[ROCm][CI] Fix ModernBERT token classification test numerical accuracy on ROCm (#31820)
Signed-off-by: Andreas Karatzas <akaratza@amd.com>
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tests/models/language/pooling/conftest.py
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29
tests/models/language/pooling/conftest.py
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# SPDX-License-Identifier: Apache-2.0
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# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
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"""Pytest configuration for vLLM language generation tests."""
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import warnings
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import torch
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from vllm.platforms import current_platform
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def pytest_sessionstart(session):
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"""Configure ROCm-specific settings before test session starts."""
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if not current_platform.is_rocm():
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return
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# Disable Flash/MemEfficient SDP on ROCm to avoid HF Transformers
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# accuracy issues: https://github.com/vllm-project/vllm/issues/30167
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# TODO: Remove once ROCm SDP accuracy issues are resolved on HuggingFace
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torch.backends.cuda.enable_flash_sdp(False)
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torch.backends.cuda.enable_mem_efficient_sdp(False)
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torch.backends.cuda.enable_math_sdp(True)
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torch.set_float32_matmul_precision("high")
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warnings.warn(
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"ROCm: Disabled flash_sdp and mem_efficient_sdp, enabled math_sdp "
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"to avoid HuggingFace Transformers accuracy issues",
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UserWarning,
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stacklevel=1,
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)
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