omni.isaac.lab.utils.configclass 源代码

# Copyright (c) 2022-2024, The Isaac Lab Project Developers.
# All rights reserved.
#
# SPDX-License-Identifier: BSD-3-Clause

"""Sub-module that provides a wrapper around the Python 3.7 onwards ``dataclasses`` module."""

import inspect
import types
from collections.abc import Callable
from copy import deepcopy
from dataclasses import MISSING, Field, dataclass, field, replace
from typing import Any, ClassVar

from .dict import class_to_dict, update_class_from_dict

_CONFIGCLASS_METHODS = ["to_dict", "from_dict", "replace", "copy", "validate"]
"""List of class methods added at runtime to dataclass."""

"""
Wrapper around dataclass.
"""


def __dataclass_transform__():
    """Add annotations decorator for PyLance."""
    return lambda a: a


[文档]@__dataclass_transform__() def configclass(cls, **kwargs): """Wrapper around `dataclass` functionality to add extra checks and utilities. As of Python 3.7, the standard dataclasses have two main issues which makes them non-generic for configuration use-cases. These include: 1. Requiring a type annotation for all its members. 2. Requiring explicit usage of :meth:`field(default_factory=...)` to reinitialize mutable variables. This function provides a decorator that wraps around Python's `dataclass`_ utility to deal with the above two issues. It also provides additional helper functions for dictionary <-> class conversion and easily copying class instances. Usage: .. code-block:: python from dataclasses import MISSING from omni.isaac.lab.utils.configclass import configclass @configclass class ViewerCfg: eye: list = [7.5, 7.5, 7.5] # field missing on purpose lookat: list = field(default_factory=[0.0, 0.0, 0.0]) @configclass class EnvCfg: num_envs: int = MISSING episode_length: int = 2000 viewer: ViewerCfg = ViewerCfg() # create configuration instance env_cfg = EnvCfg(num_envs=24) # print information as a dictionary print(env_cfg.to_dict()) # create a copy of the configuration env_cfg_copy = env_cfg.copy() # replace arbitrary fields using keyword arguments env_cfg_copy = env_cfg_copy.replace(num_envs=32) Args: cls: The class to wrap around. **kwargs: Additional arguments to pass to :func:`dataclass`. Returns: The wrapped class. .. _dataclass: https://docs.python.org/3/library/dataclasses.html """ # add type annotations _add_annotation_types(cls) # add field factory _process_mutable_types(cls) # copy mutable members # note: we check if user defined __post_init__ function exists and augment it with our own if hasattr(cls, "__post_init__"): setattr(cls, "__post_init__", _combined_function(cls.__post_init__, _custom_post_init)) else: setattr(cls, "__post_init__", _custom_post_init) # add helper functions for dictionary conversion setattr(cls, "to_dict", _class_to_dict) setattr(cls, "from_dict", _update_class_from_dict) setattr(cls, "replace", _replace_class_with_kwargs) setattr(cls, "copy", _copy_class) setattr(cls, "validate", _validate) # wrap around dataclass cls = dataclass(cls, **kwargs) # return wrapped class return cls
""" Dictionary <-> Class operations. These are redefined here to add new docstrings. """ def _class_to_dict(obj: object) -> dict[str, Any]: """Convert an object into dictionary recursively. Args: obj: The object to convert. Returns: Converted dictionary mapping. """ return class_to_dict(obj) def _update_class_from_dict(obj, data: dict[str, Any]) -> None: """Reads a dictionary and sets object variables recursively. This function performs in-place update of the class member attributes. Args: obj: The object to update. data: Input (nested) dictionary to update from. Raises: TypeError: When input is not a dictionary. ValueError: When dictionary has a value that does not match default config type. KeyError: When dictionary has a key that does not exist in the default config type. """ update_class_from_dict(obj, data, _ns="") def _replace_class_with_kwargs(obj: object, **kwargs) -> object: """Return a new object replacing specified fields with new values. This is especially useful for frozen classes. Example usage: .. code-block:: python @configclass(frozen=True) class C: x: int y: int c = C(1, 2) c1 = c.replace(x=3) assert c1.x == 3 and c1.y == 2 Args: obj: The object to replace. **kwargs: The fields to replace and their new values. Returns: The new object. """ return replace(obj, **kwargs) def _copy_class(obj: object) -> object: """Return a new object with the same fields as the original.""" return replace(obj) """ Private helper functions. """ def _add_annotation_types(cls): """Add annotations to all elements in the dataclass. By definition in Python, a field is defined as a class variable that has a type annotation. In case type annotations are not provided, dataclass ignores those members when :func:`__dict__()` is called. This function adds these annotations to the class variable to prevent any issues in case the user forgets to specify the type annotation. This makes the following a feasible operation: @dataclass class State: pos = (0.0, 0.0, 0.0) ^^ If the function is NOT used, the following type-error is returned: TypeError: 'pos' is a field but has no type annotation """ # get type hints hints = {} # iterate over class inheritance # we add annotations from base classes first for base in reversed(cls.__mro__): # check if base is object if base is object: continue # get base class annotations ann = base.__dict__.get("__annotations__", {}) # directly add all annotations from base class hints.update(ann) # iterate over base class members # Note: Do not change this to dir(base) since it orders the members alphabetically. # This is not desirable since the order of the members is important in some cases. for key in base.__dict__: # get class member value = getattr(base, key) # skip members if _skippable_class_member(key, value, hints): continue # add type annotations for members that don't have explicit type annotations # for these, we deduce the type from the default value if not isinstance(value, type): if key not in hints: # check if var type is not MISSING # we cannot deduce type from MISSING! if value is MISSING: raise TypeError( f"Missing type annotation for '{key}' in class '{cls.__name__}'." " Please add a type annotation or set a default value." ) # add type annotation hints[key] = type(value) elif key != value.__name__: # note: we don't want to add type annotations for nested configclass. Thus, we check if # the name of the type matches the name of the variable. # since Python 3.10, type hints are stored as strings hints[key] = f"type[{value.__name__}]" # Note: Do not change this line. `cls.__dict__.get("__annotations__", {})` is different from # `cls.__annotations__` because of inheritance. cls.__annotations__ = cls.__dict__.get("__annotations__", {}) cls.__annotations__ = hints def _validate(obj: object, prefix: str = "") -> list[str]: """Check the validity of configclass object. This function checks if the object is a valid configclass object. A valid configclass object contains no MISSING entries. Args: obj: The object to check. prefix: The prefix to add to the missing fields. Defaults to ''. Returns: A list of missing fields. Raises: TypeError: When the object is not a valid configuration object. """ missing_fields = [] if type(obj) is type(MISSING): missing_fields.append(prefix) return missing_fields elif isinstance(obj, (list, tuple)): for index, item in enumerate(obj): current_path = f"{prefix}[{index}]" missing_fields.extend(_validate(item, prefix=current_path)) return missing_fields elif isinstance(obj, dict): obj_dict = obj elif hasattr(obj, "__dict__"): obj_dict = obj.__dict__ else: return missing_fields for key, value in obj_dict.items(): # disregard builtin attributes if key.startswith("__"): continue current_path = f"{prefix}.{key}" if prefix else key missing_fields.extend(_validate(value, prefix=current_path)) # raise an error only once at the top-level call if prefix == "" and missing_fields: formatted_message = "\n".join(f" - {field}" for field in missing_fields) raise TypeError( f"Missing values detected in object {obj.__class__.__name__} for the following" f" fields:\n{formatted_message}\n" ) return missing_fields def _process_mutable_types(cls): """Initialize all mutable elements through :obj:`dataclasses.Field` to avoid unnecessary complaints. By default, dataclass requires usage of :obj:`field(default_factory=...)` to reinitialize mutable objects every time a new class instance is created. If a member has a mutable type and it is created without specifying the `field(default_factory=...)`, then Python throws an error requiring the usage of `default_factory`. Additionally, Python only explicitly checks for field specification when the type is a list, set or dict. This misses the use-case where the type is class itself. Thus, the code silently carries a bug with it which can lead to undesirable effects. This function deals with this issue This makes the following a feasible operation: @dataclass class State: pos: list = [0.0, 0.0, 0.0] ^^ If the function is NOT used, the following value-error is returned: ValueError: mutable default <class 'list'> for field pos is not allowed: use default_factory """ # note: Need to set this up in the same order as annotations. Otherwise, it # complains about missing positional arguments. ann = cls.__dict__.get("__annotations__", {}) # iterate over all class members and store them in a dictionary class_members = {} for base in reversed(cls.__mro__): # check if base is object if base is object: continue # iterate over base class members for key in base.__dict__: # get class member f = getattr(base, key) # skip members if _skippable_class_member(key, f): continue # store class member if it is not a type or if it is already present in annotations if not isinstance(f, type) or key in ann: class_members[key] = f # iterate over base class data fields # in previous call, things that became a dataclass field were removed from class members # so we need to add them back here as a dataclass field directly for key, f in base.__dict__.get("__dataclass_fields__", {}).items(): # store class member if not isinstance(f, type): class_members[key] = f # check that all annotations are present in class members # note: mainly for debugging purposes if len(class_members) != len(ann): raise ValueError( f"In class '{cls.__name__}', number of annotations ({len(ann)}) does not match number of class members" f" ({len(class_members)}). Please check that all class members have type annotations and/or a default" " value. If you don't want to specify a default value, please use the literal `dataclasses.MISSING`." ) # iterate over annotations and add field factory for mutable types for key in ann: # find matching field in class value = class_members.get(key, MISSING) # check if key belongs to ClassVar # in that case, we cannot use default_factory! origin = getattr(ann[key], "__origin__", None) if origin is ClassVar: continue # check if f is MISSING # note: commented out for now since it causes issue with inheritance # of dataclasses when parent have some positional and some keyword arguments. # Ref: https://stackoverflow.com/questions/51575931/class-inheritance-in-python-3-7-dataclasses # TODO: check if this is fixed in Python 3.10 # if f is MISSING: # continue if isinstance(value, Field): setattr(cls, key, value) elif not isinstance(value, type): # create field factory for mutable types value = field(default_factory=_return_f(value)) setattr(cls, key, value) def _custom_post_init(obj): """Deepcopy all elements to avoid shared memory issues for mutable objects in dataclasses initialization. This function is called explicitly instead of as a part of :func:`_process_mutable_types()` to prevent mapping proxy type i.e. a read only proxy for mapping objects. The error is thrown when using hierarchical data-classes for configuration. """ for key in dir(obj): # skip dunder members if key.startswith("__"): continue # get data member value = getattr(obj, key) # check annotation ann = obj.__class__.__dict__.get(key) # duplicate data members that are mutable if not callable(value) and not isinstance(ann, property): setattr(obj, key, deepcopy(value)) def _combined_function(f1: Callable, f2: Callable) -> Callable: """Combine two functions into one. Args: f1: The first function. f2: The second function. Returns: The combined function. """ def _combined(*args, **kwargs): # call both functions f1(*args, **kwargs) f2(*args, **kwargs) return _combined """ Helper functions """ def _skippable_class_member(key: str, value: Any, hints: dict | None = None) -> bool: """Check if the class member should be skipped in configclass processing. The following members are skipped: * Dunder members: ``__name__``, ``__module__``, ``__qualname__``, ``__annotations__``, ``__dict__``. * Manually-added special class functions: From :obj:`_CONFIGCLASS_METHODS`. * Members that are already present in the type annotations. * Functions bounded to class object or class. * Properties bounded to class object. Args: key: The class member name. value: The class member value. hints: The type hints for the class. Defaults to None, in which case, the members existence in type hints are not checked. Returns: True if the class member should be skipped, False otherwise. """ # skip dunder members if key.startswith("__"): return True # skip manually-added special class functions if key in _CONFIGCLASS_METHODS: return True # check if key is already present if hints is not None and key in hints: return True # skip functions bounded to class if callable(value): # FIXME: This doesn't yet work for static methods because they are essentially seen as function types. # check for class methods if isinstance(value, types.MethodType): return True # check for instance methods signature = inspect.signature(value) if "self" in signature.parameters or "cls" in signature.parameters: return True # skip property methods if isinstance(value, property): return True # Otherwise, don't skip return False def _return_f(f: Any) -> Callable[[], Any]: """Returns default factory function for creating mutable/immutable variables. This function should be used to create default factory functions for variables. Example: .. code-block:: python value = field(default_factory=_return_f(value)) setattr(cls, key, value) """ def _wrap(): if isinstance(f, Field): if f.default_factory is MISSING: return deepcopy(f.default) else: return f.default_factory else: return deepcopy(f) return _wrap