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d67b9ced
编写于
4月 24, 2018
作者:
T
tangwei12
提交者:
GitHub
4月 24, 2018
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差异文件
Merge pull request #9820 from seiriosPlus/quick_help
fix quick start for fluid #9660
上级
dd594652
6e8510fa
变更
5
隐藏空白更改
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Showing
5 changed file
with
218 addition
and
6 deletion
+218
-6
doc/fluid/getstarted/quickstart_cn.rst
doc/fluid/getstarted/quickstart_cn.rst
+45
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doc/fluid/getstarted/quickstart_cn.rst
doc/fluid/getstarted/quickstart_cn.rst
+45
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doc/fluid/getstarted/quickstart_en.rst
doc/fluid/getstarted/quickstart_en.rst
+49
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doc/fluid/getstarted/quickstart_en.rst
doc/fluid/getstarted/quickstart_en.rst
+49
-1
python/paddle/dataset/uci_housing.py
python/paddle/dataset/uci_housing.py
+30
-2
未找到文件。
doc/fluid/getstarted/quickstart_cn.rst
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../../v2/getstarted/quickstart_cn.rst
\ No newline at end of file
doc/fluid/getstarted/quickstart_cn.rst
0 → 100644
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快速开始
========
快速安装
--------
PaddlePaddle支持使用pip快速安装,目前支持CentOS 6以上, Ubuntu 14.04以及MacOS 10.12,并安装有Python2.7。
执行下面的命令完成快速安装,版本为cpu_avx_openblas:
.. code-block:: bash
pip install paddlepaddle
如果需要安装支持GPU的版本(cuda7.5_cudnn5_avx_openblas),需要执行:
.. code-block:: bash
pip install paddlepaddle-gpu
更详细的安装和编译方法参考: :ref:`install_steps` 。
快速使用
--------
创建一个 housing.py 并粘贴此Python代码:
.. code-block:: python
import paddle.dataset.uci_housing as uci_housing
import paddle.fluid as fluid
with fluid.scope_guard(fluid.core.Scope()):
# initialize executor with cpu
exe = fluid.Executor(place=fluid.CPUPlace())
# load inference model
[inference_program, feed_target_names,fetch_targets] = \
fluid.io.load_inference_model(uci_housing.fluid_model(), exe)
# run inference
result = exe.run(inference_program,
feed={feed_target_names[0]: uci_housing.predict_reader()},
fetch_list=fetch_targets)
# print predicted price is $12,273.97
print 'Predicted price: ${:,.2f}'.format(result[0][0][0] * 1000)
执行 :code:`python housing.py` 瞧! 它应该打印出预测住房数据的清单。
doc/fluid/getstarted/quickstart_en.rst
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0 → 100644
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Quick Start
============
Quick Install
-------------
You can use pip to install PaddlePaddle with a single command, supports
CentOS 6 above, Ubuntu 14.04 above or MacOS 10.12, with Python 2.7 installed.
Simply run the following command to install, the version is cpu_avx_openblas:
.. code-block:: bash
pip install paddlepaddle
If you need to install GPU version (cuda7.5_cudnn5_avx_openblas), run:
.. code-block:: bash
pip install paddlepaddle-gpu
For more details about installation and build: :ref:`install_steps` .
Quick Use
---------
Create a new file called housing.py, and paste this Python
code:
.. code-block:: python
import paddle.dataset.uci_housing as uci_housing
import paddle.fluid as fluid
with fluid.scope_guard(fluid.core.Scope()):
# initialize executor with cpu
exe = fluid.Executor(place=fluid.CPUPlace())
# load inference model
[inference_program, feed_target_names,fetch_targets] = \
fluid.io.load_inference_model(uci_housing.fluid_model(), exe)
# run inference
result = exe.run(inference_program,
feed={feed_target_names[0]: uci_housing.predict_reader()},
fetch_list=fetch_targets)
# print predicted price is $12,273.97
print 'Predicted price: ${:,.2f}'.format(result[0][0][0] * 1000)
Run :code:`python housing.py` and voila! It should print out a list of predictions
for the test housing data.
python/paddle/dataset/uci_housing.py
浏览文件 @
d67b9ced
...
...
@@ -19,7 +19,11 @@ https://archive.ics.uci.edu/ml/machine-learning-databases/housing/ and
parse training set and test set into paddle reader creators.
"""
import
os
import
numpy
as
np
import
tempfile
import
tarfile
import
os
import
paddle.dataset.common
...
...
@@ -34,8 +38,9 @@ feature_names = [
UCI_TRAIN_DATA
=
None
UCI_TEST_DATA
=
None
URL_MODEL
=
'https://github.com/PaddlePaddle/book/raw/develop/01.fit_a_line/fit_a_line.tar'
MD5_MODEL
=
'52fc3da8ef3937822fcdd87ee05c0c9b'
FLUID_URL_MODEL
=
'https://github.com/PaddlePaddle/book/raw/develop/01.fit_a_line/fluid/fit_a_line.fluid.tar'
FLUID_MD5_MODEL
=
'6e6dd637ccd5993961f68bfbde46090b'
def
feature_range
(
maximums
,
minimums
):
...
...
@@ -113,6 +118,29 @@ def test():
return
reader
def
fluid_model
():
parameter_tar
=
paddle
.
dataset
.
common
.
download
(
FLUID_URL_MODEL
,
'uci_housing'
,
FLUID_MD5_MODEL
,
'fit_a_line.fluid.tar'
)
tar
=
tarfile
.
TarFile
(
parameter_tar
,
mode
=
'r'
)
dirpath
=
tempfile
.
mkdtemp
()
tar
.
extractall
(
path
=
dirpath
)
return
dirpath
def
predict_reader
():
"""
It returns just one tuple data to do inference.
:return: one tuple data
:rtype: tuple
"""
global
UCI_TEST_DATA
load_data
(
paddle
.
dataset
.
common
.
download
(
URL
,
'uci_housing'
,
MD5
))
return
(
UCI_TEST_DATA
[
0
][:
-
1
],
)
def
fetch
():
paddle
.
dataset
.
common
.
download
(
URL
,
'uci_housing'
,
MD5
)
...
...
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