[1/2/N] Enable pymarkdown and python __init__ for lint system (#2011)

### What this PR does / why we need it?
1. Enable pymarkdown check
2. Enable python `__init__.py` check for vllm and vllm-ascend
3. Make clean code

### How was this patch tested?


- vLLM version: v0.9.2
- vLLM main:
29c6fbe58c

---------

Signed-off-by: wangli <wangli858794774@gmail.com>

docs/source/developer_guide/evaluation/accuracy_report/index.md

@@ -3,4 +3,4 @@
 :::{toctree}
 :caption: Accuracy Report
 :maxdepth: 1
-:::
+:::

docs/source/developer_guide/evaluation/using_evalscope.md

@@ -65,6 +65,7 @@ pip install gradio plotly evalscope
 ## 3. Run gsm8k accuracy test using EvalScope
 
 You can `evalscope eval` run gsm8k accuracy test:
+
 ```
 evalscope eval \
  --model Qwen/Qwen2.5-7B-Instruct \
@@ -98,6 +99,7 @@ pip install evalscope[perf] -U
 ### Basic usage
 
 You can use `evalscope perf` run perf test:
+
 ```
 evalscope perf \
     --url "http://localhost:8000/v1/chat/completions" \
@@ -111,7 +113,7 @@ evalscope perf \
 
 ### Output results
 
-After 1-2 mins, the output is as shown below: 
+After 1-2 mins, the output is as shown below:
 
 ```shell
 Benchmarking summary:

docs/source/developer_guide/evaluation/using_lm_eval.md

@@ -1,7 +1,7 @@
 # Using lm-eval
 This document will guide you have a accuracy testing using [lm-eval](https://github.com/EleutherAI/lm-evaluation-harness).
 
-##  1. Run docker container
+## 1. Run docker container
 
 You can run docker container on a single NPU:
 
@@ -36,6 +36,7 @@ Install lm-eval in the container.
 ```bash
 pip install lm-eval
 ```
+
 Run the following command:
 
 ```

docs/source/developer_guide/evaluation/using_opencompass.md

@@ -1,4 +1,4 @@
-# Using OpenCompass 
+# Using OpenCompass
 This document will guide you have a accuracy testing using [OpenCompass](https://github.com/open-compass/opencompass).
 
 ## 1. Online Serving
@@ -29,7 +29,9 @@ docker run --rm \
 -it $IMAGE \
 vllm serve Qwen/Qwen2.5-7B-Instruct --max_model_len 26240
 ```
+
 If your service start successfully, you can see the info shown below:
+
 ```
 INFO:     Started server process [6873]
 INFO:     Waiting for application startup.
@@ -37,6 +39,7 @@ INFO:     Application startup complete.
 ```
 
 Once your server is started, you can query the model with input prompts in new terminal:
+
 ```
 curl http://localhost:8000/v1/completions \
     -H "Content-Type: application/json" \