Use lower case visualdl as the executable. (#449)

Dockerfile.demo

@@ -5,4 +5,4 @@ WORKDIR /
 COPY ./demo/vdl_create_scratch_log vdl_create_scratch_log
 RUN python /vdl_create_scratch_log
 
-ENTRYPOINT ["visualDL", "--logdir=/scratch_log"]
\ No newline at end of file
+ENTRYPOINT ["visualdl", "--logdir=/scratch_log"]
\ No newline at end of file

README.cn.md

@@ -62,7 +62,7 @@ pip install --upgrade visualdl
 
 # 运行一个例子，vdl_create_scratch_log 将创建测试日志
 vdl_create_scratch_log
-visualDL --logdir=scratch_log --port=8080
+visualdl --logdir=scratch_log --port=8080
 
 # 访问 http://127.0.0.1:8080
 ```
@@ -104,7 +104,7 @@ pip install --upgrade visualdl
 
 # 运行一个例子，vdl_create_scratch_log 将创建测试日志
 vdl_create_scratch_log
-visualDL --logdir=scratch_log --port=8080
+visualdl --logdir=scratch_log --port=8080
 
 # 访问 http://127.0.0.1:8080
 ```
@@ -136,7 +136,7 @@ pip install --upgrade visualdl
 
 # 运行一个例子，vdl_create_scratch_log 将创建测试日志
 vdl_create_scratch_log
-visualDL --logdir=scratch_log --port=8080
+visualdl --logdir=scratch_log --port=8080
 
 # 访问 http://127.0.0.1:8080
 ```
@@ -212,7 +212,7 @@ int main() {
 当训练过程中已经产生了日志数据，就可以启动board进行实时预览可视化信息
 
 ```
-visualDL --logdir <some log dir>
+visualdl --logdir <some log dir>
 ```
 
 board 还支持一下参数来实现远程的访问：

README.md

@@ -112,7 +112,7 @@ pip install --upgrade visualdl
 
 # run a demo, vdl_create_scratch_log will create logs for testing.
 vdl_create_scratch_log
-visualDL --logdir=scratch_log --port=8080
+visualdl --logdir=scratch_log --port=8080
 
 # visit http://127.0.0.1:8080
 ```
@@ -145,7 +145,7 @@ pip install --upgrade visualdl
 
 # run a demo, vdl_create_scratch_log will create logs for testing.
 vdl_create_scratch_log
-visualDL --logdir=scratch_log --port=8080
+visualdl --logdir=scratch_log --port=8080
 
 # visit http://127.0.0.1:8080
 ```
@@ -226,7 +226,7 @@ After some logs have been generated during training, users can launch Visual DL
 
 
 ```
-visualDL --logdir <some log dir>
+visualdl --logdir <some log dir>
 ```
 
 visualDL also supports following optional parameters:

demo/mxnet/TUTORIAL_CN.md

@@ -69,7 +69,7 @@ VisualDL的一个优点是能可视化深度学习模型，帮助用户更直观
 VisualDL的使用很简单，在完成安装后只需要把模型文件（protobuf格式）用参数 -m 提供给VisualDL即可。
 
 ```bash
-visualDL --logdir=/workspace -m /workspace/super_resolution_mnist.onnx --port=8888
+visualdl --logdir=/workspace -m /workspace/super_resolution_mnist.onnx --port=8888
 ```
 
 模型图的效果如下：

demo/mxnet/TUTORIAL_EN.md

@@ -74,7 +74,7 @@ Here we use the existing model that has been transformed from MXNet to ONNX, [Su
 To display the model graph via VisualDL, pass the model file path with the parameter -m to the VisualDL
 
 ```bash
-visualDL --logdir=/workspace -m /workspace/super_resolution_mnist.onnx --port=8888
+visualdl --logdir=/workspace -m /workspace/super_resolution_mnist.onnx --port=8888
 ```
 
 The model graph is as follows:

demo/pytorch/embedding_tutorial_ch.md

@@ -121,7 +121,7 @@ embedding.add_embeddings_with_word_dict(embeddings_list, word_to_ix)
 将上述代码嵌入到您的embedding训练程序中，
 这将 embedding 和 word_dict 保存到 `./embedding_log` 文件夹中。
 
-现在我们可以用 `visualDL --logdir=./embedding_log` 执行VisualDL，
+现在我们可以用 `visualdl --logdir=./embedding_log` 执行VisualDL，
 使用浏览器导航到 `localhost:8080`，切换到 `High Dimensional` 。
 
 你可以下载教程代码 [这里](https://github.com/PaddlePaddle/VisualDL/blob/develop/demo/pytorch/pytorch_word2vec.py)。

demo/pytorch/embedding_tutorial_en.md

@@ -127,7 +127,7 @@ Insert the above code snippet into your embedding training program.
 
 This will save the embeddings and the word dictionary to the `./embedding_log` folder.
 
-We can now activate the VisualDL by running `visualDL --logdir=./embedding_log`.
+We can now activate the VisualDL by running `visualdl --logdir=./embedding_log`.
 Use your browser to navigate to `localhost:8080`, switch the tab to `High Dimensional`
 
 You can download the tutorial code [here](https://github.com/PaddlePaddle/VisualDL/blob/develop/demo/pytorch/pytorch_word2vec.py).

docs/develop/how_to_dev_backend_cn.md

@@ -32,7 +32,7 @@ VisualDL有三个功能模块.
 任何在 ```server``` 文件夹里代码的改动，都可以通过运行以下命令
 
 ```
-python visualdl/server/visualDL --logdir={LOG_DIR} --port=8080
+python visualdl/server/visualdl --logdir={LOG_DIR} --port=8080
 ```
 来重启 Flask 服务器
 
@@ -88,7 +88,7 @@ make vl_test
 - 采用轻量级 Flask 框架来搭建服务器并提供以下两种服务
   - 搭建主程序来支持前端应用
   - 提供一系列 HTTP 访问点，通过返回的 JSON 来和前端沟通
-- ```visualDL``` : 主程序入口
+- ```visualdl``` : 主程序入口
   - 定义了服务器参数
   - 给前端提供 API 和 路由匹配
 - ```lib.py``` : 调用库函数的入口

docs/develop/how_to_dev_backend_en.md

@@ -32,7 +32,7 @@ All backend and sdk logic is under visualdl sub directory
 Any code changes in ```server``` folder, simply run
 
 ```
-python visualdl/server/visualDL --logdir={LOG_DIR} --port=8080
+python visualdl/server/visualdl --logdir={LOG_DIR} --port=8080
 ```
 to restart flask server
 
@@ -87,7 +87,7 @@ make vl_test
 - Implement a server using a lightweight framework Flask, provides two services:
   - Host a main application with support of a front end web app
   - Provide a series of HTTP end points, using JSON for front end data communication
-- ```visualDL``` : main app entry point
+- ```visualdl``` : main app entry point
   - defines server arguments and config
   - provides API and router for front end
 - ```lib.py``` : delegate wrapper for function calls

docs/getting_started/installation_cn.md

@@ -9,7 +9,7 @@ pip install --upgrade visualdl
 
 # run a demo, vdl_create_scratch_log will create logs for testing.
 vdl_create_scratch_log
-visualDL --logdir=scratch_log --port=8080
+visualdl --logdir=scratch_log --port=8080
 
 # visit http://127.0.0.1:8080
 ```
@@ -51,7 +51,7 @@ pip install --upgrade visualdl
 
 # 运行一个例子，vdl_create_scratch_log 将创建测试日志
 vdl_create_scratch_log
-visualDL --logdir=scratch_log --port=8080
+visualdl --logdir=scratch_log --port=8080
 
 # 访问 http://127.0.0.1:8080
 ```
@@ -83,7 +83,7 @@ pip install --upgrade visualdl
 
 # 运行一个例子，vdl_create_scratch_log 将创建测试日志
 vdl_create_scratch_log
-visualDL --logdir=scratch_log --port=8080
+visualdl --logdir=scratch_log --port=8080
 
 # 访问 http://127.0.0.1:8080
 ```

docs/getting_started/installation_en.md

@@ -8,7 +8,7 @@ pip install --upgrade visualdl
 
 # run a demo, vdl_create_scratch_log will create logs for testing.
 vdl_create_scratch_log
-visualDL --logdir=scratch_log --port=8080
+visualdl --logdir=scratch_log --port=8080
 
 # visit http://127.0.0.1:8080
 ```
@@ -52,7 +52,7 @@ pip install --upgrade visualdl
 
 # run a demo, vdl_create_scratch_log will create logs for testing.
 vdl_create_scratch_log
-visualDL --logdir=scratch_log --port=8080
+visualdl --logdir=scratch_log --port=8080
 
 # visit http://127.0.0.1:8080
 ```
@@ -85,7 +85,7 @@ pip install --upgrade visualdl
 
 # run a demo, vdl_create_scratch_log will create logs for testing.
 vdl_create_scratch_log
-visualDL --logdir=scratch_log --port=8080
+visualdl --logdir=scratch_log --port=8080
 
 # visit http://127.0.0.1:8080
 ```

docs/getting_started/introduction_cn.md

@@ -46,7 +46,7 @@ for step in steps:
 - 启动visualdl service即可通过浏览器查看日志的可视化结果。
 
 ```shell
-visualDL --logdir ./log --port 8080
+visualdl --logdir ./log --port 8080
 ```
 ### 功能全
 1. Scalar. 支持Scalar打点数据展示，如上图所示：

docs/getting_started/introduction_en.md

@@ -48,7 +48,7 @@ for step in steps:
 - Launch Visual DL service and you can see the visualization results.
 
 ```shell
-visualDL --logdir ./log --port 8080
+visualdl --logdir ./log --port 8080
 ```
 
 ### Comprehensive Usability

docs/getting_started/quick_start_cn.md

@@ -56,7 +56,7 @@ for step in range(200):
 上述例子生成了一段随机日志，接下来可以打开board页面：
 
 ```
-visualDL --logdir ./random_log --port 8080
+visualdl --logdir ./random_log --port 8080
 ```
 
 之后用浏览器打开地址 `http://0.0.0.0:8080`，就可以看到scalar下的可视化结果
@@ -86,7 +86,7 @@ VisualDL 的 C++ SDK 与 Python 的基本一致，上面Python示例对应的C++
 VisualDL 支持开源的 [ONNX](https://github.com/onnx/onnx)模型结构的可视化，目前ONNX支持包括 `pytorch`, `Caffe2`, `Caffe`, `MxNet` 在内的多种深度学习平台的模型结构的转化。
 
 ```
-visualDL --logdir somedir --model_pb <path_to_model>
+visualdl --logdir somedir --model_pb <path_to_model>
 ```
 
 比如mnist，会得到如下graph

docs/getting_started/quick_start_en.md

@@ -62,7 +62,7 @@ for step in range(200):
 The example above randomly generated some logs. Next we can open the board page:
 
 ```
-visualDL --logdir ./random_log --port 8080
+visualdl --logdir ./random_log --port 8080
 ```
 
 Point your browser to `http://0.0.0.0:8080`, you can see the scalar as follows:
@@ -93,7 +93,7 @@ VisualDL supports the visualization for the format in [ONNX](https://github.com/
 Currently, ONNX supports format conversion among various deep learning frameworks such as `MXNet`, `PyTorch`, `Caffe2`, `Caffe`.
 
 ```
-visualDL --logdir somedir --model_pb <path_to_model>
+visualdl --logdir somedir --model_pb <path_to_model>
 ```
 
 For example, for the MNIST dataset, Graph component can render model graph as below:

scripts/start_demo_server.sh

@@ -26,4 +26,4 @@ trap finish EXIT HUP INT QUIT PIPE TERM
 cd $CURRENT_DIR
 
 # Run the visualDL with local PATH
-python ${SCRIPT_DIR}/../visualdl/server/visualDL "$@"
+python ${SCRIPT_DIR}/../visualdl/server/visualdl "$@"

scripts/start_dev_server.sh

@@ -25,4 +25,4 @@ trap finish EXIT HUP INT QUIT PIPE TERM
 cd $CURRENT_DIR
 
 #Run the visualDL with local PATH
-python ${SCRIPT_DIR}/../visualdl/server/visualDL "$@"
+python ${SCRIPT_DIR}/../visualdl/server/visualdl "$@"

setup.py

@@ -103,7 +103,7 @@ libraries = ['core.so']
 if platform == 'win32':
     libraries = ['core.pyd', 'libprotobuf.dll']
 
-scripts = ['visualdl/server/visualDL', 'demo/vdl_create_scratch_log']
+scripts = ['visualdl/server/visualdl', 'demo/vdl_create_scratch_log']
 if platform == 'win32':
     scripts.append('visualdl/server/visualDL.bat')