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82ec247a
编写于
7月 01, 2020
作者:
A
Aurelius84
提交者:
GitHub
7月 01, 2020
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差异文件
fix random failed on GPU test=develop (#25293)
上级
0371cf6f
变更
1
隐藏空白更改
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并排
Showing
1 changed file
with
20 addition
and
1 deletion
+20
-1
python/paddle/fluid/tests/unittests/dygraph_to_static/test_cycle_gan.py
...fluid/tests/unittests/dygraph_to_static/test_cycle_gan.py
+20
-1
未找到文件。
python/paddle/fluid/tests/unittests/dygraph_to_static/test_cycle_gan.py
浏览文件 @
82ec247a
...
...
@@ -32,6 +32,10 @@ import unittest
import
numpy
as
np
from
PIL
import
Image
,
ImageOps
import
os
# Use GPU:0 to elimate the influence of other tasks.
os
.
environ
[
"CUDA_VISIBLE_DEVICES"
]
=
"1"
import
paddle
import
paddle.fluid
as
fluid
from
paddle.fluid.dygraph
import
to_variable
,
declarative
,
ProgramTranslator
...
...
@@ -327,6 +331,11 @@ class conv2d(fluid.dygraph.Layer):
initializer
=
fluid
.
initializer
.
NormalInitializer
(
loc
=
0.0
,
scale
=
stddev
)),
bias_attr
=
con_bias_attr
)
# Note(Aurelius84): The calculation of GPU kernel in BN is non-deterministic,
# failure rate is 1/100 in Dev but seems incremental in CE platform.
# If on GPU, we disable BN temporarily.
if
fluid
.
is_compiled_with_cuda
():
norm
=
False
if
norm
:
self
.
bn
=
BatchNorm
(
use_global_stats
=
True
,
# set True to use deterministic algorithm
...
...
@@ -383,6 +392,8 @@ class DeConv2D(fluid.dygraph.Layer):
initializer
=
fluid
.
initializer
.
NormalInitializer
(
loc
=
0.0
,
scale
=
stddev
)),
bias_attr
=
de_bias_attr
)
if
fluid
.
is_compiled_with_cuda
():
norm
=
False
if
norm
:
self
.
bn
=
BatchNorm
(
use_global_stats
=
True
,
# set True to use deterministic algorithm
...
...
@@ -606,8 +617,16 @@ class TestCycleGANModel(unittest.TestCase):
def
test_train
(
self
):
st_out
=
self
.
train
(
to_static
=
True
)
dy_out
=
self
.
train
(
to_static
=
False
)
assert_func
=
np
.
allclose
# Note(Aurelius84): Because we disable BN on GPU,
# but here we enhance the check on CPU by `np.array_equal`
# which means the dy_out and st_out shall be exactly same.
if
not
fluid
.
is_compiled_with_cuda
():
assert_func
=
np
.
array_equal
self
.
assertTrue
(
np
.
allclose
(
dy_out
,
st_out
),
assert_func
(
dy_out
,
st_out
),
msg
=
"dy_out:
\n
{}
\n
st_out:
\n
{}"
.
format
(
dy_out
,
st_out
))
...
...
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