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dace68ac
编写于
1月 23, 2018
作者:
Y
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差异文件
Merge branch 'develop' into multihead_attention
上级
113cd6b3
7eb02eb4
变更
2
隐藏空白更改
内联
并排
Showing
2 changed file
with
5 addition
and
4 deletion
+5
-4
python/paddle/v2/dataset/wmt16.py
python/paddle/v2/dataset/wmt16.py
+3
-3
python/paddle/v2/fluid/nets.py
python/paddle/v2/fluid/nets.py
+2
-1
未找到文件。
python/paddle/v2/dataset/wmt16.py
浏览文件 @
dace68ac
...
@@ -305,9 +305,9 @@ def get_dict(lang, dict_size, reverse=False):
...
@@ -305,9 +305,9 @@ def get_dict(lang, dict_size, reverse=False):
dict_path
=
os
.
path
.
join
(
paddle
.
v2
.
dataset
.
common
.
DATA_HOME
,
dict_path
=
os
.
path
.
join
(
paddle
.
v2
.
dataset
.
common
.
DATA_HOME
,
"wmt16/%s_%d.dict"
%
(
lang
,
dict_size
))
"wmt16/%s_%d.dict"
%
(
lang
,
dict_size
))
assert
(
os
.
path
.
exists
(
dict_path
),
"Word dictionary does not exist. "
assert
os
.
path
.
exists
(
dict_path
),
"Word dictionary does not exist. "
"Please invoke paddle.dataset.wmt16.train/test/validation
"
"Please invoke paddle.dataset.wmt16.train/test/validation first
"
"first to build the dictionary."
)
"to build the dictionary."
tar_file
=
os
.
path
.
join
(
paddle
.
v2
.
dataset
.
common
.
DATA_HOME
,
"wmt16.tar.gz"
)
tar_file
=
os
.
path
.
join
(
paddle
.
v2
.
dataset
.
common
.
DATA_HOME
,
"wmt16.tar.gz"
)
return
__load_dict
(
tar_file
,
dict_size
,
lang
,
reverse
)
return
__load_dict
(
tar_file
,
dict_size
,
lang
,
reverse
)
...
...
python/paddle/v2/fluid/nets.py
浏览文件 @
dace68ac
...
@@ -248,7 +248,8 @@ def scaled_dot_product_attention(queries,
...
@@ -248,7 +248,8 @@ def scaled_dot_product_attention(queries,
reshaped
=
layers
.
reshape
(
reshaped
=
layers
.
reshape
(
x
=
x
,
x
=
x
,
shape
=
list
(
x
.
shape
[:
-
1
])
+
[
num_heads
,
hidden_size
//
num_heads
])
shape
=
list
(
x
.
shape
[:
-
1
])
+
[
num_heads
,
hidden_size
//
num_heads
])
# permuate the original dimensions into:
# permuate the dimensions into:
# [batch_size, num_heads, max_sequence_len, hidden_size_per_head]
# [batch_size, num_heads, max_sequence_len, hidden_size_per_head]
return
layers
.
transpose
(
x
=
reshaped
,
perm
=
[
0
,
2
,
1
,
3
])
return
layers
.
transpose
(
x
=
reshaped
,
perm
=
[
0
,
2
,
1
,
3
])
...
...
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