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体验新版 GitCode,发现更多精彩内容 >>
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69e0af56
编写于
5月 23, 2018
作者:
K
Kexin Zhao
浏览文件
操作
浏览文件
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电子邮件补丁
差异文件
do this to new_api example
上级
dbc6102e
变更
2
隐藏空白更改
内联
并排
Showing
2 changed file
with
31 addition
and
18 deletion
+31
-18
python/paddle/fluid/tests/book/high-level-api/label_semantic_roles/test_label_semantic_roles_newapi.py
.../label_semantic_roles/test_label_semantic_roles_newapi.py
+29
-18
python/paddle/fluid/tests/book/test_label_semantic_roles.py
python/paddle/fluid/tests/book/test_label_semantic_roles.py
+2
-0
未找到文件。
python/paddle/fluid/tests/book/high-level-api/label_semantic_roles/test_label_semantic_roles_newapi.py
浏览文件 @
69e0af56
...
...
@@ -202,24 +202,35 @@ def infer(use_cuda, inference_program, save_path):
inferencer
=
fluid
.
Inferencer
(
inference_program
,
param_path
=
save_path
,
place
=
place
)
def
create_random_lodtensor
(
lod
,
place
,
low
,
high
):
data
=
np
.
random
.
random_integers
(
low
,
high
,
[
lod
[
-
1
],
1
]).
astype
(
"int64"
)
res
=
fluid
.
LoDTensor
()
res
.
set
(
data
,
place
)
res
.
set_lod
([
lod
])
return
res
# Create an input example
lod
=
[
0
,
4
,
10
]
word
=
create_random_lodtensor
(
lod
,
place
,
low
=
0
,
high
=
WORD_DICT_LEN
-
1
)
pred
=
create_random_lodtensor
(
lod
,
place
,
low
=
0
,
high
=
PRED_DICT_LEN
-
1
)
ctx_n2
=
create_random_lodtensor
(
lod
,
place
,
low
=
0
,
high
=
WORD_DICT_LEN
-
1
)
ctx_n1
=
create_random_lodtensor
(
lod
,
place
,
low
=
0
,
high
=
WORD_DICT_LEN
-
1
)
ctx_0
=
create_random_lodtensor
(
lod
,
place
,
low
=
0
,
high
=
WORD_DICT_LEN
-
1
)
ctx_p1
=
create_random_lodtensor
(
lod
,
place
,
low
=
0
,
high
=
WORD_DICT_LEN
-
1
)
ctx_p2
=
create_random_lodtensor
(
lod
,
place
,
low
=
0
,
high
=
WORD_DICT_LEN
-
1
)
mark
=
create_random_lodtensor
(
lod
,
place
,
low
=
0
,
high
=
MARK_DICT_LEN
-
1
)
# Setup inputs by creating LoDTensors to represent sequences of words.
# Here each word is the basic element of these LoDTensors and the shape of
# each word (base_shape) should be [1] since it is simply an index to
# look up for the corresponding word vector.
# Suppose the length_based level of detail (lod) info is set to [[3, 4, 2]],
# which has only one lod level. Then the created LoDTensors will have only
# one higher level structure (sequence of words, or sentence) than the basic
# element (word). Hence the LoDTensor will hold data for three sentences of
# length 3, 4 and 2, respectively.
# Note that lod info should be a list of lists.
lod
=
[[
3
,
4
,
2
]]
base_shape
=
[
1
]
# The range of random integers is [low, high]
word
=
fluid
.
create_random_lodtensor
(
lod
,
base_shape
,
place
,
low
=
0
,
high
=
WORD_DICT_LEN
-
1
)
pred
=
fluid
.
create_random_lodtensor
(
lod
,
base_shape
,
place
,
low
=
0
,
high
=
PRED_DICT_LEN
-
1
)
ctx_n2
=
fluid
.
create_random_lodtensor
(
lod
,
base_shape
,
place
,
low
=
0
,
high
=
WORD_DICT_LEN
-
1
)
ctx_n1
=
fluid
.
create_random_lodtensor
(
lod
,
base_shape
,
place
,
low
=
0
,
high
=
WORD_DICT_LEN
-
1
)
ctx_0
=
fluid
.
create_random_lodtensor
(
lod
,
base_shape
,
place
,
low
=
0
,
high
=
WORD_DICT_LEN
-
1
)
ctx_p1
=
fluid
.
create_random_lodtensor
(
lod
,
base_shape
,
place
,
low
=
0
,
high
=
WORD_DICT_LEN
-
1
)
ctx_p2
=
fluid
.
create_random_lodtensor
(
lod
,
base_shape
,
place
,
low
=
0
,
high
=
WORD_DICT_LEN
-
1
)
mark
=
fluid
.
create_random_lodtensor
(
lod
,
base_shape
,
place
,
low
=
0
,
high
=
MARK_DICT_LEN
-
1
)
results
=
inferencer
.
infer
(
{
...
...
python/paddle/fluid/tests/book/test_label_semantic_roles.py
浏览文件 @
69e0af56
...
...
@@ -257,8 +257,10 @@ def infer(use_cuda, save_dirname=None):
# one higher level structure (sequence of words, or sentence) than the basic
# element (word). Hence the LoDTensor will hold data for three sentences of
# length 3, 4 and 2, respectively.
# Note that lod info should be a list of lists.
lod
=
[[
3
,
4
,
2
]]
base_shape
=
[
1
]
# The range of random integers is [low, high]
word
=
fluid
.
create_random_lodtensor
(
lod
,
base_shape
,
place
,
low
=
0
,
high
=
word_dict_len
-
1
)
pred
=
fluid
.
create_random_lodtensor
(
...
...
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