未验证 提交 330eb6a9 编写于 作者: J Jeff Wang 提交者: GitHub

Display documentations of demos on the Docs. (#300)

* Display documentations of demos on the Docs.

* Rename the title from `demos` to `Examples`.
上级 72e291f2
示例
=====
VisualDL 支持 Python 和 C++ 基于 DL 框架,
下面是不同平台的一些示例。
.. toctree::
:maxdepth: 1
keras/TUTORIAL_CN.md
mxnet/TUTORIAL_CN.md
pytorch/TUTORIAL_CN.md
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Examples
========
VisualDL supports Python and C++ based DL frameworks,
here are some examples for different platforms.
.. toctree::
:maxdepth: 1
keras/TUTORIAL_EN.md
mxnet/TUTORIAL_EN.md
pytorch/TUTORIAL_EN.md
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...@@ -92,4 +92,4 @@ class LossHistory(keras.callbacks.Callback): ...@@ -92,4 +92,4 @@ class LossHistory(keras.callbacks.Callback):
完整的演示程序可以在[这里](./keras_mnist_demo.py)下载。 完整的演示程序可以在[这里](https://github.com/PaddlePaddle/VisualDL/blob/develop/demo/keras/keras_mnist_demo.py)下载。
...@@ -87,4 +87,4 @@ The histograms of the training parameters is as follows: ...@@ -87,4 +87,4 @@ The histograms of the training parameters is as follows:
<img width="70%" src="https://github.com/daming-lu/large_files/blob/master/keras_demo_figs/keras_histogram.png?raw=true" /> <img width="70%" src="https://github.com/daming-lu/large_files/blob/master/keras_demo_figs/keras_histogram.png?raw=true" />
</p> </p>
The full demonstration code can be downloaded in [here](./keras_mnist_demo.py). The full demonstration code can be downloaded in [here](https://github.com/PaddlePaddle/VisualDL/blob/develop/demo/keras/keras_mnist_demo.py).
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...@@ -59,7 +59,7 @@ lenet_model.fit(train_iter, ...@@ -59,7 +59,7 @@ lenet_model.fit(train_iter,
这样就好了。在MXNet的训练过程中,每一个批次(batch)训练完后,都会调用我们的回调函数来对准确率进行记录。如您所料,随着训练的进行,准确率会不断上升直到95%以上。以下是两个epoch训练过后的准确率走向: 这样就好了。在MXNet的训练过程中,每一个批次(batch)训练完后,都会调用我们的回调函数来对准确率进行记录。如您所料,随着训练的进行,准确率会不断上升直到95%以上。以下是两个epoch训练过后的准确率走向:
<p align=center><img width="50%" src="./epoch2_small.png" /></p> <p align=center><img width="50%" src="https://github.com/PaddlePaddle/VisualDL/blob/develop/demo/mxnet/epoch2_small.png?raw=true" /></p>
## 用VisualDL展示模型图 ## 用VisualDL展示模型图
......
...@@ -61,7 +61,7 @@ That's all. In the training process of MXNet, our callback function is called to ...@@ -61,7 +61,7 @@ That's all. In the training process of MXNet, our callback function is called to
The rate of accuracy will continue to rise until more than 95%. The rate of accuracy will continue to rise until more than 95%.
The following is the accuracy of the two epochs: The following is the accuracy of the two epochs:
<p align=center><img width="50%" src="./epoch2_small.png" /></p> <p align=center><img width="50%" src="https://github.com/PaddlePaddle/VisualDL/blob/develop/demo/mxnet/epoch2_small.png?raw=true" /></p>
## Display the model graph with VisualDL ## Display the model graph with VisualDL
......
../demo/
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...@@ -7,4 +7,5 @@ VisualDL ...@@ -7,4 +7,5 @@ VisualDL
首页<README.cn.md> 首页<README.cn.md>
quick_start_cn.md quick_start_cn.md
contribute_code_cn.md contribute_code_cn.md
demo/demo_cn.rst
api/visualdl.rst api/visualdl.rst
\ No newline at end of file
...@@ -8,4 +8,5 @@ VisualDL ...@@ -8,4 +8,5 @@ VisualDL
quick_start_en.md quick_start_en.md
contribute_code_en.md contribute_code_en.md
how_to_dev_frontend_en.md how_to_dev_frontend_en.md
demo/demo_en.rst
api/visualdl.rst api/visualdl.rst
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