Upgrade to vllm 0.17.0 corex v4.1 overlay

vllm/v1/spec_decode/metadata.py

@@ -64,3 +64,45 @@ class SpecDecodeMetadata:
             bonus_logits_indices=bonus_logits_indices,
             logits_indices=logits_indices,
         )
+
+
+@dataclass
+class MultiLayerEagleMetadata:
+    # [batch_size]
+    cached_len: torch.Tensor | None = None
+    # [batch_size, layer_num]
+    cached_token_ids: torch.Tensor | None = None
+    # [batch_size, layer_num, hidden_size]
+    cached_hidden_states: torch.Tensor | None = None
+    # [batch_size, layer_num]
+    cached_slot_mappings: torch.Tensor | None = None
+    # [batch_size, layer_num]
+    cached_positions: torch.Tensor | None = None
+
+    @classmethod
+    def make_dummy(
+        cls,
+        layer_num: int,
+        hidden_size: int,
+        device: torch.device,
+    ) -> "MultiLayerEagleMetadata":
+        cached_len = torch.zeros((1), dtype=torch.int64, device=device)
+        cached_token_ids = torch.zeros(
+            (1, layer_num), dtype=torch.int32, device=device
+        )
+        cached_hidden_states = torch.zeros(
+            (1, layer_num, hidden_size), dtype=torch.float32, device=device
+        )
+        cached_slot_mappings = torch.zeros(
+            (1, layer_num), dtype=torch.int64, device=device
+        )
+        cached_positions = torch.zeros(
+            (1, layer_num), dtype=torch.int64, device=device
+        )
+        return cls(
+            cached_len=cached_len,
+            cached_token_ids=cached_token_ids,
+            cached_hidden_states=cached_hidden_states,
+            cached_slot_mappings=cached_slot_mappings,
+            cached_positions=cached_positions,
+        )