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ForeachOpsKernels.cpp
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ForeachOpsKernels.cpp
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#include <ATen/ATen.h>
#include <ATen/native/ForeachUtils.h>
namespace at { namespace native {
#define FOREACH_BINARY_OP_SCALAR(OP) \
void foreach_tensor_##OP##_scalar_kernel_slow_(TensorList tensors, Scalar scalar) { \
check_foreach_api_restrictions(tensors); \
\
for (auto& t: tensors) { \
t.OP##_(scalar); \
} \
} \
\
std::vector<Tensor> foreach_tensor_##OP##_scalar_kernel_slow(TensorList tensors, Scalar scalar) { \
check_foreach_api_restrictions(tensors); \
\
std::vector<Tensor> result; \
result.reserve(tensors.size()); \
for (const auto& t: tensors) { \
result.emplace_back(t.OP(scalar)); \
} \
\
return result; \
}
#define FOREACH_BINARY_OP_SCALARLIST(OP) \
void foreach_tensor_##OP##_scalarlist_kernel_slow_(TensorList tensors, at::ArrayRef<double> scalars) { \
check_foreach_api_restrictions(tensors, scalars); \
\
for (int i = 0; i < tensors.size(); i++) { \
tensors[i].OP##_(scalars[i]); \
} \
} \
\
std::vector<Tensor> foreach_tensor_##OP##_scalarlist_kernel_slow(TensorList tensors, at::ArrayRef<double> scalars) { \
check_foreach_api_restrictions(tensors, scalars); \
std::vector<Tensor> result; \
result.reserve(tensors.size()); \
for (int i = 0; i < tensors.size(); i++) { \
result.emplace_back(tensors[i].OP(scalars[i])); \
} \
\
return result; \
}
#define FOREACH_BINARY_OP_LIST(OP) \
std::vector<Tensor> foreach_tensor_##OP##_list_kernel_slow(TensorList tensors1, TensorList tensors2) { \
check_foreach_api_restrictions(tensors1, tensors2); \
\
std::vector<Tensor> result; \
result.reserve(tensors1.size()); \
for (int i = 0; i < tensors1.size(); i++) { \
result.emplace_back(tensors1[i].OP(tensors2[i])); \
} \
\
return result; \
} \
\
void foreach_tensor_##OP##_list_kernel_slow_(TensorList tensors1, TensorList tensors2) { \
check_foreach_api_restrictions(tensors1, tensors2); \
\
for (int i = 0; i < tensors1.size(); i++) { \
tensors1[i].OP##_(tensors2[i]); \
} \
}
#define FOREACH_BINARY_OP_LIST_ALPHA(OP) \
std::vector<Tensor> foreach_tensor_##OP##_list_kernel_slow(TensorList tensors1, TensorList tensors2, Scalar alpha) { \
check_foreach_api_restrictions(tensors1, tensors2); \
\
std::vector<Tensor> result; \
result.reserve(tensors1.size()); \
for (int i = 0; i < tensors1.size(); i++) { \
result.emplace_back(tensors1[i].OP(tensors2[i], alpha)); \
} \
\
return result; \
} \
\
void foreach_tensor_##OP##_list_kernel_slow_(TensorList tensors1, TensorList tensors2, Scalar alpha) { \
check_foreach_api_restrictions(tensors1, tensors2); \
\
for (int i = 0; i < tensors1.size(); i++) { \
tensors1[i].OP##_(tensors2[i], alpha); \
} \
}
#define FOREACH_UNARY_OP(OP) \
std::vector<Tensor> foreach_tensor_##OP##_slow(TensorList tensors) { \
check_foreach_api_restrictions(tensors); \
\
std::vector<Tensor> result; \
result.reserve(tensors.size()); \
for (const auto& t : tensors) { \
result.emplace_back(t.OP()); \
} \
\
return result; \
} \
\
void foreach_tensor_##OP##_slow_(TensorList tensors) { \
check_foreach_api_restrictions(tensors); \
\
for (auto& t : tensors) { \
t.OP##_(); \
} \
}
#define FOREACH_POINTWISE_OP_SCALAR(OP) \
std::vector<Tensor> foreach_tensor_##OP##_scalar_slow(TensorList input, TensorList tensors1, TensorList tensors2, Scalar scalar) { \
check_foreach_api_restrictions(input, tensors1, tensors2); \
\
std::vector<Tensor> result; \
for (int i = 0; i < input.size(); i++) { \
result.emplace_back(input[i].OP(tensors1[i], tensors2[i], scalar)); \
} \
\
return result; \
} \
\
void foreach_tensor_##OP##_scalar_slow_(TensorList input, TensorList tensors1, TensorList tensors2, Scalar scalar) { \
check_foreach_api_restrictions(input, tensors1, tensors2); \
\
for (int i = 0; i < input.size(); i++) { \
input[i].OP##_(tensors1[i], tensors2[i], scalar); \
} \
} \
#define FOREACH_POINTWISE_OP_SCALARLIST(OP) \
std::vector<Tensor> foreach_tensor_##OP##_scalarlist_slow(TensorList input, TensorList tensors1, TensorList tensors2, at::ArrayRef<double> scalars) { \
check_foreach_api_restrictions(input, tensors1, tensors2, scalars); \
\
std::vector<Tensor> result; \
for (int i = 0; i < input.size(); i++) { \
result.emplace_back(input[i].OP(tensors1[i], tensors2[i], scalars[i])); \
} \
\
return result; \
} \
\
void foreach_tensor_##OP##_scalarlist_slow_(TensorList input, TensorList tensors1, TensorList tensors2, at::ArrayRef<double> scalars) { \
check_foreach_api_restrictions(input, tensors1, tensors2, scalars); \
\
for (int i = 0; i < input.size(); i++) { \
input[i].OP##_(tensors1[i], tensors2[i], scalars[i]); \
} \
} \
FOREACH_BINARY_OP_LIST_ALPHA(add);
FOREACH_BINARY_OP_LIST_ALPHA(sub);
FOREACH_BINARY_OP_SCALAR(add);
FOREACH_BINARY_OP_SCALAR(sub);
FOREACH_BINARY_OP_SCALAR(mul);
FOREACH_BINARY_OP_SCALAR(div);
FOREACH_BINARY_OP_SCALARLIST(add);
FOREACH_BINARY_OP_SCALARLIST(sub);
FOREACH_BINARY_OP_SCALARLIST(mul);
FOREACH_BINARY_OP_SCALARLIST(div);
FOREACH_BINARY_OP_LIST(mul);
FOREACH_BINARY_OP_LIST(div);
FOREACH_UNARY_OP(sqrt);
FOREACH_UNARY_OP(exp);
FOREACH_UNARY_OP(abs);
FOREACH_UNARY_OP(acos);
FOREACH_UNARY_OP(asin);
FOREACH_UNARY_OP(atan);
FOREACH_UNARY_OP(ceil);
FOREACH_UNARY_OP(cos);
FOREACH_UNARY_OP(cosh);
FOREACH_UNARY_OP(erf);
FOREACH_UNARY_OP(erfc);
FOREACH_UNARY_OP(expm1);
FOREACH_UNARY_OP(floor);
FOREACH_UNARY_OP(log);
FOREACH_UNARY_OP(log10);
FOREACH_UNARY_OP(log1p);
FOREACH_UNARY_OP(log2);
FOREACH_UNARY_OP(neg);
FOREACH_UNARY_OP(tan);
FOREACH_UNARY_OP(tanh);
FOREACH_UNARY_OP(sin);
FOREACH_UNARY_OP(sinh);
FOREACH_UNARY_OP(round);
FOREACH_UNARY_OP(lgamma);
FOREACH_UNARY_OP(frac);
FOREACH_UNARY_OP(trunc);
FOREACH_UNARY_OP(reciprocal);
FOREACH_UNARY_OP(sigmoid);
FOREACH_POINTWISE_OP_SCALAR(addcdiv);
FOREACH_POINTWISE_OP_SCALAR(addcmul);
FOREACH_POINTWISE_OP_SCALARLIST(addcdiv);
FOREACH_POINTWISE_OP_SCALARLIST(addcmul);
#define FOREACH_MAXIMUM_MINIMUM_OP(NAME) \
std::vector<Tensor> foreach_tensor_##NAME##_slow(TensorList tensors1, TensorList tensors2) { \
check_foreach_api_restrictions(tensors1, tensors2); \
\
std::vector<Tensor> result; \
result.reserve(tensors1.size()); \
for (int i = 0; i < tensors1.size(); i++) { \
result.emplace_back(at::NAME(tensors1[i], tensors2[i])); \
} \
\
return result; \
} \
FOREACH_MAXIMUM_MINIMUM_OP(maximum)
FOREACH_MAXIMUM_MINIMUM_OP(minimum)
}} // namespace at::native