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testgroup
pytensor
Commits
d5f310f0
提交
d5f310f0
authored
5月 06, 2015
作者:
Frederic
浏览文件
操作
浏览文件
下载
电子邮件补丁
差异文件
Fix a GPU test
上级
19515020
隐藏空白字符变更
内嵌
并排
正在显示
1 个修改的文件
包含
10 行增加
和
10 行删除
+10
-10
test_opt.py
theano/sandbox/cuda/tests/test_opt.py
+10
-10
没有找到文件。
theano/sandbox/cuda/tests/test_opt.py
浏览文件 @
d5f310f0
...
@@ -325,10 +325,10 @@ def test_opt_gpujoin_joinvectors_negativeaxes():
...
@@ -325,10 +325,10 @@ def test_opt_gpujoin_joinvectors_negativeaxes():
rng
=
numpy
.
random
.
RandomState
(
22
)
rng
=
numpy
.
random
.
RandomState
(
22
)
x1
=
rng
.
rand
(
5
)
x1
=
rng
.
rand
(
5
)
x2
=
rng
.
rand
(
10
)
x2
=
rng
.
rand
(
10
)
t1
=
shared
(
numpy
.
asarray
(
x1
,
theano
.
config
.
floatX
))
t1
=
cuda
.
shared_constructor
(
numpy
.
asarray
(
x1
,
"float32"
))
t2
=
shared
(
numpy
.
asarray
(
x2
,
theano
.
config
.
floatX
))
t2
=
cuda
.
shared_constructor
(
numpy
.
asarray
(
x2
,
"float32"
))
t
=
T
.
concatenate
([
t1
,
t2
],
axis
=-
1
)
t
=
tensor
.
concatenate
([
t1
,
t2
],
axis
=-
1
)
f
=
theano
.
function
(
inputs
=
[],
outputs
=
t
)
f
=
theano
.
function
(
inputs
=
[],
outputs
=
t
)
assert
(
numpy
.
allclose
(
f
(),
numpy
.
concatenate
([
x1
,
x2
],
axis
=-
1
)))
assert
(
numpy
.
allclose
(
f
(),
numpy
.
concatenate
([
x1
,
x2
],
axis
=-
1
)))
...
@@ -336,18 +336,18 @@ def test_opt_gpujoin_joinvectors_negativeaxes():
...
@@ -336,18 +336,18 @@ def test_opt_gpujoin_joinvectors_negativeaxes():
# Test case for two-dimensional vectors
# Test case for two-dimensional vectors
x1
=
rng
.
rand
(
5
,
10
)
x1
=
rng
.
rand
(
5
,
10
)
x2
=
rng
.
rand
(
10
,
10
)
x2
=
rng
.
rand
(
10
,
10
)
t1
=
shared
(
numpy
.
asarray
(
x1
,
theano
.
config
.
floatX
))
t1
=
cuda
.
shared_constructor
(
numpy
.
asarray
(
x1
,
"float32"
))
t2
=
shared
(
numpy
.
asarray
(
x2
,
theano
.
config
.
floatX
))
t2
=
cuda
.
shared_constructor
(
numpy
.
asarray
(
x2
,
"float32"
))
t
=
T
.
concatenate
([
t1
,
t2
],
axis
=-
2
)
t
=
tensor
.
concatenate
([
t1
,
t2
],
axis
=-
2
)
f
=
theano
.
function
(
inputs
=
[],
outputs
=
t
)
f
=
theano
.
function
(
inputs
=
[],
outputs
=
t
)
assert
(
numpy
.
allclose
(
f
(),
numpy
.
concatenate
([
x1
,
x2
],
axis
=-
2
)))
assert
(
numpy
.
allclose
(
f
(),
numpy
.
concatenate
([
x1
,
x2
],
axis
=-
2
)))
# Now check that a value error is raised when vectors don't match
# Now check that a value error is raised when vectors don't match
# along the negative concatenation axis
# along the negative concatenation axis
try
:
try
:
t
=
T
.
concatenate
([
t1
,
t2
],
axis
=-
1
)
t
=
tensor
.
concatenate
([
t1
,
t2
],
axis
=-
1
)
f
=
theano
.
function
(
inputs
=
[],
outputs
=
t
)
f
=
theano
.
function
(
inputs
=
[],
outputs
=
t
)
f
()
f
()
assert
(
False
)
assert
(
False
)
...
@@ -357,7 +357,7 @@ def test_opt_gpujoin_joinvectors_negativeaxes():
...
@@ -357,7 +357,7 @@ def test_opt_gpujoin_joinvectors_negativeaxes():
# Finally check that a value error is raised when negative
# Finally check that a value error is raised when negative
# axis is larger in absolute value than smallest number of dims
# axis is larger in absolute value than smallest number of dims
try
:
try
:
t
=
T
.
concatenate
([
t1
,
t2
],
axis
=-
3
)
t
=
tensor
.
concatenate
([
t1
,
t2
],
axis
=-
3
)
f
=
theano
.
function
(
inputs
=
[],
outputs
=
t
)
f
=
theano
.
function
(
inputs
=
[],
outputs
=
t
)
f
()
f
()
assert
(
False
)
assert
(
False
)
...
...
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