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| # SPDX-FileCopyrightText: Copyright (c) 2025 NVIDIA CORPORATION & AFFILIATES. All rights reserved. | |
| # SPDX-License-Identifier: Apache-2.0 | |
| # | |
| # Licensed under the Apache License, Version 2.0 (the "License"); | |
| # you may not use this file except in compliance with the License. | |
| # You may obtain a copy of the License at | |
| # | |
| # http://www.apache.org/licenses/LICENSE-2.0 | |
| # | |
| # Unless required by applicable law or agreed to in writing, software | |
| # distributed under the License is distributed on an "AS IS" BASIS, | |
| # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. | |
| # See the License for the specific language governing permissions and | |
| # limitations under the License. | |
| import collections.abc as abc | |
| import dataclasses | |
| import logging | |
| from typing import Any | |
| import attrs | |
| from cosmos_predict1.utils.lazy_config.registry import _convert_target_to_string, locate | |
| __all__ = ["dump_dataclass", "instantiate"] | |
| def is_dataclass_or_attrs(target): | |
| return dataclasses.is_dataclass(target) or attrs.has(target) | |
| def dump_dataclass(obj: Any): | |
| """ | |
| Dump a dataclass recursively into a dict that can be later instantiated. | |
| Args: | |
| obj: a dataclass object | |
| Returns: | |
| dict | |
| """ | |
| assert dataclasses.is_dataclass(obj) and not isinstance( | |
| obj, type | |
| ), "dump_dataclass() requires an instance of a dataclass." | |
| ret = {"_target_": _convert_target_to_string(type(obj))} | |
| for f in dataclasses.fields(obj): | |
| v = getattr(obj, f.name) | |
| if dataclasses.is_dataclass(v): | |
| v = dump_dataclass(v) | |
| if isinstance(v, (list, tuple)): | |
| v = [dump_dataclass(x) if dataclasses.is_dataclass(x) else x for x in v] | |
| ret[f.name] = v | |
| return ret | |
| def instantiate(cfg, *args, **kwargs): | |
| """ | |
| Recursively instantiate objects defined in dictionaries by | |
| "_target_" and arguments. | |
| Args: | |
| cfg: a dict-like object with "_target_" that defines the caller, and | |
| other keys that define the arguments | |
| args: Optional positional parameters pass-through. | |
| kwargs: Optional named parameters pass-through. | |
| Returns: | |
| object instantiated by cfg | |
| """ | |
| from omegaconf import DictConfig, ListConfig, OmegaConf | |
| if isinstance(cfg, ListConfig): | |
| lst = [instantiate(x) for x in cfg] | |
| return ListConfig(lst, flags={"allow_objects": True}) | |
| if isinstance(cfg, list): | |
| # Specialize for list, because many classes take | |
| # list[objects] as arguments, such as ResNet, DatasetMapper | |
| return [instantiate(x) for x in cfg] | |
| # If input is a DictConfig backed by dataclasses (i.e. omegaconf's structured config), | |
| # instantiate it to the actual dataclass. | |
| if isinstance(cfg, DictConfig) and is_dataclass_or_attrs(cfg._metadata.object_type): | |
| return OmegaConf.to_object(cfg) | |
| if isinstance(cfg, abc.Mapping) and "_target_" in cfg: | |
| # conceptually equivalent to hydra.utils.instantiate(cfg) with _convert_=all, | |
| # but faster: https://github.com/facebookresearch/hydra/issues/1200 | |
| cfg = {k: instantiate(v) for k, v in cfg.items()} | |
| cls = cfg.pop("_target_") | |
| cls = instantiate(cls) | |
| if isinstance(cls, str): | |
| cls_name = cls | |
| cls = locate(cls_name) | |
| assert cls is not None, cls_name | |
| else: | |
| try: | |
| cls_name = cls.__module__ + "." + cls.__qualname__ | |
| except Exception: | |
| # target could be anything, so the above could fail | |
| cls_name = str(cls) | |
| assert callable(cls), f"_target_ {cls} does not define a callable object" | |
| try: | |
| # override config with kwargs | |
| instantiate_kwargs = {} | |
| instantiate_kwargs.update(cfg) | |
| instantiate_kwargs.update(kwargs) | |
| return cls(*args, **instantiate_kwargs) | |
| except TypeError: | |
| logger = logging.getLogger(__name__) | |
| logger.error(f"Error when instantiating {cls_name}!") | |
| raise | |
| return cfg # return as-is if don't know what to do | |