Fix: Complete int32 to int64 conversion (#4465)
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@@ -305,7 +305,7 @@ class HiRadixCache(RadixCache):
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if value:
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value = torch.cat(value)
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else:
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value = torch.tensor([], dtype=torch.int32)
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value = torch.tensor([], dtype=torch.int64)
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last_node_global = last_node
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while last_node.evicted:
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@@ -622,11 +622,10 @@ class HostKVCache(abc.ABC):
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self.mem_state = torch.zeros(
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(self.size,), dtype=torch.uint8, device=self.device
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)
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self.free_slots = torch.arange(self.size, dtype=torch.int32)
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self.can_use_mem_size = self.size
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# A lock for synchronized operations on memory allocation and state transitions.
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self.lock = threading.RLock()
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self.clear()
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@abc.abstractmethod
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def get_size_per_token(self):
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@@ -656,7 +655,7 @@ class HostKVCache(abc.ABC):
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def clear(self):
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self.mem_state.fill_(0)
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self.can_use_mem_size = self.size
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self.free_slots = torch.arange(self.size, dtype=torch.int32)
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self.free_slots = torch.arange(self.size, dtype=torch.int64)
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@synchronized
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def get_state(self, indices: torch.Tensor) -> MemoryStateInt:
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@@ -140,7 +140,7 @@ class RadixCache(BasePrefixCache):
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return (
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torch.empty(
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(0,),
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dtype=torch.int32,
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dtype=torch.int64,
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device=self.device,
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),
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self.root_node,
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@@ -154,7 +154,7 @@ class RadixCache(BasePrefixCache):
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if value:
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value = torch.cat(value)
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else:
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value = torch.empty((0,), dtype=torch.int32, device=self.device)
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value = torch.empty((0,), dtype=torch.int64, device=self.device)
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return value, last_node
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def insert(self, key: List, value=None):
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