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体验新版 GitCode,发现更多精彩内容 >>
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94fe929a
编写于
12月 08, 2022
作者:
H
haosicheng
提交者:
GitHub
12月 08, 2022
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电子邮件补丁
差异文件
[XPU] add set_value and set_value_grad (#48845)
上级
95332bef
变更
4
隐藏空白更改
内联
并排
Showing
4 changed file
with
392 addition
and
0 deletion
+392
-0
paddle/phi/backends/xpu/xpu2_op_list.cc
paddle/phi/backends/xpu/xpu2_op_list.cc
+7
-0
paddle/phi/kernels/xpu/set_value_grad_kernel.cc
paddle/phi/kernels/xpu/set_value_grad_kernel.cc
+128
-0
paddle/phi/kernels/xpu/set_value_kernel.cc
paddle/phi/kernels/xpu/set_value_kernel.cc
+165
-0
python/paddle/fluid/tests/unittests/xpu/test_set_value_op_xpu.py
...paddle/fluid/tests/unittests/xpu/test_set_value_op_xpu.py
+92
-0
未找到文件。
paddle/phi/backends/xpu/xpu2_op_list.cc
浏览文件 @
94fe929a
...
...
@@ -417,6 +417,13 @@ XPUOpMap& get_kl2_ops() {
phi
::
DataType
::
FLOAT32
})},
{
"sampling_id"
,
XPUKernelSet
({
phi
::
DataType
::
FLOAT32
,
phi
::
DataType
::
FLOAT64
})},
{
"set_value"
,
XPUKernelSet
({
phi
::
DataType
::
INT32
,
phi
::
DataType
::
INT64
,
phi
::
DataType
::
FLOAT16
,
phi
::
DataType
::
FLOAT32
})},
{
"set_value_grad"
,
XPUKernelSet
({
phi
::
DataType
::
FLOAT16
,
phi
::
DataType
::
FLOAT32
})},
{
"sgd"
,
XPUKernelSet
({
phi
::
DataType
::
FLOAT32
,
phi
::
DataType
::
FLOAT16
})},
{
"sgd_dense_param_sparse_grad"
,
XPUKernelSet
({
phi
::
DataType
::
FLOAT32
,
phi
::
DataType
::
FLOAT16
})},
...
...
paddle/phi/kernels/xpu/set_value_grad_kernel.cc
0 → 100644
浏览文件 @
94fe929a
// 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/set_value_grad_kernel.h"
#include "paddle/phi/backends/xpu/enforce_xpu.h"
#include "paddle/phi/backends/xpu/xpu_context.h"
#include "paddle/phi/core/kernel_registry.h"
#include "paddle/phi/common/int_array.h"
#include "paddle/phi/common/scalar.h"
#include "paddle/phi/core/dense_tensor.h"
#include "paddle/phi/core/tensor_utils.h"
#include "paddle/phi/kernels/empty_kernel.h"
#include "paddle/phi/kernels/funcs/broadcast_function.h"
#include "paddle/phi/kernels/funcs/eigen/common.h"
#include "paddle/phi/kernels/funcs/eigen/eigen_function.h"
#include "paddle/phi/kernels/funcs/elementwise_functor.h"
#include "paddle/phi/kernels/funcs/slice_utils.h"
namespace
phi
{
template
<
typename
T
,
typename
Context
>
void
SetValueGradKernel
(
const
Context
&
dev_ctx
,
const
DenseTensor
&
out_grad
,
const
IntArray
&
starts
,
const
IntArray
&
ends
,
const
IntArray
&
steps
,
const
std
::
vector
<
int64_t
>&
axes
,
const
std
::
vector
<
int64_t
>&
decrease_axes
,
const
std
::
vector
<
int64_t
>&
none_axes
,
DenseTensor
*
x_grad
,
DenseTensor
*
value_grad
)
{
using
XPUType
=
typename
XPUTypeTrait
<
T
>::
Type
;
x_grad
->
Resize
(
out_grad
.
dims
());
dev_ctx
.
template
Alloc
<
T
>(
x_grad
);
dev_ctx
.
template
Alloc
<
T
>(
value_grad
);
const
XPUType
*
dy_data
=
reinterpret_cast
<
const
XPUType
*>
(
out_grad
.
data
<
T
>
());
XPUType
*
dx_data
=
reinterpret_cast
<
XPUType
*>
(
x_grad
->
data
<
T
>
());
XPUType
*
dv_data
=
reinterpret_cast
<
XPUType
*>
(
value_grad
->
data
<
T
>
());
std
::
vector
<
int64_t
>
starts_vec
=
starts
.
GetData
();
std
::
vector
<
int64_t
>
ends_vec
=
ends
.
GetData
();
std
::
vector
<
int64_t
>
steps_vec
=
steps
.
GetData
();
auto
dy_dims
=
out_grad
.
dims
();
std
::
vector
<
int
>
dy_shape
;
for
(
int
i
=
0
;
i
<
dy_dims
.
size
();
++
i
)
{
dy_shape
.
push_back
(
dy_dims
[
i
]);
}
auto
dv_dims
=
value_grad
->
dims
();
std
::
vector
<
int
>
dv_shape
;
for
(
int
i
=
0
;
i
<
dv_dims
.
size
();
++
i
)
{
dv_shape
.
push_back
(
dv_dims
[
i
]);
}
auto
dx_dims
=
x_grad
->
dims
();
std
::
vector
<
int
>
dx_shape
;
for
(
int
i
=
0
;
i
<
dx_dims
.
size
();
++
i
)
{
dx_shape
.
push_back
(
dx_dims
[
i
]);
}
std
::
vector
<
int
>
starts_vec_int32
;
for
(
size_t
i
=
0
;
i
<
starts_vec
.
size
();
++
i
)
{
starts_vec_int32
.
push_back
(
starts_vec
[
i
]);
}
std
::
vector
<
int
>
ends_vec_int32
;
for
(
size_t
i
=
0
;
i
<
ends_vec
.
size
();
++
i
)
{
ends_vec_int32
.
push_back
(
ends_vec
[
i
]);
}
std
::
vector
<
int
>
steps_vec_int32
;
for
(
size_t
i
=
0
;
i
<
steps_vec
.
size
();
++
i
)
{
steps_vec_int32
.
push_back
(
steps_vec
[
i
]);
}
std
::
vector
<
int
>
axes_int32
;
for
(
size_t
i
=
0
;
i
<
axes
.
size
();
++
i
)
{
axes_int32
.
push_back
(
axes
[
i
]);
}
std
::
vector
<
int
>
decrease_axes_int32
;
for
(
size_t
i
=
0
;
i
<
decrease_axes
.
size
();
++
i
)
{
decrease_axes_int32
.
push_back
(
decrease_axes
[
i
]);
}
std
::
vector
<
int
>
none_axes_int32
;
for
(
size_t
i
=
0
;
i
<
none_axes
.
size
();
++
i
)
{
none_axes_int32
.
push_back
(
none_axes
[
i
]);
}
int
r
=
xpu
::
set_value_grad
(
dev_ctx
.
x_context
(),
dy_data
,
dx_data
,
dv_data
,
dy_shape
,
dv_shape
,
starts_vec_int32
,
ends_vec_int32
,
steps_vec_int32
,
axes_int32
,
decrease_axes_int32
,
none_axes_int32
);
PADDLE_ENFORCE_XDNN_SUCCESS
(
r
,
"set_value_grad"
);
}
}
// namespace phi
PD_REGISTER_KERNEL
(
set_value_grad
,
XPU
,
ALL_LAYOUT
,
phi
::
SetValueGradKernel
,
float
,
phi
::
dtype
::
float16
)
{}
paddle/phi/kernels/xpu/set_value_kernel.cc
0 → 100644
浏览文件 @
94fe929a
// 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/set_value_kernel.h"
#include "paddle/phi/backends/xpu/enforce_xpu.h"
#include "paddle/phi/backends/xpu/xpu_context.h"
#include "paddle/phi/core/kernel_registry.h"
#include "paddle/phi/common/int_array.h"
#include "paddle/phi/common/scalar.h"
#include "paddle/phi/core/dense_tensor.h"
#include "paddle/phi/core/tensor_utils.h"
#include "paddle/phi/kernels/empty_kernel.h"
#include "paddle/phi/kernels/funcs/broadcast_function.h"
#include "paddle/phi/kernels/funcs/eigen/common.h"
#include "paddle/phi/kernels/funcs/eigen/eigen_function.h"
#include "paddle/phi/kernels/funcs/elementwise_functor.h"
#include "paddle/phi/kernels/funcs/slice_utils.h"
namespace
phi
{
template
<
typename
T
,
typename
Context
>
void
SetTensorValueKernel
(
const
Context
&
dev_ctx
,
const
DenseTensor
&
x
,
const
DenseTensor
&
value
,
const
IntArray
&
starts
,
const
IntArray
&
ends
,
const
IntArray
&
steps
,
const
std
::
vector
<
int64_t
>&
axes
,
const
std
::
vector
<
int64_t
>&
decrease_axes
,
const
std
::
vector
<
int64_t
>&
none_axes
,
DenseTensor
*
out
)
{
using
XPUType
=
typename
XPUTypeTrait
<
T
>::
Type
;
out
->
Resize
(
x
.
dims
());
dev_ctx
.
template
Alloc
<
T
>(
out
);
const
XPUType
*
x_data
=
reinterpret_cast
<
const
XPUType
*>
(
x
.
data
<
T
>
());
const
XPUType
*
v_data
=
reinterpret_cast
<
const
XPUType
*>
(
value
.
data
<
T
>
());
XPUType
*
y_data
=
reinterpret_cast
<
XPUType
*>
(
out
->
data
<
T
>
());
std
::
vector
<
int64_t
>
starts_vec
=
starts
.
GetData
();
std
::
vector
<
int64_t
>
ends_vec
=
ends
.
GetData
();
std
::
vector
<
int64_t
>
steps_vec
=
steps
.
GetData
();
std
::
vector
<
int
>
starts_vec_int32
;
for
(
size_t
i
=
0
;
i
<
starts_vec
.
size
();
++
i
)
{
starts_vec_int32
.
push_back
(
starts_vec
[
i
]);
}
std
::
vector
<
int
>
ends_vec_int32
;
for
(
size_t
i
=
0
;
i
<
ends_vec
.
size
();
++
i
)
{
ends_vec_int32
.
push_back
(
ends_vec
[
i
]);
}
std
::
vector
<
int
>
steps_vec_int32
;
for
(
size_t
i
=
0
;
i
<
steps_vec
.
size
();
++
i
)
{
steps_vec_int32
.
push_back
(
steps_vec
[
i
]);
}
std
::
vector
<
int
>
axes_int32
;
for
(
size_t
i
=
0
;
i
<
axes
.
size
();
++
i
)
{
axes_int32
.
push_back
(
axes
[
i
]);
}
std
::
vector
<
int
>
decrease_axes_int32
;
for
(
size_t
i
=
0
;
i
<
decrease_axes
.
size
();
++
i
)
{
decrease_axes_int32
.
push_back
(
decrease_axes
[
i
]);
}
std
::
vector
<
int
>
none_axes_int32
;
for
(
size_t
i
=
0
;
i
<
none_axes
.
size
();
++
i
)
{
none_axes_int32
.
push_back
(
none_axes
[
i
]);
}
auto
x_dims
=
x
.
dims
();
std
::
vector
<
int
>
x_shape
;
for
(
int
i
=
0
;
i
<
x_dims
.
size
();
++
i
)
{
x_shape
.
push_back
(
x_dims
[
i
]);
}
auto
v_dims
=
value
.
dims
();
std
::
vector
<
int
>
v_shape
;
for
(
int
i
=
0
;
i
<
v_dims
.
size
();
++
i
)
{
v_shape
.
push_back
(
v_dims
[
i
]);
}
int
r
=
xpu
::
set_value
(
dev_ctx
.
x_context
(),
x_data
,
v_data
,
y_data
,
x_shape
,
v_shape
,
starts_vec_int32
,
ends_vec_int32
,
steps_vec_int32
,
axes_int32
,
decrease_axes_int32
,
none_axes_int32
);
PADDLE_ENFORCE_XDNN_SUCCESS
(
r
,
"set_value"
);
}
template
<
typename
T
,
typename
Context
>
void
SetValueKernel
(
const
Context
&
dev_ctx
,
const
DenseTensor
&
x
,
const
IntArray
&
starts
,
const
IntArray
&
ends
,
const
IntArray
&
steps
,
const
std
::
vector
<
int64_t
>&
axes
,
const
std
::
vector
<
int64_t
>&
decrease_axes
,
const
std
::
vector
<
int64_t
>&
none_axes
,
const
std
::
vector
<
int64_t
>&
shape
,
const
std
::
vector
<
Scalar
>&
values
,
DenseTensor
*
out
)
{
std
::
vector
<
T
>
assgin_values
;
assgin_values
.
reserve
(
values
.
size
());
for
(
const
auto
&
val
:
values
)
{
assgin_values
.
push_back
(
val
.
to
<
T
>
());
}
DenseTensor
value_tensor
=
Empty
<
T
>
(
dev_ctx
,
shape
);
paddle
::
framework
::
TensorFromVector
(
assgin_values
,
dev_ctx
,
&
value_tensor
);
value_tensor
.
Resize
(
phi
::
make_ddim
(
shape
));
SetTensorValueKernel
<
T
,
Context
>
(
dev_ctx
,
x
,
value_tensor
,
starts
,
ends
,
steps
,
axes
,
decrease_axes
,
none_axes
,
out
);
}
}
// namespace phi
PD_REGISTER_KERNEL
(
set_value
,
XPU
,
ALL_LAYOUT
,
phi
::
SetValueKernel
,
float
,
phi
::
dtype
::
float16
,
int
,
int64_t
)
{}
PD_REGISTER_KERNEL
(
set_value_with_tensor
,
XPU
,
ALL_LAYOUT
,
phi
::
SetTensorValueKernel
,
float
,
phi
::
dtype
::
float16
,
int
,
int64_t
)
{}
python/paddle/fluid/tests/unittests/xpu/test_set_value_op_xpu.py
0 → 100644
浏览文件 @
94fe929a
# 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.
# Test set_value op in static mode
import
sys
import
unittest
import
numpy
as
np
sys
.
path
.
append
(
"../"
)
from
op_test_xpu
import
XPUOpTest
from
xpu.get_test_cover_info
import
(
XPUOpTestWrapper
,
create_test_class
,
get_xpu_op_support_types
,
)
import
paddle
from
paddle.fluid.framework
import
_test_eager_guard
class
XPUTestSetValueOp
(
XPUOpTestWrapper
):
def
__init__
(
self
):
self
.
op_name
=
'set_value'
self
.
use_dynamic_create_class
=
False
class
TestSetValueOp
(
XPUOpTest
):
def
setUp
(
self
):
paddle
.
enable_static
()
self
.
__class__
.
op_type
=
"set_value"
self
.
place
=
paddle
.
XPUPlace
(
0
)
self
.
shape
=
[
2
]
self
.
value
=
6
self
.
dtype
=
"float32"
self
.
__class__
.
dtype
=
self
.
dtype
self
.
data
=
np
.
ones
(
self
.
shape
).
astype
(
self
.
dtype
)
self
.
program
=
paddle
.
static
.
Program
()
def
_call_setitem
(
self
,
x
):
x
[
0
]
=
self
.
value
def
_get_answer
(
self
):
self
.
data
[
0
]
=
self
.
value
class
TestSetValueOp1
(
TestSetValueOp
):
def
_run_static
(
self
):
paddle
.
enable_static
()
with
paddle
.
static
.
program_guard
(
self
.
program
):
x
=
paddle
.
ones
(
shape
=
self
.
shape
,
dtype
=
self
.
dtype
)
self
.
_call_setitem
(
x
)
exe
=
paddle
.
static
.
Executor
(
paddle
.
XPUPlace
(
0
))
out
=
exe
.
run
(
self
.
program
,
fetch_list
=
[
x
])
paddle
.
disable_static
()
return
out
def
func_test_api
(
self
):
static_out
=
self
.
_run_static
()
self
.
_get_answer
()
error_msg
=
(
"
\n
In {} mode:
\n
Expected res =
\n
{},
\n\n
but received :
\n
{}"
)
self
.
assertTrue
(
(
self
.
data
==
static_out
).
all
(),
msg
=
error_msg
.
format
(
"static"
,
self
.
data
,
static_out
),
)
def
test_api
(
self
):
with
_test_eager_guard
():
self
.
func_test_api
()
self
.
func_test_api
()
support_types
=
get_xpu_op_support_types
(
'set_value'
)
for
stype
in
support_types
:
create_test_class
(
globals
(),
XPUTestSetValueOp
,
stype
)
if
__name__
==
'__main__'
:
unittest
.
main
()
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