Fix RoPE failures in Transformers nightly (#29700)

Signed-off-by: Harry Mellor <19981378+hmellor@users.noreply.github.com>

Author: hmellor

vllm/transformers_utils/config.py

@@ -300,25 +300,10 @@ def set_default_rope_theta(config: PretrainedConfig, default_theta: float) -> No
 
 def patch_rope_parameters(config: PretrainedConfig) -> None:
     """Provide backwards compatibility for RoPE."""
-    # Patch rope_parameters differently based on Transformers version
-    if Version(version("transformers")) >= Version("5.0.0.dev0"):
-        from transformers.modeling_rope_utils import (
-            rope_config_validation,
-            standardize_rope_params,
-        )
-
-        # When Transformers v5 is installed, legacy rope_theta may be present
-        # when using custom code models written for Transformers v4
-        if (rope_theta := getattr(config, "rope_theta", None)) is not None:
-            standardize_rope_params(config, rope_theta=rope_theta)
-            rope_config_validation(config)
-            # Delete rope_theta to avoid confusion in downstream code
-            del config.rope_theta
-    else:
-        # When Transformers v4 is installed, legacy rope_scaling may be present
+    if Version(version("transformers")) < Version("5.0.0.dev0"):
+        # Transformers v4 installed, legacy config fields may be present
         if (rope_scaling := getattr(config, "rope_scaling", None)) is not None:
             config.rope_parameters = rope_scaling
-        # When Transformers v4 is installed, legacy rope_theta may be present
         if (rope_theta := getattr(config, "rope_theta", None)) is not None:
             if not hasattr(config, "rope_parameters"):
                 config.rope_parameters = {"rope_type": "default"}

vllm/transformers_utils/configs/qwen3_next.py

@@ -17,7 +17,6 @@
 """Qwen3-Next model configuration"""
 
 from transformers.configuration_utils import PretrainedConfig, layer_type_validation
-from transformers.modeling_rope_utils import rope_config_validation
 from transformers.utils import logging
 
 logger = logging.get_logger(__name__)
@@ -245,7 +244,6 @@ def __init__(
         self.attention_bias = attention_bias
         self.attention_dropout = attention_dropout
         self.head_dim = head_dim
-        rope_config_validation(self)
 
         self.layer_types = layer_types
         if self.layer_types is None: