#pragma once
#include <ATen/EmptyTensor.h>
#include <ATen/Formatting.h>
#include <ATen/core/ATenGeneral.h>
#include <ATen/core/Generator.h>
#include <c10/core/ScalarType.h>
#include <c10/core/StorageImpl.h>
#include <c10/core/UndefinedTensorImpl.h>
#include <c10/util/ArrayRef.h>
#include <c10/util/Exception.h>
#include <c10/util/accumulate.h>
#include <c10/util/irange.h>
#include <algorithm>
#include <memory>
#include <numeric>
#include <sstream>
#include <typeinfo>
#define AT_DISALLOW_COPY_AND_ASSIGN(TypeName) \
TypeName(const TypeName&) = delete; \
void operator=(const TypeName&) = delete
namespace at {
TORCH_API int _crash_if_asan(int);
// Converts a TensorList (i.e. ArrayRef<Tensor> to vector of TensorImpl*)
// NB: This is ONLY used by legacy TH bindings, and ONLY used by cat.
// Once cat is ported entirely to ATen this can be deleted!
static inline std::vector<TensorImpl*> checked_dense_tensor_list_unwrap(
ArrayRef<Tensor> tensors,
const char* name,
int pos,
c10::DeviceType device_type,
ScalarType scalar_type) {
std::vector<TensorImpl*> unwrapped;
unwrapped.reserve(tensors.size());
for (const auto i : c10::irange(tensors.size())) {
const auto& expr = tensors[i];
if (expr.layout() != Layout::Strided) {
AT_ERROR(
"Expected dense tensor but got ",
expr.layout(),
" for sequence element ",
i,
" in sequence argument at position #",
pos,
" '",
name,
"'");
}
if (expr.device().type() != device_type) {
AT_ERROR(
"Expected object of device type ",
device_type,
" but got device type ",
expr.device().type(),
" for sequence element ",
i,
" in sequence argument at position #",
pos,
" '",
name,
"'");
}
if (expr.scalar_type() != scalar_type) {
AT_ERROR(
"Expected object of scalar type ",
scalar_type,
" but got scalar type ",
expr.scalar_type(),
" for sequence element ",
i,
" in sequence argument at position #",
pos,
" '",
name,
"'");
}
unwrapped.emplace_back(expr.unsafeGetTensorImpl());
}
return unwrapped;
}
template <size_t N>
std::array<int64_t, N> check_intlist(
ArrayRef<int64_t> list,
const char* name,
int pos) {
if (list.empty()) {
// TODO: is this necessary? We used to treat nullptr-vs-not in IntList
// differently with strides as a way of faking optional.
list = {};
}
auto res = std::array<int64_t, N>();
if (list.size() == 1 && N > 1) {
res.fill(list[0]);
return res;
}
if (list.size() != N) {
AT_ERROR(
"Expected a list of ",
N,
" ints but got ",
list.size(),
" for argument #",
pos,
" '",
name,
"'");
}
std::copy_n(list.begin(), N, res.begin());
return res;
}
using at::detail::check_size_nonnegative;
namespace detail {
template <typename T>
TORCH_API Tensor tensor_cpu(ArrayRef<T> values, const TensorOptions& options);
template <typename T>
TORCH_API Tensor
tensor_backend(ArrayRef<T> values, const TensorOptions& options);
template <typename T>
TORCH_API Tensor
tensor_complex_cpu(ArrayRef<T> values, const TensorOptions& options);
template <typename T>
TORCH_API Tensor
tensor_complex_backend(ArrayRef<T> values, const TensorOptions& options);
} // namespace detail
} // namespace at