1#pragma once
2
3// @generated by torchgen/gen.py from Operator.h
4
5#include <tuple>
6#include <vector>
7
8// Forward declarations of any types needed in the operator signatures.
9// We can't directly include these classes because it will cause circular include dependencies.
10// This file is included by TensorBody.h, which defines the Tensor class.
11#include <ATen/core/ATen_fwd.h>
12
13namespace at {
14namespace _ops {
15
16
17struct TORCH_API _native_multi_head_attention {
18 using schema = ::std::tuple<at::Tensor,at::Tensor> (const at::Tensor &, const at::Tensor &, const at::Tensor &, int64_t, int64_t, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const c10::optional<at::Tensor> &, bool, bool, c10::optional<int64_t>);
19 using ptr_schema = schema*;
20 // See Note [static constexpr char* members for windows NVCC]
21 STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::_native_multi_head_attention")
22 STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "")
23 STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "_native_multi_head_attention(Tensor query, Tensor key, Tensor value, int embed_dim, int num_head, Tensor qkv_weight, Tensor qkv_bias, Tensor proj_weight, Tensor proj_bias, Tensor? mask=None, bool need_weights=True, bool average_attn_weights=True, int? mask_type=None) -> (Tensor, Tensor)")
24 static ::std::tuple<at::Tensor,at::Tensor> call(const at::Tensor & query, const at::Tensor & key, const at::Tensor & value, int64_t embed_dim, int64_t num_head, const at::Tensor & qkv_weight, const at::Tensor & qkv_bias, const at::Tensor & proj_weight, const at::Tensor & proj_bias, const c10::optional<at::Tensor> & mask, bool need_weights, bool average_attn_weights, c10::optional<int64_t> mask_type);
25 static ::std::tuple<at::Tensor,at::Tensor> redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & query, const at::Tensor & key, const at::Tensor & value, int64_t embed_dim, int64_t num_head, const at::Tensor & qkv_weight, const at::Tensor & qkv_bias, const at::Tensor & proj_weight, const at::Tensor & proj_bias, const c10::optional<at::Tensor> & mask, bool need_weights, bool average_attn_weights, c10::optional<int64_t> mask_type);
26};
27
28struct TORCH_API _native_multi_head_attention_out {
29 using schema = ::std::tuple<at::Tensor &,at::Tensor &> (const at::Tensor &, const at::Tensor &, const at::Tensor &, int64_t, int64_t, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const c10::optional<at::Tensor> &, bool, bool, c10::optional<int64_t>, at::Tensor &, at::Tensor &);
30 using ptr_schema = schema*;
31 // See Note [static constexpr char* members for windows NVCC]
32 STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::_native_multi_head_attention")
33 STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "out")
34 STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "_native_multi_head_attention.out(Tensor query, Tensor key, Tensor value, int embed_dim, int num_head, Tensor qkv_weight, Tensor qkv_bias, Tensor proj_weight, Tensor proj_bias, Tensor? mask=None, bool need_weights=True, bool average_attn_weights=True, int? mask_type=None, *, Tensor(a!) out0, Tensor(b!) out1) -> (Tensor(a!), Tensor(b!))")
35 static ::std::tuple<at::Tensor &,at::Tensor &> call(const at::Tensor & query, const at::Tensor & key, const at::Tensor & value, int64_t embed_dim, int64_t num_head, const at::Tensor & qkv_weight, const at::Tensor & qkv_bias, const at::Tensor & proj_weight, const at::Tensor & proj_bias, const c10::optional<at::Tensor> & mask, bool need_weights, bool average_attn_weights, c10::optional<int64_t> mask_type, at::Tensor & out0, at::Tensor & out1);
36 static ::std::tuple<at::Tensor &,at::Tensor &> redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & query, const at::Tensor & key, const at::Tensor & value, int64_t embed_dim, int64_t num_head, const at::Tensor & qkv_weight, const at::Tensor & qkv_bias, const at::Tensor & proj_weight, const at::Tensor & proj_bias, const c10::optional<at::Tensor> & mask, bool need_weights, bool average_attn_weights, c10::optional<int64_t> mask_type, at::Tensor & out0, at::Tensor & out1);
37};
38
39}} // namespace at::_ops
40