102ba716bf
Signed-off-by: asukaqaq-s <1311722138@qq.com> Signed-off-by: Acerak01-fy <wfy2003324@163.com> Co-authored-by: Acerak01-fy <wfy2003324@163.com> Co-authored-by: amy-why-3459 <wuhaiyan17@huawei.com>
59 lines
1.6 KiB
Python
59 lines
1.6 KiB
Python
# SPDX-License-Identifier: Apache-2.0
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# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
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"""Scheduler-to-Worker allocation payloads for diffusion KV.
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Like native vLLM's SchedulerOutput DTOs, these classes carry trusted internal
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Scheduler results. Cache geometry and block-table validation stay with the
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native cache builders and Worker installation path.
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"""
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from __future__ import annotations
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from dataclasses import dataclass
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@dataclass
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class DiffusionKVContextMetadata:
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"""Request-scoped Worker allocation for an independent K/V context.
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``context_id`` identifies this allocation within the enclosing
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:class:`DiffusionKVMetadata`.
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"""
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context_id: str
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cache_role: str
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num_tokens: int
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block_ids: tuple[list[int], ...]
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@dataclass
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class DiffusionKVSequenceMetadata:
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"""Worker allocation for one Scheduler-owned diffusion sequence.
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``context_ids`` reference request-scoped context allocations from the
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enclosing :class:`DiffusionKVMetadata`.
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"""
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sequence_id: int
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prefix_len: int
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target_len: int
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seq_len: int
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block_ids: tuple[list[int], ...]
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context_ids: tuple[str, ...] = ()
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num_computed_tokens: int = 0
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@dataclass
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class DiffusionKVMetadata:
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"""Scheduler allocation sent with a newly scheduled public request.
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Independent contexts live once at request scope so multiple sequences can
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reference the same allocation.
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"""
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request_id: str
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allocation_generation: int
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sequences: tuple[DiffusionKVSequenceMetadata, ...]
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contexts: tuple[DiffusionKVContextMetadata, ...] = ()
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