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体验新版 GitCode,发现更多精彩内容 >>
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312f3b86
编写于
8月 27, 2018
作者:
M
minqiyang
浏览文件
操作
浏览文件
下载
电子邮件补丁
差异文件
Fix random diff between python2 and python3
上级
3e1050a2
变更
3
隐藏空白更改
内联
并排
Showing
3 changed file
with
26 addition
and
26 deletion
+26
-26
python/paddle/dataset/movielens.py
python/paddle/dataset/movielens.py
+3
-2
python/paddle/fluid/layers/nn.py
python/paddle/fluid/layers/nn.py
+21
-21
python/paddle/fluid/transpiler/distribute_transpiler.py
python/paddle/fluid/transpiler/distribute_transpiler.py
+2
-3
未找到文件。
python/paddle/dataset/movielens.py
浏览文件 @
312f3b86
...
@@ -24,6 +24,7 @@ set and test set into paddle reader creators.
...
@@ -24,6 +24,7 @@ set and test set into paddle reader creators.
from
__future__
import
print_function
from
__future__
import
print_function
import
numpy
as
np
import
zipfile
import
zipfile
import
paddle.dataset.common
import
paddle.dataset.common
import
re
import
re
...
@@ -150,12 +151,12 @@ def __initialize_meta_info__():
...
@@ -150,12 +151,12 @@ def __initialize_meta_info__():
def
__reader__
(
rand_seed
=
0
,
test_ratio
=
0.1
,
is_test
=
False
):
def
__reader__
(
rand_seed
=
0
,
test_ratio
=
0.1
,
is_test
=
False
):
fn
=
__initialize_meta_info__
()
fn
=
__initialize_meta_info__
()
rand
=
random
.
Random
(
x
=
rand_seed
)
np
.
random
.
seed
(
rand_seed
)
with
zipfile
.
ZipFile
(
file
=
fn
)
as
package
:
with
zipfile
.
ZipFile
(
file
=
fn
)
as
package
:
with
package
.
open
(
'ml-1m/ratings.dat'
)
as
rating
:
with
package
.
open
(
'ml-1m/ratings.dat'
)
as
rating
:
for
line
in
rating
:
for
line
in
rating
:
line
=
cpt
.
to_text
(
line
,
encoding
=
'latin'
)
line
=
cpt
.
to_text
(
line
,
encoding
=
'latin'
)
if
(
rand
.
random
()
<
test_ratio
)
==
is_test
:
if
(
np
.
random
.
random
()
<
test_ratio
)
==
is_test
:
uid
,
mov_id
,
rating
,
_
=
line
.
strip
().
split
(
"::"
)
uid
,
mov_id
,
rating
,
_
=
line
.
strip
().
split
(
"::"
)
uid
=
int
(
uid
)
uid
=
int
(
uid
)
mov_id
=
int
(
mov_id
)
mov_id
=
int
(
mov_id
)
...
...
python/paddle/fluid/layers/nn.py
浏览文件 @
312f3b86
...
@@ -17,6 +17,7 @@ All layers just related to the neural network.
...
@@ -17,6 +17,7 @@ All layers just related to the neural network.
from
__future__
import
print_function
from
__future__
import
print_function
import
numpy
as
np
from
..layer_helper
import
LayerHelper
from
..layer_helper
import
LayerHelper
from
..initializer
import
Normal
,
Constant
from
..initializer
import
Normal
,
Constant
from
..framework
import
Variable
from
..framework
import
Variable
...
@@ -24,7 +25,6 @@ from ..param_attr import ParamAttr
...
@@ -24,7 +25,6 @@ from ..param_attr import ParamAttr
from
.layer_function_generator
import
autodoc
,
templatedoc
from
.layer_function_generator
import
autodoc
,
templatedoc
from
.tensor
import
concat
from
.tensor
import
concat
from
.
import
utils
from
.
import
utils
import
random
from
..
import
unique_name
from
..
import
unique_name
from
functools
import
reduce
from
functools
import
reduce
...
@@ -5102,7 +5102,7 @@ def random_crop(x, shape, seed=None):
...
@@ -5102,7 +5102,7 @@ def random_crop(x, shape, seed=None):
dtype
=
x
.
dtype
dtype
=
x
.
dtype
out
=
helper
.
create_tmp_variable
(
dtype
)
out
=
helper
.
create_tmp_variable
(
dtype
)
if
seed
is
None
:
if
seed
is
None
:
seed
=
random
.
randint
(
-
65536
,
65535
)
seed
=
np
.
random
.
randint
(
-
65536
,
65536
)
op_attrs
=
{
"shape"
:
shape
}
op_attrs
=
{
"shape"
:
shape
}
if
isinstance
(
seed
,
int
):
if
isinstance
(
seed
,
int
):
op_attrs
[
"startup_seed"
]
=
seed
op_attrs
[
"startup_seed"
]
=
seed
...
@@ -5416,7 +5416,7 @@ def prelu(x, mode, param_attr=None, name=None):
...
@@ -5416,7 +5416,7 @@ def prelu(x, mode, param_attr=None, name=None):
channel:elements in a channel share same weight
channel:elements in a channel share same weight
element:each element has a weight
element:each element has a weight
name(str|None): A name for this layer(optional). If set None, the layer
name(str|None): A name for this layer(optional). If set None, the layer
will be named automatically.
will be named automatically.
Returns:
Returns:
Variable: The output tensor with the same shape as input.
Variable: The output tensor with the same shape as input.
...
@@ -5530,23 +5530,23 @@ def sequence_mask(x, maxlen=None, dtype='int64', name=None):
...
@@ -5530,23 +5530,23 @@ def sequence_mask(x, maxlen=None, dtype='int64', name=None):
Supposing :code:`x` is a Tensor with shape [d_1, d_2, ..., d_n], the
Supposing :code:`x` is a Tensor with shape [d_1, d_2, ..., d_n], the
:code:`y` is a mask with shape [d_1, d_2, ..., d_n, maxlen], where:
:code:`y` is a mask with shape [d_1, d_2, ..., d_n, maxlen], where:
.. math::
.. math::
y(i_1, i_2,..., i_n, j) = (j < x(i_1, i_2,..., i_n))
y(i_1, i_2,..., i_n, j) = (j < x(i_1, i_2,..., i_n))
Args:
Args:
x (Variable): Input tensor of sequence_mask layer,
x (Variable): Input tensor of sequence_mask layer,
whose elements are integers less than :code:`maxlen`.
whose elements are integers less than :code:`maxlen`.
maxlen (int|None): Maximum length of the sequence. If :code:`maxlen`
maxlen (int|None): Maximum length of the sequence. If :code:`maxlen`
is None, it would be replace with :math:`max(x)`.
is None, it would be replace with :math:`max(x)`.
dtype (np.dtype|core.VarDesc.VarType|str): Data type of the output.
dtype (np.dtype|core.VarDesc.VarType|str): Data type of the output.
name (str|None): A name for this layer(optional). If set None, the
name (str|None): A name for this layer(optional). If set None, the
layer will be named automatically.
layer will be named automatically.
Returns:
Returns:
Variable: The output sequence mask.
Variable: The output sequence mask.
"""
"""
helper
=
LayerHelper
(
'sequence_mask'
,
**
locals
())
helper
=
LayerHelper
(
'sequence_mask'
,
**
locals
())
...
@@ -5571,23 +5571,23 @@ def stack(x, axis=0):
...
@@ -5571,23 +5571,23 @@ def stack(x, axis=0):
**Stack Layer**
**Stack Layer**
This layer stacks all of the input :code:`x` along axis.
This layer stacks all of the input :code:`x` along axis.
Input :code:`x` can be a single variable, a :code:`list` of variables,
Input :code:`x` can be a single variable, a :code:`list` of variables,
or a :code:`tuple` of variables. If :code:`x` is a :code:`list` or
or a :code:`tuple` of variables. If :code:`x` is a :code:`list` or
:code:`tuple`, the shapes of all these variables must be the same.
:code:`tuple`, the shapes of all these variables must be the same.
Supposing the shape of each input is :math:`[d_0, d_1, ..., d_{n-1}]`,
Supposing the shape of each input is :math:`[d_0, d_1, ..., d_{n-1}]`,
the shape of the output variable would be
the shape of the output variable would be
:math:`[d_0, d_1, ..., d_{axis}=len(x), ..., d_{n-1}]`.
:math:`[d_0, d_1, ..., d_{axis}=len(x), ..., d_{n-1}]`.
If :code:`axis` < 0, it would be replaced with :code:`axis+rank(x[0])+1`.
If :code:`axis` < 0, it would be replaced with :code:`axis+rank(x[0])+1`.
If :code:`axis` is None, it would be replaced with 0.
If :code:`axis` is None, it would be replaced with 0.
Args:
Args:
x (Variable|list(Variable)|tuple(Variable)): Input variables.
x (Variable|list(Variable)|tuple(Variable)): Input variables.
axis (int|None): The axis along which all inputs are stacked.
axis (int|None): The axis along which all inputs are stacked.
Returns:
Returns:
Variable: The stacked variable.
Variable: The stacked variable.
"""
"""
helper
=
LayerHelper
(
'stack'
,
**
locals
())
helper
=
LayerHelper
(
'stack'
,
**
locals
())
...
...
python/paddle/fluid/transpiler/distribute_transpiler.py
浏览文件 @
312f3b86
...
@@ -31,7 +31,6 @@ Steps to transpile pserver:
...
@@ -31,7 +31,6 @@ Steps to transpile pserver:
"""
"""
import
math
import
math
import
random
import
numpy
as
np
import
numpy
as
np
import
collections
import
collections
import
six
import
six
...
@@ -239,8 +238,8 @@ class DistributeTranspiler(object):
...
@@ -239,8 +238,8 @@ class DistributeTranspiler(object):
grad_var_mapping_items
=
list
(
six
.
iteritems
(
self
.
grad_var_mapping
))
grad_var_mapping_items
=
list
(
six
.
iteritems
(
self
.
grad_var_mapping
))
if
not
self
.
config
.
slice_var_up
:
if
not
self
.
config
.
slice_var_up
:
random
.
seed
(
self
.
origin_program
.
random_seed
)
np
.
random
.
seed
(
self
.
origin_program
.
random_seed
)
random
.
shuffle
(
grad_var_mapping_items
)
np
.
random
.
shuffle
(
grad_var_mapping_items
)
grad_name_to_send_dummy_out
=
dict
()
grad_name_to_send_dummy_out
=
dict
()
for
grad_varname
,
splited_vars
in
grad_var_mapping_items
:
for
grad_varname
,
splited_vars
in
grad_var_mapping_items
:
...
...
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