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体验新版 GitCode,发现更多精彩内容 >>
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01b688c0
编写于
3月 25, 2022
作者:
Z
Zhang Ting
提交者:
GitHub
3月 25, 2022
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电子邮件补丁
差异文件
Implement a common AlgorithmsCache for kernel auto-tune (#40793)
上级
54632b5c
变更
3
隐藏空白更改
内联
并排
Showing
3 changed file
with
169 addition
and
0 deletion
+169
-0
paddle/phi/kernels/autotune/CMakeLists.txt
paddle/phi/kernels/autotune/CMakeLists.txt
+2
-0
paddle/phi/kernels/autotune/cache.h
paddle/phi/kernels/autotune/cache.h
+122
-0
paddle/phi/kernels/autotune/cache_test.cc
paddle/phi/kernels/autotune/cache_test.cc
+45
-0
未找到文件。
paddle/phi/kernels/autotune/CMakeLists.txt
浏览文件 @
01b688c0
...
...
@@ -3,3 +3,5 @@ if (WITH_GPU)
elseif
(
WITH_ROCM
)
hip_test
(
gpu_timer_test SRCS gpu_timer_test.cu DEPS gtest
)
endif
()
cc_test
(
cache_test SRCS cache_test.cc DEPS gtest
)
paddle/phi/kernels/autotune/cache.h
0 → 100644
浏览文件 @
01b688c0
// Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved.
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
// http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
#pragma once
#include <algorithm>
#include <mutex>
#include <unordered_map>
#include <vector>
#include "glog/logging.h"
#include "paddle/phi/common/data_type.h"
#include "paddle/phi/core/enforce.h"
#include "paddle/phi/core/errors.h"
inline
void
HashCombine
(
std
::
size_t
*
seed
)
{}
// combine hash value
// https://stackoverflow.com/questions/2590677/how-do-i-combine-hash-values-in-c0x
template
<
typename
T
,
typename
...
Rest
>
inline
void
HashCombine
(
std
::
size_t
*
seed
,
const
T
&
v
,
Rest
...
rest
)
{
std
::
hash
<
T
>
hasher
;
*
seed
^=
hasher
(
v
)
+
0x9e3779b9
+
(
*
seed
<<
6
)
+
(
*
seed
>>
2
);
HashCombine
(
seed
,
rest
...);
}
// custom specialization of std::hash can be injected in namespace std
// ref: https://en.cppreference.com/w/cpp/utility/hash
namespace
std
{
template
<
typename
T
>
struct
hash
<
std
::
vector
<
T
>>
{
std
::
size_t
operator
()(
std
::
vector
<
T
>
const
&
vec
)
const
noexcept
{
std
::
size_t
seed
=
0
;
for
(
auto
val
:
vec
)
{
HashCombine
(
&
seed
,
val
);
}
return
seed
;
}
};
}
// namespace std
namespace
phi
{
namespace
autotune
{
template
<
typename
AlgorithmT
>
class
AlgorithmsCache
{
public:
AlgorithmsCache
()
{
hash_
.
clear
();
}
template
<
typename
...
Args
>
size_t
GetKey
(
Args
&&
...
args
)
{
size_t
seed
=
0
;
HashCombine
(
&
seed
,
std
::
forward
<
Args
>
(
args
)...);
return
seed
;
}
AlgorithmT
Get
(
size_t
key
)
{
std
::
lock_guard
<
std
::
mutex
>
lock
(
cache_mutex_
);
PADDLE_ENFORCE_NE
(
hash_
.
find
(
key
),
hash_
.
end
(),
phi
::
errors
::
PreconditionNotMet
(
"The key does not exist."
));
return
hash_
[
key
];
}
bool
Find
(
size_t
key
)
{
bool
ret
=
false
;
std
::
lock_guard
<
std
::
mutex
>
lock
(
cache_mutex_
);
if
(
hash_
.
find
(
key
)
!=
hash_
.
end
())
{
cache_hits_
++
;
ret
=
true
;
}
else
{
cache_misses_
++
;
}
return
ret
;
}
void
Set
(
size_t
key
,
AlgorithmT
algo
)
{
std
::
lock_guard
<
std
::
mutex
>
lock
(
cache_mutex_
);
hash_
[
key
]
=
algo
;
}
float
CacheHitRate
()
const
{
int64_t
num_accesses
=
cache_hits_
+
cache_misses_
;
float
cache_hit_rate
=
static_cast
<
float
>
(
cache_hits_
)
/
static_cast
<
float
>
(
num_accesses
);
return
cache_hit_rate
;
}
// Define the cache key of operator
size_t
ConvKey
(
const
std
::
vector
<
int64_t
>&
x_dims
,
const
std
::
vector
<
int64_t
>&
w_dims
,
const
std
::
vector
<
int
>&
strides
,
const
std
::
vector
<
int
>&
paddings
,
const
std
::
vector
<
int
>&
dilations
,
phi
::
DataType
dtype
)
{
return
GetKey
(
x_dims
,
w_dims
,
strides
,
paddings
,
dilations
,
static_cast
<
int64_t
>
(
dtype
));
}
private:
std
::
unordered_map
<
size_t
,
AlgorithmT
>
hash_
;
std
::
mutex
cache_mutex_
;
int64_t
cache_hits_
=
0
;
int64_t
cache_misses_
=
0
;
};
}
// namespace autotune
}
// namespace phi
paddle/phi/kernels/autotune/cache_test.cc
0 → 100644
浏览文件 @
01b688c0
// Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved.
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
// http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
#include "paddle/phi/kernels/autotune/cache.h"
#include <gtest/gtest.h>
#include <cmath>
#include <functional>
#include "glog/logging.h"
void
Algo
()
{
VLOG
(
3
)
<<
"algo test"
;
}
TEST
(
AlgosCache
,
AlgosCache
)
{
phi
::
autotune
::
AlgorithmsCache
<
std
::
function
<
void
()
>>
cache
;
std
::
vector
<
int64_t
>
x_shape
=
{
4
,
224
,
224
,
3
};
std
::
vector
<
int64_t
>
w_shape
=
{
32
,
3
,
3
,
3
};
std
::
vector
<
int
>
paddings
=
{
0
,
0
};
std
::
vector
<
int
>
strides
=
{
2
,
2
};
std
::
vector
<
int
>
dilations
=
{
1
,
1
};
phi
::
DataType
dtype
=
paddle
::
experimental
::
CppTypeToDataType
<
float
>::
Type
();
auto
key
=
cache
.
ConvKey
(
x_shape
,
w_shape
,
paddings
,
strides
,
dilations
,
dtype
);
EXPECT_EQ
(
cache
.
Find
(
key
),
false
);
cache
.
Set
(
key
,
Algo
);
EXPECT_EQ
(
cache
.
Find
(
key
),
true
);
auto
algo
=
cache
.
Get
(
key
);
algo
();
x_shape
=
{
4
,
128
,
128
,
3
};
key
=
cache
.
ConvKey
(
x_shape
,
w_shape
,
paddings
,
strides
,
dilations
,
dtype
);
EXPECT_EQ
(
cache
.
Find
(
key
),
false
);
float
cache_hit_rate
=
static_cast
<
float
>
(
1
)
/
static_cast
<
float
>
(
3
);
EXPECT_LT
(
std
::
abs
(
cache_hit_rate
-
cache
.
CacheHitRate
()),
1e-5
);
}
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