के लिए संदर्भ ultralytics/utils/__init__.py

class TQDM(tqdm_original):
    """
    Custom Ultralytics tqdm class with different default arguments.

    Args:
        *args (list): Positional arguments passed to original tqdm.
        **kwargs (any): Keyword arguments, with custom defaults applied.
    """

    def __init__(self, *args, **kwargs):
        """
        Initialize custom Ultralytics tqdm class with different default arguments.

        Note these can still be overridden when calling TQDM.
        """
        kwargs["disable"] = not VERBOSE or kwargs.get("disable", False)  # logical 'and' with default value if passed
        kwargs.setdefault("bar_format", TQDM_BAR_FORMAT)  # override default value if passed
        super().__init__(*args, **kwargs)

class SimpleClass:
    """Ultralytics SimpleClass is a base class providing helpful string representation, error reporting, and attribute
    access methods for easier debugging and usage.
    """

    def __str__(self):
        """Return a human-readable string representation of the object."""
        attr = []
        for a in dir(self):
            v = getattr(self, a)
            if not callable(v) and not a.startswith("_"):
                if isinstance(v, SimpleClass):
                    # Display only the module and class name for subclasses
                    s = f"{a}: {v.__module__}.{v.__class__.__name__} object"
                else:
                    s = f"{a}: {repr(v)}"
                attr.append(s)
        return f"{self.__module__}.{self.__class__.__name__} object with attributes:\n\n" + "\n".join(attr)

    def __repr__(self):
        """Return a machine-readable string representation of the object."""
        return self.__str__()

    def __getattr__(self, attr):
        """Custom attribute access error message with helpful information."""
        name = self.__class__.__name__
        raise AttributeError(f"'{name}' object has no attribute '{attr}'. See valid attributes below.\n{self.__doc__}")

class IterableSimpleNamespace(SimpleNamespace):
    """Ultralytics IterableSimpleNamespace is an extension class of SimpleNamespace that adds iterable functionality and
    enables usage with dict() and for loops.
    """

    def __iter__(self):
        """Return an iterator of key-value pairs from the namespace's attributes."""
        return iter(vars(self).items())

    def __str__(self):
        """Return a human-readable string representation of the object."""
        return "\n".join(f"{k}={v}" for k, v in vars(self).items())

    def __getattr__(self, attr):
        """Custom attribute access error message with helpful information."""
        name = self.__class__.__name__
        raise AttributeError(
            f"""
            '{name}' object has no attribute '{attr}'. This may be caused by a modified or out of date ultralytics
            'default.yaml' file.\nPlease update your code with 'pip install -U ultralytics' and if necessary replace
            {DEFAULT_CFG_PATH} with the latest version from
            https://github.com/ultralytics/ultralytics/blob/main/ultralytics/cfg/default.yaml
            """
        )

    def get(self, key, default=None):
        """Return the value of the specified key if it exists; otherwise, return the default value."""
        return getattr(self, key, default)

class ThreadingLocked:
    """
    A decorator class for ensuring thread-safe execution of a function or method. This class can be used as a decorator
    to make sure that if the decorated function is called from multiple threads, only one thread at a time will be able
    to execute the function.

    Attributes:
        lock (threading.Lock): A lock object used to manage access to the decorated function.

    Example:
        ```python
        from ultralytics.utils import ThreadingLocked

        @ThreadingLocked()
        def my_function():
            # Your code here
            pass
        ```
    """

    def __init__(self):
        """Initializes the decorator class for thread-safe execution of a function or method."""
        self.lock = threading.Lock()

    def __call__(self, f):
        """Run thread-safe execution of function or method."""
        from functools import wraps

        @wraps(f)
        def decorated(*args, **kwargs):
            """Applies thread-safety to the decorated function or method."""
            with self.lock:
                return f(*args, **kwargs)

        return decorated

class TryExcept(contextlib.ContextDecorator):
    """
    Ultralytics TryExcept class. Use as @TryExcept() decorator or 'with TryExcept():' context manager.

    Examples:
        As a decorator:
        >>> @TryExcept(msg="Error occurred in func", verbose=True)
        >>> def func():
        >>>    # Function logic here
        >>>     pass

        As a context manager:
        >>> with TryExcept(msg="Error occurred in block", verbose=True):
        >>>     # Code block here
        >>>     pass
    """

    def __init__(self, msg="", verbose=True):
        """Initialize TryExcept class with optional message and verbosity settings."""
        self.msg = msg
        self.verbose = verbose

    def __enter__(self):
        """Executes when entering TryExcept context, initializes instance."""
        pass

    def __exit__(self, exc_type, value, traceback):
        """Defines behavior when exiting a 'with' block, prints error message if necessary."""
        if self.verbose and value:
            print(emojis(f"{self.msg}{': ' if self.msg else ''}{value}"))
        return True

class Retry(contextlib.ContextDecorator):
    """
    Retry class for function execution with exponential backoff.

    Can be used as a decorator or a context manager to retry a function or block of code on exceptions, up to a
    specified number of times with an exponentially increasing delay between retries.

    Examples:
        Example usage as a decorator:
        >>> @Retry(times=3, delay=2)
        >>> def test_func():
        >>>     # Replace with function logic that may raise exceptions
        >>>     return True

        Example usage as a context manager:
        >>> with Retry(times=3, delay=2):
        >>>     # Replace with code block that may raise exceptions
        >>>     pass
    """

    def __init__(self, times=3, delay=2):
        """Initialize Retry class with specified number of retries and delay."""
        self.times = times
        self.delay = delay
        self._attempts = 0

    def __call__(self, func):
        """Decorator implementation for Retry with exponential backoff."""

        def wrapped_func(*args, **kwargs):
            """Applies retries to the decorated function or method."""
            self._attempts = 0
            while self._attempts < self.times:
                try:
                    return func(*args, **kwargs)
                except Exception as e:
                    self._attempts += 1
                    print(f"Retry {self._attempts}/{self.times} failed: {e}")
                    if self._attempts >= self.times:
                        raise e
                    time.sleep(self.delay * (2**self._attempts))  # exponential backoff delay

        return wrapped_func

    def __enter__(self):
        """Enter the runtime context related to this object."""
        self._attempts = 0

    def __exit__(self, exc_type, exc_value, traceback):
        """Exit the runtime context related to this object with exponential backoff."""
        if exc_type is not None:
            self._attempts += 1
            if self._attempts < self.times:
                print(f"Retry {self._attempts}/{self.times} failed: {exc_value}")
                time.sleep(self.delay * (2**self._attempts))  # exponential backoff delay
                return True  # Suppresses the exception and retries
        return False  # Re-raises the exception if retries are exhausted

class SettingsManager(dict):
    """
    Manages Ultralytics settings stored in a YAML file.

    Args:
        file (str | Path): Path to the Ultralytics settings YAML file. Default is USER_CONFIG_DIR / 'settings.yaml'.
        version (str): Settings version. In case of local version mismatch, new default settings will be saved.
    """

    def __init__(self, file=SETTINGS_YAML, version="0.0.4"):
        """Initialize the SettingsManager with default settings, load and validate current settings from the YAML
        file.
        """
        import copy
        import hashlib

        from ultralytics.utils.checks import check_version
        from ultralytics.utils.torch_utils import torch_distributed_zero_first

        root = GIT_DIR or Path()
        datasets_root = (root.parent if GIT_DIR and is_dir_writeable(root.parent) else root).resolve()

        self.file = Path(file)
        self.version = version
        self.defaults = {
            "settings_version": version,
            "datasets_dir": str(datasets_root / "datasets"),
            "weights_dir": str(root / "weights"),
            "runs_dir": str(root / "runs"),
            "uuid": hashlib.sha256(str(uuid.getnode()).encode()).hexdigest(),
            "sync": True,
            "api_key": "",
            "openai_api_key": "",
            "clearml": True,  # integrations
            "comet": True,
            "dvc": True,
            "hub": True,
            "mlflow": True,
            "neptune": True,
            "raytune": True,
            "tensorboard": True,
            "wandb": True,
        }

        super().__init__(copy.deepcopy(self.defaults))

        with torch_distributed_zero_first(RANK):
            if not self.file.exists():
                self.save()

            self.load()
            correct_keys = self.keys() == self.defaults.keys()
            correct_types = all(type(a) is type(b) for a, b in zip(self.values(), self.defaults.values()))
            correct_version = check_version(self["settings_version"], self.version)
            help_msg = (
                f"\nView settings with 'yolo settings' or at '{self.file}'"
                "\nUpdate settings with 'yolo settings key=value', i.e. 'yolo settings runs_dir=path/to/dir'. "
                "For help see https://docs.ultralytics.com/quickstart/#ultralytics-settings."
            )
            if not (correct_keys and correct_types and correct_version):
                LOGGER.warning(
                    "WARNING ⚠️ Ultralytics settings reset to default values. This may be due to a possible problem "
                    f"with your settings or a recent ultralytics package update. {help_msg}"
                )
                self.reset()

            if self.get("datasets_dir") == self.get("runs_dir"):
                LOGGER.warning(
                    f"WARNING ⚠️ Ultralytics setting 'datasets_dir: {self.get('datasets_dir')}' "
                    f"must be different than 'runs_dir: {self.get('runs_dir')}'. "
                    f"Please change one to avoid possible issues during training. {help_msg}"
                )

    def load(self):
        """Loads settings from the YAML file."""
        super().update(yaml_load(self.file))

    def save(self):
        """Saves the current settings to the YAML file."""
        yaml_save(self.file, dict(self))

    def update(self, *args, **kwargs):
        """Updates a setting value in the current settings."""
        super().update(*args, **kwargs)
        self.save()

    def reset(self):
        """Resets the settings to default and saves them."""
        self.clear()
        self.update(self.defaults)
        self.save()