Fix RoPE related failures in Transformers nightly tests (#29333)

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

vllm/model_executor/models/baichuan.py

@@ -233,7 +233,7 @@ class BaiChuanDecoderLayer(nn.Module):
             hidden_size=self.hidden_size,
             num_heads=config.num_attention_heads,
             position_embedding=position_embedding,
-            rope_parameters=config.rope_parameters,
+            rope_parameters=getattr(config, "rope_parameters", None),
             max_position_embeddings=max_position_embeddings,
             cache_config=cache_config,
             quant_config=quant_config,

vllm/model_executor/models/gpt_j.py

@@ -100,7 +100,7 @@ class GPTJAttention(nn.Module):
             self.head_size,
             rotary_dim=config.rotary_dim,
             max_position=max_position_embeddings,
-            rope_parameters=config.rope_parameters,
+            rope_parameters=getattr(config, "rope_parameters", None),
             is_neox_style=False,
         )
         self.attn = Attention(

vllm/model_executor/models/grok1.py

@@ -239,7 +239,7 @@ class Grok1DecoderLayer(nn.Module):
             num_heads=config.num_attention_heads,
             max_position=config.max_position_embeddings,
             num_kv_heads=config.num_key_value_heads,
-            rope_parameters=config.rope_parameters,
+            rope_parameters=getattr(config, "rope_parameters", None),
             cache_config=cache_config,
             quant_config=quant_config,
             prefix=f"{prefix}.attn",

vllm/model_executor/models/llama.py

@@ -262,7 +262,7 @@ class LlamaAttention(nn.Module):
             self.head_dim,
             rotary_dim=self.head_dim,
             max_position=self.max_position_embeddings,
-            rope_parameters=config.rope_parameters,
+            rope_parameters=getattr(config, "rope_parameters", None),
             is_neox_style=is_neox_style,
             partial_rotary_factor=self.partial_rotary_factor,
         )

vllm/transformers_utils/config.py

@@ -456,51 +456,55 @@ def set_default_rope_theta(config: PretrainedConfig, default_theta: float) -> No
 
 def patch_rope_parameters(config: PretrainedConfig) -> None:
     """Provide backwards compatibility for RoPE."""
-    # Retrieve rope_parameters differently based on Transformers version
+    # Patch rope_parameters differently based on Transformers version
     if Version(version("transformers")) >= Version("5.0.0.dev0"):
-        from transformers.modeling_rope_utils import RopeParameters
-
-        rope_parameters: RopeParameters | dict[str, RopeParameters] | None = getattr(
-            config, "rope_parameters", None
+        from transformers.modeling_rope_utils import (
+            rope_config_validation,
+            standardize_rope_params,
         )
-    elif hasattr(config, "rope_parameters"):
-        # We are in Transformers v4 and rope_parameters
-        # has already been patched for this config
-        return
+
+        # 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:
-        # Convert Transformers v4 rope_theta and rope_scaling into rope_parameters
-        rope_theta: float | None = getattr(config, "rope_theta", None)
-        rope_scaling: dict | None = getattr(config, "rope_scaling", None)
-        rope_parameters = rope_scaling
-        # Move rope_theta into rope_parameters
-        if rope_theta is not None:
-            rope_parameters = rope_parameters or {"rope_type": "default"}
-            rope_parameters["rope_theta"] = rope_theta
-        # Add original_max_position_embeddings if present
-        if rope_parameters and (
-            ompe := getattr(config, "original_max_position_embeddings", None)
-        ):
-            rope_parameters["original_max_position_embeddings"] = ompe
-        # Write back to config
-        config.rope_parameters = rope_parameters
+        # When Transformers v4 is installed, legacy rope_scaling 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"}
+            config.rope_parameters["rope_theta"] = rope_theta
 
     # No RoPE parameters to patch
-    if rope_parameters is None:
+    if not hasattr(config, "rope_parameters"):
         return
 
+    # Add original_max_position_embeddings if present
+    if ompe := getattr(config, "original_max_position_embeddings", None):
+        config.rope_parameters["original_max_position_embeddings"] = ompe
+
     # Handle nested rope_parameters in interleaved sliding attention models
-    if set(rope_parameters.keys()).issubset(ALLOWED_LAYER_TYPES):
-        for rope_parameters_layer_type in rope_parameters.values():
+    if set(config.rope_parameters.keys()).issubset(ALLOWED_LAYER_TYPES):
+        for rope_parameters_layer_type in config.rope_parameters.values():
             patch_rope_parameters_dict(rope_parameters_layer_type)
     else:
-        patch_rope_parameters_dict(rope_parameters)
+        patch_rope_parameters_dict(config.rope_parameters)
 
 
 def patch_rope_parameters_dict(rope_parameters: dict[str, Any]) -> None:
     if "rope_type" in rope_parameters and "type" in rope_parameters:
         rope_type = rope_parameters["rope_type"]
         rope_type_legacy = rope_parameters["type"]
-        if rope_type != rope_type_legacy:
+        if (rope_type_legacy == "su" and rope_type == "longrope") or (
+            rope_type_legacy == "mrope" and rope_type == "default"
+        ):
+            pass  # No action needed
+        elif rope_type != rope_type_legacy:
             raise ValueError(
                 f"Found conflicts between 'rope_type={rope_type}' (modern "
                 f"field) and 'type={rope_type_legacy}' (legacy field). "