TensorProperties.cpp

#include <ATen/ATen.h>
#include <ATen/NativeFunctions.h>
#include <ATen/WrapDimUtils.h>
#include <ATen/detail/CUDAHooksInterface.h>

#include <ATen/Config.h>
namespace at {
namespace native {

bool is_same_size(const Tensor& self, const Tensor& other) {
  return self.sizes().equals(other.sizes());
}

int64_t size(const Tensor& self, int64_t dim) {
  // false is passed to maybe_wrap_dim so behavior is identical to array access (but with wrapping)
  dim = maybe_wrap_dim(dim, self.dim(), false);
  return self.sizes()[dim];
}

int64_t stride(const Tensor& self, int64_t dim) {
  // false is passed to maybe_wrap_dim so behavior is identical to array access (but with wrapping)
  dim = maybe_wrap_dim(dim, self.dim(), false);
  return self.strides()[dim];
}

bool cudnn_is_acceptable(const Tensor& self) {
  if (!globalContext().userEnabledCuDNN()) return false;
  if (!self.is_cuda()) return false;
  auto st = self.type().scalarType();
  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.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;
}

Tensor detach(const 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;
}

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;
}

Tensor contiguous(const Tensor & self) {
  if (self.is_contiguous()) {
    return self;
  }
  return self.clone();
}

}
}