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
wmsofts
Paddle
提交
9bd44b94
P
Paddle
项目概览
wmsofts
/
Paddle
与 Fork 源项目一致
Fork自
PaddlePaddle / Paddle
通知
1
Star
0
Fork
0
代码
文件
提交
分支
Tags
贡献者
分支图
Diff
Issue
0
列表
看板
标记
里程碑
合并请求
0
Wiki
0
Wiki
分析
仓库
DevOps
项目成员
Pages
P
Paddle
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
0
Issue
0
列表
看板
标记
里程碑
合并请求
0
合并请求
0
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
体验新版 GitCode,发现更多精彩内容 >>
未验证
提交
9bd44b94
编写于
4月 10, 2019
作者:
L
lujun
提交者:
GitHub
4月 10, 2019
浏览文件
操作
浏览文件
下载
差异文件
Merge pull request #16561 from junjun315/move-api-to-root
Move dygraph api to root
上级
95410652
14db0680
变更
26
展开全部
隐藏空白更改
内联
并排
Showing
26 changed file
with
731 addition
and
295 deletion
+731
-295
paddle/fluid/API.spec
paddle/fluid/API.spec
+1
-0
python/paddle/fluid/__init__.py
python/paddle/fluid/__init__.py
+2
-0
python/paddle/fluid/dygraph/base.py
python/paddle/fluid/dygraph/base.py
+1
-1
python/paddle/fluid/dygraph/checkpoint.py
python/paddle/fluid/dygraph/checkpoint.py
+1
-9
python/paddle/fluid/dygraph/layer_object_helper.py
python/paddle/fluid/dygraph/layer_object_helper.py
+1
-1
python/paddle/fluid/dygraph/layers.py
python/paddle/fluid/dygraph/layers.py
+3
-3
python/paddle/fluid/dygraph/nn.py
python/paddle/fluid/dygraph/nn.py
+515
-73
python/paddle/fluid/framework.py
python/paddle/fluid/framework.py
+33
-29
python/paddle/fluid/initializer.py
python/paddle/fluid/initializer.py
+8
-8
python/paddle/fluid/layer_helper.py
python/paddle/fluid/layer_helper.py
+1
-1
python/paddle/fluid/layer_helper_base.py
python/paddle/fluid/layer_helper_base.py
+4
-4
python/paddle/fluid/layers/nn.py
python/paddle/fluid/layers/nn.py
+22
-22
python/paddle/fluid/optimizer.py
python/paddle/fluid/optimizer.py
+4
-4
python/paddle/fluid/tests/unittests/test_base_layer.py
python/paddle/fluid/tests/unittests/test_base_layer.py
+5
-5
python/paddle/fluid/tests/unittests/test_imperative_basic.py
python/paddle/fluid/tests/unittests/test_imperative_basic.py
+28
-28
python/paddle/fluid/tests/unittests/test_imperative_checkpoint.py
...addle/fluid/tests/unittests/test_imperative_checkpoint.py
+7
-7
python/paddle/fluid/tests/unittests/test_imperative_deepcf.py
...on/paddle/fluid/tests/unittests/test_imperative_deepcf.py
+14
-17
python/paddle/fluid/tests/unittests/test_imperative_gan.py
python/paddle/fluid/tests/unittests/test_imperative_gan.py
+9
-9
python/paddle/fluid/tests/unittests/test_imperative_gnn.py
python/paddle/fluid/tests/unittests/test_imperative_gnn.py
+5
-8
python/paddle/fluid/tests/unittests/test_imperative_mnist.py
python/paddle/fluid/tests/unittests/test_imperative_mnist.py
+5
-5
python/paddle/fluid/tests/unittests/test_imperative_optimizer.py
...paddle/fluid/tests/unittests/test_imperative_optimizer.py
+5
-5
python/paddle/fluid/tests/unittests/test_imperative_ptb_rnn.py
...n/paddle/fluid/tests/unittests/test_imperative_ptb_rnn.py
+10
-11
python/paddle/fluid/tests/unittests/test_imperative_resnet.py
...on/paddle/fluid/tests/unittests/test_imperative_resnet.py
+10
-10
python/paddle/fluid/tests/unittests/test_imperative_se_resnext.py
...addle/fluid/tests/unittests/test_imperative_se_resnext.py
+6
-6
python/paddle/fluid/tests/unittests/test_imperative_transformer.py
...ddle/fluid/tests/unittests/test_imperative_transformer.py
+10
-8
python/paddle/fluid/tests/unittests/test_layers.py
python/paddle/fluid/tests/unittests/test_layers.py
+21
-21
未找到文件。
paddle/fluid/API.spec
浏览文件 @
9bd44b94
...
...
@@ -13,6 +13,7 @@ paddle.fluid.name_scope (ArgSpec(args=['prefix'], varargs=None, keywords=None, d
paddle.fluid.cuda_places (ArgSpec(args=['device_ids'], varargs=None, keywords=None, defaults=(None,)), ('document', '7d9a51fc9cf3c5245b5227080a8064c3'))
paddle.fluid.cpu_places (ArgSpec(args=['device_count'], varargs=None, keywords=None, defaults=(None,)), ('document', '4c0cd83f0b401fc2ff84c70974e5d210'))
paddle.fluid.cuda_pinned_places (ArgSpec(args=['device_count'], varargs=None, keywords=None, defaults=(None,)), ('document', 'd0c3ebd813c39958c92b78e3eef7e912'))
paddle.fluid.in_dygraph_mode (ArgSpec(args=[], varargs=None, keywords=None, defaults=None), ('document', 'f06314a1cb30c96b5808dde2219c2dae'))
paddle.fluid.Executor.__init__ (ArgSpec(args=['self', 'place'], varargs=None, keywords=None, defaults=None), ('document', '6adf97f83acf6453d4a6a4b1070f3754'))
paddle.fluid.Executor.close (ArgSpec(args=['self'], varargs=None, keywords=None, defaults=None), ('document', 'f5369953dd0c443961cf79f7a00e1a03'))
paddle.fluid.Executor.infer_from_dataset (ArgSpec(args=['self', 'program', 'dataset', 'scope', 'thread', 'debug', 'fetch_list', 'fetch_info', 'print_period'], varargs=None, keywords=None, defaults=(None, None, None, 0, False, None, None, 100)), ('document', '9c7decb955b9c4f718114179c8985581'))
...
...
python/paddle/fluid/__init__.py
浏览文件 @
9bd44b94
...
...
@@ -66,6 +66,8 @@ from . import compiler
from
.compiler
import
*
from
paddle.fluid.layers.math_op_patch
import
monkey_patch_variable
from
.
import
install_check
from
.dygraph.nn
import
*
from
.dygraph.layers
import
*
Tensor
=
LoDTensor
...
...
python/paddle/fluid/dygraph/base.py
浏览文件 @
9bd44b94
...
...
@@ -22,7 +22,7 @@ __all__ = ['enabled', 'guard', 'to_variable']
def
enabled
():
return
framework
.
_
in_dygraph_mode
()
return
framework
.
in_dygraph_mode
()
@
signature_safe_contextmanager
...
...
python/paddle/fluid/dygraph/checkpoint.py
浏览文件 @
9bd44b94
...
...
@@ -97,20 +97,12 @@ def load_persistables(vardict, dirname, filename=None):
Examples:
.. code-block:: python
my_layer = layer(fluid.
dygraph.
Layer)
my_layer = layer(fluid.Layer)
param_path = "./my_paddle_model"
param_dict = fluid.dygraph.load_persistables(my_layer.parameters(), param_path)
param_1 = param_dict['PtbModel_0.w_1']
or:
my_layer = layer(fluid.dygraph.Layer)
param_path = "./my_paddle_model"
filename = "model.file"
param_dict = fluid.dygraph.load_persistables(my_layer.state_dict(), param_path,
filename=filename)
param_1 = param_dict['PtbModel_0.w_1']
"""
if
isinstance
(
vardict
,
collections
.
OrderedDict
):
return
_load_var_from_file
(
vardict
,
dirname
,
filename
)
...
...
python/paddle/fluid/dygraph/layer_object_helper.py
浏览文件 @
9bd44b94
...
...
@@ -16,7 +16,7 @@ from __future__ import print_function
import
copy
import
six
from
..framework
import
Parameter
,
_
in_dygraph_mode
from
..framework
import
Parameter
,
in_dygraph_mode
from
..param_attr
import
ParamAttr
from
..
import
core
from
six.moves
import
zip
...
...
python/paddle/fluid/dygraph/layers.py
浏览文件 @
9bd44b94
...
...
@@ -139,14 +139,14 @@ class Layer(core.Layer):
def
clear_gradients
(
self
):
for
p
in
self
.
parameters
():
p
.
_
clear_gradient
()
p
.
clear_gradient
()
def
_
build_once
(
self
,
*
args
):
def
build_once
(
self
,
*
args
):
pass
def
__call__
(
self
,
*
inputs
):
if
not
self
.
_built
:
self
.
_
build_once
(
*
inputs
)
self
.
build_once
(
*
inputs
)
outputs
=
self
.
forward
(
*
inputs
)
self
.
_built
=
True
...
...
python/paddle/fluid/dygraph/nn.py
浏览文件 @
9bd44b94
此差异已折叠。
点击以展开。
python/paddle/fluid/framework.py
浏览文件 @
9bd44b94
...
...
@@ -67,6 +67,7 @@ __all__ = [
'cuda_places'
,
'cpu_places'
,
'cuda_pinned_places'
,
'in_dygraph_mode'
,
]
EMPTY_VAR_NAME
=
core
.
kEmptyVarName
()
...
...
@@ -79,7 +80,10 @@ _dygraph_tracer_ = None
_dygraph_current_expected_place_
=
None
def
_in_dygraph_mode
():
def
in_dygraph_mode
():
'''
Returns(bool): True if the program is running in dynamic graph mode
'''
return
_dygraph_tracer_
is
not
None
...
...
@@ -396,7 +400,7 @@ class Variable(object):
if
not
isinstance
(
dtype
,
core
.
VarDesc
.
VarType
):
dtype
=
convert_np_dtype_to_dtype_
(
dtype
)
if
_
in_dygraph_mode
():
if
in_dygraph_mode
():
# record vars in tracer rather than blocks
self
.
_ivar
=
kwargs
.
get
(
"ivar"
,
None
)
if
not
self
.
_ivar
:
...
...
@@ -482,21 +486,21 @@ class Variable(object):
self
.
block
.
vars
[
name
]
=
self
self
.
op
=
None
self
.
stop_gradient
=
stop_gradient
self
.
_
stop_gradient
=
stop_gradient
self
.
is_data
=
is_data
def
_
numpy
(
self
):
def
numpy
(
self
):
new_ivar
=
self
.
_ivar
.
_copy_to
(
core
.
CPUPlace
(),
True
)
return
np
.
array
(
new_ivar
.
value
().
get_tensor
())
def
_
backward
(
self
):
def
backward
(
self
):
self
.
_ivar
.
_run_backward
()
def
_
gradient
(
self
):
def
gradient
(
self
):
new_ivar
=
self
.
_ivar
.
_grad_ivar
().
_copy_to
(
core
.
CPUPlace
(),
True
)
return
np
.
array
(
new_ivar
.
value
().
get_tensor
())
def
_
clear_gradient
(
self
):
def
clear_gradient
(
self
):
self
.
_ivar
.
_clear_gradient
()
def
__str__
(
self
):
...
...
@@ -516,7 +520,7 @@ class Variable(object):
Returns:
str: The debug string.
"""
if
_
in_dygraph_mode
():
if
in_dygraph_mode
():
# TODO(panyx0718): add more dygraph debug info.
return
'name %s, dtype: %s shape: %s'
%
(
self
.
name
,
self
.
dtype
,
self
.
shape
)
...
...
@@ -535,7 +539,7 @@ class Variable(object):
__repr__
=
__str__
def
_
set_desc
(
self
,
input
):
def
set_desc
(
self
,
input
):
"""
Set the variable description.
...
...
@@ -548,43 +552,43 @@ class Variable(object):
self
.
desc
=
input
@
property
def
_
stop_gradient
(
self
):
if
_
in_dygraph_mode
():
def
stop_gradient
(
self
):
if
in_dygraph_mode
():
return
self
.
_ivar
.
stop_gradient
else
:
return
self
.
stop_gradient
return
self
.
_
stop_gradient
@
_
stop_gradient
.
setter
def
_
stop_gradient
(
self
,
s
):
if
_
in_dygraph_mode
():
@
stop_gradient
.
setter
def
stop_gradient
(
self
,
s
):
if
in_dygraph_mode
():
self
.
_ivar
.
stop_gradient
=
s
else
:
self
.
stop_gradient
=
s
self
.
_
stop_gradient
=
s
@
property
def
persistable
(
self
):
if
_
in_dygraph_mode
():
if
in_dygraph_mode
():
return
self
.
_ivar
.
persistable
else
:
return
self
.
desc
.
persistable
()
@
persistable
.
setter
def
persistable
(
self
,
p
):
if
_
in_dygraph_mode
():
if
in_dygraph_mode
():
return
self
.
_ivar
.
persistable
else
:
self
.
desc
.
set_persistable
(
p
)
@
property
def
name
(
self
):
if
_
in_dygraph_mode
():
if
in_dygraph_mode
():
return
self
.
_ivar
.
name
else
:
return
cpt
.
to_text
(
self
.
desc
.
name
())
@
name
.
setter
def
name
(
self
,
new_name
):
if
_
in_dygraph_mode
():
if
in_dygraph_mode
():
self
.
_ivar
.
name
=
new_name
else
:
self
.
desc
.
set_name
(
new_name
)
...
...
@@ -592,14 +596,14 @@ class Variable(object):
@
property
def
shape
(
self
):
# convert to tuple, make it as same as numpy API.
if
_
in_dygraph_mode
():
if
in_dygraph_mode
():
return
self
.
_ivar
.
shape
else
:
return
tuple
(
self
.
desc
.
shape
())
@
property
def
dtype
(
self
):
if
_
in_dygraph_mode
():
if
in_dygraph_mode
():
return
self
.
_ivar
.
dtype
else
:
return
self
.
desc
.
dtype
()
...
...
@@ -611,7 +615,7 @@ class Variable(object):
@
property
def
type
(
self
):
if
_
in_dygraph_mode
():
if
in_dygraph_mode
():
return
self
.
_ivar
.
dtype
else
:
return
self
.
desc
.
type
()
...
...
@@ -721,7 +725,7 @@ class Variable(object):
name
=
unique_name
.
generate
(
"."
.
join
(
self
.
name
)),
dtype
=
self
.
dtype
,
persistable
=
self
.
persistable
,
stop_gradient
=
self
.
_
stop_gradient
,
)
stop_gradient
=
self
.
stop_gradient
,
)
else
:
return
self
...
...
@@ -930,7 +934,7 @@ class Operator(object):
inputs
=
None
,
outputs
=
None
,
attrs
=
None
):
if
_
in_dygraph_mode
():
if
in_dygraph_mode
():
if
type
is
None
:
raise
ValueError
(
"`type` to initialized an Operator can not be None."
)
...
...
@@ -1049,7 +1053,7 @@ class Operator(object):
for
arg
in
out_args
:
out_arg_names
.
append
(
cpt
.
to_text
(
arg
.
name
))
# TODO(minqiyang): could we remove variable's op in static mode?
if
not
_
in_dygraph_mode
():
if
not
in_dygraph_mode
():
arg
.
op
=
self
self
.
desc
.
set_output
(
out_proto
.
name
,
out_arg_names
)
...
...
@@ -1095,7 +1099,7 @@ class Operator(object):
@
property
def
type
(
self
):
if
_
in_dygraph_mode
():
if
in_dygraph_mode
():
return
self
.
iop
.
type
else
:
return
self
.
desc
.
type
()
...
...
@@ -1638,7 +1642,7 @@ class Block(object):
Returns:
Operator: the append Operator.
"""
if
_
in_dygraph_mode
():
if
in_dygraph_mode
():
op
=
Operator
(
block
=
self
,
desc
=
None
,
...
...
@@ -1710,7 +1714,7 @@ class Block(object):
return
self
.
ops
[
start
:
end
]
def
_prepend_op
(
self
,
*
args
,
**
kwargs
):
if
_
in_dygraph_mode
():
if
in_dygraph_mode
():
op
=
Operator
(
self
,
None
,
...
...
python/paddle/fluid/initializer.py
浏览文件 @
9bd44b94
...
...
@@ -165,7 +165,7 @@ class ConstantInitializer(Initializer):
'force_cpu'
:
self
.
_force_cpu
or
force_init_on_cpu
()
},
stop_gradient
=
True
)
if
not
framework
.
_
in_dygraph_mode
():
if
not
framework
.
in_dygraph_mode
():
var
.
op
=
op
return
op
...
...
@@ -245,7 +245,7 @@ class UniformInitializer(Initializer):
attrs
=
{
"in_dtype"
:
out_var
.
dtype
,
"out_dtype"
:
var
.
dtype
})
if
not
framework
.
_
in_dygraph_mode
():
if
not
framework
.
in_dygraph_mode
():
var
.
op
=
op
return
op
...
...
@@ -324,7 +324,7 @@ class NormalInitializer(Initializer):
outputs
=
{
"Out"
:
var
},
attrs
=
{
"in_dtype"
:
out_var
.
dtype
,
"out_dtype"
:
var
.
dtype
})
if
not
framework
.
_
in_dygraph_mode
():
if
not
framework
.
in_dygraph_mode
():
var
.
op
=
op
return
op
...
...
@@ -403,7 +403,7 @@ class TruncatedNormalInitializer(Initializer):
outputs
=
{
"Out"
:
var
},
attrs
=
{
"in_dtype"
:
out_var
.
dtype
,
"out_dtype"
:
var
.
dtype
})
if
not
framework
.
_
in_dygraph_mode
():
if
not
framework
.
in_dygraph_mode
():
var
.
op
=
op
return
op
...
...
@@ -509,7 +509,7 @@ class XavierInitializer(Initializer):
"seed"
:
self
.
_seed
},
stop_gradient
=
True
)
if
not
framework
.
_
in_dygraph_mode
():
if
not
framework
.
in_dygraph_mode
():
var
.
op
=
op
return
op
...
...
@@ -610,7 +610,7 @@ class MSRAInitializer(Initializer):
"seed"
:
self
.
_seed
},
stop_gradient
=
True
)
if
not
framework
.
_
in_dygraph_mode
():
if
not
framework
.
in_dygraph_mode
():
var
.
op
=
op
return
op
...
...
@@ -709,7 +709,7 @@ class BilinearInitializer(Initializer):
'shape'
:
list
(
shape
),
value_name
:
values
})
if
not
framework
.
_
in_dygraph_mode
():
if
not
framework
.
in_dygraph_mode
():
var
.
op
=
op
return
op
...
...
@@ -768,7 +768,7 @@ class NumpyArrayInitializer(Initializer):
value_name
:
values
},
stop_gradient
=
True
)
if
not
framework
.
_
in_dygraph_mode
():
if
not
framework
.
in_dygraph_mode
():
var
.
op
=
op
return
op
...
...
python/paddle/fluid/layer_helper.py
浏览文件 @
9bd44b94
...
...
@@ -17,7 +17,7 @@ from __future__ import print_function
import
copy
import
six
from
.framework
import
Parameter
,
dtype_is_floating
,
_
in_dygraph_mode
from
.framework
import
Parameter
,
dtype_is_floating
,
in_dygraph_mode
from
.
import
unique_name
from
paddle.fluid.initializer
import
Constant
,
Xavier
from
.param_attr
import
ParamAttr
...
...
python/paddle/fluid/layer_helper_base.py
浏览文件 @
9bd44b94
...
...
@@ -17,7 +17,7 @@ from __future__ import print_function
import
copy
import
numpy
as
np
from
.framework
import
Variable
,
default_main_program
,
default_startup_program
,
_
in_dygraph_mode
,
_current_expected_place
from
.framework
import
Variable
,
default_main_program
,
default_startup_program
,
in_dygraph_mode
,
_current_expected_place
from
.
import
unique_name
from
.param_attr
import
ParamAttr
,
WeightNormParamAttr
from
.
import
core
...
...
@@ -54,7 +54,7 @@ class LayerHelperBase(object):
Return Variable construct from value
"""
if
isinstance
(
value
,
np
.
ndarray
):
assert
_
in_dygraph_mode
(
assert
in_dygraph_mode
(
),
"to_variable could only be called in dygraph mode"
if
not
block
:
...
...
@@ -302,7 +302,7 @@ class LayerHelperBase(object):
param
=
self
.
_create_weight_normalize
(
attr
,
shape
,
dtype
)
WeightNormParamAttr
.
params_with_weight_norm
.
append
(
param
)
return
param
if
_
in_dygraph_mode
():
if
in_dygraph_mode
():
# In dygraph mode, we want the returned parameter to be
# initialized so that it can be used imperatively.
return
self
.
main_program
.
global_block
().
create_parameter
(
...
...
@@ -370,7 +370,7 @@ class LayerHelperBase(object):
initializer: initializer to use
"""
assert
isinstance
(
var
,
Variable
)
if
_
in_dygraph_mode
():
if
in_dygraph_mode
():
initializer
(
var
,
var
.
block
)
else
:
self
.
startup_program
.
global_block
().
create_var
(
...
...
python/paddle/fluid/layers/nn.py
浏览文件 @
9bd44b94
...
...
@@ -23,7 +23,7 @@ import os
import
inspect
from
..layer_helper
import
LayerHelper
from
..initializer
import
Normal
,
Constant
,
NumpyArrayInitializer
from
..framework
import
Variable
,
OpProtoHolder
,
_
in_dygraph_mode
from
..framework
import
Variable
,
OpProtoHolder
,
in_dygraph_mode
from
..dygraph
import
base
from
..param_attr
import
ParamAttr
from
.layer_function_generator
import
autodoc
,
templatedoc
,
_generate_doc_string_
...
...
@@ -481,7 +481,7 @@ def dynamic_lstm(input,
forward, _ = fluid.layers.dynamic_lstm(
input=forward_proj, size=hidden_dim * 4, use_peepholes=False)
"""
assert
_
in_dygraph_mode
(
assert
in_dygraph_mode
(
)
is
not
True
,
"please use lstm instead of dynamic_lstm in dygraph mode!"
assert
bias_attr
is
not
False
,
"bias_attr should not be False in dynamic_lstmp."
helper
=
LayerHelper
(
'lstm'
,
**
locals
())
...
...
@@ -867,7 +867,7 @@ def dynamic_lstmp(input,
proj_activation="tanh")
"""
assert
_
in_dygraph_mode
(
assert
in_dygraph_mode
(
)
is
not
True
,
"please use lstm instead of dynamic_lstmp in dygraph mode!"
assert
bias_attr
is
not
False
,
"bias_attr should not be False in dynamic_lstmp."
...
...
@@ -1041,7 +1041,7 @@ def dynamic_gru(input,
hidden = fluid.layers.dynamic_gru(input=x, size=hidden_dim)
"""
assert
_
in_dygraph_mode
(
assert
in_dygraph_mode
(
)
is
not
True
,
"please use gru instead of dynamic_gru in dygraph mode!"
helper
=
LayerHelper
(
'gru'
,
**
locals
())
...
...
@@ -1760,7 +1760,7 @@ def sequence_conv(input,
Variable: output of sequence_conv
"""
assert
not
_
in_dygraph_mode
(),
(
assert
not
in_dygraph_mode
(),
(
"sequence layer is not supported in dygraph mode yet."
)
helper
=
LayerHelper
(
'sequence_conv'
,
**
locals
())
dtype
=
helper
.
input_dtype
()
...
...
@@ -1821,7 +1821,7 @@ def sequence_softmax(input, use_cudnn=False, name=None):
dtype='float32', lod_level=1)
x_sequence_softmax = fluid.layers.sequence_softmax(input=x)
"""
assert
not
_
in_dygraph_mode
(),
(
assert
not
in_dygraph_mode
(),
(
"sequence layer is not supported in dygraph mode yet."
)
helper
=
LayerHelper
(
'sequence_softmax'
,
**
locals
())
dtype
=
helper
.
input_dtype
()
...
...
@@ -2315,7 +2315,7 @@ def sequence_pool(input, pool_type, is_test=False):
last_x = fluid.layers.sequence_pool(input=x, pool_type='last')
first_x = fluid.layers.sequence_pool(input=x, pool_type='first')
"""
assert
not
_
in_dygraph_mode
(),
(
assert
not
in_dygraph_mode
(),
(
"sequence layer is not supported in dygraph mode yet."
)
helper
=
LayerHelper
(
'sequence_pool'
,
**
locals
())
dtype
=
helper
.
input_dtype
()
...
...
@@ -2356,7 +2356,7 @@ def sequence_concat(input, name=None):
out = fluid.layers.sequence_concat(input=[seq1, seq2, seq3])
"""
assert
not
_
in_dygraph_mode
(),
(
assert
not
in_dygraph_mode
(),
(
"sequence layer is not supported in dygraph mode yet."
)
helper
=
LayerHelper
(
'sequence_concat'
,
**
locals
())
out
=
helper
.
create_variable_for_type_inference
(
dtype
=
helper
.
input_dtype
())
...
...
@@ -2485,7 +2485,7 @@ def sequence_slice(input, offset, length, name=None):
subseqs = fluid.layers.sequence_slice(input=seqs, offset=offset,
length=length)
"""
assert
not
_
in_dygraph_mode
(),
(
assert
not
in_dygraph_mode
(),
(
"sequence layer is not supported in dygraph mode yet."
)
helper
=
LayerHelper
(
"sequence_slice"
,
**
locals
())
dtype
=
helper
.
input_dtype
()
...
...
@@ -3307,7 +3307,7 @@ def layer_norm(input,
>>> dtype='float32')
>>> x = fluid.layers.layer_norm(input=data, begin_norm_axis=1)
"""
assert
_
in_dygraph_mode
(
assert
in_dygraph_mode
(
)
is
not
True
,
"please use FC instead of fc in dygraph mode!"
helper
=
LayerHelper
(
'layer_norm'
,
**
locals
())
dtype
=
helper
.
input_dtype
()
...
...
@@ -3946,7 +3946,7 @@ def sequence_expand(x, y, ref_level=-1, name=None):
dtype='float32', lod_level=1)
out = layers.sequence_expand(x=x, y=y, ref_level=0)
"""
assert
not
_
in_dygraph_mode
(),
(
assert
not
in_dygraph_mode
(),
(
"sequence layer is not supported in dygraph mode yet."
)
helper
=
LayerHelper
(
'sequence_expand'
,
input
=
x
,
**
locals
())
dtype
=
helper
.
input_dtype
()
...
...
@@ -4014,7 +4014,7 @@ def sequence_expand_as(x, y, name=None):
dtype='float32', lod_level=1)
out = layers.sequence_expand_as(x=x, y=y)
"""
assert
not
_
in_dygraph_mode
(),
(
assert
not
in_dygraph_mode
(),
(
"sequence layer is not supported in dygraph mode yet."
)
helper
=
LayerHelper
(
'sequence_expand_as'
,
input
=
x
,
**
locals
())
dtype
=
helper
.
input_dtype
()
...
...
@@ -4062,7 +4062,7 @@ def sequence_pad(x, pad_value, maxlen=None, name=None):
out = fluid.layers.sequence_pad(x=x, pad_value=pad_value)
"""
assert
not
_
in_dygraph_mode
(),
(
assert
not
in_dygraph_mode
(),
(
"sequence layer is not supported in dygraph mode yet."
)
helper
=
LayerHelper
(
'sequence_pad'
,
input
=
x
,
**
locals
())
dtype
=
helper
.
input_dtype
()
...
...
@@ -4130,7 +4130,7 @@ def sequence_unpad(x, length, name=None):
out = fluid.layers.sequence_unpad(x=x, length=len)
"""
assert
not
_
in_dygraph_mode
(),
(
assert
not
in_dygraph_mode
(),
(
"sequence layer is not supported in dygraph mode yet."
)
helper
=
LayerHelper
(
'sequence_unpad'
,
input
=
x
,
**
locals
())
dtype
=
helper
.
input_dtype
()
...
...
@@ -5305,7 +5305,7 @@ def sequence_reshape(input, new_dim):
x = fluid.layers.data(shape=[5, 20], dtype='float32', lod_level=1)
x_reshaped = fluid.layers.sequence_reshape(input=x, new_dim=10)
"""
assert
not
_
in_dygraph_mode
(),
(
assert
not
in_dygraph_mode
(),
(
"sequence layer is not supported in dygraph mode yet."
)
helper
=
LayerHelper
(
'sequence_reshape'
,
**
locals
())
out
=
helper
.
create_variable_for_type_inference
(
helper
.
input_dtype
())
...
...
@@ -5841,7 +5841,7 @@ def im2sequence(input,
input=layer, stride=[1, 1], filter_size=[2, 2])
"""
assert
not
_
in_dygraph_mode
(),
(
assert
not
in_dygraph_mode
(),
(
"sequence layer is not supported in dygraph mode yet."
)
if
isinstance
(
filter_size
,
int
):
...
...
@@ -6485,7 +6485,7 @@ def squeeze(input, axes, name=None):
x = layers.data(name='x', shape=[5, 1, 10])
y = layers.sequeeze(input=x, axes=[1])
"""
assert
not
_
in_dygraph_mode
(),
(
assert
not
in_dygraph_mode
(),
(
"squeeze layer is not supported in dygraph mode yet."
)
helper
=
LayerHelper
(
"squeeze"
,
**
locals
())
out
=
helper
.
create_variable_for_type_inference
(
dtype
=
input
.
dtype
)
...
...
@@ -7631,7 +7631,7 @@ def sequence_scatter(input, index, updates, name=None):
output = fluid.layers.sequence_scatter(input, index, updates)
"""
assert
not
_
in_dygraph_mode
(),
(
assert
not
in_dygraph_mode
(),
(
"sequence layer is not supported in dygraph mode yet."
)
helper
=
LayerHelper
(
'sequence_scatter'
,
**
locals
())
dtype
=
helper
.
input_dtype
()
...
...
@@ -8721,7 +8721,7 @@ def sequence_enumerate(input, win_size, pad_value=0, name=None):
x = fluid.layers.data(shape[30, 1], dtype='int32', lod_level=1)
out = fluid.layers.sequence_enumerate(input=x, win_size=3, pad_value=0)
"""
assert
not
_
in_dygraph_mode
(),
(
assert
not
in_dygraph_mode
(),
(
"sequence layer is not supported in dygraph mode yet."
)
helper
=
LayerHelper
(
'sequence_enumerate'
,
**
locals
())
out
=
helper
.
create_variable_for_type_inference
(
...
...
@@ -8762,7 +8762,7 @@ def sequence_mask(x, maxlen=None, dtype='int64', name=None):
Variable: The output sequence mask.
"""
assert
not
_
in_dygraph_mode
(),
(
assert
not
in_dygraph_mode
(),
(
"sequence layer is not supported in dygraph mode yet."
)
helper
=
LayerHelper
(
'sequence_mask'
,
**
locals
())
...
...
@@ -9241,7 +9241,7 @@ def _elementwise_op(helper):
op_type
=
helper
.
layer_type
x
=
helper
.
kwargs
.
get
(
'x'
,
None
)
y
=
helper
.
kwargs
.
get
(
'y'
,
None
)
if
_
in_dygraph_mode
():
if
in_dygraph_mode
():
x
=
base
.
to_variable
(
x
)
y
=
base
.
to_variable
(
y
)
...
...
@@ -9814,7 +9814,7 @@ def sequence_reverse(x, name=None):
Returns:
out(${y_type}): ${y_comment}
"""
assert
not
_
in_dygraph_mode
(),
(
assert
not
in_dygraph_mode
(),
(
"sequence layer is not supported in dygraph mode yet."
)
helper
=
LayerHelper
(
"sequence_reverse"
,
**
locals
())
if
name
is
None
:
...
...
python/paddle/fluid/optimizer.py
浏览文件 @
9bd44b94
...
...
@@ -55,7 +55,7 @@ class Optimizer(object):
"""
def
__init__
(
self
,
learning_rate
,
regularization
=
None
,
name
=
None
):
if
framework
.
_
in_dygraph_mode
():
if
framework
.
in_dygraph_mode
():
if
not
isinstance
(
learning_rate
,
float
)
and
\
not
isinstance
(
learning_rate
,
LearningRateDecay
):
raise
TypeError
(
...
...
@@ -205,7 +205,7 @@ class Optimizer(object):
name
=
self
.
_name
+
"_"
+
name
if
(
name
in
self
.
_accumulators
and
param
.
name
in
self
.
_accumulators
[
name
]):
if
framework
.
_
in_dygraph_mode
():
if
framework
.
in_dygraph_mode
():
return
self
.
_accumulators
[
name
][
param
.
name
]
raise
Exception
(
"Accumulator {} already exists for parameter {}"
.
format
(
name
,
param
.
name
))
...
...
@@ -363,7 +363,7 @@ class Optimizer(object):
See examples in `apply_gradients`.
"""
self
.
_dtype
=
loss
.
dtype
if
framework
.
_
in_dygraph_mode
():
if
framework
.
in_dygraph_mode
():
if
parameter_list
is
not
None
:
parameters
=
parameter_list
else
:
...
...
@@ -448,7 +448,7 @@ class Optimizer(object):
Returns:
list: A list of operators appended to the current program.
"""
if
framework
.
_
in_dygraph_mode
():
if
framework
.
in_dygraph_mode
():
with
program_guard
(
framework
.
default_main_program
(),
framework
.
default_startup_program
()):
optimize_ops
=
self
.
_create_optimization_pass
(
params_grads
)
...
...
python/paddle/fluid/tests/unittests/test_base_layer.py
浏览文件 @
9bd44b94
...
...
@@ -18,7 +18,7 @@ import numpy as np
import
paddle.fluid
as
fluid
class
L1
(
fluid
.
dygraph
.
Layer
):
class
L1
(
fluid
.
Layer
):
def
__init__
(
self
,
prefix
):
super
(
L1
,
self
).
__init__
(
prefix
)
self
.
_param_attr
=
fluid
.
ParamAttr
(
...
...
@@ -32,7 +32,7 @@ class L1(fluid.dygraph.Layer):
return
self
.
w1
+
self
.
w2
class
L2
(
fluid
.
dygraph
.
Layer
):
class
L2
(
fluid
.
Layer
):
def
__init__
(
self
,
prefix
):
super
(
L2
,
self
).
__init__
(
prefix
)
self
.
layer1
=
L1
(
self
.
full_name
())
...
...
@@ -42,7 +42,7 @@ class L2(fluid.dygraph.Layer):
return
self
.
layer1
()
+
self
.
layer2
()
class
L3
(
fluid
.
dygraph
.
Layer
):
class
L3
(
fluid
.
Layer
):
def
__init__
(
self
,
prefix
):
super
(
L3
,
self
).
__init__
(
prefix
)
self
.
layer1
=
L2
(
self
.
full_name
())
...
...
@@ -59,7 +59,7 @@ class TestBaseLayer(unittest.TestCase):
ret
=
l
()
self
.
assertEqual
(
l
.
w1
.
name
,
"test_one_level/L1_0.w_0"
)
self
.
assertEqual
(
l
.
w2
.
name
,
"test_one_level/L1_0.w_1"
)
self
.
assertTrue
(
np
.
allclose
(
ret
.
_
numpy
(),
0.2
*
np
.
ones
([
2
,
2
])))
self
.
assertTrue
(
np
.
allclose
(
ret
.
numpy
(),
0.2
*
np
.
ones
([
2
,
2
])))
def
test_three_level
(
self
):
with
fluid
.
dygraph
.
guard
():
...
...
@@ -72,7 +72,7 @@ class TestBaseLayer(unittest.TestCase):
self
.
assertEqual
(
names
[
3
],
"test_three_level/L3_0/L2_0/L1_1.w_1"
)
self
.
assertEqual
(
names
[
4
],
"test_three_level/L3_0/L2_1/L1_0.w_0"
)
self
.
assertEqual
(
names
[
5
],
"test_three_level/L3_0/L2_1/L1_0.w_1"
)
self
.
assertTrue
(
np
.
allclose
(
ret
.
_
numpy
(),
0.8
*
np
.
ones
([
2
,
2
])))
self
.
assertTrue
(
np
.
allclose
(
ret
.
numpy
(),
0.8
*
np
.
ones
([
2
,
2
])))
if
__name__
==
'__main__'
:
...
...
python/paddle/fluid/tests/unittests/test_imperative_basic.py
浏览文件 @
9bd44b94
...
...
@@ -18,11 +18,11 @@ import numpy as np
import
paddle.fluid
as
fluid
from
paddle.fluid
import
core
from
paddle.fluid
.dygraph.nn
import
FC
from
paddle.fluid
import
FC
from
test_imperative_base
import
new_program_scope
class
MyLayer
(
fluid
.
dygraph
.
Layer
):
class
MyLayer
(
fluid
.
Layer
):
def
__init__
(
self
,
name_scope
):
super
(
MyLayer
,
self
).
__init__
(
name_scope
)
...
...
@@ -34,7 +34,7 @@ class MyLayer(fluid.dygraph.Layer):
return
[
x
]
class
MyPyLayer
(
fluid
.
dygraph
.
PyLayer
):
class
MyPyLayer
(
fluid
.
PyLayer
):
def
__init__
(
self
):
super
(
MyPyLayer
,
self
).
__init__
()
...
...
@@ -48,7 +48,7 @@ class MyPyLayer(fluid.dygraph.PyLayer):
return
np
.
array
(
dout
)
*
(
1
-
np
.
square
(
np
.
array
(
out
)))
class
MLP
(
fluid
.
dygraph
.
Layer
):
class
MLP
(
fluid
.
Layer
):
def
__init__
(
self
,
name_scope
):
super
(
MLP
,
self
).
__init__
(
name_scope
)
self
.
_fc1
=
FC
(
self
.
full_name
(),
...
...
@@ -71,7 +71,7 @@ class MLP(fluid.dygraph.Layer):
return
x
class
SimpleRNNCell
(
fluid
.
dygraph
.
Layer
):
class
SimpleRNNCell
(
fluid
.
Layer
):
def
__init__
(
self
,
name_scope
,
step_input_size
,
hidden_size
,
output_size
,
param_attr
):
super
(
SimpleRNNCell
,
self
).
__init__
(
name_scope
)
...
...
@@ -81,7 +81,7 @@ class SimpleRNNCell(fluid.dygraph.Layer):
self
.
_dtype
=
core
.
VarDesc
.
VarType
.
FP32
self
.
param_attr
=
param_attr
def
_
build_once
(
self
,
inputs
,
pre_hidden
):
def
build_once
(
self
,
inputs
,
pre_hidden
):
i2h_param_shape
=
[
self
.
step_input_size
,
self
.
hidden_size
]
h2h_param_shape
=
[
self
.
hidden_size
,
self
.
hidden_size
]
h2o_param_shape
=
[
self
.
output_size
,
self
.
hidden_size
]
...
...
@@ -159,7 +159,7 @@ class SimpleRNNCell(fluid.dygraph.Layer):
return
reduce_out
,
hidden
class
SimpleRNN
(
fluid
.
dygraph
.
Layer
):
class
SimpleRNN
(
fluid
.
Layer
):
def
__init__
(
self
,
name_scope
):
super
(
SimpleRNN
,
self
).
__init__
(
name_scope
)
self
.
seq_len
=
4
...
...
@@ -200,22 +200,22 @@ class TestImperative(unittest.TestCase):
inputs
.
append
(
fluid
.
dygraph
.
base
.
to_variable
(
x
))
ret
=
fluid
.
layers
.
sums
(
inputs
)
loss
=
fluid
.
layers
.
reduce_sum
(
ret
)
loss
.
_
backward
()
self
.
assertTrue
(
np
.
allclose
(
ret
.
_
numpy
(),
x
*
10
))
self
.
assertTrue
(
np
.
allclose
(
inputs
[
0
].
_
gradient
(),
x
))
loss
.
backward
()
self
.
assertTrue
(
np
.
allclose
(
ret
.
numpy
(),
x
*
10
))
self
.
assertTrue
(
np
.
allclose
(
inputs
[
0
].
gradient
(),
x
))
def
test_layer
(
self
):
with
fluid
.
dygraph
.
guard
():
cl
=
core
.
Layer
()
cl
.
forward
([])
l
=
fluid
.
dygraph
.
Layer
(
"l"
)
l
=
fluid
.
Layer
(
"l"
)
self
.
assertRaises
(
NotImplementedError
,
l
.
forward
,
[])
def
test_pylayer_func_id
(
self
):
with
fluid
.
dygraph
.
guard
():
class
PyLayer1
(
fluid
.
dygraph
.
PyLayer
):
class
PyLayer1
(
fluid
.
PyLayer
):
def
__init__
(
self
):
super
(
PyLayer1
,
self
).
__init__
()
...
...
@@ -227,7 +227,7 @@ class TestImperative(unittest.TestCase):
def
backward
(
input
):
return
input
class
PyLayer2
(
fluid
.
dygraph
.
PyLayer
):
class
PyLayer2
(
fluid
.
PyLayer
):
def
__init__
(
self
):
super
(
PyLayer2
,
self
).
__init__
()
...
...
@@ -257,9 +257,9 @@ class TestImperative(unittest.TestCase):
my_py_layer
=
MyPyLayer
()
var_inp
=
fluid
.
dygraph
.
base
.
to_variable
(
np_inp
)
outs
=
my_py_layer
(
var_inp
)
dy_out
=
np
.
sum
(
outs
[
0
].
_
numpy
())
outs
[
0
].
_
backward
()
dy_grad
=
var_inp
.
_
gradient
()
dy_out
=
np
.
sum
(
outs
[
0
].
numpy
())
outs
[
0
].
backward
()
dy_grad
=
var_inp
.
gradient
()
with
new_program_scope
():
inp
=
fluid
.
layers
.
data
(
...
...
@@ -287,9 +287,9 @@ class TestImperative(unittest.TestCase):
l
=
MyLayer
(
"my_layer"
)
x
=
l
(
var_inp
)[
0
]
self
.
assertIsNotNone
(
x
)
dy_out
=
x
.
_
numpy
()
x
.
_
backward
()
dy_grad
=
l
.
_x_for_debug
.
_
gradient
()
dy_out
=
x
.
numpy
()
x
.
backward
()
dy_grad
=
l
.
_x_for_debug
.
gradient
()
with
new_program_scope
():
inp
=
fluid
.
layers
.
data
(
...
...
@@ -314,9 +314,9 @@ class TestImperative(unittest.TestCase):
var_inp
=
fluid
.
dygraph
.
base
.
to_variable
(
np_inp
)
mlp
=
MLP
(
"mlp"
)
out
=
mlp
(
var_inp
)
dy_out
=
out
.
_
numpy
()
out
.
_
backward
()
dy_grad
=
mlp
.
_fc1
.
_w
.
_
gradient
()
dy_out
=
out
.
numpy
()
out
.
backward
()
dy_grad
=
mlp
.
_fc1
.
_w
.
gradient
()
with
new_program_scope
():
inp
=
fluid
.
layers
.
data
(
...
...
@@ -358,7 +358,7 @@ class TestImperative(unittest.TestCase):
x
=
fluid
.
layers
.
elementwise_add
(
inp1
,
inp2
)
else
:
x
=
fluid
.
layers
.
elementwise_sub
(
inp1
,
inp2
)
dygraph_result
=
x
.
_
numpy
()
dygraph_result
=
x
.
numpy
()
# static graph
with
new_program_scope
():
...
...
@@ -407,11 +407,11 @@ class TestImperative(unittest.TestCase):
var_inp
=
fluid
.
layers
.
reshape
(
var_inp
,
shape
=
[
1
,
4
,
3
])
simple_rnn
=
SimpleRNN
(
"simple_rnn"
)
outs
,
pre_hiddens
=
simple_rnn
.
forward
(
var_inp
)
dy_out
=
outs
[
3
].
_
numpy
()
outs
[
3
].
_
backward
()
dy_grad_h2o
=
simple_rnn
.
_cell
.
_h2o_w
.
_
gradient
()
dy_grad_h2h
=
simple_rnn
.
_cell
.
_h2h_w
.
_
gradient
()
dy_grad_i2h
=
simple_rnn
.
_cell
.
_i2h_w
.
_
gradient
()
dy_out
=
outs
[
3
].
numpy
()
outs
[
3
].
backward
()
dy_grad_h2o
=
simple_rnn
.
_cell
.
_h2o_w
.
gradient
()
dy_grad_h2h
=
simple_rnn
.
_cell
.
_h2h_w
.
gradient
()
dy_grad_i2h
=
simple_rnn
.
_cell
.
_i2h_w
.
gradient
()
with
new_program_scope
():
inp
=
fluid
.
layers
.
data
(
...
...
python/paddle/fluid/tests/unittests/test_imperative_checkpoint.py
浏览文件 @
9bd44b94
...
...
@@ -18,11 +18,11 @@ import numpy as np
import
paddle
import
paddle.fluid
as
fluid
from
paddle.fluid.optimizer
import
SGDOptimizer
from
paddle.fluid
.dygraph.nn
import
Conv2D
,
Pool2D
,
FC
from
paddle.fluid
import
Conv2D
,
Pool2D
,
FC
from
paddle.fluid.dygraph.base
import
to_variable
class
SimpleImgConvPool
(
fluid
.
dygraph
.
Layer
):
class
SimpleImgConvPool
(
fluid
.
Layer
):
def
__init__
(
self
,
name_scope
,
num_channels
,
...
...
@@ -71,7 +71,7 @@ class SimpleImgConvPool(fluid.dygraph.Layer):
return
x
class
MNIST
(
fluid
.
dygraph
.
Layer
):
class
MNIST
(
fluid
.
Layer
):
def
__init__
(
self
,
name_scope
):
super
(
MNIST
,
self
).
__init__
(
name_scope
)
...
...
@@ -125,21 +125,21 @@ class TestDygraphCheckpoint(unittest.TestCase):
img
=
to_variable
(
dy_x_data
)
label
=
to_variable
(
y_data
)
label
.
_
stop_gradient
=
True
label
.
stop_gradient
=
True
cost
=
mnist
(
img
)
loss
=
fluid
.
layers
.
cross_entropy
(
cost
,
label
)
avg_loss
=
fluid
.
layers
.
mean
(
loss
)
dy_out
=
avg_loss
.
_
numpy
()
dy_out
=
avg_loss
.
numpy
()
avg_loss
.
_
backward
()
avg_loss
.
backward
()
sgd
.
minimize
(
avg_loss
)
fluid
.
dygraph
.
save_persistables
(
mnist
,
"save_dir"
)
mnist
.
clear_gradients
()
for
param
in
mnist
.
parameters
():
dy_param_init_value
[
param
.
name
]
=
param
.
_
numpy
()
dy_param_init_value
[
param
.
name
]
=
param
.
numpy
()
mnist
.
load_dict
(
fluid
.
dygraph
.
load_persistables
(
mnist
,
"save_dir"
))
...
...
python/paddle/fluid/tests/unittests/test_imperative_deepcf.py
浏览文件 @
9bd44b94
...
...
@@ -32,11 +32,11 @@ NUM_BATCHES = int(os.environ.get('NUM_BATCHES', 5))
NUM_EPOCHES
=
int
(
os
.
environ
.
get
(
'NUM_EPOCHES'
,
1
))
class
DMF
(
fluid
.
dygraph
.
Layer
):
class
DMF
(
fluid
.
Layer
):
def
__init__
(
self
,
name_scope
):
super
(
DMF
,
self
).
__init__
(
name_scope
)
self
.
_user_latent
=
fluid
.
dygraph
.
FC
(
self
.
full_name
(),
256
)
self
.
_item_latent
=
fluid
.
dygraph
.
FC
(
self
.
full_name
(),
256
)
self
.
_user_latent
=
fluid
.
FC
(
self
.
full_name
(),
256
)
self
.
_item_latent
=
fluid
.
FC
(
self
.
full_name
(),
256
)
self
.
_user_layers
=
[]
self
.
_item_layers
=
[]
...
...
@@ -45,13 +45,11 @@ class DMF(fluid.dygraph.Layer):
self
.
_user_layers
.
append
(
self
.
add_sublayer
(
'user_layer_%d'
%
i
,
fluid
.
dygraph
.
FC
(
self
.
full_name
(),
self
.
_hid_sizes
[
i
],
act
=
'relu'
)))
fluid
.
FC
(
self
.
full_name
(),
self
.
_hid_sizes
[
i
],
act
=
'relu'
)))
self
.
_item_layers
.
append
(
self
.
add_sublayer
(
'item_layer_%d'
%
i
,
fluid
.
dygraph
.
FC
(
self
.
full_name
(),
self
.
_hid_sizes
[
i
],
act
=
'relu'
)))
fluid
.
FC
(
self
.
full_name
(),
self
.
_hid_sizes
[
i
],
act
=
'relu'
)))
def
forward
(
self
,
users
,
items
):
users
=
self
.
_user_latent
(
users
)
...
...
@@ -63,19 +61,18 @@ class DMF(fluid.dygraph.Layer):
return
fluid
.
layers
.
elementwise_mul
(
users
,
items
)
class
MLP
(
fluid
.
dygraph
.
Layer
):
class
MLP
(
fluid
.
Layer
):
def
__init__
(
self
,
name_scope
):
super
(
MLP
,
self
).
__init__
(
name_scope
)
self
.
_user_latent
=
fluid
.
dygraph
.
FC
(
self
.
full_name
(),
256
)
self
.
_item_latent
=
fluid
.
dygraph
.
FC
(
self
.
full_name
(),
256
)
self
.
_user_latent
=
fluid
.
FC
(
self
.
full_name
(),
256
)
self
.
_item_latent
=
fluid
.
FC
(
self
.
full_name
(),
256
)
self
.
_match_layers
=
[]
self
.
_hid_sizes
=
[
128
,
64
]
for
i
in
range
(
len
(
self
.
_hid_sizes
)):
self
.
_match_layers
.
append
(
self
.
add_sublayer
(
'match_layer_%d'
%
i
,
fluid
.
dygraph
.
FC
(
self
.
full_name
(),
self
.
_hid_sizes
[
i
],
act
=
'relu'
)))
fluid
.
FC
(
self
.
full_name
(),
self
.
_hid_sizes
[
i
],
act
=
'relu'
)))
self
.
_mat
def
forward
(
self
,
users
,
items
):
...
...
@@ -88,7 +85,7 @@ class MLP(fluid.dygraph.Layer):
return
match_vec
class
DeepCF
(
fluid
.
dygraph
.
Layer
):
class
DeepCF
(
fluid
.
Layer
):
def
__init__
(
self
,
name_scope
,
num_users
,
num_items
,
matrix
):
super
(
DeepCF
,
self
).
__init__
(
name_scope
)
self
.
_num_users
=
num_users
...
...
@@ -99,11 +96,11 @@ class DeepCF(fluid.dygraph.Layer):
matrix
.
dtype
,
is_bias
=
False
,
default_initializer
=
fluid
.
initializer
.
NumpyArrayInitializer
(
matrix
))
self
.
_rating_matrix
.
_
stop_gradient
=
True
self
.
_rating_matrix
.
stop_gradient
=
True
self
.
_mlp
=
MLP
(
self
.
full_name
())
self
.
_dmf
=
DMF
(
self
.
full_name
())
self
.
_match_fc
=
fluid
.
dygraph
.
FC
(
self
.
full_name
(),
1
,
act
=
'sigmoid'
)
self
.
_match_fc
=
fluid
.
FC
(
self
.
full_name
(),
1
,
act
=
'sigmoid'
)
def
forward
(
self
,
users
,
items
):
# users_emb = self._user_emb(users)
...
...
@@ -255,10 +252,10 @@ class TestDygraphDeepCF(unittest.TestCase):
fluid
.
layers
.
log_loss
(
prediction
,
to_variable
(
labels_np
[
slice
:
slice
+
BATCH_SIZE
])))
loss
.
_
backward
()
loss
.
backward
()
adam
.
minimize
(
loss
)
deepcf
.
clear_gradients
()
dy_loss
=
loss
.
_
numpy
()
dy_loss
=
loss
.
numpy
()
sys
.
stderr
.
write
(
'dynamic loss: %s %s
\n
'
%
(
slice
,
dy_loss
))
self
.
assertEqual
(
static_loss
,
dy_loss
)
...
...
python/paddle/fluid/tests/unittests/test_imperative_gan.py
浏览文件 @
9bd44b94
...
...
@@ -22,12 +22,12 @@ import paddle
import
paddle.fluid
as
fluid
import
paddle.fluid.core
as
core
from
paddle.fluid.optimizer
import
SGDOptimizer
from
paddle.fluid
.dygraph.nn
import
Conv2D
,
Pool2D
,
FC
from
paddle.fluid
import
Conv2D
,
Pool2D
,
FC
from
test_imperative_base
import
new_program_scope
from
paddle.fluid.dygraph.base
import
to_variable
class
Discriminator
(
fluid
.
dygraph
.
Layer
):
class
Discriminator
(
fluid
.
Layer
):
def
__init__
(
self
,
name_scope
):
super
(
Discriminator
,
self
).
__init__
(
name_scope
)
self
.
_fc1
=
FC
(
self
.
full_name
(),
size
=
32
,
act
=
'elu'
)
...
...
@@ -38,7 +38,7 @@ class Discriminator(fluid.dygraph.Layer):
return
self
.
_fc2
(
x
)
class
Generator
(
fluid
.
dygraph
.
Layer
):
class
Generator
(
fluid
.
Layer
):
def
__init__
(
self
,
name_scope
):
super
(
Generator
,
self
).
__init__
(
name_scope
)
self
.
_fc1
=
FC
(
self
.
full_name
(),
size
=
64
,
act
=
'elu'
)
...
...
@@ -150,7 +150,7 @@ class TestDygraphGAN(unittest.TestCase):
x
=
d_fake
,
label
=
to_variable
(
np
.
zeros
([
2
,
1
],
np
.
float32
))))
d_loss
=
d_loss_real
+
d_loss_fake
d_loss
.
_
backward
()
d_loss
.
backward
()
sgd
.
minimize
(
d_loss
)
discriminator
.
clear_gradients
()
generator
.
clear_gradients
()
...
...
@@ -160,15 +160,15 @@ class TestDygraphGAN(unittest.TestCase):
g_loss
=
fluid
.
layers
.
reduce_mean
(
fluid
.
layers
.
sigmoid_cross_entropy_with_logits
(
x
=
d_fake
,
label
=
to_variable
(
np
.
ones
([
2
,
1
],
np
.
float32
))))
g_loss
.
_
backward
()
g_loss
.
backward
()
sgd
.
minimize
(
g_loss
)
for
p
in
discriminator
.
parameters
():
dy_params
[
p
.
name
]
=
p
.
_
numpy
()
dy_params
[
p
.
name
]
=
p
.
numpy
()
for
p
in
generator
.
parameters
():
dy_params
[
p
.
name
]
=
p
.
_
numpy
()
dy_params
[
p
.
name
]
=
p
.
numpy
()
dy_g_loss
=
g_loss
.
_
numpy
()
dy_d_loss
=
d_loss
.
_
numpy
()
dy_g_loss
=
g_loss
.
numpy
()
dy_d_loss
=
d_loss
.
numpy
()
self
.
assertEqual
(
dy_g_loss
,
static_g_loss
)
self
.
assertEqual
(
dy_d_loss
,
static_d_loss
)
...
...
python/paddle/fluid/tests/unittests/test_imperative_gnn.py
浏览文件 @
9bd44b94
...
...
@@ -15,14 +15,12 @@
import
contextlib
import
unittest
import
numpy
as
np
import
six
import
sys
import
paddle
import
paddle.fluid
as
fluid
import
paddle.fluid.core
as
core
from
paddle.fluid.optimizer
import
AdamOptimizer
from
paddle.fluid.dygraph.nn
import
Conv2D
,
Pool2D
,
FC
from
test_imperative_base
import
new_program_scope
from
paddle.fluid.dygraph.base
import
to_variable
...
...
@@ -31,7 +29,7 @@ def gen_data():
pass
class
GraphConv
(
fluid
.
dygraph
.
Layer
):
class
GraphConv
(
fluid
.
Layer
):
def
__init__
(
self
,
name_scope
,
in_features
,
out_features
):
super
(
GraphConv
,
self
).
__init__
(
name_scope
)
...
...
@@ -50,7 +48,7 @@ class GraphConv(fluid.dygraph.Layer):
return
fluid
.
layers
.
matmul
(
adj
,
support
)
+
self
.
bias
class
GCN
(
fluid
.
dygraph
.
Layer
):
class
GCN
(
fluid
.
Layer
):
def
__init__
(
self
,
name_scope
,
num_hidden
):
super
(
GCN
,
self
).
__init__
(
name_scope
)
self
.
gc
=
GraphConv
(
self
.
full_name
(),
num_hidden
,
32
)
...
...
@@ -134,10 +132,9 @@ class TestDygraphGNN(unittest.TestCase):
loss
=
fluid
.
layers
.
reduce_sum
(
loss
)
adam
=
AdamOptimizer
(
learning_rate
=
1e-3
)
adam
.
minimize
(
loss
)
self
.
assertEqual
(
static_loss
,
loss
.
_numpy
())
self
.
assertTrue
(
np
.
allclose
(
static_weight
,
model
.
gc
.
weight
.
_numpy
()))
sys
.
stderr
.
write
(
'%s %s
\n
'
%
(
static_loss
,
loss
.
_numpy
()))
self
.
assertEqual
(
static_loss
,
loss
.
numpy
())
self
.
assertTrue
(
np
.
allclose
(
static_weight
,
model
.
gc
.
weight
.
numpy
()))
sys
.
stderr
.
write
(
'%s %s
\n
'
%
(
static_loss
,
loss
.
numpy
()))
if
__name__
==
'__main__'
:
...
...
python/paddle/fluid/tests/unittests/test_imperative_mnist.py
浏览文件 @
9bd44b94
...
...
@@ -128,25 +128,25 @@ class TestImperativeMnist(unittest.TestCase):
img
=
to_variable
(
dy_x_data
)
label
=
to_variable
(
y_data
)
label
.
_
stop_gradient
=
True
label
.
stop_gradient
=
True
cost
=
mnist
(
img
)
loss
=
fluid
.
layers
.
cross_entropy
(
cost
,
label
)
avg_loss
=
fluid
.
layers
.
mean
(
loss
)
dy_out
=
avg_loss
.
_
numpy
()
dy_out
=
avg_loss
.
numpy
()
if
epoch
==
0
and
batch_id
==
0
:
for
param
in
mnist
.
parameters
():
dy_param_init_value
[
param
.
name
]
=
param
.
_
numpy
()
dy_param_init_value
[
param
.
name
]
=
param
.
numpy
()
avg_loss
.
_
backward
()
avg_loss
.
backward
()
sgd
.
minimize
(
avg_loss
)
mnist
.
clear_gradients
()
dy_param_value
=
{}
for
param
in
mnist
.
parameters
():
dy_param_value
[
param
.
name
]
=
param
.
_
numpy
()
dy_param_value
[
param
.
name
]
=
param
.
numpy
()
with
new_program_scope
():
fluid
.
default_startup_program
().
random_seed
=
seed
...
...
python/paddle/fluid/tests/unittests/test_imperative_optimizer.py
浏览文件 @
9bd44b94
...
...
@@ -28,7 +28,7 @@ from paddle.fluid.dygraph.base import to_variable
from
test_imperative_base
import
new_program_scope
class
MLP
(
fluid
.
dygraph
.
Layer
):
class
MLP
(
fluid
.
Layer
):
def
__init__
(
self
,
name_scope
,
param_attr
=
None
,
bias_attr
=
None
):
super
(
MLP
,
self
).
__init__
(
name_scope
)
...
...
@@ -75,18 +75,18 @@ class TestImperativeOptimizerBase(unittest.TestCase):
cost
=
mlp
(
img
)
avg_loss
=
fluid
.
layers
.
reduce_mean
(
cost
)
dy_out
=
avg_loss
.
_
numpy
()
dy_out
=
avg_loss
.
numpy
()
if
batch_id
==
0
:
for
param
in
mlp
.
parameters
():
dy_param_init_value
[
param
.
name
]
=
param
.
_
numpy
()
dy_param_init_value
[
param
.
name
]
=
param
.
numpy
()
avg_loss
.
_
backward
()
avg_loss
.
backward
()
optimizer
.
minimize
(
avg_loss
)
mlp
.
clear_gradients
()
dy_param_value
=
{}
for
param
in
mlp
.
parameters
():
dy_param_value
[
param
.
name
]
=
param
.
_
numpy
()
dy_param_value
[
param
.
name
]
=
param
.
numpy
()
with
new_program_scope
():
fluid
.
default_startup_program
().
random_seed
=
seed
...
...
python/paddle/fluid/tests/unittests/test_imperative_ptb_rnn.py
浏览文件 @
9bd44b94
...
...
@@ -24,10 +24,9 @@ from paddle.fluid.dygraph.base import to_variable
from
test_imperative_base
import
new_program_scope
import
numpy
as
np
import
six
from
paddle.fluid.backward
import
append_backward
class
SimpleLSTMRNN
(
fluid
.
dygraph
.
Layer
):
class
SimpleLSTMRNN
(
fluid
.
Layer
):
def
__init__
(
self
,
name_scope
,
hidden_size
,
...
...
@@ -45,7 +44,7 @@ class SimpleLSTMRNN(fluid.dygraph.Layer):
self
.
cell_array
=
[]
self
.
hidden_array
=
[]
def
_
build_once
(
self
,
input_embedding
,
init_hidden
=
None
,
init_cell
=
None
):
def
build_once
(
self
,
input_embedding
,
init_hidden
=
None
,
init_cell
=
None
):
self
.
weight_1_arr
=
[]
self
.
weight_2_arr
=
[]
self
.
bias_arr
=
[]
...
...
@@ -132,7 +131,7 @@ class SimpleLSTMRNN(fluid.dygraph.Layer):
return
real_res
,
last_hidden
,
last_cell
class
PtbModel
(
fluid
.
dygraph
.
Layer
):
class
PtbModel
(
fluid
.
Layer
):
def
__init__
(
self
,
name_scope
,
hidden_size
,
...
...
@@ -177,7 +176,7 @@ class PtbModel(fluid.dygraph.Layer):
default_initializer
=
fluid
.
initializer
.
UniformInitializer
(
low
=-
self
.
init_scale
,
high
=
self
.
init_scale
))
def
_
build_once
(
self
,
input
,
label
,
init_hidden
,
init_cell
):
def
build_once
(
self
,
input
,
label
,
init_hidden
,
init_cell
):
pass
def
forward
(
self
,
input
,
label
,
init_hidden
,
init_cell
):
...
...
@@ -260,13 +259,13 @@ class TestDygraphPtbRnn(unittest.TestCase):
init_cell
)
if
i
==
0
:
for
param
in
ptb_model
.
parameters
():
dy_param_init
[
param
.
name
]
=
param
.
_
numpy
()
dy_loss
.
_
backward
()
dy_param_init
[
param
.
name
]
=
param
.
numpy
()
dy_loss
.
backward
()
sgd
.
minimize
(
dy_loss
)
ptb_model
.
clear_gradients
()
if
i
==
batch_num
-
1
:
for
param
in
ptb_model
.
parameters
():
dy_param_updated
[
param
.
name
]
=
param
.
_
numpy
()
dy_param_updated
[
param
.
name
]
=
param
.
numpy
()
with
new_program_scope
():
fluid
.
default_startup_program
().
random_seed
=
seed
...
...
@@ -334,11 +333,11 @@ class TestDygraphPtbRnn(unittest.TestCase):
static_param_updated
[
static_param_name_list
[
k
-
3
]]
=
out
[
k
]
self
.
assertTrue
(
np
.
array_equal
(
static_loss_value
,
dy_loss
.
_
numpy
()))
self
.
assertTrue
(
np
.
array_equal
(
static_loss_value
,
dy_loss
.
numpy
()))
self
.
assertTrue
(
np
.
array_equal
(
static_last_cell_value
,
last_cell
.
_
numpy
()))
np
.
array_equal
(
static_last_cell_value
,
last_cell
.
numpy
()))
self
.
assertTrue
(
np
.
array_equal
(
static_last_hidden_value
,
last_hidden
.
_
numpy
()))
np
.
array_equal
(
static_last_hidden_value
,
last_hidden
.
numpy
()))
for
key
,
value
in
six
.
iteritems
(
static_param_init
):
self
.
assertTrue
(
np
.
array_equal
(
value
,
dy_param_init
[
key
]))
for
key
,
value
in
six
.
iteritems
(
static_param_updated
):
...
...
python/paddle/fluid/tests/unittests/test_imperative_resnet.py
浏览文件 @
9bd44b94
...
...
@@ -21,7 +21,7 @@ import paddle
import
paddle.fluid
as
fluid
from
paddle.fluid
import
core
from
paddle.fluid.layer_helper
import
LayerHelper
from
paddle.fluid
.dygraph.nn
import
Conv2D
,
Pool2D
,
BatchNorm
,
FC
from
paddle.fluid
import
Conv2D
,
Pool2D
,
BatchNorm
,
FC
from
paddle.fluid.dygraph.base
import
to_variable
from
test_imperative_base
import
new_program_scope
...
...
@@ -68,7 +68,7 @@ def optimizer_setting(params):
return
optimizer
class
ConvBNLayer
(
fluid
.
dygraph
.
Layer
):
class
ConvBNLayer
(
fluid
.
Layer
):
def
__init__
(
self
,
name_scope
,
num_channels
,
...
...
@@ -99,7 +99,7 @@ class ConvBNLayer(fluid.dygraph.Layer):
return
y
class
BottleneckBlock
(
fluid
.
dygraph
.
Layer
):
class
BottleneckBlock
(
fluid
.
Layer
):
def
__init__
(
self
,
name_scope
,
num_channels
,
...
...
@@ -156,7 +156,7 @@ class BottleneckBlock(fluid.dygraph.Layer):
return
layer_helper
.
append_activation
(
y
)
class
ResNet
(
fluid
.
dygraph
.
Layer
):
class
ResNet
(
fluid
.
Layer
):
def
__init__
(
self
,
name_scope
,
layers
=
50
,
class_dim
=
102
):
super
(
ResNet
,
self
).
__init__
(
name_scope
)
...
...
@@ -247,7 +247,7 @@ class TestDygraphResnet(unittest.TestCase):
dy_param_init_value
=
{}
for
param
in
resnet
.
parameters
():
dy_param_init_value
[
param
.
name
]
=
param
.
_
numpy
()
dy_param_init_value
[
param
.
name
]
=
param
.
numpy
()
for
batch_id
,
data
in
enumerate
(
train_reader
()):
if
batch_id
>=
batch_num
:
...
...
@@ -260,20 +260,20 @@ class TestDygraphResnet(unittest.TestCase):
img
=
to_variable
(
dy_x_data
)
label
=
to_variable
(
y_data
)
label
.
_
stop_gradient
=
True
label
.
stop_gradient
=
True
out
=
resnet
(
img
)
loss
=
fluid
.
layers
.
cross_entropy
(
input
=
out
,
label
=
label
)
avg_loss
=
fluid
.
layers
.
mean
(
x
=
loss
)
dy_out
=
avg_loss
.
_
numpy
()
dy_out
=
avg_loss
.
numpy
()
if
batch_id
==
0
:
for
param
in
resnet
.
parameters
():
if
param
.
name
not
in
dy_param_init_value
:
dy_param_init_value
[
param
.
name
]
=
param
.
_
numpy
()
dy_param_init_value
[
param
.
name
]
=
param
.
numpy
()
avg_loss
.
_
backward
()
avg_loss
.
backward
()
dy_grad_value
=
{}
for
param
in
resnet
.
parameters
():
...
...
@@ -288,7 +288,7 @@ class TestDygraphResnet(unittest.TestCase):
dy_param_value
=
{}
for
param
in
resnet
.
parameters
():
dy_param_value
[
param
.
name
]
=
param
.
_
numpy
()
dy_param_value
[
param
.
name
]
=
param
.
numpy
()
with
new_program_scope
():
fluid
.
default_startup_program
().
random_seed
=
seed
...
...
python/paddle/fluid/tests/unittests/test_imperative_se_resnext.py
浏览文件 @
9bd44b94
...
...
@@ -333,7 +333,7 @@ class TestImperativeResneXt(unittest.TestCase):
dy_param_init_value
=
{}
for
param
in
se_resnext
.
parameters
():
dy_param_init_value
[
param
.
name
]
=
param
.
_
numpy
()
dy_param_init_value
[
param
.
name
]
=
param
.
numpy
()
for
epoch_id
in
range
(
epoch_num
):
for
batch_id
,
data
in
enumerate
(
train_reader
()):
...
...
@@ -349,19 +349,19 @@ class TestImperativeResneXt(unittest.TestCase):
img
=
to_variable
(
dy_x_data
)
label
=
to_variable
(
y_data
)
label
.
_
stop_gradient
=
True
label
.
stop_gradient
=
True
out
=
se_resnext
(
img
)
loss
=
fluid
.
layers
.
cross_entropy
(
input
=
out
,
label
=
label
)
avg_loss
=
fluid
.
layers
.
mean
(
x
=
loss
)
dy_out
=
avg_loss
.
_
numpy
()
dy_out
=
avg_loss
.
numpy
()
if
batch_id
==
0
:
for
param
in
se_resnext
.
parameters
():
if
param
.
name
not
in
dy_param_init_value
:
dy_param_init_value
[
param
.
name
]
=
param
.
_
numpy
()
avg_loss
.
_
backward
()
dy_param_init_value
[
param
.
name
]
=
param
.
numpy
()
avg_loss
.
backward
()
#dy_grad_value = {}
#for param in se_resnext.parameters():
...
...
@@ -375,7 +375,7 @@ class TestImperativeResneXt(unittest.TestCase):
dy_param_value
=
{}
for
param
in
se_resnext
.
parameters
():
dy_param_value
[
param
.
name
]
=
param
.
_
numpy
()
dy_param_value
[
param
.
name
]
=
param
.
numpy
()
with
new_program_scope
():
fluid
.
default_startup_program
().
random_seed
=
seed
...
...
python/paddle/fluid/tests/unittests/test_imperative_transformer.py
浏览文件 @
9bd44b94
...
...
@@ -16,7 +16,8 @@ from __future__ import print_function
import
unittest
import
paddle.fluid
as
fluid
from
paddle.fluid.dygraph
import
Embedding
,
LayerNorm
,
FC
,
to_variable
,
Layer
,
guard
from
paddle.fluid
import
Embedding
,
LayerNorm
,
FC
,
Layer
from
paddle.fluid.dygraph
import
to_variable
,
guard
from
test_imperative_base
import
new_program_scope
from
paddle.fluid
import
core
import
numpy
as
np
...
...
@@ -992,14 +993,14 @@ class TestDygraphTransformer(unittest.TestCase):
enc_inputs
,
dec_inputs
,
label
,
weights
)
if
i
==
0
:
for
param
in
transformer
.
parameters
():
dy_param_init
[
param
.
name
]
=
param
.
_
numpy
()
dy_param_init
[
param
.
name
]
=
param
.
numpy
()
dy_avg_cost
.
_
backward
()
dy_avg_cost
.
backward
()
optimizer
.
minimize
(
dy_avg_cost
)
transformer
.
clear_gradients
()
if
i
==
batch_num
-
1
:
for
param
in
transformer
.
parameters
():
dy_param_updated
[
param
.
name
]
=
param
.
_
numpy
()
dy_param_updated
[
param
.
name
]
=
param
.
numpy
()
with
new_program_scope
():
fluid
.
default_startup_program
().
random_seed
=
seed
...
...
@@ -1076,13 +1077,14 @@ class TestDygraphTransformer(unittest.TestCase):
4
]]
=
out
[
k
]
self
.
assertTrue
(
np
.
array_equal
(
static_avg_cost_value
,
dy_avg_cost
.
_
numpy
()))
np
.
array_equal
(
static_avg_cost_value
,
dy_avg_cost
.
numpy
()))
self
.
assertTrue
(
np
.
array_equal
(
static_sum_cost_value
,
dy_sum_cost
.
_
numpy
()))
np
.
array_equal
(
static_sum_cost_value
,
dy_sum_cost
.
numpy
()))
self
.
assertTrue
(
np
.
array_equal
(
static_predict_value
,
dy_predict
.
_
numpy
()))
np
.
array_equal
(
static_predict_value
,
dy_predict
.
numpy
()))
self
.
assertTrue
(
np
.
array_equal
(
static_token_num_value
,
dy_token_num
.
_numpy
()))
np
.
array_equal
(
static_token_num_value
,
dy_token_num
.
numpy
()))
for
key
,
value
in
six
.
iteritems
(
static_param_init
):
self
.
assertTrue
(
np
.
array_equal
(
value
,
dy_param_init
[
key
]))
for
key
,
value
in
six
.
iteritems
(
static_param_updated
):
...
...
python/paddle/fluid/tests/unittests/test_layers.py
浏览文件 @
9bd44b94
...
...
@@ -114,7 +114,7 @@ class TestLayer(LayerTest):
dy_ret
=
fc2
(
ret
)
self
.
assertTrue
(
np
.
array_equal
(
static_ret
,
static_ret2
))
self
.
assertTrue
(
np
.
array_equal
(
static_ret
,
dy_ret
.
_
numpy
()))
self
.
assertTrue
(
np
.
array_equal
(
static_ret
,
dy_ret
.
numpy
()))
def
test_layer_norm
(
self
):
inp
=
np
.
ones
([
3
,
32
,
32
],
dtype
=
'float32'
)
...
...
@@ -142,7 +142,7 @@ class TestLayer(LayerTest):
dy_ret
=
lm
(
base
.
to_variable
(
inp
))
self
.
assertTrue
(
np
.
allclose
(
static_ret
,
static_ret2
))
self
.
assertTrue
(
np
.
allclose
(
dy_ret
.
_
numpy
(),
static_ret2
))
self
.
assertTrue
(
np
.
allclose
(
dy_ret
.
numpy
(),
static_ret2
))
def
test_relu
(
self
):
with
self
.
static_graph
():
...
...
@@ -156,7 +156,7 @@ class TestLayer(LayerTest):
t
=
np
.
ones
([
3
,
3
],
dtype
=
'float32'
)
dy_ret
=
layers
.
relu
(
base
.
to_variable
(
t
))
self
.
assertTrue
(
np
.
allclose
(
static_ret
,
dy_ret
.
_
numpy
()))
self
.
assertTrue
(
np
.
allclose
(
static_ret
,
dy_ret
.
numpy
()))
def
test_matmul
(
self
):
with
self
.
static_graph
():
...
...
@@ -177,7 +177,7 @@ class TestLayer(LayerTest):
t2
=
np
.
ones
([
3
,
3
],
dtype
=
'float32'
)
dy_ret
=
layers
.
matmul
(
base
.
to_variable
(
t
),
base
.
to_variable
(
t2
))
self
.
assertTrue
(
np
.
allclose
(
static_ret
,
dy_ret
.
_
numpy
()))
self
.
assertTrue
(
np
.
allclose
(
static_ret
,
dy_ret
.
numpy
()))
def
test_conv2d
(
self
):
with
self
.
static_graph
():
...
...
@@ -204,7 +204,7 @@ class TestLayer(LayerTest):
'conv2d'
,
num_channels
=
3
,
num_filters
=
3
,
filter_size
=
[
2
,
2
])
dy_ret
=
conv2d
(
base
.
to_variable
(
images
))
self
.
assertTrue
(
np
.
allclose
(
static_ret
,
dy_ret
.
_
numpy
()))
self
.
assertTrue
(
np
.
allclose
(
static_ret
,
dy_ret
.
numpy
()))
self
.
assertTrue
(
np
.
allclose
(
static_ret
,
static_ret2
))
def
test_gru_unit
(
self
):
...
...
@@ -246,7 +246,7 @@ class TestLayer(LayerTest):
for
i
in
range
(
len
(
static_ret
)):
self
.
assertTrue
(
np
.
allclose
(
static_ret
[
i
],
static_ret2
[
i
]))
self
.
assertTrue
(
np
.
allclose
(
static_ret
[
i
],
dy_ret
[
i
].
_
numpy
()))
self
.
assertTrue
(
np
.
allclose
(
static_ret
[
i
],
dy_ret
[
i
].
numpy
()))
def
test_elementwise_math
(
self
):
n
=
np
.
ones
([
3
,
3
],
dtype
=
'float32'
)
...
...
@@ -288,8 +288,8 @@ class TestLayer(LayerTest):
ret
=
layers
.
elementwise_sub
(
ret
,
n5
)
dy_ret
=
layers
.
elementwise_mul
(
ret
,
n6
)
self
.
assertTrue
(
np
.
allclose
(
static_ret
,
dy_ret
.
_
numpy
()),
'%s vs %s'
%
(
static_ret
,
dy_ret
.
_
numpy
()))
np
.
allclose
(
static_ret
,
dy_ret
.
numpy
()),
'%s vs %s'
%
(
static_ret
,
dy_ret
.
numpy
()))
def
test_elementwise_minmax
(
self
):
n
=
np
.
ones
([
3
,
3
],
dtype
=
'float32'
)
...
...
@@ -299,8 +299,8 @@ class TestLayer(LayerTest):
min_ret
=
layers
.
elementwise_min
(
n
,
n2
)
max_ret
=
layers
.
elementwise_max
(
n
,
n2
)
self
.
assertTrue
(
np
.
allclose
(
n
,
min_ret
.
_
numpy
()))
self
.
assertTrue
(
np
.
allclose
(
n2
,
max_ret
.
_
numpy
()))
self
.
assertTrue
(
np
.
allclose
(
n
,
min_ret
.
numpy
()))
self
.
assertTrue
(
np
.
allclose
(
n2
,
max_ret
.
numpy
()))
def
test_sequence_conv
(
self
):
inp_np
=
np
.
arange
(
12
).
reshape
([
3
,
4
]).
astype
(
'float32'
)
...
...
@@ -367,7 +367,7 @@ class TestLayer(LayerTest):
'conv2d_transpose'
,
num_filters
=
10
,
output_size
=
28
)
dy_rlt
=
conv2d_transpose
(
base
.
to_variable
(
inp_np
))
self
.
assertTrue
(
np
.
allclose
(
static_rlt2
,
static_rlt
))
self
.
assertTrue
(
np
.
allclose
(
dy_rlt
.
_
numpy
(),
static_rlt
))
self
.
assertTrue
(
np
.
allclose
(
dy_rlt
.
numpy
(),
static_rlt
))
def
test_bilinear_tensor_product
(
self
):
inp_np_x
=
np
.
array
([[
1
,
2
,
3
]]).
astype
(
'float32'
)
...
...
@@ -410,7 +410,7 @@ class TestLayer(LayerTest):
dy_rlt
=
btp
(
base
.
to_variable
(
inp_np_x
),
base
.
to_variable
(
inp_np_y
))
self
.
assertTrue
(
np
.
allclose
(
static_rlt2
,
static_rlt
))
self
.
assertTrue
(
np
.
allclose
(
dy_rlt
.
_
numpy
(),
static_rlt
))
self
.
assertTrue
(
np
.
allclose
(
dy_rlt
.
numpy
(),
static_rlt
))
def
test_prelu
(
self
):
inp_np
=
np
.
ones
([
5
,
200
,
100
,
100
]).
astype
(
'float32'
)
...
...
@@ -451,7 +451,7 @@ class TestLayer(LayerTest):
dy_rlt
=
prelu
(
base
.
to_variable
(
inp_np
))
self
.
assertTrue
(
np
.
allclose
(
static_rlt2
,
static_rlt
))
self
.
assertTrue
(
np
.
allclose
(
dy_rlt
.
_
numpy
(),
static_rlt
))
self
.
assertTrue
(
np
.
allclose
(
dy_rlt
.
numpy
(),
static_rlt
))
def
test_embeding
(
self
):
inp_word
=
np
.
array
([[[
1
]]]).
astype
(
'int64'
)
...
...
@@ -484,7 +484,7 @@ class TestLayer(LayerTest):
static_rlt3
=
emb2
(
base
.
to_variable
(
inp_word
))
self
.
assertTrue
(
np
.
allclose
(
static_rlt2
,
static_rlt
))
self
.
assertTrue
(
np
.
allclose
(
static_rlt3
.
_
numpy
(),
static_rlt
))
self
.
assertTrue
(
np
.
allclose
(
static_rlt3
.
numpy
(),
static_rlt
))
def
test_nce
(
self
):
window_size
=
5
...
...
@@ -598,7 +598,7 @@ class TestLayer(LayerTest):
nce_loss3
=
nce
(
embs3
,
words
[
label_word
])
self
.
assertTrue
(
np
.
allclose
(
static_rlt2
,
static_rlt
))
self
.
assertTrue
(
np
.
allclose
(
nce_loss3
.
_
numpy
(),
static_rlt
))
self
.
assertTrue
(
np
.
allclose
(
nce_loss3
.
numpy
(),
static_rlt
))
def
test_conv3d
(
self
):
with
self
.
static_graph
():
...
...
@@ -625,7 +625,7 @@ class TestLayer(LayerTest):
conv3d
=
nn
.
Conv3D
(
'conv3d'
,
num_filters
=
3
,
filter_size
=
2
)
dy_ret
=
conv3d
(
base
.
to_variable
(
images
))
self
.
assertTrue
(
np
.
allclose
(
static_ret
,
dy_ret
.
_
numpy
()))
self
.
assertTrue
(
np
.
allclose
(
static_ret
,
dy_ret
.
numpy
()))
self
.
assertTrue
(
np
.
allclose
(
static_ret
,
static_ret2
))
def
test_row_conv
(
self
):
...
...
@@ -719,7 +719,7 @@ class TestLayer(LayerTest):
groupNorm
=
nn
.
GroupNorm
(
'GroupNorm'
,
groups
=
2
)
dy_ret
=
groupNorm
(
base
.
to_variable
(
input
))
self
.
assertTrue
(
np
.
allclose
(
static_ret
,
dy_ret
.
_
numpy
()))
self
.
assertTrue
(
np
.
allclose
(
static_ret
,
dy_ret
.
numpy
()))
self
.
assertTrue
(
np
.
allclose
(
static_ret
,
static_ret2
))
def
test_spectral_norm
(
self
):
...
...
@@ -769,7 +769,7 @@ class TestLayer(LayerTest):
spectralNorm
=
nn
.
SpectralNorm
(
'SpectralNorm'
,
dim
=
1
,
power_iters
=
2
)
dy_ret
=
spectralNorm
(
base
.
to_variable
(
input
))
self
.
assertTrue
(
np
.
allclose
(
static_ret
,
dy_ret
.
_
numpy
()))
self
.
assertTrue
(
np
.
allclose
(
static_ret
,
dy_ret
.
numpy
()))
self
.
assertTrue
(
np
.
allclose
(
static_ret
,
static_ret2
))
def
test_tree_conv
(
self
):
...
...
@@ -842,7 +842,7 @@ class TestLayer(LayerTest):
dy_ret
=
treeConv
(
base
.
to_variable
(
vectors
),
base
.
to_variable
(
adj
))
self
.
assertTrue
(
np
.
allclose
(
static_ret
,
static_ret2
))
self
.
assertTrue
(
np
.
allclose
(
static_ret
,
dy_ret
.
_
numpy
()))
self
.
assertTrue
(
np
.
allclose
(
static_ret
,
dy_ret
.
numpy
()))
def
test_conv3d_transpose
(
self
):
input_array
=
np
.
arange
(
0
,
48
).
reshape
(
...
...
@@ -872,7 +872,7 @@ class TestLayer(LayerTest):
use_cudnn
=
False
)
dy_rlt
=
conv3d_transpose
(
base
.
to_variable
(
input_array
))
self
.
assertTrue
(
np
.
allclose
(
static_rlt2
,
static_rlt
))
self
.
assertTrue
(
np
.
allclose
(
dy_rlt
.
_
numpy
(),
static_rlt
))
self
.
assertTrue
(
np
.
allclose
(
dy_rlt
.
numpy
(),
static_rlt
))
class
TestBook
(
LayerTest
):
...
...
@@ -907,7 +907,7 @@ class TestBook(LayerTest):
if
isinstance
(
dy_result
,
tuple
):
dy_result
=
dy_result
[
0
]
self
.
assertTrue
(
np
.
array_equal
(
static_result
[
0
],
dy_result
.
_
numpy
()))
self
.
assertTrue
(
np
.
array_equal
(
static_result
[
0
],
dy_result
.
numpy
()))
def
_get_np_data
(
self
,
shape
,
dtype
,
append_batch_size
=
True
):
np
.
random
.
seed
(
self
.
seed
)
...
...
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