ci: update lmms-eval to speed up multimodal CI (#11000)
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@@ -22,7 +22,7 @@ case "${GPU_ARCH}" in
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docker exec ci_sglang rm -rf python/pyproject.toml && mv python/pyproject_other.toml python/pyproject.toml
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docker exec ci_sglang pip install -e "python[dev_hip]" --no-deps # TODO: only for mi35x
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# For lmms_evals evaluating MMMU
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docker exec -w / ci_sglang git clone --branch v0.3.3 --depth 1 https://github.com/EvolvingLMMs-Lab/lmms-eval.git
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docker exec -w / ci_sglang git clone --branch v0.4.1 --depth 1 https://github.com/EvolvingLMMs-Lab/lmms-eval.git
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docker exec -w /lmms-eval ci_sglang pip install -e . --no-deps # TODO: only for mi35x
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;;
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mi30x|mi300|mi325)
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@@ -30,7 +30,7 @@ case "${GPU_ARCH}" in
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docker exec ci_sglang rm -rf python/pyproject.toml && mv python/pyproject_other.toml python/pyproject.toml
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docker exec ci_sglang pip install -e "python[dev_hip]"
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# For lmms_evals evaluating MMMU
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docker exec -w / ci_sglang git clone --branch v0.3.3 --depth 1 https://github.com/EvolvingLMMs-Lab/lmms-eval.git
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docker exec -w / ci_sglang git clone --branch v0.4.1 --depth 1 https://github.com/EvolvingLMMs-Lab/lmms-eval.git
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docker exec -w /lmms-eval ci_sglang pip install -e .
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;;
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*)
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@@ -66,7 +66,7 @@ $PIP_CMD install mooncake-transfer-engine==0.3.6.post1 nvidia-cuda-nvrtc-cu12 py
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if [ "$IS_BLACKWELL" != "1" ]; then
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# For lmms_evals evaluating MMMU
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git clone --branch v0.3.3 --depth 1 https://github.com/EvolvingLMMs-Lab/lmms-eval.git
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git clone --branch v0.4.1 --depth 1 https://github.com/EvolvingLMMs-Lab/lmms-eval.git
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$PIP_CMD install -e lmms-eval/ $PIP_INSTALL_SUFFIX
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# Install xformers
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@@ -81,7 +81,7 @@ class TestVLMModels(CustomTestCase):
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model = "openai_compatible"
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tp = 1
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tasks = "mmmu_val"
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batch_size = 2
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batch_size = 32
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log_suffix = "openai_compatible"
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os.makedirs(output_path, exist_ok=True)
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@@ -179,7 +179,15 @@ class TestVLMModels(CustomTestCase):
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self.run_mmmu_eval(model.model, output_path)
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# Get the result file
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result_file_path = glob.glob(f"{output_path}/*.json")[0]
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# Search recursively for JSON result files (lmms-eval v0.4.1+ creates subdirectories)
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result_files = glob.glob(f"{output_path}/**/*.json", recursive=True)
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if not result_files:
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result_files = glob.glob(f"{output_path}/*.json")
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if not result_files:
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raise FileNotFoundError(f"No JSON result files found in {output_path}")
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result_file_path = result_files[0]
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with open(result_file_path, "r") as f:
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result = json.load(f)
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