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0a4ffbc7
编写于
12月 22, 2021
作者:
C
Chen Weihang
提交者:
GitHub
12月 23, 2021
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电子邮件补丁
差异文件
[PTen] Move dot kernel impl (#38359)
* move dot kernel impl * remove needless cmake items
上级
ebbd3564
变更
9
隐藏空白更改
内联
并排
Showing
9 changed file
with
156 addition
and
68 deletion
+156
-68
paddle/pten/api/lib/kernel_declare.h
paddle/pten/api/lib/kernel_declare.h
+2
-2
paddle/pten/include/linalg.h
paddle/pten/include/linalg.h
+2
-1
paddle/pten/kernels/cpu/dot_kernel.cc
paddle/pten/kernels/cpu/dot_kernel.cc
+61
-0
paddle/pten/kernels/cpu/linalg.cc
paddle/pten/kernels/cpu/linalg.cc
+0
-33
paddle/pten/kernels/cpu/linalg.h
paddle/pten/kernels/cpu/linalg.h
+0
-6
paddle/pten/kernels/dot_kernel.h
paddle/pten/kernels/dot_kernel.h
+27
-0
paddle/pten/kernels/gpu/dot_kernel.cu
paddle/pten/kernels/gpu/dot_kernel.cu
+64
-0
paddle/pten/kernels/gpu/linalg.cu
paddle/pten/kernels/gpu/linalg.cu
+0
-20
paddle/pten/kernels/gpu/linalg.h
paddle/pten/kernels/gpu/linalg.h
+0
-6
未找到文件。
paddle/pten/api/lib/kernel_declare.h
浏览文件 @
0a4ffbc7
...
...
@@ -20,13 +20,13 @@ limitations under the License. */
// the kernel declare statement is automatically generated according to the
// file name of the kernel, and this header file will be removed
PT_DECLARE_KERNEL
(
dot
,
CPU
,
ALL_LAYOUT
);
PT_DECLARE_KERNEL
(
matmul
,
CPU
,
ALL_LAYOUT
);
PT_DECLARE_KERNEL
(
cast
,
CPU
,
ALL_LAYOUT
);
PT_DECLARE_KERNEL
(
sign
,
CPU
,
ALL_LAYOUT
);
PT_DECLARE_KERNEL
(
conj
,
CPU
,
ALL_LAYOUT
);
#if defined(PADDLE_WITH_CUDA) || defined(PADDLE_WITH_HIP)
PT_DECLARE_KERNEL
(
dot
,
GPU
,
ALL_LAYOUT
);
PT_DECLARE_KERNEL
(
matmul
,
GPU
,
ALL_LAYOUT
);
PT_DECLARE_KERNEL
(
cast
,
GPU
,
ALL_LAYOUT
);
PT_DECLARE_KERNEL
(
sign
,
GPU
,
ALL_LAYOUT
);
PT_DECLARE_KERNEL
(
conj
,
GPU
,
ALL_LAYOUT
);
...
...
paddle/pten/include/linalg.h
浏览文件 @
0a4ffbc7
...
...
@@ -18,6 +18,7 @@
#include "paddle/pten/api/lib/utils/storage.h"
#include "paddle/pten/include/infermeta.h"
#include "paddle/pten/kernels/cpu/linalg.h"
#include "paddle/pten/kernels/dot_kernel.h"
#include "paddle/pten/kernels/gpu/linalg.h"
namespace
pten
{
...
...
@@ -31,7 +32,7 @@ DenseTensor Dot(const ContextT& dev_ctx,
pten
::
make_intrusive
<
paddle
::
experimental
::
SharedStorage
>
(
dev_ctx
.
GetPlace
()),
std
::
move
(
out_meta
));
Dot
<
T
>
(
dev_ctx
,
x
,
y
,
&
dense_out
);
Dot
<
T
,
ContextT
>
(
dev_ctx
,
x
,
y
,
&
dense_out
);
return
dense_out
;
}
...
...
paddle/pten/kernels/cpu/dot_kernel.cc
0 → 100644
浏览文件 @
0a4ffbc7
// Copyright (c) 2021 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/pten/kernels/dot_kernel.h"
#include "paddle/pten/backends/cpu/cpu_context.h"
#include "paddle/pten/core/kernel_registry.h"
// See Note [ Why still include the fluid headers? ]
#include "paddle/fluid/platform/complex.h"
namespace
pten
{
template
<
typename
T
,
typename
ContextT
>
void
Dot
(
const
ContextT
&
dev_ctx
,
const
DenseTensor
&
x
,
const
DenseTensor
&
y
,
DenseTensor
*
out
)
{
auto
const
*
x_ptr
=
x
.
data
<
T
>
(),
*
x_ptr_
=
&
x_ptr
[
0
];
auto
const
*
y_ptr
=
y
.
data
<
T
>
(),
*
y_ptr_
=
&
y_ptr
[
0
];
auto
*
z
=
out
->
mutable_data
<
T
>
();
// Loop over the total N elements of both operands while sum-reducing every
// B pairs along the way where B is the dimension of the least ordered axis
auto
&&
d
=
x
.
dims
();
auto
const
N
=
x
.
numel
();
auto
const
B
=
d
[
d
.
size
()
-
1
];
for
(
int
j
=
0
;
j
<
N
/
B
;
j
++
)
{
T
ss
=
0
;
for
(
int
i
=
0
;
i
<
B
;
i
++
)
ss
+=
(
*
x_ptr_
++
)
*
(
*
y_ptr_
++
);
z
[
j
]
=
ss
;
}
}
}
// namespace pten
using
complex64
=
::
paddle
::
platform
::
complex
<
float
>
;
using
complex128
=
::
paddle
::
platform
::
complex
<
double
>
;
PT_REGISTER_CTX_KERNEL
(
dot
,
CPU
,
ALL_LAYOUT
,
pten
::
Dot
,
float
,
double
,
int
,
int64_t
,
complex64
,
complex128
)
{}
paddle/pten/kernels/cpu/linalg.cc
浏览文件 @
0a4ffbc7
...
...
@@ -25,28 +25,6 @@
namespace
pten
{
template
<
typename
T
>
void
Dot
(
const
CPUContext
&
dev_ctx
,
const
DenseTensor
&
x
,
const
DenseTensor
&
y
,
DenseTensor
*
out
)
{
auto
const
*
x_ptr
=
x
.
data
<
T
>
(),
*
x_ptr_
=
&
x_ptr
[
0
];
auto
const
*
y_ptr
=
y
.
data
<
T
>
(),
*
y_ptr_
=
&
y_ptr
[
0
];
auto
*
z
=
out
->
mutable_data
<
T
>
();
// Loop over the total N elements of both operands while sum-reducing every
// B pairs along the way where B is the dimension of the least ordered axis
auto
&&
d
=
x
.
dims
();
auto
const
N
=
x
.
numel
();
auto
const
B
=
d
[
d
.
size
()
-
1
];
for
(
int
j
=
0
;
j
<
N
/
B
;
j
++
)
{
T
ss
=
0
;
for
(
int
i
=
0
;
i
<
B
;
i
++
)
ss
+=
(
*
x_ptr_
++
)
*
(
*
y_ptr_
++
);
z
[
j
]
=
ss
;
}
}
template
<
typename
T
>
void
Matmul
(
const
CPUContext
&
dev_ctx
,
const
DenseTensor
&
x
,
...
...
@@ -73,17 +51,6 @@ void Matmul(const CPUContext& dev_ctx,
using
complex64
=
::
paddle
::
platform
::
complex
<
float
>
;
using
complex128
=
::
paddle
::
platform
::
complex
<
double
>
;
PT_REGISTER_KERNEL
(
dot
,
CPU
,
ALL_LAYOUT
,
pten
::
Dot
,
float
,
double
,
int
,
int64_t
,
complex64
,
complex128
)
{}
PT_REGISTER_KERNEL
(
matmul
,
CPU
,
ALL_LAYOUT
,
...
...
paddle/pten/kernels/cpu/linalg.h
浏览文件 @
0a4ffbc7
...
...
@@ -22,12 +22,6 @@
namespace
pten
{
template
<
typename
T
>
void
Dot
(
const
CPUContext
&
dev_ctx
,
const
DenseTensor
&
x
,
const
DenseTensor
&
y
,
DenseTensor
*
out
);
template
<
typename
T
>
void
Matmul
(
const
CPUContext
&
dev_ctx
,
const
DenseTensor
&
x
,
...
...
paddle/pten/kernels/dot_kernel.h
0 → 100644
浏览文件 @
0a4ffbc7
// Copyright (c) 2021 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 "paddle/pten/core/dense_tensor.h"
namespace
pten
{
template
<
typename
T
,
typename
ContextT
>
void
Dot
(
const
ContextT
&
dev_ctx
,
const
DenseTensor
&
x
,
const
DenseTensor
&
y
,
DenseTensor
*
out
);
}
// namespace pten
paddle/pten/kernels/
hybird/eigen/dot.h
→
paddle/pten/kernels/
gpu/dot_kernel.cu
浏览文件 @
0a4ffbc7
/* Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved.
// Copyright (c) 2021 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.
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
#include "paddle/pten/kernels/dot_kernel.h"
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 "paddle/pten/core/dense_tensor.h"
#include "paddle/pten/backends/gpu/gpu_context.h"
#include "paddle/pten/core/kernel_registry.h"
#include "paddle/pten/kernels/hybird/eigen/common.h"
// See Note [ Why still include the fluid headers? ]
#include "paddle/fluid/operators/eigen/eigen_function.h"
#include "paddle/fluid/platform/complex.h"
namespace
pten
{
namespace
eigen
{
template
<
typename
DevCtx
,
typename
T
>
void
Dot
(
const
DevCtx
&
dev_ctx
,
template
<
typename
T
,
typename
Context
T
>
void
Dot
(
const
ContextT
&
dev_ctx
,
const
DenseTensor
&
x
,
const
DenseTensor
&
y
,
DenseTensor
*
out
)
{
...
...
@@ -46,5 +47,18 @@ void Dot(const DevCtx& dev_ctx,
}
}
}
// namespace eigen
}
// namespace pten
using
complex64
=
::
paddle
::
platform
::
complex
<
float
>
;
using
complex128
=
::
paddle
::
platform
::
complex
<
double
>
;
PT_REGISTER_CTX_KERNEL
(
dot
,
GPU
,
ALL_LAYOUT
,
pten
::
Dot
,
float
,
double
,
int
,
int64_t
,
complex64
,
complex128
)
{}
paddle/pten/kernels/gpu/linalg.cu
浏览文件 @
0a4ffbc7
...
...
@@ -15,7 +15,6 @@
#include "paddle/pten/kernels/gpu/linalg.h"
#include "paddle/pten/core/kernel_registry.h"
#include "paddle/pten/kernels/hybird/eigen/dot.h"
#include "paddle/pten/kernels/hybird/math/matmul_func.h"
// See Note [ Why still include the fluid headers? ]
...
...
@@ -23,14 +22,6 @@
namespace
pten
{
template
<
typename
T
>
void
Dot
(
const
GPUContext
&
dev_ctx
,
const
DenseTensor
&
x
,
const
DenseTensor
&
y
,
DenseTensor
*
out
)
{
eigen
::
Dot
<
GPUContext
,
T
>
(
dev_ctx
,
x
,
y
,
out
);
}
template
<
typename
T
>
void
Matmul
(
const
GPUContext
&
dev_ctx
,
const
DenseTensor
&
x
,
...
...
@@ -58,17 +49,6 @@ using float16 = paddle::platform::float16;
using
complex64
=
::
paddle
::
platform
::
complex
<
float
>
;
using
complex128
=
::
paddle
::
platform
::
complex
<
double
>
;
PT_REGISTER_KERNEL
(
dot
,
GPU
,
ALL_LAYOUT
,
pten
::
Dot
,
float
,
double
,
int
,
int64_t
,
complex64
,
complex128
)
{}
PT_REGISTER_KERNEL
(
matmul
,
GPU
,
ALL_LAYOUT
,
...
...
paddle/pten/kernels/gpu/linalg.h
浏览文件 @
0a4ffbc7
...
...
@@ -22,12 +22,6 @@
namespace
pten
{
template
<
typename
T
>
void
Dot
(
const
GPUContext
&
dev_ctx
,
const
DenseTensor
&
x
,
const
DenseTensor
&
y
,
DenseTensor
*
out
);
template
<
typename
T
>
void
Matmul
(
const
GPUContext
&
dev_ctx
,
const
DenseTensor
&
x
,
...
...
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