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体验新版 GitCode,发现更多精彩内容 >>
提交
e7fa61e2
编写于
1月 15, 2019
作者:
P
peizhilin
浏览文件
操作
浏览文件
下载
电子邮件补丁
差异文件
fix unit test cases
test=develop
上级
a7fc3d42
变更
4
隐藏空白更改
内联
并排
Showing
4 changed file
with
26 addition
and
18 deletion
+26
-18
python/paddle/fluid/tests/book/high-level-api/recommender_system/test_recommender_system_newapi.py
...-api/recommender_system/test_recommender_system_newapi.py
+11
-8
python/paddle/fluid/tests/book/test_recommender_system.py
python/paddle/fluid/tests/book/test_recommender_system.py
+12
-8
python/paddle/fluid/tests/unittests/test_auc_op.py
python/paddle/fluid/tests/unittests/test_auc_op.py
+1
-1
python/paddle/fluid/tests/unittests/test_nce.py
python/paddle/fluid/tests/unittests/test_nce.py
+2
-1
未找到文件。
python/paddle/fluid/tests/book/high-level-api/recommender_system/test_recommender_system_newapi.py
浏览文件 @
e7fa61e2
...
...
@@ -231,14 +231,17 @@ def infer(use_cuda, inference_program, params_dirname):
# Correspondingly, recursive_sequence_lengths = [[3, 2]] contains one
# level of detail info, indicating that `data` consists of two sequences
# of length 3 and 2, respectively.
user_id
=
fluid
.
create_lod_tensor
([[
1
]],
[[
1
]],
place
)
gender_id
=
fluid
.
create_lod_tensor
([[
1
]],
[[
1
]],
place
)
age_id
=
fluid
.
create_lod_tensor
([[
0
]],
[[
1
]],
place
)
job_id
=
fluid
.
create_lod_tensor
([[
10
]],
[[
1
]],
place
)
movie_id
=
fluid
.
create_lod_tensor
([[
783
]],
[[
1
]],
place
)
category_id
=
fluid
.
create_lod_tensor
([[
10
,
8
,
9
]],
[[
3
]],
place
)
movie_title
=
fluid
.
create_lod_tensor
([[
1069
,
4140
,
2923
,
710
,
988
]],
[[
5
]],
place
)
user_id
=
fluid
.
create_lod_tensor
([[
np
.
int64
(
1
)]],
[[
1
]],
place
)
gender_id
=
fluid
.
create_lod_tensor
([[
np
.
int64
(
1
)]],
[[
1
]],
place
)
age_id
=
fluid
.
create_lod_tensor
([[
np
.
int64
(
0
)]],
[[
1
]],
place
)
job_id
=
fluid
.
create_lod_tensor
([[
np
.
int64
(
10
)]],
[[
1
]],
place
)
movie_id
=
fluid
.
create_lod_tensor
([[
np
.
int64
(
783
)]],
[[
1
]],
place
)
category_id
=
fluid
.
create_lod_tensor
(
[
np
.
array
(
[
10
,
8
,
9
],
dtype
=
'int64'
)],
[[
3
]],
place
)
movie_title
=
fluid
.
create_lod_tensor
(
[
np
.
array
(
[
1069
,
4140
,
2923
,
710
,
988
],
dtype
=
'int64'
)],
[[
5
]],
place
)
results
=
inferencer
.
infer
(
{
...
...
python/paddle/fluid/tests/book/test_recommender_system.py
浏览文件 @
e7fa61e2
...
...
@@ -271,26 +271,30 @@ def infer(use_cuda, save_dirname=None):
# Correspondingly, recursive_sequence_lengths = [[3, 2]] contains one
# level of detail info, indicating that `data` consists of two sequences
# of length 3 and 2, respectively.
user_id
=
fluid
.
create_lod_tensor
([[
1
]],
[[
1
]],
place
)
user_id
=
fluid
.
create_lod_tensor
([[
np
.
int64
(
1
)
]],
[[
1
]],
place
)
assert
feed_target_names
[
1
]
==
"gender_id"
gender_id
=
fluid
.
create_lod_tensor
([[
1
]],
[[
1
]],
place
)
gender_id
=
fluid
.
create_lod_tensor
([[
np
.
int64
(
1
)
]],
[[
1
]],
place
)
assert
feed_target_names
[
2
]
==
"age_id"
age_id
=
fluid
.
create_lod_tensor
([[
0
]],
[[
1
]],
place
)
age_id
=
fluid
.
create_lod_tensor
([[
np
.
int64
(
0
)
]],
[[
1
]],
place
)
assert
feed_target_names
[
3
]
==
"job_id"
job_id
=
fluid
.
create_lod_tensor
([[
10
]],
[[
1
]],
place
)
job_id
=
fluid
.
create_lod_tensor
([[
np
.
int64
(
10
)
]],
[[
1
]],
place
)
assert
feed_target_names
[
4
]
==
"movie_id"
movie_id
=
fluid
.
create_lod_tensor
([[
783
]],
[[
1
]],
place
)
movie_id
=
fluid
.
create_lod_tensor
([[
np
.
int64
(
783
)
]],
[[
1
]],
place
)
assert
feed_target_names
[
5
]
==
"category_id"
category_id
=
fluid
.
create_lod_tensor
([[
10
,
8
,
9
]],
[[
3
]],
place
)
category_id
=
fluid
.
create_lod_tensor
(
[
np
.
array
(
[
10
,
8
,
9
],
dtype
=
'int64'
)],
[[
3
]],
place
)
assert
feed_target_names
[
6
]
==
"movie_title"
movie_title
=
fluid
.
create_lod_tensor
([[
1069
,
4140
,
2923
,
710
,
988
]],
[[
5
]],
place
)
movie_title
=
fluid
.
create_lod_tensor
(
[
np
.
array
(
[
1069
,
4140
,
2923
,
710
,
988
],
dtype
=
'int64'
)],
[[
5
]],
place
)
# Construct feed as a dictionary of {feed_target_name: feed_target_data}
# and results will contain a list of data corresponding to fetch_targets.
...
...
python/paddle/fluid/tests/unittests/test_auc_op.py
浏览文件 @
e7fa61e2
...
...
@@ -24,7 +24,7 @@ class TestAucOp(OpTest):
def
setUp
(
self
):
self
.
op_type
=
"auc"
pred
=
np
.
random
.
random
((
128
,
2
)).
astype
(
"float32"
)
labels
=
np
.
random
.
randint
(
0
,
2
,
(
128
,
1
))
labels
=
np
.
random
.
randint
(
0
,
2
,
(
128
,
1
))
.
astype
(
"int64"
)
num_thresholds
=
200
stat_pos
=
np
.
zeros
((
num_thresholds
+
1
,
)).
astype
(
"int64"
)
...
...
python/paddle/fluid/tests/unittests/test_nce.py
浏览文件 @
e7fa61e2
...
...
@@ -68,7 +68,8 @@ class TestNCE(OpTest):
weight
=
np
.
random
.
randn
(
num_classes
,
dim
).
astype
(
np
.
float32
)
bias
=
np
.
random
.
randn
(
num_classes
).
astype
(
np
.
float32
)
sample_weight
=
np
.
random
.
randn
(
batch_size
).
astype
(
np
.
float32
)
labels
=
np
.
random
.
randint
(
0
,
num_classes
,
(
batch_size
,
num_true_class
))
labels
=
np
.
random
.
randint
(
0
,
num_classes
,
(
batch_size
,
num_true_class
)).
astype
(
"int64"
)
self
.
attrs
=
{
'num_total_classes'
:
num_classes
,
'num_neg_samples'
:
num_neg_samples
,
...
...
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