SILONG ZENG
e56dba9b0d
[CI]cleanup e2e test ( #4800 )
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### What this PR does / why we need it?
This PR refactors the E2E multicard test suite to improve test case
identification and maintainability. Specifically, it renames various
test functions to be more descriptive (explicitly indicating model
families like Qwen/DeepSeek and parallelism strategies like DP/TP/PP/EP)
and cleans up outdated or redundant test configurations in the offline
distributed inference tests.
**Key Changes:**
1. Test Function Renaming (Standardization): Renamed multiple test
functions across **`tests/e2e/multicard/`** to include clear
suffixes/prefixes regarding the model and parallel strategy. This helps
differentiate test cases in CI logs and prevents naming collisions.
**`test_aclgraph_capture_replay.py`:**
- `test_aclgraph_capture_replay_dp2` ->
`test_aclgraph_capture_replay_metrics_dp2`
**`test_data_parallel.py`:**
- `test_data_parallel_inference` -> `test_qwen_inference_dp2`
**`test_data_parallel_tp2.py`:**
- `test_data_parallel_inference` -> `test_qwen_inference_dp2_tp2`
**`test_expert_parallel.py`:**
- `test_e2e_ep_correctness` -> `test_deepseek_correctness_ep`
**`test_external_launcher.py`:**
- `test_external_launcher` -> `test_qwen_external_launcher`
- `test_moe_external_launcher` -> `test_qwen_moe_external_launcher_ep`
- `test_external_launcher_and_sleepmode` ->
`test_qwen_external_launcher_with_sleepmode`
- `test_external_launcher_and_sleepmode_level2` ->
`test_qwen_external_launcher_with_sleepmode_level2`
- `test_mm_allreduce` ->
`test_qwen_external_launcher_with_matmul_allreduce`
**`test_full_graph_mode.py`:**
- `test_models_distributed_Qwen3_MOE_TP2_WITH_FULL_DECODE_ONLY` ->
`test_qwen_moe_with_full_decode_only`
- `test_models_distributed_Qwen3_MOE_TP2_WITH_FULL` ->
`test_qwen_moe_with_full`
**`test_fused_moe_allgather_ep.py`:**
- `test_generate_with_allgather `->
`test_deepseek_moe_fused_allgather_ep`
- `test_generate_with_alltoall` -> `test_deepseek_moe_fused_alltoall_ep`
**`test_offline_weight_load.py`:**
- `test_offline_weight_load_and_sleepmode` ->
`test_qwen_offline_weight_load_and_sleepmode`
**`test_pipeline_parallel.py`:**
- `test_models` -> `test_models_pp2`
2. Distributed Inference Cleanup
(**`test_offline_inference_distributed.py`**):
**model list changes:**
```
QWEN_DENSE_MODELS = [
- "vllm-ascend/Qwen3-8B-W8A8", "vllm-ascend/Qwen2.5-0.5B-Instruct-W8A8"
+ "vllm-ascend/Qwen3-8B-W8A8",
]
```
```
- QWEN_W4A8_OLD_VERSION_MODELS = [
- "vllm-ascend/Qwen3-8B-W4A8",
- ]
- QWEN_W4A8_NEW_VERSION_MODELS = [
- "vllm-ascend/DeepSeek-V3-W4A8-Pruing",
- "vllm-ascend/DeepSeek-V3.1-W4A8-puring",
- ]
+ DEEPSEEK_W4A8_MODELS = [
+ "vllm-ascend/DeepSeek-V3.1-W4A8-puring",
+ ]
```
**Test Function Changes:**
- removed `test_models_distributed_QwQ`
- removed `test_models_distributed_Qwen3_W8A8`
- removed `test_models_distributed_Qwen3_W4A8DYNAMIC_old_version`
- `test_models_distributed_Qwen3_W4A8DYNAMIC_new_version` ->
`test_models_distributed_Qwen3_W4A8DYNAMIC`
- vLLM version: v0.12.0
- vLLM main:
ad32e3e19c2609716663@qq.com >
2025-12-11 20:35:32 +08:00
lhp-deep
b230e7e987
[MOE]move weight transpose to wakeup for RL secnarios ( #4626 )
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### What this PR does / why we need it?
In reinforcement learning scenarios, the current inference applies a
transpose operation to the weights. For a cleaner architecture, the
weight transpose module was moved to wakeup.
### Does this PR introduce _any_ user-facing change?
### How was this patch tested?
- vLLM version: v0.12.0
- vLLM main:
ad32e3e19cliuhaopeng1@huawei.com >
Co-authored-by: weijinqian0 <1184188277@qq.com >
2025-12-08 20:34:52 +08:00
