Skip to content
体验新版
项目
组织
正在加载...
登录
切换导航
打开侧边栏
机器未来
Paddle
提交
b1f24660
P
Paddle
项目概览
机器未来
/
Paddle
与 Fork 源项目一致
Fork自
PaddlePaddle / Paddle
通知
1
Star
1
Fork
0
代码
文件
提交
分支
Tags
贡献者
分支图
Diff
Issue
1
列表
看板
标记
里程碑
合并请求
0
Wiki
0
Wiki
分析
仓库
DevOps
项目成员
Pages
P
Paddle
项目概览
项目概览
详情
发布
仓库
仓库
文件
提交
分支
标签
贡献者
分支图
比较
Issue
1
Issue
1
列表
看板
标记
里程碑
合并请求
0
合并请求
0
Pages
分析
分析
仓库分析
DevOps
Wiki
0
Wiki
成员
成员
收起侧边栏
关闭侧边栏
动态
分支图
创建新Issue
提交
Issue看板
提交
b1f24660
编写于
1月 11, 2018
作者:
X
Xi Chen
浏览文件
操作
浏览文件
下载
电子邮件补丁
差异文件
add dist demo fit_a_line
上级
5d9dcfc1
变更
1
隐藏空白更改
内联
并排
Showing
1 changed file
with
63 addition
and
0 deletion
+63
-0
python/paddle/v2/fluid/tests/book_distribute/test_dist_fit_a_line.py
...le/v2/fluid/tests/book_distribute/test_dist_fit_a_line.py
+63
-0
未找到文件。
python/paddle/v2/fluid/tests/book_distribute/test_dist_fit_a_line.py
0 → 100644
浏览文件 @
b1f24660
import
numpy
as
np
import
paddle.v2
as
paddle
import
paddle.v2.fluid
as
fluid
import
os
x
=
fluid
.
layers
.
data
(
name
=
'x'
,
shape
=
[
13
],
dtype
=
'float32'
)
y_predict
=
fluid
.
layers
.
fc
(
input
=
x
,
size
=
1
,
act
=
None
)
y
=
fluid
.
layers
.
data
(
name
=
'y'
,
shape
=
[
1
],
dtype
=
'float32'
)
cost
=
fluid
.
layers
.
square_error_cost
(
input
=
y_predict
,
label
=
y
)
avg_cost
=
fluid
.
layers
.
mean
(
x
=
cost
)
sgd_optimizer
=
fluid
.
optimizer
.
SGD
(
learning_rate
=
0.001
)
optimize_ops
,
params_grads
=
sgd_optimizer
.
minimize
(
avg_cost
)
BATCH_SIZE
=
20
train_reader
=
paddle
.
batch
(
paddle
.
reader
.
shuffle
(
paddle
.
dataset
.
uci_housing
.
train
(),
buf_size
=
500
),
batch_size
=
BATCH_SIZE
)
place
=
fluid
.
CPUPlace
()
feeder
=
fluid
.
DataFeeder
(
place
=
place
,
feed_list
=
[
x
,
y
])
exe
=
fluid
.
Executor
(
place
)
t
=
fluid
.
DistributeTranspiler
()
# all parameter server endpoints list for spliting parameters
pserver_endpoints
=
os
.
getenv
(
"PSERVERS"
)
# server endpoint for current node
current_endpoint
=
os
.
getenv
(
"SERVER_ENDPOINT"
)
# run as trainer or parameter server
training_role
=
os
.
getenv
(
"TRAINING_ROLE"
,
"TRAINER"
)
# get the training role: trainer/pserver
t
.
transpile
(
optimize_ops
,
params_grads
,
pservers
=
pserver_endpoints
,
trainers
=
2
)
if
training_role
==
"PSERVER"
:
if
not
current_endpoint
:
print
(
"need env SERVER_ENDPOINT"
)
exit
(
1
)
pserver_prog
=
t
.
get_pserver_program
(
current_endpoint
,
optimize_ops
)
exe
.
run
(
fluid
.
default_startup_program
())
exe
.
run
(
pserver_prog
)
else
:
trainer_prog
=
t
.
get_trainer_program
()
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
(
trainer_prog
,
feed
=
feeder
.
feed
(
data
),
fetch_list
=
[
avg_cost
])
if
avg_loss_value
[
0
]
<
10.0
:
exit
(
0
)
# if avg cost less than 10.0, we think our code is good.
exit
(
1
)
编辑
预览
Markdown
is supported
0%
请重试
或
添加新附件
.
添加附件
取消
You are about to add
0
people
to the discussion. Proceed with caution.
先完成此消息的编辑!
取消
想要评论请
注册
或
登录