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sglang/python/sglang/srt/managers/scheduler_runtime_checker_mixin.py

292 lines
11 KiB
Python

from __future__ import annotations
import logging
import signal
import sys
import time
from typing import TYPE_CHECKING
from sglang.srt.disaggregation.utils import DisaggregationMode
from sglang.srt.environ import envs
from sglang.srt.managers.schedule_batch import ScheduleBatch
from sglang.srt.mem_cache.mamba_radix_cache import MambaRadixCache
from sglang.srt.mem_cache.swa_radix_cache import SWARadixCache
from sglang.srt.utils.common import (
disable_request_logging,
pyspy_dump_schedulers,
raise_error_or_warn,
)
if TYPE_CHECKING:
from sglang.srt.managers.scheduler import Scheduler
logger = logging.getLogger(__name__)
class SchedulerRuntimeCheckerMixin:
def _check_hybrid_memory(self: Scheduler):
(
full_num_used,
swa_num_used,
_,
_,
full_available_size,
full_evictable_size,
swa_available_size,
swa_evictable_size,
) = self._get_swa_token_info()
memory_leak = full_num_used != 0 or swa_num_used != 0
token_msg = (
f"{self.full_tokens_per_layer=}, {full_available_size=}, {full_evictable_size=}, {self.tree_cache.full_protected_size()=}\n"
f"{self.swa_tokens_per_layer=}, {swa_available_size=}, {swa_evictable_size=}, {self.tree_cache.swa_protected_size()=}\n"
)
return memory_leak, token_msg
def _check_mamba_memory(self: Scheduler):
(
full_num_used,
mamba_num_used,
_,
_,
full_available_size,
full_evictable_size,
mamba_available_size,
mamba_evictable_size,
) = self._get_mamba_token_info()
memory_leak = (
full_num_used != self.tree_cache.full_protected_size()
or mamba_num_used != self.tree_cache.mamba_protected_size()
)
token_msg = (
f"{full_available_size=}, {full_evictable_size=}, {self.token_to_kv_pool_allocator.size=}, {self.tree_cache.full_protected_size()=}\n"
f"{mamba_available_size=}, {mamba_evictable_size=}, {self.req_to_token_pool.mamba_pool.size=}, {self.tree_cache.mamba_protected_size()=}\n"
)
return memory_leak, token_msg
def _check_radix_cache_memory(self: Scheduler):
_, _, available_size, evictable_size = self._get_token_info()
protected_size = self.tree_cache.protected_size()
memory_leak = (available_size + evictable_size) != (
# self.max_total_num_tokens
# if not self.enable_hierarchical_cache
# else self.max_total_num_tokens - protected_size
self.max_total_num_tokens
- protected_size
)
token_msg = f"{self.max_total_num_tokens=}, {available_size=}, {evictable_size=}, {protected_size=}\n"
return memory_leak, token_msg
def _check_runtime_mem_leak(self: Scheduler):
current_batch: ScheduleBatch = self.last_batch
if current_batch is None:
return
_, _, available_size, evictable_size = self._get_token_info()
protected_size = self.tree_cache.protected_size()
extend_size = 0
for i, req in enumerate(current_batch.reqs):
seq_len = len(req.origin_input_ids) + len(req.output_ids)
fill_len = len(req.fill_ids) if req.fill_ids is not None else 0
prefix_len = (
len(req.prefix_indices) if req.prefix_indices is not None else 0
)
if current_batch.forward_mode.is_decode():
if req.finished():
unreleased_len = 1
else:
unreleased_len = seq_len - prefix_len
else:
unreleased_len = fill_len - prefix_len
extend_size += unreleased_len
if (
current_batch.forward_mode.is_extend()
and self.running_batch is not None
and not self.running_batch.is_empty()
and self.running_batch.forward_mode.is_decode()
):
for i, req in enumerate(self.running_batch.reqs):
seq_len = len(req.origin_input_ids) + len(req.output_ids)
prefix_len = (
len(req.prefix_indices) if req.prefix_indices is not None else 0
)
if req.finished():
unreleased_len = 0
else:
unreleased_len = seq_len - prefix_len - 1
extend_size += unreleased_len
total_tokens = available_size + evictable_size + protected_size + extend_size
assert (
total_tokens == self.max_total_num_tokens
), f"Mem Leak Detected! {total_tokens=} vs {self.max_total_num_tokens=}"
def _check_req_pool(self: Scheduler):
if self.disaggregation_mode == DisaggregationMode.DECODE:
req_total_size = (
self.req_to_token_pool.size + self.req_to_token_pool.pre_alloc_size
)
else:
req_total_size = self.req_to_token_pool.size
if len(self.req_to_token_pool.free_slots) != req_total_size:
msg = (
"req_to_token_pool memory leak detected!"
f"available_size={len(self.req_to_token_pool.free_slots)}, "
f"total_size={self.req_to_token_pool.size}\n"
)
raise_error_or_warn(
self,
envs.SGLANG_ENABLE_STRICT_MEM_CHECK_DURING_IDLE,
"count_req_pool_leak_warnings",
msg,
)
def check_memory(self: Scheduler):
if self.is_hybrid:
memory_leak, token_msg = self._check_hybrid_memory()
elif self.is_hybrid_gdn and isinstance(self.tree_cache, MambaRadixCache):
memory_leak, token_msg = self._check_mamba_memory()
else:
memory_leak, token_msg = self._check_radix_cache_memory()
if memory_leak:
msg = "token_to_kv_pool_allocator memory leak detected! " f"{token_msg}"
raise_error_or_warn(
self,
envs.SGLANG_ENABLE_STRICT_MEM_CHECK_DURING_IDLE,
"count_memory_leak_warnings",
msg,
)
self._check_req_pool()
if (
self.enable_metrics
and self.current_scheduler_metrics_enabled()
and time.perf_counter() > self.metrics_collector.last_log_time + 30
):
# During idle time, also collect metrics every 30 seconds.
if self.is_hybrid:
(
full_num_used,
swa_num_used,
full_token_usage,
swa_token_usage,
_,
_,
_,
_,
) = self._get_swa_token_info()
num_used = max(full_num_used, swa_num_used)
token_usage = max(full_token_usage, swa_token_usage)
elif self.is_hybrid_gdn:
(
num_used,
_,
token_usage,
_,
_,
_,
_,
_,
) = self._get_mamba_token_info()
else:
num_used, token_usage, _, _ = self._get_token_info()
num_running_reqs = len(self.running_batch.reqs)
self.stats.num_running_reqs = num_running_reqs
self.stats.num_used_tokens = num_used
self.stats.token_usage = round(token_usage, 2)
self.stats.gen_throughput = 0
self.stats.num_queue_reqs = len(self.waiting_queue)
self.stats.num_grammar_queue_reqs = len(self.grammar_queue)
if self.disaggregation_mode == DisaggregationMode.PREFILL:
self.stats.num_prefill_prealloc_queue_reqs = len(
self.disagg_prefill_bootstrap_queue.queue
)
self.stats.num_prefill_inflight_queue_reqs = len(
self.disagg_prefill_inflight_queue
)
if self.disaggregation_mode == DisaggregationMode.DECODE:
self.stats.num_decode_prealloc_queue_reqs = len(
self.disagg_decode_prealloc_queue.queue
)
self.stats.num_decode_transfer_queue_reqs = len(
self.disagg_decode_transfer_queue.queue
)
self.metrics_collector.log_stats(self.stats)
self._publish_kv_events()
def check_tree_cache(self: Scheduler):
if (self.is_hybrid and isinstance(self.tree_cache, SWARadixCache)) or (
self.is_hybrid_gdn and isinstance(self.tree_cache, MambaRadixCache)
):
self.tree_cache.sanity_check()
def self_check_during_idle(self: Scheduler):
if self.disaggregation_mode == DisaggregationMode.PREFILL:
if len(self.disagg_prefill_inflight_queue) > 0:
return
elif self.disaggregation_mode == DisaggregationMode.DECODE:
queue_size = (
len(self.waiting_queue)
+ len(self.disagg_decode_transfer_queue.queue)
+ len(self.disagg_decode_prealloc_queue.queue)
)
if self.server_args.disaggregation_decode_enable_offload_kvcache:
queue_size += len(self.decode_offload_manager.ongoing_offload)
if queue_size:
return
self.check_memory()
self.check_tree_cache()
self.new_token_ratio = self.init_new_token_ratio
self.maybe_sleep_on_idle()
def watchdog_thread(self: Scheduler):
"""A watch dog thread that will try to kill the server itself if one forward batch takes too long."""
self.watchdog_last_forward_ct = 0
self.watchdog_last_time = time.perf_counter()
while True:
current = time.perf_counter()
if self.cur_batch is not None:
if self.watchdog_last_forward_ct == self.forward_ct:
if current > self.watchdog_last_time + self.watchdog_timeout:
break
else:
self.watchdog_last_forward_ct = self.forward_ct
self.watchdog_last_time = current
time.sleep(self.watchdog_timeout // 2)
if not disable_request_logging():
# Print batch size and memory pool info to check whether there are de-sync issues.
if self.is_hybrid:
_, info_msg = self._check_hybrid_memory()
elif self.is_hybrid_gdn and isinstance(self.tree_cache, MambaRadixCache):
_, info_msg = self._check_mamba_memory()
else:
_, info_msg = self._check_radix_cache_memory()
logger.error(
f"{self.cur_batch.batch_size()=}\n"
f"{self.cur_batch.reqs=}\n"
f"{info_msg}"
)
pyspy_dump_schedulers()
logger.error(f"Watchdog timeout ({self.watchdog_timeout=})")
print(file=sys.stderr, flush=True)
print(file=sys.stdout, flush=True)
# Wait for some time so that the parent process can print the error.
time.sleep(5)
self.parent_process.send_signal(signal.SIGQUIT)