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体验新版 GitCode,发现更多精彩内容 >>
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a54c423e
编写于
9月 21, 2018
作者:
X
Xin Pan
提交者:
GitHub
9月 21, 2018
浏览文件
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差异文件
Merge pull request #13512 from tensor-tang/remove/kwargs
remove kwargs of some activation api
上级
cdf3a4c2
21f35eef
变更
6
隐藏空白更改
内联
并排
Showing
6 changed file
with
279 addition
and
28 deletion
+279
-28
paddle/fluid/API.spec
paddle/fluid/API.spec
+19
-19
python/paddle/fluid/clip.py
python/paddle/fluid/clip.py
+1
-1
python/paddle/fluid/layers/layer_function_generator.py
python/paddle/fluid/layers/layer_function_generator.py
+27
-1
python/paddle/fluid/layers/nn.py
python/paddle/fluid/layers/nn.py
+71
-0
python/paddle/fluid/layers/ops.py
python/paddle/fluid/layers/ops.py
+9
-7
python/paddle/fluid/tests/unittests/test_layers.py
python/paddle/fluid/tests/unittests/test_layers.py
+152
-0
未找到文件。
paddle/fluid/API.spec
浏览文件 @
a54c423e
...
...
@@ -167,6 +167,9 @@ paddle.fluid.layers.stanh ArgSpec(args=['x', 'scale_a', 'scale_b', 'name'], vara
paddle.fluid.layers.hard_sigmoid ArgSpec(args=['x', 'slope', 'offset', 'name'], varargs=None, keywords=None, defaults=(0.2, 0.5, None))
paddle.fluid.layers.swish ArgSpec(args=['x', 'beta', 'name'], varargs=None, keywords=None, defaults=(1.0, None))
paddle.fluid.layers.prelu ArgSpec(args=['x', 'mode', 'param_attr', 'name'], varargs=None, keywords=None, defaults=(None, None))
paddle.fluid.layers.brelu ArgSpec(args=['x', 't_min', 't_max', 'name'], varargs=None, keywords=None, defaults=(0.0, 24.0, None))
paddle.fluid.layers.leaky_relu ArgSpec(args=['x', 'alpha', 'name'], varargs=None, keywords=None, defaults=(0.02, None))
paddle.fluid.layers.soft_relu ArgSpec(args=['x', 'threshold', 'name'], varargs=None, keywords=None, defaults=(40.0, None))
paddle.fluid.layers.flatten ArgSpec(args=['x', 'axis', 'name'], varargs=None, keywords=None, defaults=(1, None))
paddle.fluid.layers.sequence_mask ArgSpec(args=['x', 'maxlen', 'dtype', 'name'], varargs=None, keywords=None, defaults=(None, 'int64', None))
paddle.fluid.layers.stack ArgSpec(args=['x', 'axis'], varargs=None, keywords=None, defaults=(0,))
...
...
@@ -262,26 +265,23 @@ paddle.fluid.layers.sum ArgSpec(args=[], varargs='args', keywords='kwargs', defa
paddle.fluid.layers.slice ArgSpec(args=[], varargs='args', keywords='kwargs', defaults=None)
paddle.fluid.layers.shape ArgSpec(args=[], varargs='args', keywords='kwargs', defaults=None)
paddle.fluid.layers.maxout ArgSpec(args=[], varargs='args', keywords='kwargs', defaults=None)
paddle.fluid.layers.sigmoid ArgSpec(args=[], varargs='args', keywords='kwargs', defaults=None)
paddle.fluid.layers.logsigmoid ArgSpec(args=[], varargs='args', keywords='kwargs', defaults=None)
paddle.fluid.layers.exp ArgSpec(args=[], varargs='args', keywords='kwargs', defaults=None)
paddle.fluid.layers.tanh ArgSpec(args=[], varargs='args', keywords='kwargs', defaults=None)
paddle.fluid.layers.tanh_shrink ArgSpec(args=[], varargs='args', keywords='kwargs', defaults=None)
paddle.fluid.layers.softshrink ArgSpec(args=[], varargs='args', keywords='kwargs', defaults=None)
paddle.fluid.layers.sqrt ArgSpec(args=[], varargs='args', keywords='kwargs', defaults=None)
paddle.fluid.layers.abs ArgSpec(args=[], varargs='args', keywords='kwargs', defaults=None)
paddle.fluid.layers.ceil ArgSpec(args=[], varargs='args', keywords='kwargs', defaults=None)
paddle.fluid.layers.floor ArgSpec(args=[], varargs='args', keywords='kwargs', defaults=None)
paddle.fluid.layers.cos ArgSpec(args=[], varargs='args', keywords='kwargs', defaults=None)
paddle.fluid.layers.sin ArgSpec(args=[], varargs='args', keywords='kwargs', defaults=None)
paddle.fluid.layers.round ArgSpec(args=[], varargs='args', keywords='kwargs', defaults=None)
paddle.fluid.layers.reciprocal ArgSpec(args=[], varargs='args', keywords='kwargs', defaults=None)
paddle.fluid.layers.square ArgSpec(args=[], varargs='args', keywords='kwargs', defaults=None)
paddle.fluid.layers.softplus ArgSpec(args=[], varargs='args', keywords='kwargs', defaults=None)
paddle.fluid.layers.softsign ArgSpec(args=[], varargs='args', keywords='kwargs', defaults=None)
paddle.fluid.layers.brelu ArgSpec(args=[], varargs='args', keywords='kwargs', defaults=None)
paddle.fluid.layers.leaky_relu ArgSpec(args=[], varargs='args', keywords='kwargs', defaults=None)
paddle.fluid.layers.soft_relu ArgSpec(args=[], varargs='args', keywords='kwargs', defaults=None)
paddle.fluid.layers.sigmoid ArgSpec(args=['x', 'name'], varargs=None, keywords=None, defaults=(None,))
paddle.fluid.layers.logsigmoid ArgSpec(args=['x', 'name'], varargs=None, keywords=None, defaults=(None,))
paddle.fluid.layers.exp ArgSpec(args=['x', 'name'], varargs=None, keywords=None, defaults=(None,))
paddle.fluid.layers.tanh ArgSpec(args=['x', 'name'], varargs=None, keywords=None, defaults=(None,))
paddle.fluid.layers.tanh_shrink ArgSpec(args=['x', 'name'], varargs=None, keywords=None, defaults=(None,))
paddle.fluid.layers.sqrt ArgSpec(args=['x', 'name'], varargs=None, keywords=None, defaults=(None,))
paddle.fluid.layers.abs ArgSpec(args=['x', 'name'], varargs=None, keywords=None, defaults=(None,))
paddle.fluid.layers.ceil ArgSpec(args=['x', 'name'], varargs=None, keywords=None, defaults=(None,))
paddle.fluid.layers.floor ArgSpec(args=['x', 'name'], varargs=None, keywords=None, defaults=(None,))
paddle.fluid.layers.cos ArgSpec(args=['x', 'name'], varargs=None, keywords=None, defaults=(None,))
paddle.fluid.layers.sin ArgSpec(args=['x', 'name'], varargs=None, keywords=None, defaults=(None,))
paddle.fluid.layers.round ArgSpec(args=['x', 'name'], varargs=None, keywords=None, defaults=(None,))
paddle.fluid.layers.reciprocal ArgSpec(args=['x', 'name'], varargs=None, keywords=None, defaults=(None,))
paddle.fluid.layers.square ArgSpec(args=['x', 'name'], varargs=None, keywords=None, defaults=(None,))
paddle.fluid.layers.softplus ArgSpec(args=['x', 'name'], varargs=None, keywords=None, defaults=(None,))
paddle.fluid.layers.softsign ArgSpec(args=['x', 'name'], varargs=None, keywords=None, defaults=(None,))
paddle.fluid.layers.uniform_random ArgSpec(args=['shape', 'dtype', 'min', 'max', 'seed'], varargs=None, keywords=None, defaults=(None, None, None, None))
paddle.fluid.layers.hard_shrink ArgSpec(args=['x', 'threshold'], varargs=None, keywords=None, defaults=(None,))
paddle.fluid.layers.cumsum ArgSpec(args=['x', 'axis', 'exclusive', 'reverse'], varargs=None, keywords=None, defaults=(None, None, None))
...
...
python/paddle/fluid/clip.py
浏览文件 @
a54c423e
...
...
@@ -280,7 +280,7 @@ class GradientClipByGlobalNorm(BaseGradientClipAttr):
group_scale_name
=
self
.
group_name
+
"_scale"
if
group_scale_name
not
in
self
.
context
:
group_norm_var
=
layers
.
sums
(
input
=
self
.
context
[
self
.
group_name
])
layers
.
sqrt
(
x
=
group_norm_var
,
out
=
group_norm_var
)
group_norm_var
=
layers
.
sqrt
(
x
=
group_norm_var
)
clip_var
=
self
.
context
[
self
.
group_name
+
"_clip"
]
group_scale_var
=
layers
.
elementwise_div
(
x
=
clip_var
,
...
...
python/paddle/fluid/layers/layer_function_generator.py
浏览文件 @
a54c423e
...
...
@@ -23,7 +23,10 @@ from ..proto import framework_pb2
from
..framework
import
OpProtoHolder
,
Variable
from
..layer_helper
import
LayerHelper
__all__
=
[
'deprecated'
,
'generate_layer_fn'
,
'autodoc'
,
'templatedoc'
]
__all__
=
[
'deprecated'
,
'generate_layer_fn'
,
'generate_layer_fn_noattr'
,
'autodoc'
,
'templatedoc'
]
def
_convert_
(
name
):
...
...
@@ -205,6 +208,29 @@ def generate_layer_fn(op_type):
return
func
def
generate_layer_fn_noattr
(
op_type
):
"""Register the Python layer for an Operator without Attribute.
Args:
op_type: The name of the operator to be created.
This function takes in the operator type (sigmoid, exp , tanh etc) and
creates the operator functionality.
"""
op_proto
=
OpProtoHolder
.
instance
().
get_op_proto
(
op_type
)
def
func
(
x
,
name
=
None
):
helper
=
LayerHelper
(
op_type
,
**
locals
())
output
=
helper
.
create_tmp_variable
(
dtype
=
x
.
dtype
)
helper
.
append_op
(
type
=
op_type
,
inputs
=
{
"X"
:
x
},
outputs
=
{
"Out"
:
output
})
return
output
func
.
__name__
=
op_type
func
.
__doc__
=
_generate_doc_string_
(
op_proto
)
return
func
def
deprecated
(
func_or_class
):
"""
Deprecated warning decorator. It will result a warning message.
...
...
python/paddle/fluid/layers/nn.py
浏览文件 @
a54c423e
...
...
@@ -114,6 +114,9 @@ __all__ = [
'hard_sigmoid'
,
'swish'
,
'prelu'
,
'brelu'
,
'leaky_relu'
,
'soft_relu'
,
'flatten'
,
'sequence_mask'
,
'stack'
,
...
...
@@ -6096,6 +6099,74 @@ def prelu(x, mode, param_attr=None, name=None):
return
out
@
templatedoc
()
def
brelu
(
x
,
t_min
=
0.0
,
t_max
=
24.0
,
name
=
None
):
"""
${comment}
Args:
x(${x_type}): ${x_comment}
t_min(${t_min_type}|0.0): ${t_min_comment}
t_max(${t_max_type}|24.0): ${t_max_comment}
name(str|None): A name for this layer(optional). If set None, the layer
will be named automatically.
Returns:
output(${out_type}): ${out_comment}
"""
helper
=
LayerHelper
(
'brelu'
,
**
locals
())
out
=
helper
.
create_tmp_variable
(
dtype
=
x
.
dtype
)
helper
.
append_op
(
type
=
'brelu'
,
inputs
=
{
'X'
:
x
},
outputs
=
{
'Out'
:
out
},
attrs
=
{
't_min'
:
t_min
,
't_max'
:
t_max
})
return
out
@
templatedoc
()
def
leaky_relu
(
x
,
alpha
=
0.02
,
name
=
None
):
"""
${comment}
Args:
x(${x_type}): ${x_comment}
alpha(${alpha_type}|0.02): ${alpha_comment}
name(str|None): A name for this layer(optional). If set None, the layer
will be named automatically.
Returns:
output(${out_type}): ${out_comment}
"""
helper
=
LayerHelper
(
'leaky_relu'
,
**
locals
())
out
=
helper
.
create_tmp_variable
(
dtype
=
x
.
dtype
)
helper
.
append_op
(
type
=
'leaky_relu'
,
inputs
=
{
'X'
:
x
},
outputs
=
{
'Out'
:
out
},
attrs
=
{
'alpha'
:
alpha
})
return
out
@
templatedoc
()
def
soft_relu
(
x
,
threshold
=
40.0
,
name
=
None
):
"""
${comment}
Args:
x(${x_type}): ${x_comment}
threshold(${threshold_type}|40.0): ${threshold_comment}
name(str|None): A name for this layer(optional). If set None, the layer
will be named automatically.
Returns:
output(${out_type}): ${out_comment}
"""
helper
=
LayerHelper
(
'soft_relu'
,
**
locals
())
out
=
helper
.
create_tmp_variable
(
dtype
=
x
.
dtype
)
helper
.
append_op
(
type
=
'soft_relu'
,
inputs
=
{
'X'
:
x
},
outputs
=
{
'Out'
:
out
},
attrs
=
{
'threshold'
:
threshold
})
return
out
def
flatten
(
x
,
axis
=
1
,
name
=
None
):
"""
**Flatten layer**
...
...
python/paddle/fluid/layers/ops.py
浏览文件 @
a54c423e
...
...
@@ -13,15 +13,14 @@
# limitations under the License.
from
__future__
import
print_function
from
.layer_function_generator
import
generate_layer_fn
from
.layer_function_generator
import
generate_layer_fn
,
generate_layer_fn_noattr
__activations__
=
[
__activations_
noattr_
_
=
[
'sigmoid'
,
'logsigmoid'
,
'exp'
,
'tanh'
,
'tanh_shrink'
,
'softshrink'
,
'sqrt'
,
'abs'
,
'ceil'
,
...
...
@@ -33,9 +32,6 @@ __activations__ = [
'square'
,
'softplus'
,
'softsign'
,
'brelu'
,
'leaky_relu'
,
'soft_relu'
,
]
__all__
=
[
...
...
@@ -64,11 +60,17 @@ __all__ = [
'slice'
,
'shape'
,
'maxout'
,
]
+
__activations__
'softshrink'
,
]
for
_OP
in
set
(
__all__
):
globals
()[
_OP
]
=
generate_layer_fn
(
_OP
)
__all__
+=
__activations_noattr__
for
_OP
in
set
(
__activations_noattr__
):
globals
()[
_OP
]
=
generate_layer_fn_noattr
(
_OP
)
__all__
+=
[
"uniform_random"
]
_uniform_random_
=
generate_layer_fn
(
'uniform_random'
)
...
...
python/paddle/fluid/tests/unittests/test_layers.py
浏览文件 @
a54c423e
...
...
@@ -573,6 +573,158 @@ class TestBook(unittest.TestCase):
self
.
assertIsNotNone
(
out
)
print
(
str
(
program
))
def
test_brelu
(
self
):
program
=
Program
()
with
program_guard
(
program
):
input
=
layers
.
data
(
name
=
"input"
,
shape
=
[
16
],
dtype
=
"float32"
)
out
=
layers
.
brelu
(
input
,
t_min
=
1.0
,
t_max
=
20.0
,
name
=
'brelu'
)
self
.
assertIsNotNone
(
out
)
print
(
str
(
program
))
def
test_leaky_relu
(
self
):
program
=
Program
()
with
program_guard
(
program
):
input
=
layers
.
data
(
name
=
"input"
,
shape
=
[
16
],
dtype
=
"float32"
)
out
=
layers
.
leaky_relu
(
input
,
alpha
=
0.1
,
name
=
'leaky_relu'
)
self
.
assertIsNotNone
(
out
)
print
(
str
(
program
))
def
test_soft_relu
(
self
):
program
=
Program
()
with
program_guard
(
program
):
input
=
layers
.
data
(
name
=
"input"
,
shape
=
[
16
],
dtype
=
"float32"
)
out
=
layers
.
soft_relu
(
input
,
threshold
=
30.0
,
name
=
'soft_relu'
)
self
.
assertIsNotNone
(
out
)
print
(
str
(
program
))
def
test_sigmoid
(
self
):
program
=
Program
()
with
program_guard
(
program
):
input
=
layers
.
data
(
name
=
"input"
,
shape
=
[
16
],
dtype
=
"float32"
)
out
=
layers
.
sigmoid
(
input
,
name
=
'sigmoid'
)
self
.
assertIsNotNone
(
out
)
print
(
str
(
program
))
def
test_logsigmoid
(
self
):
program
=
Program
()
with
program_guard
(
program
):
input
=
layers
.
data
(
name
=
"input"
,
shape
=
[
16
],
dtype
=
"float32"
)
out
=
layers
.
logsigmoid
(
input
,
name
=
'logsigmoid'
)
self
.
assertIsNotNone
(
out
)
print
(
str
(
program
))
def
test_exp
(
self
):
program
=
Program
()
with
program_guard
(
program
):
input
=
layers
.
data
(
name
=
"input"
,
shape
=
[
16
],
dtype
=
"float32"
)
out
=
layers
.
exp
(
input
,
name
=
'exp'
)
self
.
assertIsNotNone
(
out
)
print
(
str
(
program
))
def
test_tanh
(
self
):
program
=
Program
()
with
program_guard
(
program
):
input
=
layers
.
data
(
name
=
"input"
,
shape
=
[
16
],
dtype
=
"float32"
)
out
=
layers
.
tanh
(
input
,
name
=
'tanh'
)
self
.
assertIsNotNone
(
out
)
print
(
str
(
program
))
def
test_tanh_shrink
(
self
):
program
=
Program
()
with
program_guard
(
program
):
input
=
layers
.
data
(
name
=
"input"
,
shape
=
[
16
],
dtype
=
"float32"
)
out
=
layers
.
tanh_shrink
(
input
,
name
=
'tanh_shrink'
)
self
.
assertIsNotNone
(
out
)
print
(
str
(
program
))
def
test_sqrt
(
self
):
program
=
Program
()
with
program_guard
(
program
):
input
=
layers
.
data
(
name
=
"input"
,
shape
=
[
16
],
dtype
=
"float32"
)
out
=
layers
.
sqrt
(
input
,
name
=
'sqrt'
)
self
.
assertIsNotNone
(
out
)
print
(
str
(
program
))
def
test_abs
(
self
):
program
=
Program
()
with
program_guard
(
program
):
input
=
layers
.
data
(
name
=
"input"
,
shape
=
[
16
],
dtype
=
"float32"
)
out
=
layers
.
abs
(
input
,
name
=
'abs'
)
self
.
assertIsNotNone
(
out
)
print
(
str
(
program
))
def
test_ceil
(
self
):
program
=
Program
()
with
program_guard
(
program
):
input
=
layers
.
data
(
name
=
"input"
,
shape
=
[
16
],
dtype
=
"float32"
)
out
=
layers
.
ceil
(
input
,
name
=
'ceil'
)
self
.
assertIsNotNone
(
out
)
print
(
str
(
program
))
def
test_floor
(
self
):
program
=
Program
()
with
program_guard
(
program
):
input
=
layers
.
data
(
name
=
"input"
,
shape
=
[
16
],
dtype
=
"float32"
)
out
=
layers
.
floor
(
input
,
name
=
'floor'
)
self
.
assertIsNotNone
(
out
)
print
(
str
(
program
))
def
test_cos
(
self
):
program
=
Program
()
with
program_guard
(
program
):
input
=
layers
.
data
(
name
=
"input"
,
shape
=
[
16
],
dtype
=
"float32"
)
out
=
layers
.
cos
(
input
,
name
=
'cos'
)
self
.
assertIsNotNone
(
out
)
print
(
str
(
program
))
def
test_sin
(
self
):
program
=
Program
()
with
program_guard
(
program
):
input
=
layers
.
data
(
name
=
"input"
,
shape
=
[
16
],
dtype
=
"float32"
)
out
=
layers
.
sin
(
input
,
name
=
'sin'
)
self
.
assertIsNotNone
(
out
)
print
(
str
(
program
))
def
test_round
(
self
):
program
=
Program
()
with
program_guard
(
program
):
input
=
layers
.
data
(
name
=
"input"
,
shape
=
[
16
],
dtype
=
"float32"
)
out
=
layers
.
round
(
input
,
name
=
'round'
)
self
.
assertIsNotNone
(
out
)
print
(
str
(
program
))
def
test_reciprocal
(
self
):
program
=
Program
()
with
program_guard
(
program
):
input
=
layers
.
data
(
name
=
"input"
,
shape
=
[
16
],
dtype
=
"float32"
)
out
=
layers
.
reciprocal
(
input
,
name
=
'reciprocal'
)
self
.
assertIsNotNone
(
out
)
print
(
str
(
program
))
def
test_square
(
self
):
program
=
Program
()
with
program_guard
(
program
):
input
=
layers
.
data
(
name
=
"input"
,
shape
=
[
16
],
dtype
=
"float32"
)
out
=
layers
.
square
(
input
,
name
=
'square'
)
self
.
assertIsNotNone
(
out
)
print
(
str
(
program
))
def
test_softplus
(
self
):
program
=
Program
()
with
program_guard
(
program
):
input
=
layers
.
data
(
name
=
"input"
,
shape
=
[
16
],
dtype
=
"float32"
)
out
=
layers
.
softplus
(
input
,
name
=
'softplus'
)
self
.
assertIsNotNone
(
out
)
print
(
str
(
program
))
def
test_softsign
(
self
):
program
=
Program
()
with
program_guard
(
program
):
input
=
layers
.
data
(
name
=
"input"
,
shape
=
[
16
],
dtype
=
"float32"
)
out
=
layers
.
softsign
(
input
,
name
=
'softsign'
)
self
.
assertIsNotNone
(
out
)
print
(
str
(
program
))
def
test_roi_perspective_transform
(
self
):
program
=
Program
()
with
program_guard
(
program
):
...
...
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