPATCH_ALL_TYPES_AND_COMPLEX_AND3(
kBool,
kHalf,
kBFloat16,
tensors[0].scalar_type(),
"foreach_binary_op_scalarlist_cuda_",
[&]() {
return foreach_binary_op<scalar_t, std::minus>(tensors, scalars);
});
}
FOREACH_BINARY_OP_SCALARLIST(all_types_half_bfloat16, clamp_max, minimum, true);
FOREACH_BINARY_OP_SCALARLIST(all_types_half_bfloat16, clamp_min, maximum, true);
} // namespace at::native