### What this PR does / why we need it?
This PR introduces a new model loader called Netloader, which leverages
high-bandwidth P2P direct transfer between NPU cards to achieve weight
loading. Netloader is implemented as a plugin through the newly added
'register_model_loader' function in vLLM 0.10. It facilitates the
process of weight loading by sending weights from a pre-loaded model
(server) to an empty model of a newly started instance (client). The
server operates concurrently with normal inference tasks through
sub-threads and the 'stateless_init_torch_distributed_process_group' in
vLLM. The client initiates a transfer request after verifying that the
model and partitioning method are the same as the server's, and uses
HCCL's collective communication (send/recv) to load the weights in the
order they are stored in the model.
Application Scenarios:
1. Significantly Reduces Inference Instance Startup Time By reusing the
weights of already loaded instances and performing high-speed transfers
directly between computing cards, this method reduces model loading
latency compared to traditional remote/local pull methods.
2. Reduces Network and Storage Pressure Avoids the need to repeatedly
download weight files from remote repositories, reducing the impact on
centralized storage and network traffic, thereby enhancing overall
system stability and service quality.
3. Improves Resource Utilization and Reduces Costs Accelerating the
loading process reduces reliance on redundant computing pools, allowing
computing resources to be elastically scaled and reclaimed as needed.
4. Enhances Business Continuity and High Availability In fault recovery
scenarios, new instances can quickly take over existing services,
avoiding prolonged business interruptions and improving the system's
high availability and user experience.
### Does this PR introduce _any_ user-facing change?
Netloader utilizes the existing --load-format=netloader and
--model-loader-extra-config to be activated. The
model-loader-extra-config needs to be input as a JSON string (as it is
now)
Afterwards, you can check whether the outputs for the same sentence are
consistent when the temperature is set to 0.
Signed-off-by: destinysky <kangrui10@126.com>
- vLLM version: v0.11.0rc3
- vLLM main: https://github.com/vllm-project/vllm/commit/v0.11.0
---------
Signed-off-by: destinysky <kangrui10@126.com>
### What this PR does / why we need it?
Adapt deepseek-v3.2 to vllm 0.11.0, removing the useless patch.
The final goal is to remove all the patches and align the code arch to
vllm, thus we need to do the following work in next prs.
TODO:
- [x] remove patch on attention spec
- [ ] refactor the kvcache creation logic
### Does this PR introduce _any_ user-facing change?
N/A
### How was this patch tested?
1. CI passed with existing test.
2. Test pass with deepseek-v3.2-exp
- vLLM version: v0.11.0rc3
- vLLM main: https://github.com/vllm-project/vllm/commit/v0.11.0
Signed-off-by: MengqingCao <cmq0113@163.com>
### What this PR does / why we need it?
Register the connector in the plugin
### Does this PR introduce _any_ user-facing change?
### How was this patch tested?
- vLLM version: v0.11.0rc3
- vLLM main: https://github.com/vllm-project/vllm/commit/v0.11.0
---------
Signed-off-by: fems14 <1804143737@qq.com>
make sure pytorch infer_schema check is patched before some case which
using fused moe ops:
1. model register
2. quantization loading
3. fused moe ut
Signed-off-by: wangxiyuan <wangxiyuan1007@gmail.com>
### What this PR does / why we need it?
- Revert "Re-patch TritonPlaceholder on main to make CI happy (#753)"
because upstream main CI already merged:
https://github.com/vllm-project/vllm/pull/17446
- Keep 0.8.5.post1 compatible
### Does this PR introduce _any_ user-facing change?
No
### How was this patch tested?
CI passed
---------
Signed-off-by: Yikun Jiang <yikunkero@gmail.com>
### What this PR does / why we need it?
This PR adds sleep mode feature for vllm-ascend, when sleeps, we do
mainly two things:
- offload model weights
- discard kv cache
RLHF tools(such as https://github.com/volcengine/verl and
https://github.com/OpenRLHF/OpenRLHF) have a strong need of sleep mode
to accelerate the training process.
This PR may solve #375 and #320 .
### Does this PR introduce _any_ user-facing change?
No existing user interfaces changed.
Users will have two new methods(`sleep()` and `wake_up()`) to use.
### How was this patch tested?
This PR is tested with Qwen/Qwen2.5-0.5B-Instruct.
At first, we have free NPU memory M1.
After `llm = LLM("Qwen/Qwen2.5-0.5B-Instruct", enable_sleep_mode=True)`
executed, we have free NPU memory M2. M2 < M1.
Then we call `llm.sleep(level=1)`, we have free NPU memory M3.
We have M3 > M2, M3 is very close to M1.
Plus, we have the same output tokens before sleep and after wake up,
with the config of `SamplingParams(temperature=0, max_tokens=10)` and
with the same input tokens of course.
This PR is utilizing the CMake procedure of #371 , thanks a lot.
Signed-off-by: Shuqiao Li <celestialli@outlook.com>
This PR added patch module for vllm
1. platform patch: the patch will be registered when load the platform
2. worker patch: the patch will be registered when worker is started.
The detail is:
1. patch_common: patch for main and 0.8.4 version
4. patch_main: patch for main verison
5. patch_0_8_4: patch for 0.8.4 version
### What this PR does / why we need it?
vLLM Ascend plugin (vllm-ascend) is a backend plugin for running vLLM on
the Ascend NPU.
This plugin is the recommended approach for supporting the Ascend
backend within the vLLM community. It adheres to the principles outlined
in the [RFC]: Hardware pluggable, providing a hardware-pluggable
interface that decouples the integration of the Ascend NPU with vLLM.
This patch also include changes to make CI work and use cache speed up
e2e test, including:
1. Change push (post merge ci) and pull_request (pr ci) trigger branch
to main
2. Make mypy work by ignore base_communicator and clear unused deps
3. Several improvements for vllm_ascend_test:
- use cache (pip, ms, hf) speed up e2e test (25mins --> 5mins)
- switch `git clone` command to `action/checkout` to speedup checkout
and
- Enable sv for pytest for better info dump
- Remove network host to resole `docker: conflicting ontions: cannot
attach both user-defined and non-user-definednetwork-modes`, which is a
problem on docker 1.45 but not on 1.39.
4. Adapt MLA decode optimizations:
cabaf4eff3
### Does this PR introduce _any_ user-facing change?
Yes, init the PR.
### How was this patch tested?
- This is the first PR to make ascend NPU work on vLLM. All code is
tested on ascend with vLLM V0 Engine.
- CI passed
---------
Signed-off-by: wangxiyuan <wangxiyuan1007@gmail.com>
Signed-off-by: Yikun Jiang <yikunkero@gmail.com>
Co-authored-by: wangxiyuan <wangxiyuan1007@gmail.com>
Co-authored-by: MengqingCao <cmq0113@163.com>
Co-authored-by: wangshuai09 <391746016@qq.com>
Co-authored-by: Shanshan Shen <467638484@qq.com>
Co-authored-by: wangli <wangli858794774@gmail.com>
