xhs-note-crawling/python/py/Lib/site-packages/torch/include/ATen/TensorMeta.h

#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION)
#pragma once

#include <ATen/DimVector.h>
#include <ATen/core/Dimname.h>
#include <c10/core/TensorOptions.h>
#include <c10/util/strides.h>

namespace at {

class Tensor;

namespace impl {

// Use this to define the prototype for a meta function.  There are two
// versions; one that takes one argument (just the operator name), or FUNC2
// variant that takes two arguments (operator name and overload name).
//
// Example usage:
//
//    TORCH_META_FUNC2(add, Tensor) (
//      const Tensor& self, const Tensor& other
//    ) {
//      ... compute sizes and options ...
//      set_output(sizes, options);
//    }
//
#define TORCH_META_FUNC(name) void structured_##name::meta
#define TORCH_META_FUNC2(name, overload) \
  void structured_##name##_##overload::meta

// These are versions of TORCH_META_FUNC(2) that include a precompute_out struct
// as a return value. They should be used when the kernel in question has
// precomputed values declared in native_functions.yaml and the corresponding
// implementation should return an instance of the aforementioned struct.
#define TORCH_PRECOMPUTE_META_FUNC(name) \
  structured_##name::meta_return_ty structured_##name::meta
#define TORCH_PRECOMPUTE_META_FUNC2(name, overload) \
  structured_##name##_##overload::meta_return_ty    \
      structured_##name##_##overload::meta

// Use this to create a precompute struct in a meta function.
#define TORCH_PRECOMPUTE_STRUCT(name) structured_##name::precompute_out<>
#define TORCH_PRECOMPUTE_STRUCT2(name, overload) \
  structured_##name##_##overload::precompute_out<>

// Use this to define the prototype for an implementation.  This takes only
// one argument, which is the name of the dispatch key entry you're
// implementing.
//
// Example usage:
//
//    TORCH_IMPL_FUNC(add_cpu) (
//      Tensor& result, const Tensor& self, const Tensor& other
//    ) {
//      ... do the actual implementation ...
//    }
//
#define TORCH_IMPL_FUNC(name) void structured_##name::impl

// Base class for all structured kernel classes.  The set_output virtual
// method is varied depending whether or not the operator is
// functional/out/inplace, and could also be specialized for CPU/CUDA/etc
// (although presently it isn't).
//
// A notable subclass of this interface is TensorIteratorBase.
struct TORCH_API MetaBase {
  MetaBase() = default;
  MetaBase(const MetaBase&) = default;
  MetaBase& operator=(const MetaBase&) = default;
  MetaBase(MetaBase&&) noexcept = default;
  MetaBase& operator=(MetaBase&&) noexcept = default;
  virtual const Tensor& maybe_get_output(int64_t output_idx) = 0;

  // Note: [set_output_*]
  // See: https://github.com/pytorch/pytorch/issues/69813
  // Whenever defining the output properties in the META function of a
  // structured kernel (what was usually done with `set_output`), use one of
  // these 3 variants, instead. In order to decide which variant to use, check
  // the following decision tree:
  //
  // - Can the kernel you are going to implement support output tensors
  //   with arbitrary strides?
  //     |
  //     -- YES: `set_output_raw_strided`
  //     |
  //     -- NO: Should the output tensor strides be contiguous?
  //         |
  //         -- YES: `set_output_contiguous`
  //         |
  //         -- NO: `set_output_strided`
  //
  // Use this function whenever the kernel requires specific strides for the
  // output. If `strides` does not match the given output strides, proxy outputs
  // will be created and passed to the IMPL function.
  virtual void set_output_strided(
      int64_t output_idx [[maybe_unused]],
      IntArrayRef sizes [[maybe_unused]],
      IntArrayRef strides [[maybe_unused]],
      TensorOptions options [[maybe_unused]],
      DimnameList names [[maybe_unused]] = {}) {
    TORCH_INTERNAL_ASSERT(false, "set_output_strided not implemented.");
  }

  // Use this function whenever the kernel knows how to handle arbitrary strided
  // outputs. This function has the same behavior as the old `set_output`: it
  // will only re-stride if the given output was resized.
  virtual void set_output_raw_strided(
      int64_t output_idx [[maybe_unused]],
      IntArrayRef sizes [[maybe_unused]],
      IntArrayRef strides_hint [[maybe_unused]],
      TensorOptions options [[maybe_unused]],
      DimnameList names [[maybe_unused]] = {}) {
    TORCH_INTERNAL_ASSERT(false, "set_output_strided not implemented.");
  }

  // Use this function if the kernel requires contiguous strides.
  // Alias for `set_output_strided`, but with contiguous strides.
  void set_output_contiguous(
      int64_t output_idx,
      IntArrayRef sizes,
      TensorOptions options,
      DimnameList names = {}) {
    auto strides = c10::contiguous_strides(sizes);
    set_output_strided(output_idx, sizes, strides, options, names);
  }

  // Returns a reference to an undefined tensor if there is no presupplied
  // output
  const Tensor& maybe_get_output() {
    return maybe_get_output(0);
  }
  virtual ~MetaBase() = default;
};

} // namespace impl

} // namespace at

#else
#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined."
#endif  // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION)