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体验新版 GitCode,发现更多精彩内容 >>
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25e723e7
编写于
4月 25, 2021
作者:
L
liym27
提交者:
GitHub
4月 25, 2021
浏览文件
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浏览文件
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电子邮件补丁
差异文件
[Setitem] Support grad computation of op set_value (#32431)
上级
5943ff7b
变更
3
隐藏空白更改
内联
并排
Showing
3 changed file
with
134 addition
and
9 deletion
+134
-9
paddle/fluid/operators/set_value_op.cc
paddle/fluid/operators/set_value_op.cc
+61
-8
paddle/fluid/pybind/imperative.cc
paddle/fluid/pybind/imperative.cc
+2
-1
python/paddle/fluid/tests/unittests/test_set_value_op.py
python/paddle/fluid/tests/unittests/test_set_value_op.py
+71
-0
未找到文件。
paddle/fluid/operators/set_value_op.cc
浏览文件 @
25e723e7
...
...
@@ -146,22 +146,75 @@ Assignment to a Tensor in static mode.
)DOC"
);
}
};
template
<
typename
T
>
class
SetValueGradMaker
:
public
framework
::
SingleGradOpMaker
<
T
>
{
public:
using
framework
::
SingleGradOpMaker
<
T
>::
SingleGradOpMaker
;
protected:
void
Apply
(
GradOpPtr
<
T
>
op
)
const
override
{
if
(
this
->
HasInput
(
"ValueTensor"
))
{
op
->
SetType
(
"slice"
);
op
->
SetInput
(
"Input"
,
this
->
OutputGrad
(
"Out"
));
if
(
this
->
HasInput
(
"StartsTensorList"
))
{
op
->
SetInput
(
"StartsTensorList"
,
this
->
Input
(
"StartsTensorList"
));
}
if
(
this
->
HasInput
(
"EndsTensorList"
))
{
op
->
SetInput
(
"EndsTensorList"
,
this
->
Input
(
"EndsTensorList"
));
}
// convert std::vector<int64_t > to std::vector<int >
std
::
vector
<
int64_t
>
axes_int64
=
static_cast
<
std
::
vector
<
int64_t
>>
(
BOOST_GET_CONST
(
std
::
vector
<
int64_t
>
,
this
->
GetAttr
(
"axes"
)));
std
::
vector
<
int64_t
>
starts_int64
=
static_cast
<
std
::
vector
<
int64_t
>>
(
BOOST_GET_CONST
(
std
::
vector
<
int64_t
>
,
this
->
GetAttr
(
"starts"
)));
std
::
vector
<
int64_t
>
ends_int64
=
static_cast
<
std
::
vector
<
int64_t
>>
(
BOOST_GET_CONST
(
std
::
vector
<
int64_t
>
,
this
->
GetAttr
(
"ends"
)));
std
::
vector
<
int64_t
>
decrease_axes_int64
=
static_cast
<
std
::
vector
<
int64_t
>>
(
BOOST_GET_CONST
(
std
::
vector
<
int64_t
>
,
this
->
GetAttr
(
"decrease_axes"
)));
std
::
vector
<
int
>
axes
(
axes_int64
.
begin
(),
axes_int64
.
end
());
std
::
vector
<
int
>
starts
(
starts_int64
.
begin
(),
starts_int64
.
end
());
std
::
vector
<
int
>
ends
(
ends_int64
.
begin
(),
ends_int64
.
end
());
std
::
vector
<
int
>
decrease_axes
(
decrease_axes_int64
.
begin
(),
decrease_axes_int64
.
end
());
op
->
SetAttr
(
"axes"
,
axes
);
op
->
SetAttr
(
"starts"
,
starts
);
op
->
SetAttr
(
"ends"
,
ends
);
op
->
SetAttr
(
"decrease_axis"
,
decrease_axes
);
op
->
SetAttr
(
"infer_flags"
,
std
::
vector
<
int
>
({}));
op
->
SetOutput
(
"Out"
,
this
->
InputGrad
(
"ValueTensor"
));
}
else
{
op
->
SetType
(
"assign"
);
op
->
SetInput
(
"X"
,
this
->
OutputGrad
(
"Out"
));
op
->
SetOutput
(
"Out"
,
this
->
InputGrad
(
"Input"
));
}
}
};
DECLARE_INPLACE_OP_INFERER
(
SetValueOpInplaceInferer
,
{
"Input"
,
"Out"
});
}
// namespace operators
}
// namespace paddle
namespace
ops
=
paddle
::
operators
;
namespace
plat
=
paddle
::
platform
;
REGISTER_OPERATOR
(
set_value
,
ops
::
SetValue
,
ops
::
SetValueMaker
,
paddle
::
framework
::
EmptyGradOpMaker
<
paddle
::
framework
::
OpDesc
>
,
paddle
::
framework
::
EmptyGradOpMaker
<
paddle
::
imperative
::
OpBase
>
);
REGISTER_OPERATOR
(
set_value
,
ops
::
SetValue
,
ops
::
SetValueMaker
,
ops
::
SetValueGradMaker
<
paddle
::
framework
::
OpDesc
>
,
ops
::
SetValueGradMaker
<
paddle
::
imperative
::
OpBase
>
,
ops
::
SetValueOpInplaceInferer
);
REGISTER_OP_CPU_KERNEL
(
set_value
,
ops
::
SetValueKernel
<
paddle
::
platform
::
CPUDeviceContext
,
int
>
,
ops
::
SetValueKernel
<
p
addle
::
platform
::
CPUDeviceContext
,
int64_t
>
,
ops
::
SetValueKernel
<
p
addle
::
platform
::
CPUDeviceContext
,
float
>
,
ops
::
SetValueKernel
<
p
addle
::
platform
::
CPUDeviceContext
,
double
>
,
ops
::
SetValueKernel
<
p
addle
::
platform
::
CPUDeviceContext
,
bool
>
);
ops
::
SetValueKernel
<
p
lat
::
CPUDeviceContext
,
int64_t
>
,
ops
::
SetValueKernel
<
p
lat
::
CPUDeviceContext
,
float
>
,
ops
::
SetValueKernel
<
p
lat
::
CPUDeviceContext
,
double
>
,
ops
::
SetValueKernel
<
p
lat
::
CPUDeviceContext
,
bool
>
);
REGISTER_OP_VERSION
(
set_value
)
.
AddCheckpoint
(
...
...
paddle/fluid/pybind/imperative.cc
浏览文件 @
25e723e7
...
...
@@ -718,7 +718,8 @@ void BindImperative(py::module *m_ptr) {
{
// Release gil and do tracing
py
::
gil_scoped_release
release
;
tracer
->
TraceOp
(
"set_value"
,
ins
,
outs
,
std
::
move
(
attrs
));
tracer
->
TraceOp
(
"set_value"
,
ins
,
outs
,
std
::
move
(
attrs
),
{{
"Input"
,
"Out"
}});
}
}
else
{
auto
self_numpy
=
TensorToPyArray
(
*
self_tensor
);
...
...
python/paddle/fluid/tests/unittests/test_set_value_op.py
浏览文件 @
25e723e7
...
...
@@ -775,5 +775,76 @@ class TestError(TestSetValueBase):
self
.
_broadcast_mismatch
()
# 5. Test backward
class
Model
(
paddle
.
nn
.
Layer
):
def
__init__
(
self
):
super
(
Model
,
self
).
__init__
()
self
.
conv
=
paddle
.
nn
.
Conv2D
(
12
,
12
,
3
)
def
forward
(
self
,
x
,
y
):
x
=
self
.
conv
(
x
)
y
=
self
.
conv
(
y
)
var
=
y
.
flatten
()
x
[
0
,
:,
0
,
0
]
=
var
loss
=
paddle
.
mean
(
x
)
return
loss
,
var
,
x
class
TestBackward
(
unittest
.
TestCase
):
def
test_static
(
self
):
paddle
.
enable_static
()
main_program
=
paddle
.
static
.
Program
()
startup_program
=
paddle
.
static
.
Program
()
x_np
=
np
.
random
.
random
(
size
=
(
4
,
4
)).
astype
(
'float32'
)
y_np
=
np
.
random
.
random
(
size
=
(
4
,
4
)).
astype
(
'float32'
)
label_np
=
np
.
random
.
randint
(
2
,
size
=
(
4
,
1
)).
astype
(
'int64'
)
with
paddle
.
static
.
program_guard
(
main_program
,
startup_program
):
x
=
paddle
.
static
.
data
(
name
=
"x"
,
shape
=
[
4
,
4
],
dtype
=
'float32'
)
y
=
paddle
.
static
.
data
(
name
=
"y"
,
shape
=
[
4
,
4
],
dtype
=
'float32'
)
label
=
paddle
.
static
.
data
(
name
=
"label"
,
shape
=
[
4
,
1
],
dtype
=
'int64'
)
z
=
paddle
.
add
(
x
,
y
)
var
=
y
[
0
,
:]
z
[
0
,
:]
=
var
prediction
=
paddle
.
static
.
nn
.
fc
(
x
=
z
,
size
=
2
,
activation
=
'softmax'
)
cost
=
paddle
.
nn
.
functional
.
cross_entropy
(
input
=
prediction
,
label
=
label
)
loss
=
paddle
.
mean
(
cost
)
sgd
=
paddle
.
optimizer
.
SGD
(
learning_rate
=
0.01
)
sgd
.
minimize
(
loss
)
exe
=
paddle
.
static
.
Executor
(
paddle
.
CPUPlace
())
exe
.
run
(
startup_program
)
var_grad
,
z_grad
=
exe
.
run
(
main_program
,
feed
=
{
"x"
:
x_np
,
"y"
:
y_np
,
"label"
:
label_np
},
fetch_list
=
[
var
.
name
+
"@GRAD"
,
z
.
name
+
"@GRAD"
])
self
.
assertTrue
((
var_grad
==
z_grad
[
0
,
:]).
all
())
def
test_dynamic
(
self
):
paddle
.
disable_static
()
model
=
Model
()
x
=
paddle
.
ones
([
1
,
12
,
3
,
3
]).
astype
(
"float32"
)
y
=
paddle
.
ones
([
1
,
12
,
3
,
3
]).
astype
(
"float32"
)
loss
,
var
,
x
=
model
(
x
,
y
)
loss
.
backward
()
self
.
assertTrue
(
var
.
grad
.
shape
==
x
.
grad
[
0
,
:,
0
,
0
].
shape
)
self
.
assertTrue
((
var
.
grad
==
x
.
grad
[
0
,
:,
0
,
0
]).
all
())
if
__name__
==
'__main__'
:
unittest
.
main
()
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