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

// @generated by torchgen/gen.py from Operator.h

#include <string_view>
#include <tuple>
#include <vector>

// Forward declarations of any types needed in the operator signatures.
// We can't directly include these classes because it will cause circular include dependencies.
// This file is included by TensorBody.h, which defines the Tensor class.
#include <ATen/core/ATen_fwd.h>

namespace at {
namespace _ops {


struct TORCH_API _scaled_mm_v2 {
  using schema = at::Tensor (const at::Tensor &, const at::Tensor &, at::TensorList, at::IntArrayRef, at::IntArrayRef, at::TensorList, at::IntArrayRef, at::IntArrayRef, const ::std::optional<at::Tensor> &, ::std::optional<at::ScalarType>, at::IntArrayRef, bool);
  using ptr_schema = schema*;
  // See Note [static constexpr char* members for windows NVCC]
  static constexpr const char* name = "aten::_scaled_mm_v2";
  static constexpr const char* overload_name = "";
  static constexpr const char* schema_str = "_scaled_mm_v2(Tensor self, Tensor mat2, Tensor[] scale_a, int[] recipe_a, int[] swizzle_a, Tensor[] scale_b, int[] recipe_b, int[] swizzle_b, Tensor? bias, ScalarType? out_dtype, int[] contraction_dim=[], bool use_fast_accum=False) -> Tensor";
  static at::Tensor call(const at::Tensor & self, const at::Tensor & mat2, at::TensorList scale_a, at::IntArrayRef recipe_a, at::IntArrayRef swizzle_a, at::TensorList scale_b, at::IntArrayRef recipe_b, at::IntArrayRef swizzle_b, const ::std::optional<at::Tensor> & bias, ::std::optional<at::ScalarType> out_dtype, at::IntArrayRef contraction_dim, bool use_fast_accum);
  static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & mat2, at::TensorList scale_a, at::IntArrayRef recipe_a, at::IntArrayRef swizzle_a, at::TensorList scale_b, at::IntArrayRef recipe_b, at::IntArrayRef swizzle_b, const ::std::optional<at::Tensor> & bias, ::std::optional<at::ScalarType> out_dtype, at::IntArrayRef contraction_dim, bool use_fast_accum);
};

struct TORCH_API _scaled_mm_v2_out {
  using schema = at::Tensor & (const at::Tensor &, const at::Tensor &, at::TensorList, at::IntArrayRef, at::IntArrayRef, at::TensorList, at::IntArrayRef, at::IntArrayRef, const ::std::optional<at::Tensor> &, ::std::optional<at::ScalarType>, at::IntArrayRef, bool, at::Tensor &);
  using ptr_schema = schema*;
  // See Note [static constexpr char* members for windows NVCC]
  static constexpr const char* name = "aten::_scaled_mm_v2";
  static constexpr const char* overload_name = "out";
  static constexpr const char* schema_str = "_scaled_mm_v2.out(Tensor self, Tensor mat2, Tensor[] scale_a, int[] recipe_a, int[] swizzle_a, Tensor[] scale_b, int[] recipe_b, int[] swizzle_b, Tensor? bias, ScalarType? out_dtype, int[] contraction_dim=[], bool use_fast_accum=False, *, Tensor(a!) out) -> Tensor(a!)";
  static at::Tensor & call(const at::Tensor & self, const at::Tensor & mat2, at::TensorList scale_a, at::IntArrayRef recipe_a, at::IntArrayRef swizzle_a, at::TensorList scale_b, at::IntArrayRef recipe_b, at::IntArrayRef swizzle_b, const ::std::optional<at::Tensor> & bias, ::std::optional<at::ScalarType> out_dtype, at::IntArrayRef contraction_dim, bool use_fast_accum, at::Tensor & out);
  static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & mat2, at::TensorList scale_a, at::IntArrayRef recipe_a, at::IntArrayRef swizzle_a, at::TensorList scale_b, at::IntArrayRef recipe_b, at::IntArrayRef swizzle_b, const ::std::optional<at::Tensor> & bias, ::std::optional<at::ScalarType> out_dtype, at::IntArrayRef contraction_dim, bool use_fast_accum, at::Tensor & out);
};

}} // namespace at::_ops

#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)
