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体验新版 GitCode,发现更多精彩内容 >>
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a4c52237
编写于
7月 25, 2018
作者:
C
chengduo
提交者:
GitHub
7月 25, 2018
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差异文件
Update test_pe_mnist threshold (#12348)
* update test_pe_mnist threshold * clean code
上级
b73806b2
变更
1
隐藏空白更改
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Showing
1 changed file
with
28 addition
and
57 deletion
+28
-57
python/paddle/fluid/tests/unittests/test_parallel_executor_mnist.py
...dle/fluid/tests/unittests/test_parallel_executor_mnist.py
+28
-57
未找到文件。
python/paddle/fluid/tests/unittests/test_parallel_executor_mnist.py
浏览文件 @
a4c52237
...
...
@@ -107,44 +107,24 @@ class TestMNIST(TestParallelExecutorBase):
label
=
np
.
ones
(
shape
=
[
32
,
1
],
dtype
=
'int64'
)
return
img
,
label
# simple_fc
def
check_simple_fc_convergence
(
self
,
use_cuda
,
use_reduce
=
False
):
def
_compare_reduce_and_allreduce
(
self
,
model
,
use_cuda
,
random_data
=
True
):
if
use_cuda
and
not
core
.
is_compiled_with_cuda
():
return
self
.
check_network_convergence
(
simple_fc_net
,
use_cuda
=
use_cuda
)
self
.
check_network_convergence
(
simple_fc_net
,
use_cuda
=
use_cuda
,
allow_op_delay
=
True
)
img
,
label
=
self
.
_init_data
()
model
,
use_cuda
=
use_cuda
,
use_reduce
=
True
)
self
.
check_network_convergence
(
simple_fc_net
,
feed_dict
=
{
"image"
:
img
,
"label"
:
label
},
use_cuda
=
use_cuda
,
use_reduce
=
use_reduce
)
model
,
use_cuda
=
use_cuda
,
allow_op_delay
=
True
,
use_reduce
=
True
)
def
check_simple_fc_convergence_with_Reduce
(
self
,
use_cuda
):
if
use_cuda
and
not
core
.
is_compiled_with_cuda
():
return
self
.
check_network_convergence
(
simple_fc_net
,
use_cuda
=
use_cuda
,
use_reduce
=
True
)
self
.
check_network_convergence
(
simple_fc_net
,
use_cuda
=
use_cuda
,
allow_op_delay
=
True
,
use_reduce
=
True
)
img
,
label
=
self
.
_init_data
()
img
,
label
=
self
.
_init_data
(
random_data
)
all_reduce_first_loss
,
all_reduce_last_loss
=
self
.
check_network_convergence
(
simple_fc_net
,
model
,
feed_dict
=
{
"image"
:
img
,
"label"
:
label
},
use_cuda
=
use_cuda
,
use_reduce
=
False
)
reduce_first_loss
,
reduce_last_loss
=
self
.
check_network_convergence
(
simple_fc_net
,
model
,
feed_dict
=
{
"image"
:
img
,
"label"
:
label
},
use_cuda
=
use_cuda
,
...
...
@@ -153,7 +133,24 @@ class TestMNIST(TestParallelExecutorBase):
for
loss
in
zip
(
all_reduce_first_loss
,
reduce_first_loss
):
self
.
assertAlmostEquals
(
loss
[
0
],
loss
[
1
],
delta
=
1e-6
)
for
loss
in
zip
(
all_reduce_last_loss
,
reduce_last_loss
):
self
.
assertAlmostEquals
(
loss
[
0
],
loss
[
1
],
delta
=
1e-6
)
self
.
assertAlmostEquals
(
loss
[
0
],
loss
[
1
],
delta
=
1e-4
)
# simple_fc
def
check_simple_fc_convergence
(
self
,
use_cuda
,
use_reduce
=
False
):
if
use_cuda
and
not
core
.
is_compiled_with_cuda
():
return
self
.
check_network_convergence
(
simple_fc_net
,
use_cuda
=
use_cuda
)
self
.
check_network_convergence
(
simple_fc_net
,
use_cuda
=
use_cuda
,
allow_op_delay
=
True
)
img
,
label
=
self
.
_init_data
()
self
.
check_network_convergence
(
simple_fc_net
,
feed_dict
=
{
"image"
:
img
,
"label"
:
label
},
use_cuda
=
use_cuda
,
use_reduce
=
use_reduce
)
def
test_simple_fc
(
self
):
# use_cuda
...
...
@@ -162,8 +159,8 @@ class TestMNIST(TestParallelExecutorBase):
def
test_simple_fc_with_new_strategy
(
self
):
# use_cuda, use_reduce
self
.
check_simple_fc_convergence_with_Reduce
(
True
)
self
.
check_simple_fc_convergence_with_Reduce
(
False
)
self
.
_compare_reduce_and_allreduce
(
simple_fc_net
,
True
)
self
.
_compare_reduce_and_allreduce
(
simple_fc_net
,
False
)
def
check_simple_fc_parallel_accuracy
(
self
,
use_cuda
):
if
use_cuda
and
not
core
.
is_compiled_with_cuda
():
...
...
@@ -209,39 +206,13 @@ class TestMNIST(TestParallelExecutorBase):
"label"
:
label
},
use_cuda
=
use_cuda
)
def
check_batchnorm_fc_convergence_use_reduce
(
self
,
use_cuda
):
if
use_cuda
and
not
core
.
is_compiled_with_cuda
():
return
self
.
check_network_convergence
(
fc_with_batchnorm
,
use_cuda
=
use_cuda
,
use_reduce
=
True
)
img
,
label
=
self
.
_init_data
()
all_reduce_first_loss
,
all_reduce_last_loss
=
self
.
check_network_convergence
(
fc_with_batchnorm
,
feed_dict
=
{
"image"
:
img
,
"label"
:
label
},
use_cuda
=
use_cuda
,
use_reduce
=
False
)
reduce_first_loss
,
reduce_last_loss
=
self
.
check_network_convergence
(
fc_with_batchnorm
,
feed_dict
=
{
"image"
:
img
,
"label"
:
label
},
use_cuda
=
use_cuda
,
use_reduce
=
True
)
for
loss
in
zip
(
all_reduce_first_loss
,
reduce_first_loss
):
self
.
assertAlmostEquals
(
loss
[
0
],
loss
[
1
],
delta
=
1e-6
)
for
loss
in
zip
(
all_reduce_last_loss
,
reduce_last_loss
):
self
.
assertAlmostEquals
(
loss
[
0
],
loss
[
1
],
delta
=
1e-4
)
def
test_batchnorm_fc
(
self
):
self
.
check_batchnorm_fc_convergence
(
True
)
self
.
check_batchnorm_fc_convergence
(
False
)
def
test_batchnorm_fc_with_new_strategy
(
self
):
self
.
check_batchnorm_fc_convergence_use_reduce
(
True
)
self
.
check_batchnorm_fc_convergence_use_reduce
(
False
)
self
.
_compare_reduce_and_allreduce
(
fc_with_batchnorm
,
True
)
self
.
_compare_reduce_and_allreduce
(
fc_with_batchnorm
,
False
)
if
__name__
==
'__main__'
:
...
...
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