[Bugfix] gemma[2,3] interleaved attention when sliding window is disabled (#17180)

Signed-off-by: Chen Zhang <zhangch99@outlook.com>

vllm/model_executor/models/gemma2.py

@@ -145,8 +145,8 @@ class Gemma2Attention(nn.Module):
         # reference:
         # https://github.com/huggingface/transformers/blob/54be2d7ae87e873482b984cc956e165ca4dc0ba3/src/transformers/models/gemma2/modeling_gemma2.py#L312 # noqa
         layer_idx = extract_layer_index(prefix)
-        use_sliding_window = (layer_idx % 2 == 0 and
-                              config.interleaved_sliding_window is not None)
+        use_sliding_window = (layer_idx % 2 == 0 and getattr(
+            config, "interleaved_sliding_window", None) is not None)
         sliding_window = config.interleaved_sliding_window if \
             use_sliding_window else None
         self.attn = Attention(self.num_heads,

vllm/model_executor/models/gemma3.py

@@ -146,7 +146,9 @@ class Gemma3Attention(nn.Module):
 
         # TODO(woosuk): Add reference to the original HF implementation.
         layer_idx = extract_layer_index(prefix)
-        self.is_sliding = bool((layer_idx + 1) % config.sliding_window_pattern)
+        self.is_sliding = (getattr(
+            config, "interleaved_sliding_window", None) is not None and bool(
+                (layer_idx + 1) % config.sliding_window_pattern))
         # Initialize the rotary embedding.
         if self.is_sliding:
             # Local attention. Override the values in config.json.

vllm/model_executor/models/gemma3_mm.py

@@ -478,7 +478,8 @@ class Gemma3ForConditionalGeneration(nn.Module, SupportsMultiModal, SupportsPP,
         self.config = config
         self.quant_config = quant_config
         self.multimodal_config = multimodal_config
-        self.sliding_window = config.text_config.interleaved_sliding_window
+        self.sliding_window = getattr(config.text_config,
+                                      "interleaved_sliding_window", None)
 
         self.vision_tower = SiglipVisionModel(config.vision_config,
                                               quant_config,
@@ -680,6 +681,7 @@ class Gemma3ForConditionalGeneration(nn.Module, SupportsMultiModal, SupportsPP,
             global_attn_mask = torch.where(img_mask == 2, 0, global_attn_mask)
             global_attn_masks.append(global_attn_mask)
 
+            if self.sliding_window is not None:
                 # Create a local causal mask with sliding window (1024).
                 local_attn_mask = torch.ones_like(global_attn_mask)
                 local_attn_mask = torch.tril(local_attn_mask,