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ff95924a
编写于
9月 13, 2017
作者:
Q
Qiao Longfei
提交者:
GitHub
9月 13, 2017
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差异文件
Merge pull request #392 from jacquesqiao/add-save-topo
add save topology to chapter 1
上级
e75fd183
0ab5ab2d
变更
6
隐藏空白更改
内联
并排
Showing
6 changed file
with
52 addition
and
9 deletion
+52
-9
.tools/build_docker.sh
.tools/build_docker.sh
+1
-1
01.fit_a_line/README.cn.md
01.fit_a_line/README.cn.md
+11
-1
01.fit_a_line/README.md
01.fit_a_line/README.md
+12
-1
01.fit_a_line/index.cn.html
01.fit_a_line/index.cn.html
+11
-1
01.fit_a_line/index.html
01.fit_a_line/index.html
+12
-1
01.fit_a_line/train.py
01.fit_a_line/train.py
+5
-4
未找到文件。
.tools/build_docker.sh
浏览文件 @
ff95924a
...
...
@@ -64,7 +64,7 @@ RUN pip install -U nltk \
RUN
${
update_mirror_cmd
}
apt-get update &&
\
apt-get install -y locales patch &&
\
apt-get -y install gcc curl git &&
\
apt-get -y install gcc curl git
vim
&&
\
apt-get -y clean &&
\
localedef -f UTF-8 -i en_US en_US.UTF-8 &&
\
pip install --upgrade pip &&
\
...
...
01.fit_a_line/README.cn.md
浏览文件 @
ff95924a
...
...
@@ -126,8 +126,18 @@ y_predict = paddle.layer.fc(input=x,
size
=
1
,
act
=
paddle
.
activation
.
Linear
())
y
=
paddle
.
layer
.
data
(
name
=
'y'
,
type
=
paddle
.
data_type
.
dense_vector
(
1
))
cost
=
paddle
.
layer
.
mse
_cost
(
input
=
y_predict
,
label
=
y
)
cost
=
paddle
.
layer
.
square_error
_cost
(
input
=
y_predict
,
label
=
y
)
```
### 保存网络拓扑
```
python
# Save the inference topology to protobuf.
inference_topology
=
paddle
.
topology
.
Topology
(
layers
=
y_predict
)
with
open
(
"inference_topology.pkl"
,
'wb'
)
as
f
:
inference_topology
.
serialize_for_inference
(
f
)
```
### 创建参数
```
python
...
...
01.fit_a_line/README.md
浏览文件 @
ff95924a
...
...
@@ -132,8 +132,19 @@ y_predict = paddle.layer.fc(input=x,
size
=
1
,
act
=
paddle
.
activation
.
Linear
())
y
=
paddle
.
layer
.
data
(
name
=
'y'
,
type
=
paddle
.
data_type
.
dense_vector
(
1
))
cost
=
paddle
.
layer
.
mse
_cost
(
input
=
y_predict
,
label
=
y
)
cost
=
paddle
.
layer
.
square_error
_cost
(
input
=
y_predict
,
label
=
y
)
```
### Save Topology
```
python
# Save the inference topology to protobuf.
inference_topology
=
paddle
.
topology
.
Topology
(
layers
=
y_predict
)
with
open
(
"inference_topology.pkl"
,
'wb'
)
as
f
:
inference_topology
.
serialize_for_inference
(
f
)
```
### Create Parameters
```
python
...
...
01.fit_a_line/index.cn.html
浏览文件 @
ff95924a
...
...
@@ -168,8 +168,18 @@ y_predict = paddle.layer.fc(input=x,
size=1,
act=paddle.activation.Linear())
y = paddle.layer.data(name='y', type=paddle.data_type.dense_vector(1))
cost = paddle.layer.
mse
_cost(input=y_predict, label=y)
cost = paddle.layer.
square_error
_cost(input=y_predict, label=y)
```
### 保存网络拓扑
```python
# Save the inference topology to protobuf.
inference_topology = paddle.topology.Topology(layers=y_predict)
with open("inference_topology.pkl", 'wb') as f:
inference_topology.serialize_for_inference(f)
```
### 创建参数
```python
...
...
01.fit_a_line/index.html
浏览文件 @
ff95924a
...
...
@@ -174,8 +174,19 @@ y_predict = paddle.layer.fc(input=x,
size=1,
act=paddle.activation.Linear())
y = paddle.layer.data(name='y', type=paddle.data_type.dense_vector(1))
cost = paddle.layer.
mse
_cost(input=y_predict, label=y)
cost = paddle.layer.
square_error
_cost(input=y_predict, label=y)
```
### Save Topology
```python
# Save the inference topology to protobuf.
inference_topology = paddle.topology.Topology(layers=y_predict)
with open("inference_topology.pkl", 'wb') as f:
inference_topology.serialize_for_inference(f)
```
### Create Parameters
```python
...
...
01.fit_a_line/train.py
浏览文件 @
ff95924a
...
...
@@ -12,6 +12,11 @@ def main():
y
=
paddle
.
layer
.
data
(
name
=
'y'
,
type
=
paddle
.
data_type
.
dense_vector
(
1
))
cost
=
paddle
.
layer
.
square_error_cost
(
input
=
y_predict
,
label
=
y
)
# Save the inference topology to protobuf.
inference_topology
=
paddle
.
topology
.
Topology
(
layers
=
y_predict
)
with
open
(
"inference_topology.pkl"
,
'wb'
)
as
f
:
inference_topology
.
serialize_for_inference
(
f
)
# create parameters
parameters
=
paddle
.
parameters
.
create
(
cost
)
...
...
@@ -21,10 +26,6 @@ def main():
trainer
=
paddle
.
trainer
.
SGD
(
cost
=
cost
,
parameters
=
parameters
,
update_equation
=
optimizer
)
# save model proto as file
with
open
(
"model.proto"
,
"w"
)
as
f
:
f
.
write
(
str
(
trainer
.
__topology_in_proto__
))
feeding
=
{
'x'
:
0
,
'y'
:
1
}
# event_handler to print training and testing info
...
...
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