#pragma once

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

#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 _cslt_sparse_mm_search {
  using schema = int64_t (const at::Tensor &, const at::Tensor &, const c10::optional<at::Tensor> &, const c10::optional<at::Tensor> &, c10::optional<at::ScalarType>, bool);
  using ptr_schema = schema*;
  // See Note [static constexpr char* members for windows NVCC]
  STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::_cslt_sparse_mm_search")
  STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "")
  STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "_cslt_sparse_mm_search(Tensor compressed_A, Tensor dense_B, Tensor? bias=None, Tensor? alpha=None, ScalarType? out_dtype=None, bool transpose_result=False) -> int")
  static int64_t call(const at::Tensor & compressed_A, const at::Tensor & dense_B, const c10::optional<at::Tensor> & bias, const c10::optional<at::Tensor> & alpha, c10::optional<at::ScalarType> out_dtype, bool transpose_result);
  static int64_t redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & compressed_A, const at::Tensor & dense_B, const c10::optional<at::Tensor> & bias, const c10::optional<at::Tensor> & alpha, c10::optional<at::ScalarType> out_dtype, bool transpose_result);
};

}} // namespace at::_ops
