__init__.py 3.24 KB
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# SPDX-License-Identifier: Apache-2.0
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# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
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import logging
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import os
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from typing import Any, Callable
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import torch

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import vllm.envs as envs
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logger = logging.getLogger(__name__)

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DEFAULT_PLUGINS_GROUP = 'vllm.general_plugins'

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# make sure one process only loads plugins once
plugins_loaded = False

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def load_plugins_by_group(group: str) -> dict[str, Callable[[], Any]]:
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    import sys
    if sys.version_info < (3, 10):
        from importlib_metadata import entry_points
    else:
        from importlib.metadata import entry_points

    allowed_plugins = envs.VLLM_PLUGINS

    discovered_plugins = entry_points(group=group)
    if len(discovered_plugins) == 0:
        logger.debug("No plugins for group %s found.", group)
        return {}
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    # Check if the only discovered plugin is the default one
    is_default_group = (group == DEFAULT_PLUGINS_GROUP)
    # Use INFO for non-default groups and DEBUG for the default group
    log_level = logger.debug if is_default_group else logger.info

    log_level("Available plugins for group %s:", group)
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    for plugin in discovered_plugins:
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        log_level("- %s -> %s", plugin.name, plugin.value)
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    if allowed_plugins is None:
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        log_level("All plugins in this group will be loaded. "
                  "Set `VLLM_PLUGINS` to control which plugins to load.")
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    plugins = dict[str, Callable[[], Any]]()
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    for plugin in discovered_plugins:
        if allowed_plugins is None or plugin.name in allowed_plugins:
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            if allowed_plugins is not None:
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                log_level("Loading plugin %s", plugin.name)
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            try:
                func = plugin.load()
                plugins[plugin.name] = func
            except Exception:
                logger.exception("Failed to load plugin %s", plugin.name)
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    return plugins


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def load_general_plugins():
    """WARNING: plugins can be loaded for multiple times in different
    processes. They should be designed in a way that they can be loaded
    multiple times without causing issues.
    """
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    global plugins_loaded
    if plugins_loaded:
        return
    plugins_loaded = True
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    # some platform-specific configurations
    from vllm.platforms import current_platform

    if current_platform.is_xpu():
        # see https://github.com/pytorch/pytorch/blob/43c5f59/torch/_dynamo/config.py#L158
        torch._dynamo.config.disable = True
    elif current_platform.is_hpu():
        # NOTE(kzawora): PT HPU lazy backend (PT_HPU_LAZY_MODE = 1)
        # does not support torch.compile
        # Eager backend (PT_HPU_LAZY_MODE = 0) must be selected for
        # torch.compile support
        is_lazy = os.environ.get('PT_HPU_LAZY_MODE', '1') == '1'
        if is_lazy:
            torch._dynamo.config.disable = True
            # NOTE(kzawora) multi-HPU inference with HPUGraphs (lazy-only)
            # requires enabling lazy collectives
            # see https://docs.habana.ai/en/latest/PyTorch/Inference_on_PyTorch/Inference_Using_HPU_Graphs.html # noqa: E501
            os.environ['PT_HPU_ENABLE_LAZY_COLLECTIVES'] = 'true'

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    plugins = load_plugins_by_group(group=DEFAULT_PLUGINS_GROUP)
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    # general plugins, we only need to execute the loaded functions
    for func in plugins.values():
        func()