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体验新版 GitCode,发现更多精彩内容 >>
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69f5c0ee
编写于
2月 16, 2019
作者:
X
Xin Pan
提交者:
GitHub
2月 16, 2019
浏览文件
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差异文件
Merge pull request #15557 from panyx0718/imperative
add sugar for fetching parameters and layers
上级
832bd720
792719fb
变更
8
隐藏空白更改
内联
并排
Showing
8 changed file
with
201 addition
and
63 deletion
+201
-63
paddle/fluid/imperative/layer.cc
paddle/fluid/imperative/layer.cc
+1
-1
python/paddle/fluid/imperative/layers.py
python/paddle/fluid/imperative/layers.py
+94
-19
python/paddle/fluid/imperative/nn.py
python/paddle/fluid/imperative/nn.py
+0
-6
python/paddle/fluid/tests/unittests/test_base_layer.py
python/paddle/fluid/tests/unittests/test_base_layer.py
+82
-0
python/paddle/fluid/tests/unittests/test_imperative.py
python/paddle/fluid/tests/unittests/test_imperative.py
+12
-0
python/paddle/fluid/tests/unittests/test_imperative_gan.py
python/paddle/fluid/tests/unittests/test_imperative_gan.py
+0
-7
python/paddle/fluid/tests/unittests/test_imperative_ptb_rnn.py
...n/paddle/fluid/tests/unittests/test_imperative_ptb_rnn.py
+0
-16
python/paddle/fluid/tests/unittests/test_imperative_resnet.py
...on/paddle/fluid/tests/unittests/test_imperative_resnet.py
+12
-14
未找到文件。
paddle/fluid/imperative/layer.cc
浏览文件 @
69f5c0ee
...
...
@@ -207,7 +207,7 @@ framework::LoDTensor& VarBase::GradValue() {
std
::
map
<
std
::
string
,
std
::
vector
<
VarBase
*>>
OpBase
::
ApplyGrad
()
{
if
(
grad_op_descs_
.
empty
()
&&
backward_id_
<=
0
)
{
LOG
(
WARNING
)
<<
"op with no grad: "
<<
op_desc_
->
Type
();
VLOG
(
3
)
<<
"op with no grad: "
<<
op_desc_
->
Type
();
return
{};
}
...
...
python/paddle/fluid/imperative/layers.py
浏览文件 @
69f5c0ee
...
...
@@ -12,6 +12,7 @@
# See the License for the specific language governing permissions and
# limitations under the License.
import
collections
import
contextlib
import
sys
import
numpy
as
np
...
...
@@ -30,31 +31,45 @@ class Layer(core.Layer):
def
__init__
(
self
,
dtype
=
core
.
VarDesc
.
VarType
.
FP32
,
name
=
None
):
self
.
_built
=
False
self
.
_dtype
=
dtype
self
.
_parameters
=
collections
.
OrderedDict
()
self
.
_sub_layers
=
collections
.
OrderedDict
()
def
parameters
(
self
,
include_sublayers
=
True
):
"""Returns a list of Parameters from current and sub-layers.
Args:
include_sublayers: If true, also include the parameters from
sublayers.
Returns a list of Parameters.
"""
ret
=
[
p
for
p
in
self
.
_parameters
.
values
()]
if
include_sublayers
:
for
l
in
self
.
_sub_layers
.
values
():
for
p
in
l
.
parameters
(
include_sublayers
):
ret
.
append
(
p
)
return
ret
def
sublayers
(
self
,
include_sublayers
=
True
):
"""Returns a list of sub layers.
def
parameters
(
self
):
params
=
[]
for
key
in
self
.
__dict__
.
keys
():
value
=
self
.
__dict__
[
key
]
if
isinstance
(
value
,
framework
.
Parameter
):
params
.
append
(
value
)
elif
isinstance
(
value
,
core
.
Layer
):
params
.
extend
(
value
.
parameters
())
elif
isinstance
(
value
,
collections
.
Container
):
if
len
(
value
)
==
0
:
continue
if
isinstance
(
value
[
0
],
framework
.
Parameter
):
params
.
extend
(
value
)
elif
isinstance
(
value
[
0
],
core
.
Layer
):
for
v
in
value
:
params
.
extend
(
v
.
parameters
())
return
params
Args:
include_sublayers: If true, also include the layers from sublayers.
Returns a list of sub layers.
"""
ret
=
[
l
for
l
in
self
.
_sub_layers
.
values
()]
if
include_sublayers
:
for
l
in
self
.
_sub_layers
.
values
():
for
sub_l
in
l
.
sublayers
(
include_sublayers
):
ret
.
append
(
sub_l
)
return
ret
def
clear_gradients
(
self
):
for
p
in
self
.
parameters
():
p
.
_clear_gradient
()
def
_build_once
(
self
,
input
s
):
def
_build_once
(
self
,
*
arg
s
):
pass
def
__call__
(
self
,
*
inputs
):
...
...
@@ -71,6 +86,66 @@ class Layer(core.Layer):
def
backward
(
self
,
*
inputs
):
raise
ValueError
(
"Layer shouldn't implement backward"
)
def
add_sublayer
(
self
,
name
,
sublayer
):
"""Adds a sub Layer instance.
Added sublayer can be access like self.name.
Args:
name: name of this sublayer.
sublayer: an instance of Layer.
Returns:
the sublayer passed in.
"""
assert
isinstance
(
sublayer
,
core
.
Layer
)
self
.
_sub_layers
[
name
]
=
sublayer
return
sublayer
def
add_parameter
(
self
,
name
,
parameter
):
"""Adds a Parameter instance.
Added parameter can be access like self.name.
Args:
name: name of this sublayer.
parameter: an instance of Parameter.
Returns:
the parameter passed in.
"""
assert
isinstance
(
parameter
,
framework
.
Parameter
)
self
.
_parameters
[
name
]
=
parameter
return
parameter
def
__getattr__
(
self
,
name
):
if
name
in
self
.
_parameters
:
return
self
.
_parameters
[
name
]
elif
name
in
self
.
_sub_layers
:
return
self
.
_sub_layers
[
name
]
def
__setattr__
(
self
,
name
,
value
):
if
isinstance
(
value
,
framework
.
Parameter
):
params
=
self
.
__dict__
.
get
(
'_parameters'
,
None
)
if
params
is
None
:
raise
ValueError
(
"super(YourLayer, self).__init__() should be called first"
)
params
[
name
]
=
value
elif
isinstance
(
value
,
core
.
Layer
):
layers
=
self
.
__dict__
.
get
(
'_sub_layers'
,
None
)
if
layers
is
None
:
raise
ValueError
(
"super(YourLayer, self).__init__() should be called first"
)
layers
[
name
]
=
value
else
:
object
.
__setattr__
(
self
,
name
,
value
)
def
__delattr__
(
self
,
name
):
if
name
in
self
.
_parameters
:
del
self
.
_parameters
[
name
]
elif
name
in
self
.
_sub_layers
:
del
self
.
_sub_layers
[
name
]
else
:
object
.
__delattr__
(
self
,
name
)
class
PyLayer
(
core
.
PyLayer
):
"""Layers composed of user-defined python codes."""
...
...
python/paddle/fluid/imperative/nn.py
浏览文件 @
69f5c0ee
...
...
@@ -225,9 +225,6 @@ class FC(layers.Layer):
act
=
act
,
name
=
name
)
def
parameters
(
self
):
return
[
self
.
_w
,
self
.
_b
]
def
_build_once
(
self
,
input
):
input_shape
=
input
.
shape
param_shape
=
[
...
...
@@ -478,9 +475,6 @@ class Embedding(layers.Layer):
dtype
=
self
.
_dtype
,
is_bias
=
False
)
def
parameters
(
self
):
return
[
self
.
_w
]
def
forward
(
self
,
input
):
out
=
self
.
_helper
.
create_variable_for_type_inference
(
self
.
_dtype
)
self
.
_helper
.
append_op
(
...
...
python/paddle/fluid/tests/unittests/test_base_layer.py
0 → 100644
浏览文件 @
69f5c0ee
# Copyright (c) 2018 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.
import
unittest
import
numpy
as
np
import
paddle.fluid
as
fluid
from
paddle.fluid.layer_helper
import
LayerHelper
class
L1
(
fluid
.
imperative
.
Layer
):
def
__init__
(
self
):
super
(
L1
,
self
).
__init__
()
self
.
_helper
=
LayerHelper
(
'MyLayer'
,
param_attr
=
fluid
.
ParamAttr
(
initializer
=
fluid
.
initializer
.
Constant
(
value
=
0.1
)))
self
.
w1
=
self
.
_helper
.
create_parameter
(
attr
=
self
.
_helper
.
param_attr
,
shape
=
[
2
,
2
],
dtype
=
'float32'
,
is_bias
=
False
)
self
.
w2
=
self
.
_helper
.
create_parameter
(
attr
=
self
.
_helper
.
param_attr
,
shape
=
[
2
,
2
],
dtype
=
'float32'
,
is_bias
=
False
)
def
forward
(
self
):
return
self
.
w1
+
self
.
w2
class
L2
(
fluid
.
imperative
.
Layer
):
def
__init__
(
self
):
super
(
L2
,
self
).
__init__
()
self
.
layer1
=
L1
()
self
.
layer2
=
L1
()
def
forward
(
self
):
return
self
.
layer1
()
+
self
.
layer2
()
class
L3
(
fluid
.
imperative
.
Layer
):
def
__init__
(
self
):
super
(
L3
,
self
).
__init__
()
self
.
layer1
=
L2
()
self
.
layer2
=
L2
()
def
forward
(
self
):
return
self
.
layer1
()
+
self
.
layer2
()
class
TestBaseLayer
(
unittest
.
TestCase
):
def
test_one_level
(
self
):
with
fluid
.
imperative
.
guard
():
l
=
L1
()
ret
=
l
()
self
.
assertEqual
(
l
.
w1
.
name
,
"MyLayer_0.w_0"
)
self
.
assertEqual
(
l
.
w2
.
name
,
"MyLayer_0.w_1"
)
self
.
assertTrue
(
np
.
allclose
(
ret
.
_numpy
(),
0.2
*
np
.
ones
([
2
,
2
])))
def
test_three_level
(
self
):
with
fluid
.
imperative
.
guard
():
l
=
L3
()
ret
=
l
()
self
.
assertTrue
(
np
.
allclose
(
ret
.
_numpy
(),
0.8
*
np
.
ones
([
2
,
2
])))
if
__name__
==
'__main__'
:
unittest
.
main
()
python/paddle/fluid/tests/unittests/test_imperative.py
浏览文件 @
69f5c0ee
...
...
@@ -333,6 +333,18 @@ class TestImperative(unittest.TestCase):
self
.
assertTrue
(
np
.
allclose
(
dy_out
,
static_out
))
self
.
assertTrue
(
np
.
allclose
(
dy_grad
,
static_grad
))
params
=
mlp
.
parameters
(
True
)
self
.
assertEqual
(
"FC_0.w_0"
,
params
[
0
].
name
)
self
.
assertEqual
(
"FC_0.b_0"
,
params
[
1
].
name
)
self
.
assertEqual
(
"FC_1.w_0"
,
params
[
2
].
name
)
self
.
assertEqual
(
"FC_1.b_0"
,
params
[
3
].
name
)
self
.
assertEqual
(
len
(
params
),
4
)
sublayers
=
mlp
.
sublayers
(
True
)
self
.
assertEqual
(
mlp
.
_fc1
,
sublayers
[
0
])
self
.
assertEqual
(
mlp
.
_fc2
,
sublayers
[
1
])
self
.
assertEqual
(
len
(
sublayers
),
2
)
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
],
[
10.0
,
11.0
,
12.0
]])
...
...
python/paddle/fluid/tests/unittests/test_imperative_gan.py
浏览文件 @
69f5c0ee
...
...
@@ -33,9 +33,6 @@ class Discriminator(fluid.imperative.Layer):
self
.
_fc1
=
FC
(
size
=
32
,
act
=
'elu'
,
name
=
"d_fc1"
)
self
.
_fc2
=
FC
(
size
=
1
,
name
=
"d_fc2"
)
def
parameters
(
self
):
return
self
.
_fc1
.
parameters
()
+
self
.
_fc2
.
parameters
()
def
forward
(
self
,
inputs
):
x
=
self
.
_fc1
(
inputs
)
return
self
.
_fc2
(
x
)
...
...
@@ -48,10 +45,6 @@ class Generator(fluid.imperative.Layer):
self
.
_fc2
=
FC
(
size
=
64
,
act
=
'elu'
,
name
=
"g_fc2"
)
self
.
_fc3
=
FC
(
size
=
1
,
name
=
"g_fc3"
)
def
parameters
(
self
):
return
self
.
_fc1
.
parameters
()
+
self
.
_fc2
.
parameters
(
)
+
self
.
_fc3
.
parameters
()
def
forward
(
self
,
inputs
):
x
=
self
.
_fc1
(
inputs
)
x
=
self
.
_fc2
(
x
)
...
...
python/paddle/fluid/tests/unittests/test_imperative_ptb_rnn.py
浏览文件 @
69f5c0ee
...
...
@@ -75,16 +75,6 @@ class SimpleLSTMRNN(fluid.imperative.Layer):
self
.
hidden_array
.
append
(
pre_hidden
)
self
.
cell_array
.
append
(
pre_cell
)
def
parameters
(
self
):
parameters
=
list
()
for
param
in
self
.
weight_1_arr
:
parameters
.
append
(
param
)
for
param
in
self
.
weight_2_arr
:
parameters
.
append
(
param
)
for
bias
in
self
.
bias_arr
:
parameters
.
append
(
bias
)
return
parameters
def
forward
(
self
,
input_embedding
,
init_hidden
=
None
,
init_cell
=
None
):
res
=
[]
for
index
in
range
(
self
.
_num_steps
):
...
...
@@ -177,12 +167,6 @@ class PtbModel(fluid.imperative.Layer):
def
_build_once
(
self
,
input
,
label
,
init_hidden
,
init_cell
):
pass
def
parameters
(
self
):
parameters
=
self
.
simple_lstm_rnn
.
parameters
()
+
[
self
.
softmax_weight
,
self
.
softmax_bias
]
+
self
.
embedding
.
parameters
()
return
parameters
def
forward
(
self
,
input
,
label
,
init_hidden
,
init_cell
):
init_h
=
fluid
.
layers
.
reshape
(
...
...
python/paddle/fluid/tests/unittests/test_imperative_resnet.py
浏览文件 @
69f5c0ee
...
...
@@ -21,7 +21,6 @@ import paddle
import
paddle.fluid
as
fluid
from
paddle.fluid
import
core
from
paddle.fluid.layer_helper
import
LayerHelper
from
paddle.fluid.optimizer
import
SGDOptimizer
from
paddle.fluid.imperative.nn
import
Conv2D
,
Pool2D
,
BatchNorm
,
FC
from
paddle.fluid.imperative.base
import
to_variable
from
test_imperative_base
import
new_program_scope
...
...
@@ -173,11 +172,13 @@ class ResNet(fluid.imperative.Layer):
for
block
in
range
(
len
(
depth
)):
shortcut
=
False
for
i
in
range
(
depth
[
block
]):
bottleneck_block
=
BottleneckBlock
(
num_channels
=
num_channels
,
num_filters
=
num_filters
[
block
],
stride
=
2
if
i
==
0
and
block
!=
0
else
1
,
shortcut
=
shortcut
)
bottleneck_block
=
self
.
add_sublayer
(
'bb_%d_%d'
%
(
block
,
i
),
BottleneckBlock
(
num_channels
=
num_channels
,
num_filters
=
num_filters
[
block
],
stride
=
2
if
i
==
0
and
block
!=
0
else
1
,
shortcut
=
shortcut
))
num_channels
=
bottleneck_block
.
_num_channels_out
self
.
bottleneck_block_list
.
append
(
bottleneck_block
)
shortcut
=
True
...
...
@@ -223,8 +224,7 @@ class TestImperativeResnet(unittest.TestCase):
batch_size
=
batch_size
)
dy_param_init_value
=
{}
for
param
in
fluid
.
default_main_program
().
global_block
(
).
all_parameters
():
for
param
in
resnet
.
parameters
():
dy_param_init_value
[
param
.
name
]
=
param
.
_numpy
()
for
batch_id
,
data
in
enumerate
(
train_reader
()):
...
...
@@ -247,16 +247,14 @@ class TestImperativeResnet(unittest.TestCase):
dy_out
=
avg_loss
.
_numpy
()
if
batch_id
==
0
:
for
param
in
fluid
.
default_main_program
().
global_block
(
).
all_parameters
():
for
param
in
resnet
.
parameters
():
if
param
.
name
not
in
dy_param_init_value
:
dy_param_init_value
[
param
.
name
]
=
param
.
_numpy
()
avg_loss
.
_backward
()
dy_grad_value
=
{}
for
param
in
fluid
.
default_main_program
().
global_block
(
).
all_parameters
():
for
param
in
resnet
.
parameters
():
if
not
param
.
stop_gradient
:
np_array
=
np
.
array
(
param
.
_ivar
.
_grad_ivar
().
value
()
.
get_tensor
())
...
...
@@ -267,8 +265,7 @@ class TestImperativeResnet(unittest.TestCase):
resnet
.
clear_gradients
()
dy_param_value
=
{}
for
param
in
fluid
.
default_main_program
().
global_block
(
).
all_parameters
():
for
param
in
resnet
.
parameters
():
dy_param_value
[
param
.
name
]
=
param
.
_numpy
()
with
new_program_scope
():
...
...
@@ -349,6 +346,7 @@ class TestImperativeResnet(unittest.TestCase):
self
.
assertTrue
(
np
.
allclose
(
static_out
,
dy_out
))
self
.
assertEqual
(
len
(
dy_param_init_value
),
len
(
static_param_init_value
))
for
key
,
value
in
six
.
iteritems
(
static_param_init_value
):
self
.
assertTrue
(
np
.
allclose
(
value
,
dy_param_init_value
[
key
]))
self
.
assertTrue
(
np
.
isfinite
(
value
.
all
()))
...
...
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