A high-throughput and memory-efficient inference and serving engine for LLMs
Mirrored from https://github.com/tduncan-lum/Nvidia-Optimization-Stack---VLLM.git
Synced Nov 12, 01:00 UTC
Use Transformers v5 RoPE standardisation and validation (#30046)
Signed-off-by: Harry Mellor <19981378+hmellor@users.noreply.github.com>
Harry Mellor committed
Dec 4, 2025 at 14:54 UTC
5c32a06a049829c59300929627002998d1cc34ba
1 file changed
+6
-1
vllm/transformers_utils/config.py
+6
-1
@@ -304,14 +304,19 @@ def set_default_rope_theta(config: PretrainedConfig, default_theta: float) -> No
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def patch_rope_parameters(config: PretrainedConfig) -> None:
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"""Provide backwards compatibility for RoPE."""
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+ rope_theta = getattr(config, "rope_theta", None)
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if Version(version("transformers")) < Version("5.0.0.dev0"):
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# Transformers v4 installed, legacy config fields may be present
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if (rope_scaling := getattr(config, "rope_scaling", None)) is not None:
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config.rope_parameters = rope_scaling
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- if (rope_theta := getattr(config, "rope_theta", None)) is not None:
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+ if rope_theta is not None:
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if not hasattr(config, "rope_parameters"):
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config.rope_parameters = {"rope_type": "default"}
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config.rope_parameters["rope_theta"] = rope_theta
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+ elif rope_theta is not None or hasattr(config, "rope_parameters"):
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+ # Transformers v5 installed
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+ config.standardize_rope_params()
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+ config.validate_rope()
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# No RoPE parameters to patch
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if getattr(config, "rope_parameters", None) is None: