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体验新版 GitCode,发现更多精彩内容 >>
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48d9fd08
编写于
2月 26, 2019
作者:
D
dzhwinter
浏览文件
操作
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电子邮件补丁
差异文件
fix default value. test=develop
上级
dfb21219
变更
2
隐藏空白更改
内联
并排
Showing
2 changed file
with
10 addition
and
60 deletion
+10
-60
python/paddle/fluid/tests/unittests/ir_memory_optimize_net_base.py
...ddle/fluid/tests/unittests/ir_memory_optimize_net_base.py
+10
-5
python/paddle/fluid/tests/unittests/test_ir_memory_optimize_ifelse_net.py
...uid/tests/unittests/test_ir_memory_optimize_ifelse_net.py
+0
-55
未找到文件。
python/paddle/fluid/tests/unittests/ir_memory_optimize_net_base.py
浏览文件 @
48d9fd08
...
...
@@ -117,7 +117,7 @@ class TestIrMemOptBase(BuildIrMemOptBase):
self
.
network
=
None
def
test_network
(
self
):
if
self
.
network
is
None
:
if
self
.
network
is
None
or
not
core
.
is_compiled_with_cuda
()
:
return
baseline_first_loss
,
baseline_last_loss
=
None
,
None
...
...
@@ -139,7 +139,12 @@ class TestIrMemOptBase(BuildIrMemOptBase):
self
.
network
,
use_cuda
=
use_cuda
,
memory_opt
=
use_python_mem_opt
)
self
.
assertAlmostEquals
(
np
.
mean
(
baseline_last_loss
),
np
.
mean
(
cur_last_loss
),
delta
=
1e-2
)
self
.
assertAlmostEquals
(
np
.
mean
(
baseline_first_loss
),
np
.
mean
(
cur_first_loss
),
delta
=
1e-2
)
self
.
assertAlmostEquals
(
np
.
mean
(
baseline_last_loss
),
np
.
mean
(
cur_last_loss
),
delta
=
1e-2
)
self
.
assertAlmostEquals
(
np
.
mean
(
baseline_first_loss
),
np
.
mean
(
cur_first_loss
),
delta
=
1e-2
)
python/paddle/fluid/tests/unittests/test_ir_memory_optimize_ifelse_net.py
已删除
100644 → 0
浏览文件 @
dfb21219
# Copyright (c) 2019 PaddlePaddle Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
from
__future__
import
print_function
import
paddle.fluid
as
fluid
import
unittest
from
ir_memory_optimize_net_base
import
TestIrMemOptBase
from
paddle.fluid.layers.control_flow
import
ConditionalBlock
def
lstm_net
(
data
,
label
,
dict_dim
,
emb_dim
=
128
,
hid_dim
=
128
,
hid_dim2
=
96
,
class_dim
=
2
,
emb_lr
=
30.0
):
emb
=
fluid
.
layers
.
embedding
(
input
=
data
,
size
=
[
dict_dim
,
emb_dim
],
param_attr
=
fluid
.
ParamAttr
(
learning_rate
=
emb_lr
))
fc0
=
fluid
.
layers
.
fc
(
input
=
emb
,
size
=
hid_dim
*
4
)
lstm_h
,
c
=
fluid
.
layers
.
dynamic_lstm
(
input
=
fc0
,
size
=
hid_dim
*
4
,
is_reverse
=
False
)
lstm_max
=
fluid
.
layers
.
sequence_pool
(
input
=
lstm_h
,
pool_type
=
'max'
)
lstm_max_tanh
=
fluid
.
layers
.
tanh
(
lstm_max
)
fc1
=
fluid
.
layers
.
fc
(
input
=
lstm_max_tanh
,
size
=
hid_dim2
,
act
=
'tanh'
)
prediction
=
fluid
.
layers
.
fc
(
input
=
fc1
,
size
=
class_dim
,
act
=
'softmax'
)
cost
=
fluid
.
layers
.
cross_entropy
(
input
=
prediction
,
label
=
label
)
avg_cost
=
fluid
.
layers
.
mean
(
x
=
cost
)
return
avg_cost
class
TestIrMemOptRNN
(
TestIrMemOptBase
):
def
setUp
(
self
):
self
.
network
=
lstm_net
self
.
iter
=
2
if
__name__
==
"__main__"
:
unittest
.
main
()
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