[Doc]: Fix doc (#219)

* add reminder for pspnet in doc

* update table format

* fix format

* rename file

* fix comment

README.md

@@ -47,7 +47,7 @@ Please refer to [get_started.md](docs/get_started.md) for installation.
 
 ## Getting Started
 
-Please read [get_started.md](docs/get_started.md) for the basic usage of MMDeploy. There are also tutorials for [how to convert a model](docs/tutorials/how_to_convert_model.md), [how to write a config](docs/tutorials/how_to_write_config.md), [how to support new models](docs/tutorials/how_to_support_new_models.md) and [how to test model](docs/tutorials/how_to_test_model.md).
+Please read [how_to_convert_model.md](docs/tutorials/how_to_convert_model.md) for the basic usage of MMDeploy. There are also tutorials on [how to write config](docs/tutorials/how_to_write_config.md), [how to support new models](docs/tutorials/how_to_support_new_models.md) and [how to measure performance of models](docs/tutorials/how_to_measure_performance_of_models.md).
 
 Please refer to [FAQ](docs/faq.md) for frequently asked questions.
 

README_zh-CN.md

@@ -47,7 +47,7 @@ MMDeploy 是一个开源深度学习模型部署工具箱，它是 [OpenMMLab](h
 
 请阅读 [如何进行模型转换](docs/tutorials/how_to_convert_model.md) 来了解基本的 MMDeploy 使用。
 
-我们还提供了诸如 [如何编写配置文件](docs/tutorials/how_to_write_config.md)， [如何添加新模型支持](docs/tutorials/how_to_support_new_models.md) 和 [如何测试模型效果](docs/tutorials/how_to_test_model.md) 等教程。
+我们还提供了诸如 [如何编写配置文件](docs/tutorials/how_to_write_config.md)， [如何添加新模型支持](docs/tutorials/how_to_support_new_models.md) 和 [如何测试模型效果](docs/tutorials/how_to_measure_performance_of_models.md) 等教程。
 
 如果遇到问题，请参考 [常见问题解答](docs/faq.md)。
 

docs/codebases/mmseg.md

@@ -8,16 +8,18 @@ Please refer to [get_started.md](https://github.com/open-mmlab/mmsegmentation/bl
 
 ### List of MMSegmentation models supported by MMDeploy
 
-|    model   | OnnxRuntime |    TensorRT   | NCNN |  PPL  | OpenVino |  model config file(example)                                                               |
-|:---------- | :---------: | :-----------: | :---:| :---: | :------: | :---------------------------------------------------------------------------------------  |
-| FCN        |      Y      |       Y       |   Y  |   Y   |    ?     | $PATH_TO_MMSEG/configs/fcn/fcn_r50-d8_512x1024_40k_cityscapes.py                          |
-| PSPNet     |      Y      |       Y       |   N  |   Y   |    ?     | $PATH_TO_MMSEG/configs/pspnet/pspnet_r50-d8_512x1024_40k_cityscapes.py                    |
-| DeepLabV3  |      Y      |       Y       |   Y  |   Y   |    ?     | $PATH_TO_MMSEG/configs/deeplabv3/deeplabv3_r50-d8_512x1024_40k_cityscapes.py              |
-| DeepLabV3+ |      Y      |       Y       |   Y  |   Y   |    ?     | $PATH_TO_MMSEG/configs/deeplabv3plus/deeplabv3plus_r50-d8_512x1024_40k_cityscapes.py      |
+| model                         | OnnxRuntime | TensorRT | NCNN | PPL | OpenVino | model config file(example)                                                         |
+|:------------------------------|:-----------:|:--------:|:----:|:---:|:--------:|:-----------------------------------------------------------------------------------|
+| FCN                           |      Y      |    Y     |  Y   |  Y  |    ?     | ${MMSEG_DIR}/configs/fcn/fcn_r50-d8_512x1024_40k_cityscapes.py                     |
+| PSPNet[*](#pspnet) |      Y      |    Y     |  N   |  Y  |    ?     | ${MMSEG_DIR}/configs/pspnet/pspnet_r50-d8_512x1024_40k_cityscapes.py               |
+| DeepLabV3                     |      Y      |    Y     |  Y   |  Y  |    ?     | ${MMSEG_DIR}/configs/deeplabv3/deeplabv3_r50-d8_512x1024_40k_cityscapes.py         |
+| DeepLabV3+                    |      Y      |    Y     |  Y   |  Y  |    ?     | ${MMSEG_DIR}/configs/deeplabv3plus/deeplabv3plus_r50-d8_512x1024_40k_cityscapes.py |
 
 ### Reminder
 
-None
+- Only `whole` inference mode is supported for all mmseg models.
+
+- <i id="pspnet">PSPNet</i> only supports static shape, better to use the deployment config file of static shape such as `configs/mmseg/segmentation_tensorrt_static-512x1024.py`. Because [nn.AdaptiveAvgPool2d](https://github.com/open-mmlab/mmsegmentation/blob/97f9670c5a4a2a3b4cfb411bcc26db16b23745f7/mmseg/models/decode_heads/psp_head.py#L38) in psp_head is not supported in most of backends dynamically.
 
 ### FAQs
 

docs/index.rst

@@ -16,7 +16,7 @@ You can switch between Chinese and English documents in the lower-left corner of
    tutorials/how_to_convert_model.md
    tutorials/how_to_write_config.md
    tutorials/how_to_evaluate_a_model.md
-   tutorials/how_to_test_model.md
+   tutorials/how_to_measure_performance_of_models.md
    tutorials/how_to_support_new_models.md
    tutorials/how_to_add_test_units_for_backend_ops.md
    tutorials/how_to_test_rewritten_models.md

docs/tutorials/how_to_measure_performance_of_models.md

@@ -1,4 +1,4 @@
-## How to test model
+# How to measure the performance of a model
 
 After we convert a PyTorch model to a backend model, we may need to test the speed of the model before using it. In MMDeploy, we provide a tool to test the speed of backend models in `tools/test.py`