EngineX/xc-llm-ascend
3
0
Fork 0
Code Issues Pull Requests Projects Releases Wiki Activity

[Doc] Add release note (#59)

Browse Source 
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>
This commit is contained in:
wangxiyuan
2025-02-18 11:20:06 +08:00
committed by GitHub
parent 7cc024a2d3
commit 7606977739
7 changed files with 91 additions and 17 deletions
Download Patch File Download Diff File Expand all files Collapse all files

67
docs/source/installation.md
View File

@@ -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'
```