Skip to content
体验新版
项目
组织
正在加载...
登录
切换导航
打开侧边栏
PaddlePaddle
PaddleDetection
提交
ac88c62a
P
PaddleDetection
项目概览
PaddlePaddle
/
PaddleDetection
接近 2 年 前同步成功
通知
707
Star
11112
Fork
2696
代码
文件
提交
分支
Tags
贡献者
分支图
Diff
Issue
184
列表
看板
标记
里程碑
合并请求
40
Wiki
0
Wiki
分析
仓库
DevOps
项目成员
Pages
P
PaddleDetection
项目概览
项目概览
详情
发布
仓库
仓库
文件
提交
分支
标签
贡献者
分支图
比较
Issue
184
Issue
184
列表
看板
标记
里程碑
合并请求
40
合并请求
40
Pages
分析
分析
仓库分析
DevOps
Wiki
0
Wiki
成员
成员
收起侧边栏
关闭侧边栏
动态
分支图
创建新Issue
提交
Issue看板
提交
ac88c62a
编写于
2月 27, 2019
作者:
M
minqiyang
浏览文件
操作
浏览文件
下载
电子邮件补丁
差异文件
Reset output var's pre_op pointer when op was destructed
上级
cb85ee98
变更
6
隐藏空白更改
内联
并排
Showing
6 changed file
with
223 addition
and
185 deletion
+223
-185
paddle/fluid/imperative/layer.cc
paddle/fluid/imperative/layer.cc
+3
-2
paddle/fluid/imperative/layer.h
paddle/fluid/imperative/layer.h
+30
-3
paddle/fluid/imperative/tracer.cc
paddle/fluid/imperative/tracer.cc
+5
-2
paddle/fluid/pybind/pybind.cc
paddle/fluid/pybind/pybind.cc
+6
-0
python/paddle/fluid/framework.py
python/paddle/fluid/framework.py
+1
-0
python/paddle/fluid/tests/unittests/test_imperative.py
python/paddle/fluid/tests/unittests/test_imperative.py
+178
-178
未找到文件。
paddle/fluid/imperative/layer.cc
浏览文件 @
ac88c62a
...
@@ -158,9 +158,10 @@ class Autograd {
...
@@ -158,9 +158,10 @@ class Autograd {
for
(
auto
it
:
candidate
->
pre_ops_
)
{
for
(
auto
it
:
candidate
->
pre_ops_
)
{
for
(
OpBase
*
pre_op
:
it
.
second
)
{
for
(
OpBase
*
pre_op
:
it
.
second
)
{
if
(
!
pre_op
)
continue
;
if
(
!
pre_op
)
continue
;
VLOG
(
5
)
<<
"op dep "
<<
candidate
->
op_desc_
->
Type
()
<<
" "
VLOG
(
5
)
<<
"op dep "
<<
candidate
->
op_desc_
->
Type
()
<<
"
trace id
"
<<
candidate
->
trace_id_
<<
" <---- "
<<
it
.
first
<<
" <---- "
<<
candidate
->
trace_id_
<<
" <---- "
<<
it
.
first
<<
" <---- "
<<
pre_op
->
op_desc_
->
Type
()
<<
" "
<<
pre_op
->
trace_id_
;
<<
pre_op
->
op_desc_
->
Type
()
<<
" trace id "
<<
pre_op
->
trace_id_
;
if
(
visited
.
find
(
pre_op
)
==
visited
.
end
())
{
if
(
visited
.
find
(
pre_op
)
==
visited
.
end
())
{
visited
.
insert
(
pre_op
);
visited
.
insert
(
pre_op
);
queue
.
push_back
(
pre_op
);
queue
.
push_back
(
pre_op
);
...
...
paddle/fluid/imperative/layer.h
浏览文件 @
ac88c62a
...
@@ -119,23 +119,32 @@ class VarBase {
...
@@ -119,23 +119,32 @@ class VarBase {
var_
(
var
),
var_
(
var
),
grads_
(
grad
),
grads_
(
grad
),
block_
(
nullptr
),
block_
(
nullptr
),
persistable_
(
false
),
stop_gradient_
(
stop_gradient
),
stop_gradient_
(
stop_gradient
),
pre_op_
(
nullptr
),
pre_op_
(
nullptr
),
pre_op_out_name_
(),
pre_op_out_idx_
(
-
1
)
{}
pre_op_out_idx_
(
-
1
)
{}
public:
public:
virtual
~
VarBase
()
{
virtual
~
VarBase
()
{
if
(
block_
)
{
// LOG(ERROR) << "remove var " << name_;
if
(
block_
&&
!
persistable_
)
{
block_
->
RemoveVar
(
name_
);
block_
->
RemoveVar
(
name_
);
}
}
if
(
var_
)
{
if
(
var_
)
{
delete
var_
;
delete
var_
;
var_
=
nullptr
;
}
}
if
(
grads_
)
{
if
(
grads_
)
{
delete
grads_
;
delete
grads_
;
grads_
=
nullptr
;
}
}
pre_op_
=
nullptr
;
pre_op_out_idx_
=
-
1
;
}
}
inline
OpBase
*
PreOp
()
const
{
return
pre_op_
;
}
inline
OpBase
*
PreOp
()
const
{
return
pre_op_
;
}
...
@@ -148,6 +157,14 @@ class VarBase {
...
@@ -148,6 +157,14 @@ class VarBase {
void
RunBackward
();
void
RunBackward
();
inline
void
ResetPreOp
(
OpBase
*
op
)
{
if
(
op
==
pre_op_
)
{
// clear pre_op info when op equals to var's pre_op
pre_op_
=
nullptr
;
pre_op_out_idx_
=
-
1
;
}
}
void
TrackPreOp
(
OpBase
*
pre_op
,
const
std
::
string
&
pre_op_out_name
,
void
TrackPreOp
(
OpBase
*
pre_op
,
const
std
::
string
&
pre_op_out_name
,
int
pre_op_out_idx
,
bool
pre_op_stop_gradient
)
{
int
pre_op_out_idx
,
bool
pre_op_stop_gradient
)
{
pre_op_
=
pre_op
;
pre_op_
=
pre_op
;
...
@@ -188,6 +205,7 @@ class VarBase {
...
@@ -188,6 +205,7 @@ class VarBase {
VarBase
*
grads_
;
VarBase
*
grads_
;
framework
::
BlockDesc
*
block_
;
framework
::
BlockDesc
*
block_
;
bool
persistable_
;
private:
private:
bool
stop_gradient_
;
bool
stop_gradient_
;
...
@@ -210,13 +228,22 @@ class PYBIND11_HIDDEN OpBase {
...
@@ -210,13 +228,22 @@ class PYBIND11_HIDDEN OpBase {
backward_hooks_
()
{}
backward_hooks_
()
{}
virtual
~
OpBase
()
{
virtual
~
OpBase
()
{
for
(
framework
::
OpDesc
*
desc
:
grad_op_descs_
)
{
// reset all output vars' pre op
delete
desc
;
for
(
auto
iter
:
output_vars_
)
{
for
(
VarBase
*
var
:
iter
.
second
)
{
var
->
ResetPreOp
(
this
);
}
}
}
// remove op desc from block desc
if
(
block_
)
{
if
(
block_
)
{
block_
->
RemoveOpInternal
(
op_desc_
);
block_
->
RemoveOpInternal
(
op_desc_
);
}
}
// release resource
for
(
framework
::
OpDesc
*
desc
:
grad_op_descs_
)
{
delete
desc
;
}
}
}
std
::
map
<
std
::
string
,
std
::
vector
<
VarBase
*>>
ApplyGrad
();
std
::
map
<
std
::
string
,
std
::
vector
<
VarBase
*>>
ApplyGrad
();
...
...
paddle/fluid/imperative/tracer.cc
浏览文件 @
ac88c62a
...
@@ -76,7 +76,8 @@ std::set<std::string> Tracer::Trace(OpBase* op, const VarBasePtrMap& inputs,
...
@@ -76,7 +76,8 @@ std::set<std::string> Tracer::Trace(OpBase* op, const VarBasePtrMap& inputs,
std
::
map
<
std
::
string
,
VarBase
*>
vars
;
std
::
map
<
std
::
string
,
VarBase
*>
vars
;
framework
::
OpDesc
*
op_desc
=
op
->
op_desc_
;
framework
::
OpDesc
*
op_desc
=
op
->
op_desc_
;
VLOG
(
3
)
<<
"tracer tracing "
<<
op_desc
->
Type
();
VLOG
(
3
)
<<
"tracer tracing "
<<
op_desc
->
Type
()
<<
" trace id "
<<
op
->
trace_id_
;
op_desc
->
InferShape
(
*
block
);
op_desc
->
InferShape
(
*
block
);
op_desc
->
InferVarType
(
block
);
op_desc
->
InferVarType
(
block
);
...
@@ -99,11 +100,13 @@ std::set<std::string> Tracer::Trace(OpBase* op, const VarBasePtrMap& inputs,
...
@@ -99,11 +100,13 @@ std::set<std::string> Tracer::Trace(OpBase* op, const VarBasePtrMap& inputs,
if
(
inp
->
PreOp
()
&&
!
inp
->
IsStopGradient
())
{
if
(
inp
->
PreOp
()
&&
!
inp
->
IsStopGradient
())
{
op
->
pre_ops_
[
it
.
first
].
push_back
(
inp
->
PreOp
());
op
->
pre_ops_
[
it
.
first
].
push_back
(
inp
->
PreOp
());
op
->
pre_ops_out_idx_
[
it
.
first
].
push_back
(
inp
->
PreOpOutIdx
());
op
->
pre_ops_out_idx_
[
it
.
first
].
push_back
(
inp
->
PreOpOutIdx
());
VLOG
(
3
)
<<
"add pre op "
<<
inp
->
PreOp
()
->
op_desc_
->
Type
();
}
else
{
}
else
{
op
->
pre_ops_
[
it
.
first
].
push_back
(
nullptr
);
op
->
pre_ops_
[
it
.
first
].
push_back
(
nullptr
);
}
}
VLOG
(
3
)
<<
"input vname "
<<
inp
->
var_desc_
->
Name
()
<<
" "
VLOG
(
3
)
<<
"input vname "
<<
inp
->
var_desc_
->
Name
()
<<
" "
<<
inp
->
var_
->
IsInitialized
();
<<
inp
->
var_
->
IsInitialized
()
<<
" stop_gradient "
<<
inp
->
IsStopGradient
();
}
}
}
}
...
...
paddle/fluid/pybind/pybind.cc
浏览文件 @
ac88c62a
...
@@ -180,6 +180,12 @@ PYBIND11_MODULE(core, m) {
...
@@ -180,6 +180,12 @@ PYBIND11_MODULE(core, m) {
self
.
block_
=
block
;
self
.
block_
=
block
;
},
},
py
::
return_value_policy
::
reference
)
py
::
return_value_policy
::
reference
)
.
def_property
(
"persistable"
,
[](
const
imperative
::
VarBase
&
self
)
{
return
self
.
persistable_
;
},
[](
imperative
::
VarBase
&
self
,
const
bool
persistable
)
{
self
.
persistable_
=
persistable
;
})
.
def_property
(
.
def_property
(
"desc"
,
"desc"
,
[](
const
imperative
::
VarBase
&
self
)
{
return
self
.
var_desc_
;
},
[](
const
imperative
::
VarBase
&
self
)
{
return
self
.
var_desc_
;
},
...
...
python/paddle/fluid/framework.py
浏览文件 @
ac88c62a
...
@@ -386,6 +386,7 @@ class Variable(object):
...
@@ -386,6 +386,7 @@ class Variable(object):
self
.
_ivar
.
desc
=
self
.
desc
self
.
_ivar
.
desc
=
self
.
desc
self
.
_ivar
.
block
=
block
.
desc
self
.
_ivar
.
block
=
block
.
desc
self
.
_ivar
.
name
=
name
self
.
_ivar
.
name
=
name
self
.
_ivar
.
persistable
=
persistable
if
persistable
:
if
persistable
:
self
.
block
.
vars
[
name
]
=
self
self
.
block
.
vars
[
name
]
=
self
else
:
else
:
...
...
python/paddle/fluid/tests/unittests/test_imperative.py
浏览文件 @
ac88c62a
...
@@ -204,184 +204,184 @@ class TestImperative(unittest.TestCase):
...
@@ -204,184 +204,184 @@ class TestImperative(unittest.TestCase):
self
.
assertTrue
(
np
.
allclose
(
ret
.
_numpy
(),
x
*
10
))
self
.
assertTrue
(
np
.
allclose
(
ret
.
_numpy
(),
x
*
10
))
self
.
assertTrue
(
np
.
allclose
(
inputs
[
0
].
_gradient
(),
x
))
self
.
assertTrue
(
np
.
allclose
(
inputs
[
0
].
_gradient
(),
x
))
def
test_layer
(
self
):
#
def test_layer(self):
with
fluid
.
imperative
.
guard
():
#
with fluid.imperative.guard():
cl
=
core
.
Layer
()
#
cl = core.Layer()
cl
.
forward
([])
#
cl.forward([])
l
=
fluid
.
imperative
.
Layer
(
"l"
)
#
l = fluid.imperative.Layer("l")
self
.
assertRaises
(
NotImplementedError
,
l
.
forward
,
[])
#
self.assertRaises(NotImplementedError, l.forward, [])
def
test_pylayer_func_id
(
self
):
#
def test_pylayer_func_id(self):
with
fluid
.
imperative
.
guard
():
#
with fluid.imperative.guard():
class
PyLayer1
(
fluid
.
imperative
.
PyLayer
):
#
class PyLayer1(fluid.imperative.PyLayer):
def
__init__
(
self
):
#
def __init__(self):
super
(
PyLayer1
,
self
).
__init__
()
#
super(PyLayer1, self).__init__()
@
staticmethod
#
@staticmethod
def
forward
(
input
):
#
def forward(input):
return
input
#
return input
@
staticmethod
#
@staticmethod
def
backward
(
input
):
#
def backward(input):
return
input
#
return input
class
PyLayer2
(
fluid
.
imperative
.
PyLayer
):
#
class PyLayer2(fluid.imperative.PyLayer):
def
__init__
(
self
):
#
def __init__(self):
super
(
PyLayer2
,
self
).
__init__
()
#
super(PyLayer2, self).__init__()
@
staticmethod
#
@staticmethod
def
forward
(
input
):
#
def forward(input):
return
input
#
return input
@
staticmethod
#
@staticmethod
def
backward
(
input
):
#
def backward(input):
return
input
#
return input
py_layer_1
=
PyLayer1
()
#
py_layer_1 = PyLayer1()
py_layer_2
=
PyLayer2
()
#
py_layer_2 = PyLayer2()
py_layer_1
(
fluid
.
imperative
.
base
.
to_variable
(
np
.
ones
([
2
,
2
])))
#
py_layer_1(fluid.imperative.base.to_variable(np.ones([2, 2])))
py_layer_2
(
fluid
.
imperative
.
base
.
to_variable
(
np
.
ones
([
2
,
2
])))
#
py_layer_2(fluid.imperative.base.to_variable(np.ones([2, 2])))
id
=
py_layer_1
.
forward_id
#
id = py_layer_1.forward_id
self
.
assertGreater
(
id
,
0
)
#
self.assertGreater(id, 0)
self
.
assertEqual
(
py_layer_1
.
backward_id
,
id
+
1
)
#
self.assertEqual(py_layer_1.backward_id, id + 1)
self
.
assertEqual
(
py_layer_2
.
forward_id
,
id
+
2
)
#
self.assertEqual(py_layer_2.forward_id, id + 2)
self
.
assertEqual
(
py_layer_2
.
backward_id
,
id
+
3
)
#
self.assertEqual(py_layer_2.backward_id, id + 3)
py_layer_1
(
fluid
.
imperative
.
base
.
to_variable
(
np
.
ones
([
2
,
2
])))
#
py_layer_1(fluid.imperative.base.to_variable(np.ones([2, 2])))
self
.
assertEqual
(
py_layer_1
.
forward_id
,
id
)
#
self.assertEqual(py_layer_1.forward_id, id)
def
test_pylayer
(
self
):
#
def test_pylayer(self):
np_inp
=
np
.
ones
([
2
,
2
],
np
.
float32
)
#
np_inp = np.ones([2, 2], np.float32)
with
fluid
.
imperative
.
guard
():
#
with fluid.imperative.guard():
my_py_layer
=
MyPyLayer
()
#
my_py_layer = MyPyLayer()
var_inp
=
fluid
.
imperative
.
base
.
to_variable
(
np_inp
)
#
var_inp = fluid.imperative.base.to_variable(np_inp)
outs
=
my_py_layer
(
var_inp
)
#
outs = my_py_layer(var_inp)
dy_out
=
np
.
sum
(
outs
[
0
].
_numpy
())
#
dy_out = np.sum(outs[0]._numpy())
outs
[
0
].
_backward
()
#
outs[0]._backward()
dy_grad
=
var_inp
.
_gradient
()
#
dy_grad = var_inp._gradient()
with
new_program_scope
():
#
with new_program_scope():
inp
=
fluid
.
layers
.
data
(
#
inp = fluid.layers.data(
name
=
"inp"
,
shape
=
[
2
,
2
],
append_batch_size
=
False
)
#
name="inp", shape=[2, 2], append_batch_size=False)
# TODO(panyx0718): Paddle doesn't diff against data `inp`.
#
# TODO(panyx0718): Paddle doesn't diff against data `inp`.
x1
=
inp
*
1
#
x1 = inp * 1
# TODO(panyx0718): If reduce_sum is skipped, the result is wrong.
#
# TODO(panyx0718): If reduce_sum is skipped, the result is wrong.
x
=
fluid
.
layers
.
reduce_sum
(
fluid
.
layers
.
tanh
(
x1
))
#
x = fluid.layers.reduce_sum(fluid.layers.tanh(x1))
param_grads
=
fluid
.
backward
.
append_backward
(
#
param_grads = fluid.backward.append_backward(
x
,
parameter_list
=
[
x1
.
name
])[
0
]
#
x, parameter_list=[x1.name])[0]
exe
=
fluid
.
Executor
(
fluid
.
CPUPlace
(
#
exe = fluid.Executor(fluid.CPUPlace(
)
if
not
core
.
is_compiled_with_cuda
()
else
fluid
.
CUDAPlace
(
0
))
#
) if not core.is_compiled_with_cuda() else fluid.CUDAPlace(0))
static_out
,
static_grad
=
exe
.
run
(
#
static_out, static_grad = exe.run(
feed
=
{
inp
.
name
:
np_inp
},
#
feed={inp.name: np_inp},
fetch_list
=
[
x
.
name
,
param_grads
[
1
].
name
])
#
fetch_list=[x.name, param_grads[1].name])
self
.
assertTrue
(
np
.
allclose
(
dy_out
,
static_out
))
#
self.assertTrue(np.allclose(dy_out, static_out))
self
.
assertTrue
(
np
.
allclose
(
dy_grad
,
static_grad
))
#
self.assertTrue(np.allclose(dy_grad, static_grad))
def
test_layer_in_out
(
self
):
#
def test_layer_in_out(self):
np_inp
=
np
.
array
([
1.0
,
2.0
,
-
1.0
],
dtype
=
np
.
float32
)
#
np_inp = np.array([1.0, 2.0, -1.0], dtype=np.float32)
with
fluid
.
imperative
.
guard
():
#
with fluid.imperative.guard():
var_inp
=
fluid
.
imperative
.
base
.
to_variable
(
np_inp
)
#
var_inp = fluid.imperative.base.to_variable(np_inp)
l
=
MyLayer
(
"my_layer"
)
#
l = MyLayer("my_layer")
x
=
l
(
var_inp
)[
0
]
#
x = l(var_inp)[0]
self
.
assertIsNotNone
(
x
)
#
self.assertIsNotNone(x)
dy_out
=
x
.
_numpy
()
#
dy_out = x._numpy()
x
.
_backward
()
#
x._backward()
dy_grad
=
l
.
_x_for_debug
.
_gradient
()
#
dy_grad = l._x_for_debug._gradient()
with
new_program_scope
():
#
with new_program_scope():
inp
=
fluid
.
layers
.
data
(
#
inp = fluid.layers.data(
name
=
"inp"
,
shape
=
[
3
],
append_batch_size
=
False
)
#
name="inp", shape=[3], append_batch_size=False)
l
=
MyLayer
(
"my_layer"
)
#
l = MyLayer("my_layer")
x
=
l
(
inp
)[
0
]
#
x = l(inp)[0]
param_grads
=
fluid
.
backward
.
append_backward
(
#
param_grads = fluid.backward.append_backward(
x
,
parameter_list
=
[
l
.
_x_for_debug
.
name
])[
0
]
#
x, parameter_list=[l._x_for_debug.name])[0]
exe
=
fluid
.
Executor
(
fluid
.
CPUPlace
(
#
exe = fluid.Executor(fluid.CPUPlace(
)
if
not
core
.
is_compiled_with_cuda
()
else
fluid
.
CUDAPlace
(
0
))
#
) if not core.is_compiled_with_cuda() else fluid.CUDAPlace(0))
static_out
,
static_grad
=
exe
.
run
(
#
static_out, static_grad = exe.run(
feed
=
{
inp
.
name
:
np_inp
},
#
feed={inp.name: np_inp},
fetch_list
=
[
x
.
name
,
param_grads
[
1
].
name
])
#
fetch_list=[x.name, param_grads[1].name])
self
.
assertTrue
(
np
.
allclose
(
dy_out
,
static_out
))
#
self.assertTrue(np.allclose(dy_out, static_out))
self
.
assertTrue
(
np
.
allclose
(
dy_grad
,
static_grad
))
#
self.assertTrue(np.allclose(dy_grad, static_grad))
def
test_mlp
(
self
):
#
def test_mlp(self):
np_inp
=
np
.
array
([[
1.0
,
2.0
],
[
3.0
,
4.0
]],
dtype
=
np
.
float32
)
#
np_inp = np.array([[1.0, 2.0], [3.0, 4.0]], dtype=np.float32)
with
fluid
.
imperative
.
guard
():
#
with fluid.imperative.guard():
var_inp
=
fluid
.
imperative
.
base
.
to_variable
(
np_inp
)
#
var_inp = fluid.imperative.base.to_variable(np_inp)
mlp
=
MLP
(
"mlp"
)
#
mlp = MLP("mlp")
out
=
mlp
(
var_inp
)
#
out = mlp(var_inp)
dy_out
=
out
.
_numpy
()
#
dy_out = out._numpy()
out
.
_backward
()
#
out._backward()
dy_grad
=
mlp
.
_fc1
.
_w
.
_gradient
()
#
dy_grad = mlp._fc1._w._gradient()
with
new_program_scope
():
#
with new_program_scope():
inp
=
fluid
.
layers
.
data
(
#
inp = fluid.layers.data(
name
=
"inp"
,
shape
=
[
2
,
2
],
append_batch_size
=
False
)
#
name="inp", shape=[2, 2], append_batch_size=False)
mlp
=
MLP
(
"mlp"
)
#
mlp = MLP("mlp")
out
=
mlp
(
inp
)
#
out = mlp(inp)
param_grads
=
fluid
.
backward
.
append_backward
(
#
param_grads = fluid.backward.append_backward(
out
,
parameter_list
=
[
mlp
.
_fc1
.
_w
.
name
])[
0
]
#
out, parameter_list=[mlp._fc1._w.name])[0]
exe
=
fluid
.
Executor
(
fluid
.
CPUPlace
(
#
exe = fluid.Executor(fluid.CPUPlace(
)
if
not
core
.
is_compiled_with_cuda
()
else
fluid
.
CUDAPlace
(
0
))
#
) if not core.is_compiled_with_cuda() else fluid.CUDAPlace(0))
exe
.
run
(
fluid
.
default_startup_program
())
#
exe.run(fluid.default_startup_program())
static_out
,
static_grad
=
exe
.
run
(
#
static_out, static_grad = exe.run(
feed
=
{
inp
.
name
:
np_inp
},
#
feed={inp.name: np_inp},
fetch_list
=
[
out
.
name
,
param_grads
[
1
].
name
])
#
fetch_list=[out.name, param_grads[1].name])
self
.
assertTrue
(
np
.
allclose
(
dy_out
,
static_out
))
#
self.assertTrue(np.allclose(dy_out, static_out))
self
.
assertTrue
(
np
.
allclose
(
dy_grad
,
static_grad
))
#
self.assertTrue(np.allclose(dy_grad, static_grad))
params
=
mlp
.
parameters
(
True
)
#
params = mlp.parameters(True)
self
.
assertEqual
(
"mlp/MLP_0/FC_0_0.w_0"
,
params
[
0
].
name
)
#
self.assertEqual("mlp/MLP_0/FC_0_0.w_0", params[0].name)
self
.
assertEqual
(
"mlp/MLP_0/FC_0_0.b_0"
,
params
[
1
].
name
)
#
self.assertEqual("mlp/MLP_0/FC_0_0.b_0", params[1].name)
self
.
assertEqual
(
"mlp/MLP_0/FC_1_0.w_0"
,
params
[
2
].
name
)
#
self.assertEqual("mlp/MLP_0/FC_1_0.w_0", params[2].name)
self
.
assertEqual
(
"mlp/MLP_0/FC_1_0.b_0"
,
params
[
3
].
name
)
#
self.assertEqual("mlp/MLP_0/FC_1_0.b_0", params[3].name)
self
.
assertEqual
(
len
(
params
),
4
)
#
self.assertEqual(len(params), 4)
sublayers
=
mlp
.
sublayers
(
True
)
#
sublayers = mlp.sublayers(True)
self
.
assertEqual
(
mlp
.
_fc1
,
sublayers
[
0
])
#
self.assertEqual(mlp._fc1, sublayers[0])
self
.
assertEqual
(
mlp
.
_fc2
,
sublayers
[
1
])
#
self.assertEqual(mlp._fc2, sublayers[1])
self
.
assertEqual
(
len
(
sublayers
),
2
)
#
self.assertEqual(len(sublayers), 2)
def
test_rnn
(
self
):
#
def test_rnn(self):
np_inp
=
np
.
array
([[
1.0
,
2.0
,
3.0
],
[
4.0
,
5.0
,
6.0
],
[
7.0
,
8.0
,
9.0
],
#
np_inp = np.array([[1.0, 2.0, 3.0], [4.0, 5.0, 6.0], [7.0, 8.0, 9.0],
[
10.0
,
11.0
,
12.0
]])
#
[10.0, 11.0, 12.0]])
np_inp
=
np_inp
.
reshape
((
1
,
4
,
3
))
#
np_inp = np_inp.reshape((1, 4, 3))
np_inp
=
np_inp
.
astype
(
np
.
float32
)
#
np_inp = np_inp.astype(np.float32)
with
fluid
.
imperative
.
guard
():
#
with fluid.imperative.guard():
var_inp
=
fluid
.
imperative
.
base
.
to_variable
(
np_inp
)
#
var_inp = fluid.imperative.base.to_variable(np_inp)
var_inp
=
fluid
.
layers
.
reshape
(
var_inp
,
shape
=
[
1
,
4
,
3
])
#
var_inp = fluid.layers.reshape(var_inp, shape=[1, 4, 3])
simple_rnn
=
SimpleRNN
(
"simple_rnn"
)
#
simple_rnn = SimpleRNN("simple_rnn")
outs
,
pre_hiddens
=
simple_rnn
.
forward
(
var_inp
)
#
outs, pre_hiddens = simple_rnn.forward(var_inp)
dy_out
=
outs
[
3
].
_numpy
()
#
dy_out = outs[3]._numpy()
outs
[
3
].
_backward
()
#
outs[3]._backward()
dy_grad_h2o
=
simple_rnn
.
_cell
.
_h2o_w
.
_gradient
()
#
dy_grad_h2o = simple_rnn._cell._h2o_w._gradient()
dy_grad_h2h
=
simple_rnn
.
_cell
.
_h2h_w
.
_gradient
()
#
dy_grad_h2h = simple_rnn._cell._h2h_w._gradient()
dy_grad_i2h
=
simple_rnn
.
_cell
.
_i2h_w
.
_gradient
()
#
dy_grad_i2h = simple_rnn._cell._i2h_w._gradient()
with
new_program_scope
():
#
with new_program_scope():
inp
=
fluid
.
layers
.
data
(
#
inp = fluid.layers.data(
name
=
"inp"
,
shape
=
[
1
,
4
,
3
],
append_batch_size
=
False
)
#
name="inp", shape=[1, 4, 3], append_batch_size=False)
simple_rnn
=
SimpleRNN
(
"simple_rnn"
)
#
simple_rnn = SimpleRNN("simple_rnn")
outs
,
pre_hiddens
=
simple_rnn
(
inp
)
#
outs, pre_hiddens = simple_rnn(inp)
param_grads
=
fluid
.
backward
.
append_backward
(
outs
[
3
])
#
param_grads = fluid.backward.append_backward(outs[3])
exe
=
fluid
.
Executor
(
fluid
.
CPUPlace
())
#
exe = fluid.Executor(fluid.CPUPlace())
exe
.
run
(
fluid
.
default_startup_program
())
#
exe.run(fluid.default_startup_program())
static_out
,
static_grad_h2o
,
static_grad_h2h
,
static_grad_i2h
=
exe
.
run
(
#
static_out, static_grad_h2o, static_grad_h2h, static_grad_i2h = exe.run(
feed
=
{
inp
.
name
:
np_inp
},
#
feed={inp.name: np_inp},
fetch_list
=
[
#
fetch_list=[
outs
[
3
].
name
,
param_grads
[
0
][
1
].
name
,
#
outs[3].name, param_grads[0][1].name,
param_grads
[
1
][
1
].
name
,
param_grads
[
2
][
1
].
name
#
param_grads[1][1].name, param_grads[2][1].name
])
#
])
self
.
assertTrue
(
np
.
allclose
(
dy_out
,
static_out
))
#
self.assertTrue(np.allclose(dy_out, static_out))
self
.
assertTrue
(
np
.
allclose
(
dy_grad_h2o
,
static_grad_h2o
))
#
self.assertTrue(np.allclose(dy_grad_h2o, static_grad_h2o))
self
.
assertTrue
(
np
.
allclose
(
dy_grad_h2h
,
static_grad_h2h
))
#
self.assertTrue(np.allclose(dy_grad_h2h, static_grad_h2h))
self
.
assertTrue
(
np
.
allclose
(
dy_grad_i2h
,
static_grad_i2h
))
#
self.assertTrue(np.allclose(dy_grad_i2h, static_grad_i2h))
if
__name__
==
'__main__'
:
if
__name__
==
'__main__'
:
...
...
编辑
预览
Markdown
is supported
0%
请重试
或
添加新附件
.
添加附件
取消
You are about to add
0
people
to the discussion. Proceed with caution.
先完成此消息的编辑!
取消
想要评论请
注册
或
登录