[v1] Add cross-attention KV cache support for encoder-decoder models (#23664)

Signed-off-by: Russell Bryant <rbryant@redhat.com>

vllm/v1/kv_cache_interface.py

@@ -11,6 +11,7 @@ from typing_extensions import Self
 
 from vllm.config import VllmConfig
 from vllm.logger import init_logger
+from vllm.multimodal import MULTIMODAL_REGISTRY
 from vllm.utils import cdiv, get_dtype_size
 
 logger = init_logger(__name__)
@@ -211,6 +212,20 @@ class EncoderOnlyAttentionSpec(AttentionSpec):
         return 0
 
 
+@dataclass(frozen=True)
+class CrossAttentionSpec(AttentionSpec):
+    """
+    KV cache spec for cross-attention layers in encoder-decoder models.
+    """
+
+    def max_memory_usage_bytes(self, vllm_config: VllmConfig) -> int:
+        # For cross-attention, we need to cache encoder states
+        # Get encoder length (e.g., 1500 for Whisper).
+        max_encoder_len = MULTIMODAL_REGISTRY.\
+            get_encdec_max_encoder_len(vllm_config.model_config)
+        return cdiv(max_encoder_len, self.block_size) * self.page_size_bytes
+
+
 @dataclass
 class KVCacheTensor:
     """