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b148f065
编写于
1月 31, 2018
作者:
Y
Yang Yu
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电子邮件补丁
差异文件
Make Fit a line a normal unittest
上级
c091dbdf
变更
1
隐藏空白更改
内联
并排
Showing
1 changed file
with
59 addition
and
29 deletion
+59
-29
python/paddle/v2/fluid/tests/book/test_fit_a_line.py
python/paddle/v2/fluid/tests/book/test_fit_a_line.py
+59
-29
未找到文件。
python/paddle/v2/fluid/tests/book/test_fit_a_line.py
浏览文件 @
b148f065
...
...
@@ -12,44 +12,74 @@
# See the License for the specific language governing permissions and
# limitations under the License.
import
numpy
as
np
import
paddle.v2
as
paddle
import
paddle.v2.fluid
as
fluid
import
contextlib
import
unittest
x
=
fluid
.
layers
.
data
(
name
=
'x'
,
shape
=
[
13
],
dtype
=
'float32'
)
y_predict
=
fluid
.
layers
.
fc
(
input
=
x
,
size
=
1
,
act
=
None
)
def
main
(
use_cuda
):
if
use_cuda
and
not
fluid
.
core
.
is_compiled_with_cuda
():
return
y
=
fluid
.
layers
.
data
(
name
=
'y'
,
shape
=
[
1
],
dtype
=
'float32'
)
x
=
fluid
.
layers
.
data
(
name
=
'x'
,
shape
=
[
13
],
dtype
=
'float32'
)
cost
=
fluid
.
layers
.
square_error_cost
(
input
=
y_predict
,
label
=
y
)
avg_cost
=
fluid
.
layers
.
mean
(
x
=
cost
)
y_predict
=
fluid
.
layers
.
fc
(
input
=
x
,
size
=
1
,
act
=
None
)
sgd_optimizer
=
fluid
.
optimizer
.
SGD
(
learning_rate
=
0.001
)
sgd_optimizer
.
minimize
(
avg_cost
)
y
=
fluid
.
layers
.
data
(
name
=
'y'
,
shape
=
[
1
],
dtype
=
'float32'
)
BATCH_SIZE
=
20
cost
=
fluid
.
layers
.
square_error_cost
(
input
=
y_predict
,
label
=
y
)
avg_cost
=
fluid
.
layers
.
mean
(
x
=
cost
)
train_reader
=
paddle
.
batch
(
paddle
.
reader
.
shuffle
(
paddle
.
dataset
.
uci_housing
.
train
(),
buf_size
=
500
),
batch_size
=
BATCH_SIZE
)
sgd_optimizer
=
fluid
.
optimizer
.
SGD
(
learning_rate
=
0.001
)
sgd_optimizer
.
minimize
(
avg_cost
)
place
=
fluid
.
CPUPlace
()
feeder
=
fluid
.
DataFeeder
(
place
=
place
,
feed_list
=
[
x
,
y
])
exe
=
fluid
.
Executor
(
place
)
BATCH_SIZE
=
20
exe
.
run
(
fluid
.
default_startup_program
())
train_reader
=
paddle
.
batch
(
paddle
.
reader
.
shuffle
(
paddle
.
dataset
.
uci_housing
.
train
(),
buf_size
=
500
),
batch_size
=
BATCH_SIZE
)
PASS_NUM
=
100
for
pass_id
in
range
(
PASS_NUM
):
fluid
.
io
.
save_persistables
(
exe
,
"./fit_a_line.model/"
)
fluid
.
io
.
load_persistables
(
exe
,
"./fit_a_line.model/"
)
for
data
in
train_reader
():
avg_loss_value
,
=
exe
.
run
(
fluid
.
default_main_program
(),
feed
=
feeder
.
feed
(
data
),
fetch_list
=
[
avg_cost
])
print
(
avg_loss_value
)
if
avg_loss_value
[
0
]
<
10.0
:
exit
(
0
)
# if avg cost less than 10.0, we think our code is good.
exit
(
1
)
place
=
fluid
.
CUDAPlace
(
0
)
if
use_cuda
else
fluid
.
CPUPlace
()
feeder
=
fluid
.
DataFeeder
(
place
=
place
,
feed_list
=
[
x
,
y
])
exe
=
fluid
.
Executor
(
place
)
exe
.
run
(
fluid
.
default_startup_program
())
PASS_NUM
=
100
for
pass_id
in
range
(
PASS_NUM
):
fluid
.
io
.
save_persistables
(
exe
,
"./fit_a_line.model/"
)
fluid
.
io
.
load_persistables
(
exe
,
"./fit_a_line.model/"
)
for
data
in
train_reader
():
avg_loss_value
,
=
exe
.
run
(
fluid
.
default_main_program
(),
feed
=
feeder
.
feed
(
data
),
fetch_list
=
[
avg_cost
])
print
(
avg_loss_value
)
if
avg_loss_value
[
0
]
<
10.0
:
return
raise
AssertionError
(
"Fit a line cost is too large, {0:2.2}"
.
format
(
avg_loss_value
[
0
]))
class
TestFitALine
(
unittest
.
TestCase
):
def
test_cpu
(
self
):
with
self
.
program_scope_guard
():
main
(
use_cuda
=
False
)
def
test_cuda
(
self
):
with
self
.
program_scope_guard
():
main
(
use_cuda
=
True
)
@
contextlib
.
contextmanager
def
program_scope_guard
(
self
):
prog
=
fluid
.
Program
()
startup_prog
=
fluid
.
Program
()
scope
=
fluid
.
core
.
Scope
()
with
fluid
.
scope_guard
(
scope
):
with
fluid
.
program_guard
(
prog
,
startup_prog
):
yield
if
__name__
==
'__main__'
:
unittest
.
main
()
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