blob: 899cf68a7a5a93de05ebdd2fd2bf3373d29e9590 [file] [log] [blame]
#define TORCH_ASSERT_ONLY_METHOD_OPERATORS
#include <ATen/core/Tensor.h>
#include <ATen/Context.h>
#include <ATen/NamedTensorUtils.h>
#include <ATen/detail/CUDAHooksInterface.h>
#include <ATen/native/TensorProperties.h>
#ifndef AT_PER_OPERATOR_HEADERS
#include <ATen/Functions.h>
#include <ATen/NativeFunctions.h>
#else
#include <ATen/ops/_nested_tensor_size_native.h>
#include <ATen/ops/contiguous_native.h>
#include <ATen/ops/cudnn_is_acceptable_native.h>
#include <ATen/ops/detach_native.h>
#include <ATen/ops/equal.h>
#include <ATen/ops/is_same_size_native.h>
#include <ATen/ops/is_set_to_native.h>
#include <ATen/ops/size_native.h>
#include <ATen/ops/stride_native.h>
#include <ATen/ops/sym_numel_native.h>
#include <ATen/ops/sym_size_native.h>
#include <ATen/ops/sym_storage_offset_native.h>
#include <ATen/ops/sym_stride_native.h>
#endif
#include <c10/util/irange.h>
namespace at::native {
bool is_same_size(const Tensor& self, const Tensor& other) {
return self.sym_sizes().equals(other.sym_sizes());
}
bool nested_is_same_size(const Tensor& self, const Tensor& other) {
TORCH_CHECK(
self.is_nested() && other.is_nested(),
"Expected both self and other to be nested tensors. ",
"Self ", self.is_nested()? "is " : "is not ",
"nested. While Other ",
other.is_nested()? "is " : "is not ",
"nested.")
const auto self_nt_size = _nested_tensor_size(self);
const auto other_nt_size = _nested_tensor_size(other);
return at::equal(self_nt_size, other_nt_size);
}
int64_t size(const Tensor& self, int64_t dim) {
return self.size(dim);
}
int64_t stride(const Tensor& self, int64_t dim) {
return self.stride(dim);
}
c10::SymInt sym_size(const Tensor& self, int64_t dim) {
return self.sym_size(dim);
}
c10::SymInt sym_stride(const Tensor& self, int64_t dim) {
return self.sym_stride(dim);
}
c10::SymInt sym_numel(const Tensor& self) {
return self.sym_numel();
}
c10::SymInt sym_storage_offset(const Tensor& self) {
return self.sym_storage_offset();
}
int64_t size(const Tensor& self, Dimname dim) {
size_t pos_dim = dimname_to_position(self, dim);
return self.sizes()[pos_dim];
}
int64_t stride(const Tensor& self, Dimname dim) {
size_t pos_dim = dimname_to_position(self, dim);
return self.strides()[pos_dim];
}
bool cudnn_is_acceptable(const TensorBase& self) {
if (!globalContext().userEnabledCuDNN()) return false;
if (!self.is_cuda()) return false;
auto st = self.scalar_type();
if (!(st == kDouble || st == kFloat || st == kHalf)) return false;
if (!detail::getCUDAHooks().compiledWithCuDNN()) return false;
// cuDNN functions like grid_sampler returns CUDNN_STATUS_BAD_PARAM on empty
// tensors. Maybe some cuDNN functions actually support empty tensors, but
// native/THNN kernels shouldn't be much slower because the output is also
// likely empty.
if (self.sym_numel() == 0) return false;
// NB: In the old Python code, there was also a test to see if the
// cuDNN library was actually dynamically linked or not. I'm not
// sure if we can actually test this.
return true;
}
bool cudnn_is_acceptable(const Tensor& self) {
return cudnn_is_acceptable(static_cast<const TensorBase&>(self));
}
Tensor & detach_(Tensor & self) {
// this just exists to give us a hook in VariableType and an entry in Declarations.yaml
//AT_ERROR("detach_ is not implemented for Tensor");
return self;
}
static Tensor contiguous(const Tensor & self) {
return contiguous(self, MemoryFormat::Contiguous);
}
Tensor contiguous(const Tensor& self, MemoryFormat memory_format) {
if (self.is_contiguous(memory_format)) {
return self;
}
TORCH_CHECK(
memory_format != MemoryFormat::Preserve,
"preserve memory format is unsupported by the contiguous operator");
return self.clone(memory_format);
}
bool is_set_to(const Tensor& self, const Tensor& src) {
if (self.storage().unsafeGetStorageImpl() == src.storage().unsafeGetStorageImpl() &&
self.storage_offset() == src.storage_offset() &&
self.dim() == src.dim()) {
for (const auto d : c10::irange(self.dim())) {
if (self.size(d) != src.size(d) || self.stride(d) != src.stride(d)) {
return false;
}
}
return true;
}
return false;
}
} // namespace at::native