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6e80b84d
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6e80b84d
编写于
1月 06, 2023
作者:
W
Weilong Wu
提交者:
GitHub
1月 06, 2023
浏览文件
操作
浏览文件
下载
电子邮件补丁
差异文件
[Eager] polish several api (#49589)
上级
cac5f5a7
变更
3
隐藏空白更改
内联
并排
Showing
3 changed file
with
13 addition
and
15 deletion
+13
-15
python/paddle/nn/functional/activation.py
python/paddle/nn/functional/activation.py
+9
-11
python/paddle/nn/functional/common.py
python/paddle/nn/functional/common.py
+3
-2
python/paddle/nn/functional/pooling.py
python/paddle/nn/functional/pooling.py
+1
-2
未找到文件。
python/paddle/nn/functional/activation.py
浏览文件 @
6e80b84d
...
@@ -494,11 +494,6 @@ def prelu(x, weight, data_format="NCHW", name=None):
...
@@ -494,11 +494,6 @@ def prelu(x, weight, data_format="NCHW", name=None):
# [-1.25, 6. , 7. , -2. ],
# [-1.25, 6. , 7. , -2. ],
# [ 6. , 7. , 8. , 9. ]]]]
# [ 6. , 7. , 8. , 9. ]]]]
"""
"""
check_variable_and_dtype
(
x
,
'x'
,
[
'float16'
,
'float32'
,
'float64'
],
'prelu'
)
check_variable_and_dtype
(
weight
,
'weight'
,
[
'float16'
,
'float32'
,
'float64'
],
'prelu'
)
assert
(
assert
(
len
(
weight
.
shape
)
==
1
len
(
weight
.
shape
)
==
1
),
"The dim count of weight shape should be 1 in prelu()."
),
"The dim count of weight shape should be 1 in prelu()."
...
@@ -541,6 +536,12 @@ def prelu(x, weight, data_format="NCHW", name=None):
...
@@ -541,6 +536,12 @@ def prelu(x, weight, data_format="NCHW", name=None):
if
in_dygraph_mode
():
if
in_dygraph_mode
():
return
_C_ops
.
prelu
(
x
,
weight
,
data_format
,
mode
)
return
_C_ops
.
prelu
(
x
,
weight
,
data_format
,
mode
)
else
:
else
:
check_variable_and_dtype
(
x
,
'x'
,
[
'float16'
,
'float32'
,
'float64'
],
'prelu'
)
check_variable_and_dtype
(
weight
,
'weight'
,
[
'float16'
,
'float32'
,
'float64'
],
'prelu'
)
helper
=
LayerHelper
(
'prelu'
,
**
locals
())
helper
=
LayerHelper
(
'prelu'
,
**
locals
())
out
=
helper
.
create_variable_for_type_inference
(
x
.
dtype
)
out
=
helper
.
create_variable_for_type_inference
(
x
.
dtype
)
helper
.
append_op
(
helper
.
append_op
(
...
@@ -622,12 +623,6 @@ def rrelu(x, lower=1.0 / 8.0, upper=1.0 / 3.0, training=True, name=None):
...
@@ -622,12 +623,6 @@ def rrelu(x, lower=1.0 / 8.0, upper=1.0 / 3.0, training=True, name=None):
# [-1.3766339 6. 7. -2.3465784 ]
# [-1.3766339 6. 7. -2.3465784 ]
# [ 6. 7. 8. 9. ]]]]
# [ 6. 7. 8. 9. ]]]]
"""
"""
if
not
in_dynamic_mode
():
check_variable_and_dtype
(
x
,
'X'
,
[
'float16'
,
'float32'
,
'float64'
],
'rrelu'
)
if
not
isinstance
(
lower
,
float
)
or
not
isinstance
(
upper
,
float
):
if
not
isinstance
(
lower
,
float
)
or
not
isinstance
(
upper
,
float
):
raise
TypeError
(
raise
TypeError
(
"The lower and upper values must be float type. Received: lower {}, upper {}."
.
format
(
"The lower and upper values must be float type. Received: lower {}, upper {}."
.
format
(
...
@@ -664,6 +659,9 @@ def rrelu(x, lower=1.0 / 8.0, upper=1.0 / 3.0, training=True, name=None):
...
@@ -664,6 +659,9 @@ def rrelu(x, lower=1.0 / 8.0, upper=1.0 / 3.0, training=True, name=None):
)
)
return
out
return
out
else
:
else
:
check_variable_and_dtype
(
x
,
'X'
,
[
'float16'
,
'float32'
,
'float64'
],
'rrelu'
)
helper
=
LayerHelper
(
'rrelu'
,
**
locals
())
helper
=
LayerHelper
(
'rrelu'
,
**
locals
())
out
=
helper
.
create_variable_for_type_inference
(
x
.
dtype
)
out
=
helper
.
create_variable_for_type_inference
(
x
.
dtype
)
noise
=
helper
.
create_variable_for_type_inference
(
dtype
=
x
.
dtype
)
noise
=
helper
.
create_variable_for_type_inference
(
dtype
=
x
.
dtype
)
...
...
python/paddle/nn/functional/common.py
浏览文件 @
6e80b84d
...
@@ -422,9 +422,7 @@ def interpolate(
...
@@ -422,9 +422,7 @@ def interpolate(
return
paddle
.
nn
.
functional
.
adaptive_avg_pool2d
(
x
,
size
)
return
paddle
.
nn
.
functional
.
adaptive_avg_pool2d
(
x
,
size
)
elif
len
(
x
.
shape
)
==
5
:
elif
len
(
x
.
shape
)
==
5
:
return
paddle
.
nn
.
functional
.
adaptive_avg_pool3d
(
x
,
size
)
return
paddle
.
nn
.
functional
.
adaptive_avg_pool3d
(
x
,
size
)
helper
=
LayerHelper
(
'{}_interp_v2'
.
format
(
resample_type
),
**
locals
())
helper
=
LayerHelper
(
'{}_interp_v2'
.
format
(
resample_type
),
**
locals
())
dtype
=
helper
.
input_dtype
(
input_param_name
=
'x'
)
if
len
(
x
.
shape
)
==
3
and
data_format
not
in
[
'NCW'
,
'NWC'
]:
if
len
(
x
.
shape
)
==
3
and
data_format
not
in
[
'NCW'
,
'NWC'
]:
raise
ValueError
(
raise
ValueError
(
"Got wrong value for param `data_format`: "
"Got wrong value for param `data_format`: "
...
@@ -678,6 +676,9 @@ def interpolate(
...
@@ -678,6 +676,9 @@ def interpolate(
else
:
else
:
out
=
_legacy_C_ops
.
bicubic_interp_v2
(
x
,
*
dy_attr
)
out
=
_legacy_C_ops
.
bicubic_interp_v2
(
x
,
*
dy_attr
)
return
out
return
out
dtype
=
helper
.
input_dtype
(
input_param_name
=
'x'
)
out
=
helper
.
create_variable_for_type_inference
(
dtype
)
out
=
helper
.
create_variable_for_type_inference
(
dtype
)
helper
.
append_op
(
helper
.
append_op
(
type
=
'{}_interp_v2'
.
format
(
resample_type
),
type
=
'{}_interp_v2'
.
format
(
resample_type
),
...
...
python/paddle/nn/functional/pooling.py
浏览文件 @
6e80b84d
...
@@ -597,8 +597,6 @@ def max_pool1d(
...
@@ -597,8 +597,6 @@ def max_pool1d(
"""
"""
"""NCL to NCHW"""
"""NCL to NCHW"""
data_format
=
"NCHW"
data_format
=
"NCHW"
if
not
in_dynamic_mode
():
check_variable_and_dtype
(
x
,
'x'
,
[
'float32'
,
'float64'
],
'max_pool1d'
)
_check_input
(
x
,
3
)
_check_input
(
x
,
3
)
x
=
unsqueeze
(
x
,
[
2
])
x
=
unsqueeze
(
x
,
[
2
])
kernel_size
=
[
1
]
+
utils
.
convert_to_list
(
kernel_size
,
1
,
'pool_size'
)
kernel_size
=
[
1
]
+
utils
.
convert_to_list
(
kernel_size
,
1
,
'pool_size'
)
...
@@ -641,6 +639,7 @@ def max_pool1d(
...
@@ -641,6 +639,7 @@ def max_pool1d(
return
squeeze
(
pool_out
,
[
2
])
return
squeeze
(
pool_out
,
[
2
])
else
:
else
:
check_variable_and_dtype
(
x
,
'x'
,
[
'float32'
,
'float64'
],
'max_pool1d'
)
op_type
=
'max_pool2d_with_index'
if
return_mask
else
"pool2d"
op_type
=
'max_pool2d_with_index'
if
return_mask
else
"pool2d"
helper
=
LayerHelper
(
op_type
,
**
locals
())
helper
=
LayerHelper
(
op_type
,
**
locals
())
dtype
=
helper
.
input_dtype
(
input_param_name
=
'x'
)
dtype
=
helper
.
input_dtype
(
input_param_name
=
'x'
)
...
...
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