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体验新版 GitCode,发现更多精彩内容 >>
提交
a305cb21
编写于
3月 08, 2018
作者:
Y
Yu Yang
浏览文件
操作
浏览文件
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电子邮件补丁
差异文件
Use new program when unittest
上级
9d4c93a0
变更
1
隐藏空白更改
内联
并排
Showing
1 changed file
with
21 addition
and
19 deletion
+21
-19
python/paddle/fluid/tests/unittests/test_recordio_reader.py
python/paddle/fluid/tests/unittests/test_recordio_reader.py
+21
-19
未找到文件。
python/paddle/fluid/tests/unittests/test_recordio_reader.py
浏览文件 @
a305cb21
...
...
@@ -21,7 +21,7 @@ import paddle.v2 as paddle
class
TestRecordIO
(
unittest
.
TestCase
):
def
setUp
(
self
):
# Convert mnist to recordio file
with
fluid
.
program_guard
(
fluid
.
Program
()):
with
fluid
.
program_guard
(
fluid
.
Program
()
,
fluid
.
Program
()
):
reader
=
paddle
.
batch
(
mnist
.
train
(),
batch_size
=
32
)
feeder
=
fluid
.
DataFeeder
(
feed_list
=
[
# order is image and label
...
...
@@ -35,24 +35,26 @@ class TestRecordIO(unittest.TestCase):
'./mnist.recordio'
,
reader
,
feeder
)
def
test_main
(
self
):
data_file
=
fluid
.
layers
.
open_recordio_file
(
'./mnist.recordio'
,
shapes
=
[[
-
1
,
784
],
[
-
1
,
1
]],
lod_levels
=
[
0
,
0
],
dtypes
=
[
'float32'
,
'int64'
])
img
,
label
=
fluid
.
layers
.
read_file
(
data_file
)
# use new program
with
fluid
.
program_guard
(
fluid
.
Program
(),
fluid
.
Program
()):
data_file
=
fluid
.
layers
.
open_recordio_file
(
'./mnist.recordio'
,
shapes
=
[[
-
1
,
784
],
[
-
1
,
1
]],
lod_levels
=
[
0
,
0
],
dtypes
=
[
'float32'
,
'int64'
])
img
,
label
=
fluid
.
layers
.
read_file
(
data_file
)
hidden
=
fluid
.
layers
.
fc
(
input
=
img
,
size
=
100
,
act
=
'tanh'
)
prediction
=
fluid
.
layers
.
fc
(
input
=
hidden
,
size
=
10
,
act
=
'softmax'
)
loss
=
fluid
.
layers
.
cross_entropy
(
input
=
prediction
,
label
=
label
)
avg_loss
=
fluid
.
layers
.
mean
(
loss
)
hidden
=
fluid
.
layers
.
fc
(
input
=
img
,
size
=
100
,
act
=
'tanh'
)
prediction
=
fluid
.
layers
.
fc
(
input
=
hidden
,
size
=
10
,
act
=
'softmax'
)
loss
=
fluid
.
layers
.
cross_entropy
(
input
=
prediction
,
label
=
label
)
avg_loss
=
fluid
.
layers
.
mean
(
loss
)
fluid
.
optimizer
.
Adam
(
learning_rate
=
1e-3
).
minimize
(
avg_loss
)
fluid
.
optimizer
.
Adam
(
learning_rate
=
1e-3
).
minimize
(
avg_loss
)
exe
=
fluid
.
Executor
(
fluid
.
CPUPlace
())
exe
.
run
(
fluid
.
default_startup_program
())
avg_loss_np
=
[]
for
i
in
xrange
(
100
):
# train 100 mini-batch
tmp
,
=
exe
.
run
(
fetch_list
=
[
avg_loss
])
avg_loss_np
.
append
(
tmp
)
self
.
assertLess
(
avg_loss_np
[
-
1
],
avg_loss_np
[
0
])
exe
=
fluid
.
Executor
(
fluid
.
CPUPlace
())
exe
.
run
(
fluid
.
default_startup_program
())
avg_loss_np
=
[]
for
i
in
xrange
(
100
):
# train 100 mini-batch
tmp
,
=
exe
.
run
(
fetch_list
=
[
avg_loss
])
avg_loss_np
.
append
(
tmp
)
self
.
assertLess
(
avg_loss_np
[
-
1
],
avg_loss_np
[
0
])
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