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change commit id to 0.11.1
Signed-off-by: Icey <[email protected]>
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.github/workflows/format_pr_body.yaml

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@@ -36,7 +36,7 @@ jobs:
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- name: Get vLLM version
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run: |
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VLLM_COMMIT=83f478bb19489b41e9d208b47b4bb5a95ac171ac
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VLLM_COMMIT=releases/v0.11.1
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echo "VLLM_COMMIT=https://github.com/vllm-project/vllm/commit/$VLLM_COMMIT" >> $GITHUB_ENV
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- name: Checkout repository

.github/workflows/vllm_ascend_test.yaml

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@@ -42,7 +42,7 @@ jobs:
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lint:
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uses: ./.github/workflows/pre-commit.yml
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with:
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vllm: 83f478bb19489b41e9d208b47b4bb5a95ac171ac
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vllm: releases/v0.11.1
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changes:
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runs-on: ubuntu-latest
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VLLM_USE_MODELSCOPE: True
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strategy:
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matrix:
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vllm_version: [83f478bb19489b41e9d208b47b4bb5a95ac171ac, v0.11.0]
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vllm_version: [releases/v0.11.1, v0.11.0]
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steps:
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- name: Install packages
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run: |
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name: e2e-light
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strategy:
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matrix:
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vllm_version: [83f478bb19489b41e9d208b47b4bb5a95ac171ac, v0.11.0]
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vllm_version: [releases/v0.11.1, v0.11.0]
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# Note (yikun): If CI resource are limited we can split job into two chain jobs
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needs: [lint, changes]
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# only trigger e2e test after lint passed and the change is e2e related with pull request.

.github/workflows/vllm_ascend_test_full.yaml

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@@ -69,7 +69,7 @@ jobs:
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name: e2e-full
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strategy:
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matrix:
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vllm_version: [83f478bb19489b41e9d208b47b4bb5a95ac171ac, v0.11.0]
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vllm_version: [releases/v0.11.1, v0.11.0]
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needs: [changes]
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if: ${{ needs.changes.outputs.e2e_tracker == 'true' }}
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uses: ./.github/workflows/_e2e_test.yaml

tests/e2e/singlecard/test_embedding_aclgraph.py

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@@ -24,10 +24,10 @@
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from tests.e2e.utils import check_embeddings_close
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os.environ["VLLM_WORKER_MULTIPROC_METHOD"] = "spawn"
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os.environ["VLLM_USE_MODELSCOPE"] = "True"
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MODELS = ["BAAI/bge-m3"]
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@pytest.mark.parametrize("model_name", MODELS)
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def test_aclgrpah_embed_models_correctness(model_name):
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queries = ['What is the capital of China?', 'Explain gravity']
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model_name,
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task="embed",
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enforce_eager=False,
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# load_format="dummy",
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) as vllm_aclgraph_runner:
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vllm_aclgraph_outputs = vllm_aclgraph_runner.encode(queries)
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with VllmRunner(
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model_name,
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task="embed",
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# load_format="dummy",
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enforce_eager=True,
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) as vllm_runner:
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vllm_outputs = vllm_runner.encode(queries)

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