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chore: import upstream snapshot with attribution
2026-07-13 12:38:16 +08:00

118 lines
4.7 KiB
Python

from __future__ import annotations
import math
from dataclasses import dataclass
from typing import TYPE_CHECKING
if TYPE_CHECKING:
from sglang.srt.server_args import ServerArgs
@dataclass(frozen=True, slots=True, kw_only=True)
class CanaryLaunchCapacities:
"""Pre-allocation sizes for the per-forward tensors a SingleForwardManager owns. Computed
once at install_canary from ServerArgs + ModelRunner metadata; all fields are upper
bounds - actual per-step usage may be smaller but never larger.
Fields:
per_forward_verify_capacity: VerifyPlan row capacity for the per-forward HEAD/TAIL
launches. Sized to pool_slot_count * 3 (3x headroom; radix prefix sharing across
running reqs can cause sum_r prefix_lens[r] to exceed the pool slot count). When
the per-step actual count exceeds this, the plan kernel sets VerifyPlan.enable=0
and the verify kernel skips the step; host logs a warn (no install-time raise).
per_forward_write_req_capacity: WritePlan row capacity for per-forward writes, also used
to size the static PlanInput buffers (= max batch size under cuda graph).
per_forward_write_entry_capacity: Capacity for the expected_input_* placeholder tensors,
one entry per token written in a single forward.
"""
per_forward_verify_capacity: int
per_forward_write_req_capacity: int
per_forward_write_entry_capacity: int
def __post_init__(self) -> None:
for name, value in (
("per_forward_verify_capacity", self.per_forward_verify_capacity),
("per_forward_write_req_capacity", self.per_forward_write_req_capacity),
("per_forward_write_entry_capacity", self.per_forward_write_entry_capacity),
):
if value <= 0:
raise ValueError(f"kv-canary: {name} must be positive, got {value}")
@classmethod
def from_args(
cls,
*,
server_args: ServerArgs,
req_to_token_pool_size: int,
max_seq_len_per_req: int,
pool_slot_count: int,
) -> CanaryLaunchCapacities:
if req_to_token_pool_size <= 0:
raise ValueError(
"kv-canary: req_to_token_pool_size must be positive, "
f"got {req_to_token_pool_size}"
)
if max_seq_len_per_req <= 0:
raise ValueError(
"kv-canary: max_seq_len_per_req must be positive, "
f"got {max_seq_len_per_req}"
)
if pool_slot_count <= 0:
raise ValueError(
f"kv-canary: pool_slot_count must be positive, got {pool_slot_count}"
)
cuda_graph_config = server_args.cuda_graph_config
cuda_graph_max_bs = (
cuda_graph_config.decode.max_bs if cuda_graph_config is not None else 0
) or 0
if cuda_graph_max_bs < 0:
raise ValueError(
f"kv-canary: cuda_graph_max_bs must be non-negative, got {cuda_graph_max_bs}"
)
spec_num_draft_tokens = server_args.speculative_num_draft_tokens
if spec_num_draft_tokens is None:
spec_num_draft_tokens = 0
if spec_num_draft_tokens < 0:
raise ValueError(
"kv-canary: speculative_num_draft_tokens must be non-negative, "
f"got {spec_num_draft_tokens}"
)
max_prefill_tokens = server_args.max_prefill_tokens
if max_prefill_tokens <= 0:
raise ValueError(
f"kv-canary: max_prefill_tokens must be positive, got {max_prefill_tokens}"
)
num_tokens_per_bs = 1
if spec_num_draft_tokens:
num_tokens_per_bs = max(num_tokens_per_bs, spec_num_draft_tokens)
max_bs = max(cuda_graph_max_bs, req_to_token_pool_size)
chunked_prefill_size = server_args.chunked_prefill_size
chunked_limit = (
chunked_prefill_size
if chunked_prefill_size is not None and chunked_prefill_size >= 0
else math.inf
)
max_extend_tokens_per_forward = min(max_prefill_tokens, chunked_limit)
write_entry_capacity = max(
max_bs * num_tokens_per_bs, max_extend_tokens_per_forward
)
# Radix prefix sharing lets sum_r prefix_lens[r] exceed pool_slot_count; observed up to ~2x
# on 20 parallel token-oracle prompts. 3x headroom keeps the partial-fallback path
# (plan kernel enable=0 + host warn) exceptional. Overflow does not raise at install time.
per_forward_verify_capacity = int(pool_slot_count * 3)
return cls(
per_forward_verify_capacity=per_forward_verify_capacity,
per_forward_write_req_capacity=max_bs,
per_forward_write_entry_capacity=write_entry_capacity,
)