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vLLM/vllm/v1/worker/encoder_cudagraph_defs.py
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2026-04-14 16:49:32 +08:00

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Python

# SPDX-License-Identifier: Apache-2.0
# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
"""Data transfer objects for encoder CUDA graph management."""
from dataclasses import dataclass
from typing import Any
import torch
@dataclass
class EncoderCudaGraphConfig:
"""Configuration for encoder CUDA graph management.
Provided by the model at init time via
``get_encoder_cudagraph_config()``. Values are fixed for the
lifetime of the manager.
"""
modalities: list[str]
"""Supported modalities (e.g. ["image"])."""
input_key_by_modality: dict[str, str]
"""Per-modality input tensor key mapping, e.g.
{"image": "pixel_values", "video": "pixel_values_videos"}.
"""
buffer_keys: list[str]
"""Keys for the tensor buffers recorded into the CUDA graph.
Before replay the manager zeros then slice-copies new data
into these buffers."""
out_hidden_size: int
"""Output hidden dim of the vision encoder.
Used for DP gather buffer allocation."""
@dataclass
class EncoderCudaGraphCaptureInputs:
"""Everything needed for one CUDA graph capture.
Returned by ``prepare_encoder_cudagraph_capture_inputs()``.
"""
mm_kwargs: dict[str, Any]
"""Dummy forward inputs (model-specific keys).
For Qwen3-VL this contains pixel_values and grid_thw."""
buffers: dict[str, torch.Tensor]
"""Precomputed tensor buffers that will be recorded into the
CUDA graph. The manager stores references to these exact
tensor objects and copies new data into them before each
``graph.replay()`` call (buffer identity invariant)."""
@dataclass
class EncoderCudaGraphReplayBuffers:
"""New buffer values for graph replay, computed by the model from
actual batch inputs.
Returned by ``prepare_encoder_cudagraph_replay_buffers()``.
Keys match ``EncoderCudaGraphConfig.buffer_keys``.
"""
buffers: dict[str, torch.Tensor | None]
"""Data to copy into the captured buffers before replay.
``None`` values leave the corresponding captured buffer
unchanged."""