mirror of
https://github.com/nerfstudio-project/nerfstudio.git
synced 2026-11-12 19:04:03 +08:00
wyyyz1937365497
f3f42692aa
feat(plugins): 支持可调用入口点以避免循环导入 在插件注册表中添加对函数入口点的支持，通过检测并调用可调用对象来避免循环导入问题。 这使得入口点可以作为函数定义，而不是直接的类实例，从而提高模块间的解耦性。 ```
103 lines
3.8 KiB
Python
103 lines
3.8 KiB
Python
# Copyright 2022 the Regents of the University of California, Nerfstudio Team and contributors. All rights reserved.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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"""
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Module that keeps all registered plugins and allows for plugin discovery.
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"""
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import importlib
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import os
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import sys
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import typing as t
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from dataclasses import dataclass
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from rich.progress import Console
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from nerfstudio.data.dataparsers.base_dataparser import DataParserConfig
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if sys.version_info < (3, 10):
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from importlib_metadata import entry_points
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else:
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from importlib.metadata import entry_points
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CONSOLE = Console(width=120)
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@dataclass
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class DataParserSpecification:
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"""
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DataParser specification class used to register custom dataparsers with Nerfstudio.
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The registered dataparsers will be available in commands such as `ns-train`
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"""
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config: DataParserConfig
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"""Dataparser configuration"""
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description: t.Optional[str] = None
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"""Description of the dataparser"""
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def discover_dataparsers() -> t.Tuple[t.Dict[str, DataParserConfig], t.Dict[str, str]]:
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"""
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Discovers all dataparsers registered using the `nerfstudio.dataparser_configs` entrypoint.
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And also dataparsers in the NERFSTUDIO_DATAPARSER_CONFIGS environment variable.
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"""
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dataparsers = {}
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descriptions = {}
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discovered_entry_points = entry_points(group="nerfstudio.dataparser_configs")
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for name in discovered_entry_points.names:
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spec = discovered_entry_points[name].load()
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# Support callable (function) entry points to avoid circular imports
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if callable(spec):
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spec = spec()
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if not isinstance(spec, DataParserSpecification):
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CONSOLE.print(
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f"[bold yellow]Warning: Could not entry point {spec} as it is not an instance of DataParserSpecification"
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)
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continue
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spec = t.cast(DataParserSpecification, spec)
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dataparsers[name] = spec.config
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descriptions[name] = spec.description
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if "NERFSTUDIO_DATAPARSER_CONFIGS" in os.environ:
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try:
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strings = os.environ["NERFSTUDIO_DATAPARSER_CONFIGS"].split(",")
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for definition in strings:
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if not definition:
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continue
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name, path = definition.split("=")
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CONSOLE.print(f"[bold green]Info: Loading method {name} from environment variable")
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module, config_name = path.split(":")
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dataparser_config = getattr(importlib.import_module(module), config_name)
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# method_config specified as function or class -> instance
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if callable(dataparser_config):
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dataparser_config = dataparser_config()
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# check for valid instance type
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if not isinstance(dataparser_config, DataParserSpecification):
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raise TypeError("Method is not an instance of DataParserSpecification")
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# save to methods
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dataparsers[name] = dataparser_config.config
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descriptions[name] = dataparser_config.description
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except Exception: # pylint: disable=broad-except
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CONSOLE.print_exception()
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CONSOLE.print(
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"[bold red]Error: Could not load methods from environment variable NERFSTUDIO_DATAPARSER_CONFIGS"
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)
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return dataparsers, descriptions
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