[Doc] Add release note (#59)

Add release note template and init the first release note content

Signed-off-by: wangxiyuan <wangxiyuan1007@gmail.com>
Co-authored-by: Yikun Jiang <yikunkero@gmail.com>

docs/source/conf.py

@@ -77,6 +77,7 @@ exclude_patterns = [
     '.DS_Store',
     '.venv',
     'README.md',
+    'user_guide/release.template.md',
     # TODO(yikun): Remove this after zh supported
     '**/*.zh.md'
 ]

docs/source/index.md

@@ -40,10 +40,11 @@ tutorials
 
 % What does vLLM Ascend Plugin support?
 :::{toctree}
-:caption: Features
+:caption: User Guide
 :maxdepth: 1
-features/suppoted_features
-features/supported_models
+user_guide/suppoted_features
+user_guide/supported_models
+user_guide/release_notes
 :::
 
 % How to contribute to the vLLM project

docs/source/installation.md

@@ -5,7 +5,7 @@ This document describes how to install vllm-ascend manually.
 ## Requirements
 
 - OS: Linux
-- Python: 3.10 or higher
+- Python: 3.9 or higher
 - A hardware with Ascend NPU. It's usually the Atlas 800 A2 series.
 - Software:
 
@@ -15,11 +15,15 @@ This document describes how to install vllm-ascend manually.
     | torch-npu    | >= 2.5.1rc1       | Required for vllm-ascend |
     | torch        | >= 2.5.1          | Required for torch-npu and vllm |
 
+You have 2 way to install:
+- **Using pip**: first prepare env manually or via CANN image, then install `vllm-ascend` using pip.
+- **Using docker**: use the `vllm-ascend` pre-built docker image directly.
+
 ## Configure a new environment
 
-Before installing, you need to make sure firmware/driver and CANN is installed correctly.
+Before installing, you need to make sure firmware/driver and CANN are installed correctly, refer to [link](https://ascend.github.io/docs/sources/ascend/quick_install.html) for more details.
 
-### Install firmwares and drivers
+### Configure hardware environment
 
 To verify that the Ascend NPU firmware and driver were correctly installed, run:
 
@@ -29,16 +33,16 @@ npu-smi info
 
 Refer to [Ascend Environment Setup Guide](https://ascend.github.io/docs/sources/ascend/quick_install.html) for more details.
 
-### Install CANN
+### Configure software environment
 
 :::::{tab-set}
 :sync-group: install
 
-::::{tab-item} Using pip
+::::{tab-item} Before using pip
 :selected:
 :sync: pip
 
-The easiest way to prepare your CANN environment is using container directly:
+The easiest way to prepare your software environment is using CANN image directly:
 
 ```bash
 # Update DEVICE according to your device (/dev/davinci[0-7])
@@ -59,6 +63,7 @@ docker run --rm \
 ```
 
 You can also install CANN manually:
+> NOTE: This guide takes aarc64 as an example. If you run on x86, you need to replace `aarch64` with `x86_64` for the package name shown below.
 
 ```bash
 # Create a virtual environment
@@ -66,20 +71,30 @@ python -m venv vllm-ascend-env
 source vllm-ascend-env/bin/activate
 
 # Install required python packages.
-pip3 install -i https://pypi.tuna.tsinghua.edu.cn/simple attrs numpy==1.24.0 decorator sympy cffi pyyaml pathlib2 psutil protobuf scipy requests absl-py wheel typing_extensions
+pip3 install -i https://pypi.tuna.tsinghua.edu.cn/simple attrs numpy<2.0.0 decorator sympy cffi pyyaml pathlib2 psutil protobuf scipy requests absl-py wheel typing_extensions
 
 # Download and install the CANN package.
 wget https://ascend-repo.obs.cn-east-2.myhuaweicloud.com/CANN/CANN%208.0.0/Ascend-cann-toolkit_8.0.0_linux-aarch64.run
-sh Ascend-cann-toolkit_8.0.0_linux-aarch64.run --full
+chmod +x ./Ascend-cann-toolkit_8.0.0_linux-aarch64.run
+./Ascend-cann-toolkit_8.0.0_linux-aarch64.run --full
+
 wget https://ascend-repo.obs.cn-east-2.myhuaweicloud.com/CANN/CANN%208.0.0/Ascend-cann-kernels-910b_8.0.0_linux-aarch64.run
-sh Ascend-cann-kernels-910b_8.0.0_linux-aarch64.run --full
+chmod +x ./Ascend-cann-kernels-910b_8.0.0_linux-aarch64.run
+./Ascend-cann-kernels-910b_8.0.0_linux-aarch64.run --install
+
+wget https://ascend-repo.obs.cn-east-2.myhuaweicloud.com/CANN/CANN%208.0.0/Ascend-cann-nnal_8.0.0_linux-aarch64.run
+chmod +x./Ascend-cann-nnal_8.0.0_linux-aarch64.run
+./Ascend-cann-nnal_8.0.0_linux-aarch64.run --install
+
+source /usr/local/Ascend/ascend-toolkit/set_env.sh
+source /usr/local/Ascend/nnal/set_env.sh
 ```
 
 ::::
 
-::::{tab-item} Using Docker
+::::{tab-item} Before using docker
 :sync: docker
-No more extra step if you are using `vllm-ascend` image.
+No more extra step if you are using `vllm-ascend` prebuilt docker image.
 ::::
 :::::
 
@@ -120,8 +135,6 @@ pip install -e . -f https://download.pytorch.org/whl/torch/
 You can just pull the **prebuilt image** and run it with bash.
 
 ```bash
-
-
 # Update DEVICE according to your device (/dev/davinci[0-7])
 DEVICE=/dev/davinci7
 # Update the vllm-ascend image
@@ -172,7 +185,7 @@ prompts = [
 # Create a sampling params object.
 sampling_params = SamplingParams(max_tokens=100, temperature=0.0)
 # Create an LLM.
-llm = LLM(model="facebook/opt-125m")
+llm = LLM(model="Qwen/Qwen2.5-0.5B-Instruct")
 
 # Generate texts from the prompts.
 outputs = llm.generate(prompts, sampling_params)
@@ -188,3 +201,29 @@ Then run:
 # export VLLM_USE_MODELSCOPE=true to speed up download if huggingface is not reachable.
 python example.py
 ```
+
+The output will be like:
+
+```bash
+INFO 02-18 02:33:37 __init__.py:28] Available plugins for group vllm.platform_plugins:
+INFO 02-18 02:33:37 __init__.py:30] name=ascend, value=vllm_ascend:register
+INFO 02-18 02:33:37 __init__.py:32] all available plugins for group vllm.platform_plugins will be loaded.
+INFO 02-18 02:33:37 __init__.py:34] set environment variable VLLM_PLUGINS to control which plugins to load.
+INFO 02-18 02:33:37 __init__.py:42] plugin ascend loaded.
+INFO 02-18 02:33:37 __init__.py:174] Platform plugin ascend is activated
+INFO 02-18 02:33:50 config.py:526] This model supports multiple tasks: {'reward', 'embed', 'generate', 'score', 'classify'}. Defaulting to 'generate'.
+INFO 02-18 02:33:50 llm_engine.py:232] Initializing a V0 LLM engine (v0.7.1) with config: model='Qwen/Qwen2.5-0.5B-Instruct', speculative_config=None, tokenizer='./opt-125m', skip_tokenizer_init=False, tokenizer_mode=auto, revision=None, override_neuron_config=None, tokenizer_revision=None, trust_remote_code=False, dtype=torch.float16, max_seq_len=2048, download_dir=None, load_format=auto, tensor_parallel_size=1, pipeline_parallel_size=1, disable_custom_all_reduce=False, quantization=None, enforce_eager=False, kv_cache_dtype=auto,  device_config=npu, decoding_config=DecodingConfig(guided_decoding_backend='xgrammar'), observability_config=ObservabilityConfig(otlp_traces_endpoint=None, collect_model_forward_time=False, collect_model_execute_time=False), seed=0, served_model_name=./opt-125m, num_scheduler_steps=1, multi_step_stream_outputs=True, enable_prefix_caching=False, chunked_prefill_enabled=False, use_async_output_proc=True, disable_mm_preprocessor_cache=False, mm_processor_kwargs=None, pooler_config=None, compilation_config={"splitting_ops":[],"compile_sizes":[],"cudagraph_capture_sizes":[256,248,240,232,224,216,208,200,192,184,176,168,160,152,144,136,128,120,112,104,96,88,80,72,64,56,48,40,32,24,16,8,4,2,1],"max_capture_size":256}, use_cached_outputs=False,
+INFO 02-18 02:33:52 importing.py:14] Triton not installed or not compatible; certain GPU-related functions will not be available.
+Loading pt checkpoint shards:   0% Completed | 0/1 [00:00<?, ?it/s]
+Loading pt checkpoint shards: 100% Completed | 1/1 [00:00<00:00,  4.30it/s]
+Loading pt checkpoint shards: 100% Completed | 1/1 [00:00<00:00,  4.29it/s]
+
+INFO 02-18 02:33:59 executor_base.py:108] # CPU blocks: 98559, # CPU blocks: 7281
+INFO 02-18 02:33:59 executor_base.py:113] Maximum concurrency for 2048 tokens per request: 769.99x
+INFO 02-18 02:33:59 llm_engine.py:429] init engine (profile, create kv cache, warmup model) took 1.52 seconds
+Processed prompts: 100%|██████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 4/4 [00:00<00:00,  4.92it/s, est. speed input: 31.99 toks/s, output: 78.73 toks/s]
+Prompt: 'Hello, my name is', Generated text: ' John, I am the daughter of Bill and Jocelyn, I am married'
+Prompt: 'The president of the United States is', Generated text: " States President. I don't like him.\nThis is my favorite comment so"
+Prompt: 'The capital of France is', Generated text: " Texas and everyone I've spoken to in the city knows the state's name,"
+Prompt: 'The future of AI is', Generated text: ' people trying to turn a good computer into a machine, not a computer being human'
+```

docs/source/user_guide/release.template.md

@@ -0,0 +1,13 @@
+## {version}
+### Highlights
+- {feature}
+### Bug fixes
+- {bug}
+### Other changes
+- {change}
+### Known issues
+- {issue}
+### Upgrade Notes
+- {upgrade}
+### Deprecation Notes
+- {deprecation}

docs/source/user_guide/release_notes.md

@@ -0,0 +1,20 @@
+# Release note
+
+## v0.7.1.rc1
+
+We are excited to announce the release candidate of v0.7.1 for vllm-ascend. vllm-ascend is a community maintained hardware plugin for running vLLM on the Ascend NPU. With this release, users can now enjoy the latest features and improvements of vLLM on the Ascend NPU.
+
+Note that this is a release candidate, and there may be some bugs or issues. We appreciate your feedback and suggestions [here](https://github.com/vllm-project/vllm-ascend/issues/19)
+
+### Highlights
+
+- The first release which official supports the Ascend NPU on vLLM originally. Please follow the [official doc](https://vllm-ascend.readthedocs.io/en/latest/) to start the journey.
+
+### Other changes
+
+- Added the Ascend quantization config option, the implementation will comming soon.
+
+### Known issues
+
+- This release relies on an unreleased torch_npu version. Please [install](https://vllm-ascend.readthedocs.io/en/latest/installation.html) it manually.
+- There are logs like `No platform deteced, vLLM is running on UnspecifiedPlatform` or `Failed to import from vllm._C with ModuleNotFoundError("No module named 'vllm._C'")` shown when runing vllm-ascend. It actually doesn't affect any functionality and performance. You can just ignore it. And it has been fixed in this [PR](https://github.com/vllm-project/vllm/pull/12432) which will be included in v0.7.3 soon.