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23a79923
编写于
8月 29, 2022
作者:
Z
zhangbo9674
提交者:
GitHub
8月 29, 2022
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电子邮件补丁
差异文件
move expand_v2 to phi, test=kunlun (#45469)
上级
de436f07
变更
2
显示空白变更内容
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并排
Showing
2 changed file
with
133 addition
and
142 deletion
+133
-142
paddle/fluid/operators/expand_v2_op_xpu.cc
paddle/fluid/operators/expand_v2_op_xpu.cc
+0
-142
paddle/phi/kernels/xpu/expand_kernel.cc
paddle/phi/kernels/xpu/expand_kernel.cc
+133
-0
未找到文件。
paddle/fluid/operators/expand_v2_op_xpu.cc
已删除
100644 → 0
浏览文件 @
de436f07
/* 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. */
#ifdef PADDLE_WITH_XPU
#include "paddle/fluid/framework/op_registry.h"
#include "paddle/fluid/operators/expand_v2_op.h"
namespace
paddle
{
namespace
operators
{
template
<
typename
T
>
class
ExpandV2XPUKernel
:
public
framework
::
OpKernel
<
T
>
{
using
XPUType
=
typename
XPUTypeTrait
<
T
>::
Type
;
public:
void
Compute
(
const
framework
::
ExecutionContext
&
context
)
const
override
{
auto
*
X
=
context
.
Input
<
framework
::
Tensor
>
(
"X"
);
auto
*
Out
=
context
.
Output
<
framework
::
Tensor
>
(
"Out"
);
auto
in_dims
=
X
->
dims
();
auto
expand_shape
=
get_expand_shape
(
context
);
auto
vec_in_dims
=
phi
::
vectorize
<
int
>
(
in_dims
);
auto
diff
=
expand_shape
.
size
()
-
vec_in_dims
.
size
();
vec_in_dims
.
insert
(
vec_in_dims
.
begin
(),
diff
,
1
);
std
::
vector
<
int
>
final_expand_shape
(
vec_in_dims
.
size
());
for
(
size_t
i
=
0
;
i
<
vec_in_dims
.
size
();
++
i
)
{
PADDLE_ENFORCE_NE
(
expand_shape
[
i
],
0
,
platform
::
errors
::
InvalidArgument
(
"The expanded size cannot be zero."
));
if
(
i
<
diff
)
{
// expand_shape = [3,4,-1,-1], X = [10,2] -->
// final_expand_shape = [3,4,10,2]
PADDLE_ENFORCE_GT
(
expand_shape
[
i
],
0
,
platform
::
errors
::
InvalidArgument
(
"The expanded size (%d) for non-existing dimensions must be "
"positive for expand_v2 op."
,
expand_shape
[
i
]));
final_expand_shape
[
i
]
=
expand_shape
[
i
];
}
else
if
(
expand_shape
[
i
]
>
0
)
{
// expand_shape = [3,4,10,4], X =
// [10,1] --> final_expand_shape =
// [3,4,10,4]
if
(
vec_in_dims
[
i
]
!=
1
)
{
PADDLE_ENFORCE_EQ
(
vec_in_dims
[
i
],
expand_shape
[
i
],
platform
::
errors
::
InvalidArgument
(
"The value (%d) of the non-singleton dimension does not match"
" the corresponding value (%d) in shape for expand_v2 op."
,
vec_in_dims
[
i
],
expand_shape
[
i
]));
final_expand_shape
[
i
]
=
expand_shape
[
i
];
}
else
{
final_expand_shape
[
i
]
=
expand_shape
[
i
];
}
}
else
{
// expand_shape = [3,4,-1,-1], X = [10,2] --> final_expand_shape
// = [3,4,10,2]
PADDLE_ENFORCE_EQ
(
expand_shape
[
i
],
-
1
,
platform
::
errors
::
InvalidArgument
(
"When the value in shape is negative for expand_v2 op, "
"only -1 is supported, but the value received is %d."
,
expand_shape
[
i
]));
final_expand_shape
[
i
]
=
vec_in_dims
[
i
];
}
}
auto
rank
=
X
->
dims
().
size
();
PADDLE_ENFORCE_GE
(
rank
,
1
,
platform
::
errors
::
InvalidArgument
(
"The rank of the input 'X' for expand_v2_npu op must be positive, "
"but the value received is %d."
,
rank
));
auto
shape_size
=
final_expand_shape
.
size
();
PADDLE_ENFORCE_GE
(
shape_size
,
rank
,
platform
::
errors
::
InvalidArgument
(
"The number (%d) of elements of 'shape' for expand_v2_npu op must "
"be "
"greater than or equal to the rank (%d) of the input 'X'."
,
shape_size
,
rank
));
framework
::
DDim
out_dims
=
phi
::
make_ddim
(
final_expand_shape
);
Out
->
Resize
(
out_dims
);
Out
->
mutable_data
<
T
>
(
context
.
GetPlace
());
auto
&
x_shape
=
vec_in_dims
;
auto
out_shape
=
phi
::
vectorize
<
int
>
(
out_dims
);
const
auto
&
dev_ctx
=
context
.
template
device_context
<
paddle
::
platform
::
XPUDeviceContext
>();
int
r
=
XPU_SUCCESS
;
if
(
std
::
is_same
<
T
,
bool
>::
value
)
{
auto
x_data
=
reinterpret_cast
<
const
int8_t
*>
(
X
->
data
<
T
>
());
auto
out_data
=
reinterpret_cast
<
int8_t
*>
(
Out
->
data
<
T
>
());
r
=
xpu
::
broadcast
<
int8_t
>
(
dev_ctx
.
x_context
(),
x_data
,
out_data
,
x_shape
,
out_shape
);
}
else
{
auto
x_data
=
reinterpret_cast
<
const
XPUType
*>
(
X
->
data
<
T
>
());
auto
out_data
=
reinterpret_cast
<
XPUType
*>
(
Out
->
data
<
T
>
());
r
=
xpu
::
broadcast
<
XPUType
>
(
dev_ctx
.
x_context
(),
x_data
,
out_data
,
x_shape
,
out_shape
);
}
PADDLE_ENFORCE_EQ
(
r
,
XPU_SUCCESS
,
platform
::
errors
::
External
(
"XPU API(broadcast) return wrong "
"value[%d %s] in ExpandV2XPUKernel."
,
r
,
XPUAPIErrorMsg
[
r
]));
}
};
}
// namespace operators
}
// namespace paddle
namespace
ops
=
paddle
::
operators
;
REGISTER_OP_XPU_KERNEL
(
expand_v2
,
ops
::
ExpandV2XPUKernel
<
float
>
,
ops
::
ExpandV2XPUKernel
<
paddle
::
platform
::
float16
>
,
ops
::
ExpandV2XPUKernel
<
bool
>
,
ops
::
ExpandV2XPUKernel
<
int
>
,
ops
::
ExpandV2XPUKernel
<
int64_t
>
);
#endif
paddle/phi/kernels/xpu/expand_kernel.cc
0 → 100644
浏览文件 @
23a79923
// 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/expand_kernel.h"
#include "paddle/phi/backends/xpu/enforce_xpu.h"
#include "paddle/phi/core/kernel_registry.h"
namespace
phi
{
template
<
typename
T
,
typename
Context
>
void
ExpandKernel
(
const
Context
&
ctx
,
const
DenseTensor
&
x
,
const
IntArray
&
shape
,
DenseTensor
*
out
)
{
using
XPUType
=
typename
XPUTypeTrait
<
T
>::
Type
;
auto
in_dims
=
x
.
dims
();
auto
expand_shape
=
shape
.
GetData
();
auto
vec_in_dims
=
phi
::
vectorize
<
int
>
(
in_dims
);
auto
diff
=
expand_shape
.
size
()
-
vec_in_dims
.
size
();
vec_in_dims
.
insert
(
vec_in_dims
.
begin
(),
diff
,
1
);
std
::
vector
<
int
>
final_expand_shape
(
vec_in_dims
.
size
());
for
(
size_t
i
=
0
;
i
<
vec_in_dims
.
size
();
++
i
)
{
PADDLE_ENFORCE_NE
(
expand_shape
[
i
],
0
,
phi
::
errors
::
InvalidArgument
(
"The expanded size cannot be zero."
));
if
(
i
<
diff
)
{
// expand_shape = [3,4,-1,-1], X = [10,2] -->
// final_expand_shape = [3,4,10,2]
PADDLE_ENFORCE_GT
(
expand_shape
[
i
],
0
,
phi
::
errors
::
InvalidArgument
(
"The expanded size (%d) for non-existing dimensions must be "
"positive for expand_v2 op."
,
expand_shape
[
i
]));
final_expand_shape
[
i
]
=
expand_shape
[
i
];
}
else
if
(
expand_shape
[
i
]
>
0
)
{
// expand_shape = [3,4,10,4], X =
// [10,1] --> final_expand_shape =
// [3,4,10,4]
if
(
vec_in_dims
[
i
]
!=
1
)
{
PADDLE_ENFORCE_EQ
(
vec_in_dims
[
i
],
expand_shape
[
i
],
phi
::
errors
::
InvalidArgument
(
"The value (%d) of the non-singleton dimension does not match"
" the corresponding value (%d) in shape for expand_v2 op."
,
vec_in_dims
[
i
],
expand_shape
[
i
]));
final_expand_shape
[
i
]
=
expand_shape
[
i
];
}
else
{
final_expand_shape
[
i
]
=
expand_shape
[
i
];
}
}
else
{
// expand_shape = [3,4,-1,-1], X = [10,2] --> final_expand_shape
// = [3,4,10,2]
PADDLE_ENFORCE_EQ
(
expand_shape
[
i
],
-
1
,
phi
::
errors
::
InvalidArgument
(
"When the value in shape is negative for expand_v2 op, "
"only -1 is supported, but the value received is %d."
,
expand_shape
[
i
]));
final_expand_shape
[
i
]
=
vec_in_dims
[
i
];
}
}
auto
rank
=
x
.
dims
().
size
();
PADDLE_ENFORCE_GE
(
rank
,
1
,
phi
::
errors
::
InvalidArgument
(
"The rank of the input 'X' for expand_v2_npu op must be positive, "
"but the value received is %d."
,
rank
));
auto
shape_size
=
final_expand_shape
.
size
();
PADDLE_ENFORCE_GE
(
shape_size
,
rank
,
phi
::
errors
::
InvalidArgument
(
"The number (%d) of elements of 'shape' for expand_v2_npu op must "
"be "
"greater than or equal to the rank (%d) of the input 'X'."
,
shape_size
,
rank
));
DDim
out_dims
=
phi
::
make_ddim
(
final_expand_shape
);
out
->
Resize
(
out_dims
);
ctx
.
template
Alloc
<
T
>(
out
);
auto
&
x_shape
=
vec_in_dims
;
auto
out_shape
=
phi
::
vectorize
<
int
>
(
out_dims
);
int
r
=
XPU_SUCCESS
;
if
(
std
::
is_same
<
T
,
bool
>::
value
)
{
auto
x_data
=
reinterpret_cast
<
const
int8_t
*>
(
x
.
data
<
T
>
());
auto
out_data
=
reinterpret_cast
<
int8_t
*>
(
out
->
data
<
T
>
());
r
=
xpu
::
broadcast
<
int8_t
>
(
ctx
.
x_context
(),
x_data
,
out_data
,
x_shape
,
out_shape
);
}
else
{
auto
x_data
=
reinterpret_cast
<
const
XPUType
*>
(
x
.
data
<
T
>
());
auto
out_data
=
reinterpret_cast
<
XPUType
*>
(
out
->
data
<
T
>
());
r
=
xpu
::
broadcast
<
XPUType
>
(
ctx
.
x_context
(),
x_data
,
out_data
,
x_shape
,
out_shape
);
}
PADDLE_ENFORCE_EQ
(
r
,
XPU_SUCCESS
,
phi
::
errors
::
External
(
"XPU API(broadcast) return wrong "
"value[%d %s] in ExpandV2XPUKernel."
,
r
,
XPUAPIErrorMsg
[
r
]));
}
}
// namespace phi
PD_REGISTER_KERNEL
(
expand
,
XPU
,
ALL_LAYOUT
,
phi
::
ExpandKernel
,
float
,
phi
::
dtype
::
float16
,
bool
,
int
,
int64_t
)
{}
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