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262 lines
10 KiB
Python
262 lines
10 KiB
Python
from __future__ import annotations
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import logging
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import time
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from typing import TYPE_CHECKING, List, Optional, Set
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import torch
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from sglang.srt.mem_cache.base_prefix_cache import (
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BasePrefixCache,
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DecLockRefParams,
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DecLockRefResult,
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EvictParams,
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EvictResult,
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IncLockRefResult,
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MatchPrefixParams,
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MatchResult,
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)
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from sglang.srt.mem_cache.cpp_radix_tree.radix_tree import (
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IOHandle,
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RadixTreeCpp,
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TreeNodeCpp,
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)
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from sglang.srt.mem_cache.radix_cache import RadixKey
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if TYPE_CHECKING:
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from sglang.srt.managers.schedule_batch import Req
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from sglang.srt.mem_cache.cache_init_params import CacheInitParams
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from sglang.srt.server_args import ServerArgs
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logger = logging.getLogger(__name__)
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class RadixCacheCpp(BasePrefixCache):
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def __init__(
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self,
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params: CacheInitParams,
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server_args: ServerArgs,
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enable_write_cancel: bool = False,
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):
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self.disable = params.disable
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self.enable_write_cancel = enable_write_cancel
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assert (
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params.enable_kv_cache_events is False
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), "HiRadixCache does not support kv cache events yet"
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# record the nodes with ongoing write through
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self.ongoing_write_through: Set[IOHandle] = set()
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# record the node segments with ongoing load back
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self.ongoing_load_back: Set[IOHandle] = set()
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# todo: dynamically adjust the threshold
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self.write_through_threshold = (
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1 if server_args.hicache_write_policy == "write_through" else 2
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)
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self.token_to_kv_pool_allocator = params.token_to_kv_pool_allocator
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self.device = self.token_to_kv_pool_allocator.device
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self.req_to_token_pool = params.req_to_token_pool
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self.page_size = params.page_size
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self.kv_cache = self.token_to_kv_pool_allocator.get_kvcache()
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self.tp_group = params.tp_cache_group
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if params.enable_metrics:
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self.init_metrics_collector()
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if not server_args.enable_hierarchical_cache:
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self.tree = RadixTreeCpp(
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disabled=self.disable,
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page_size=self.page_size,
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host_size=None, # no host cache, this should be removed in the future
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write_through_threshold=self.write_through_threshold,
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)
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self.cache_controller = None
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return # early return if hicache is not used
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raise NotImplementedError("Host cache is not supported yet")
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def _merge_tensor(self, l: List[torch.Tensor]) -> torch.Tensor:
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"""
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Merge a list of tensors into a single tensor.
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Args:
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l (List[torch.Tensor]): List of tensors to merge.
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Returns:
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torch.Tensor: Merged tensor.
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"""
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if len(l) == 0:
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return torch.empty(0, dtype=torch.int64, device=self.device)
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elif len(l) == 1:
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return l[0]
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else:
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return torch.cat(l)
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def reset(self):
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if self.cache_controller is not None:
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# need to clear the acks before resetting the cache controller
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raise NotImplementedError("Host cache is not supported yet")
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self.tree.reset()
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def match_prefix(self, params: MatchPrefixParams) -> MatchResult:
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key = params.key
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device_indices_vec, host_indices_length, node_gpu, node_cpu = (
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self.tree.match_prefix(key.raw_token_ids())
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)
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return MatchResult(
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device_indices=self._merge_tensor(device_indices_vec),
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last_device_node=node_gpu,
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last_host_node=node_cpu,
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best_match_node=node_cpu,
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host_hit_length=host_indices_length,
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)
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def _insert(self, key: RadixKey, value: torch.Tensor) -> int:
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"""
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Insert a key-value pair into the radix tree.
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Args:
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key (RadixKey): The key to insert, represented as a RadixKey.
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value (torch.Tensor): The value to associate with the key.
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Returns:
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int: Number of device indices that were already present in the tree before the insertion.
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"""
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ongoing_write, length = self.tree.writing_through(key.token_ids, value)
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if self.cache_controller is None:
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assert len(ongoing_write) == 0, "Implementation error"
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return length
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raise NotImplementedError("Host cache is not supported yet")
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def dec_lock_ref(
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self, node: TreeNodeCpp, params: Optional[DecLockRefParams] = None
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) -> DecLockRefResult:
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"""
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Decrement the reference count of a node to root of the radix tree.
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Args:
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node (TreeNodeCpp): The handle of the node to decrement the reference count for.
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"""
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self.tree.lock_ref(node, False) # do not increment
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return DecLockRefResult()
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def inc_lock_ref(self, node: TreeNodeCpp) -> IncLockRefResult:
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"""
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Increment the reference count of from a node to root of the radix tree.
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Args:
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node (TreeNodeCpp): The handle of the node to increment the reference count for.
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"""
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self.tree.lock_ref(node, True)
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return IncLockRefResult()
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def evict(self, params: EvictParams) -> EvictResult:
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start_time = time.perf_counter()
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num_tokens = params.num_tokens
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evicted_device_indices = self.tree.evict(num_tokens)
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num_evicted = 0
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for indice in evicted_device_indices:
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num_evicted += len(indice)
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self.token_to_kv_pool_allocator.free(indice)
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self.update_eviction_metrics(num_evicted, start_time)
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return EvictResult(num_tokens_evicted=num_evicted)
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def evictable_size(self):
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return self.tree.evictable_size()
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def protected_size(self):
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return self.tree.protected_size()
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def total_size(self):
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return self.tree.total_size()
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def cache_finished_req(self, req: Req, is_insert: bool = True):
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"""Cache request when it finishes."""
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assert req.req_pool_idx is not None
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kv_committed_len = req.pop_committed_kv_cache()
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token_ids = (req.origin_input_ids + req.output_ids)[:kv_committed_len]
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kv_indices = self.req_to_token_pool.req_to_token[
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req.req_pool_idx, :kv_committed_len
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].to(dtype=torch.int64, copy=True)
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# NOTE: our C++ implementation don't need `token_ids` and `kv_indices` to be page-aligned
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# it will automatically align them, but length of them should be equal
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old_prefix_len = len(req.prefix_indices) // self.page_size * self.page_size
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page_aligned_overall_len = kv_committed_len // self.page_size * self.page_size
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if is_insert:
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new_prefix_len = self._insert(
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RadixKey(token_ids, req.extra_key), kv_indices
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)
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# NOTE: kv_indices[:old_prefix_len] == req.prefix_indices
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assert old_prefix_len <= new_prefix_len, "Wrong prefix indices"
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# Free duplicates that were already in the pool
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if old_prefix_len < new_prefix_len:
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self.token_to_kv_pool_allocator.free(
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kv_indices[old_prefix_len:new_prefix_len]
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)
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else:
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self.token_to_kv_pool_allocator.free(
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kv_indices[old_prefix_len:page_aligned_overall_len]
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)
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# need to free the unaligned part, since it cannot be inserted into the radix tree
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if page_aligned_overall_len < kv_committed_len:
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# NOTE: sglang PagedAllocator support unaligned free (which will automatically align it)
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self.token_to_kv_pool_allocator.free(kv_indices[page_aligned_overall_len:])
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# Remove req slot release the cache lock
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self.dec_lock_ref(req.last_node)
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def cache_unfinished_req(self, req: Req, chunked=False):
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"""Cache request when it is unfinished."""
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assert req.req_pool_idx is not None
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token_ids = req.get_fill_ids()
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prefill_len = len(token_ids) # prefill only (maybe chunked)
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kv_indices = self.req_to_token_pool.req_to_token[
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req.req_pool_idx, :prefill_len
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].to(dtype=torch.int64, copy=True)
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# NOTE: our C++ implementation don't need `token_ids` and `kv_indices` to be page-aligned
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# it will automatically align them, but length of them should be equal
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old_prefix_len = len(req.prefix_indices) // self.page_size * self.page_size
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new_prefix_len = self._insert(RadixKey(token_ids, req.extra_key), kv_indices)
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# NOTE: kv_indices[:old_prefix_len] == req.prefix_indices
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assert old_prefix_len <= new_prefix_len, "Wrong prefix indices"
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# TODO(dark): optimize the `insert` and `match` (e.g. merge into 1 function)
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# The prefix indices need to updated to reuse the kv indices in the pool
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new_indices_vec, _, new_last_node, _ = self.tree.match_prefix(
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RadixKey(token_ids, req.extra_key).token_ids
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)
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new_indices = self._merge_tensor(new_indices_vec)
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assert new_prefix_len <= len(new_indices)
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# KVCache between old & new is newly generated, but already exists in the pool
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# we need to free this newly generated kv indices and reuse the indices in the pool
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if old_prefix_len < new_prefix_len:
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self.token_to_kv_pool_allocator.free(
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kv_indices[old_prefix_len:new_prefix_len]
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)
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reused_indices = new_indices[old_prefix_len:new_prefix_len]
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self.req_to_token_pool.req_to_token[
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req.req_pool_idx, old_prefix_len:new_prefix_len
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] = reused_indices
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if req.last_node != new_last_node:
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self.dec_lock_ref(req.last_node)
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self.inc_lock_ref(new_last_node)
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# NOTE: there might be unaligned tail, so we may need to append it
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assert len(new_indices) <= prefill_len < len(new_indices) + self.page_size
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if self.page_size != 1 and len(new_indices) < prefill_len:
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req.prefix_indices = torch.cat(
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[new_indices, kv_indices[len(new_indices) :]]
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)
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else:
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req.prefix_indices = new_indices
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req.last_node = new_last_node
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def pretty_print(self):
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return self.tree.debug_print()
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