class_docstr: A set of patterns that candidate strings will be matched against.
  
  A candidate is composed of a list of segments separated by ``separator``, e.g. "foo.bar.baz".
  
  A pattern contains one or more segments. Segments can be:
      - A literal string (e.g. "foo"), which matches exactly.
      - A string containing a wildcard (e.g. "torch*", or "foo*baz*"). The wildcard matches
        any string, including the empty string.
      - A double wildcard ("**"). This matches against zero or more complete segments.
  
  Examples:
      ``torch.**``: matches ``torch`` and all its submodules, e.g. ``torch.nn`` and ``torch.nn.functional``.
      ``torch.*``: matches ``torch.nn`` or ``torch.functional``, but not ``torch.nn.functional``.
      ``torch*.**``: matches ``torch``, ``torchvision``, and all their submodules.
  
  A candidates will match the ``GlobGroup`` if it matches any of the ``include`` patterns and
  none of the ``exclude`` patterns.
  
  Args:
      include (Union[str, Iterable[str]]): A string or list of strings,
          each representing a pattern to be matched against. A candidate
          will match if it matches *any* include pattern
      exclude (Union[str, Iterable[str]]): A string or list of strings,
          each representing a pattern to be matched against. A candidate
          will be excluded from matching if it matches *any* exclude pattern.
      separator (str): A string that delimits segments in candidates and
          patterns. By default this is "." which corresponds to how modules are
          named in Python. Another common value for this is "/", which is
          the Unix path separator.
code: def __init__(
      self,
      include: GlobPattern,
      *,
      exclude: GlobPattern = (),
      separator: str = ".",
  ):
      self._dbg = f"GlobGroup(include={include}, exclude={exclude})"
      self.include = GlobGroup._glob_list(include, separator)
      self.exclude = GlobGroup._glob_list(exclude, separator)
      self.separator = separator
  
file_path: pytorch/torch/package/glob_group.py
imports: import re
  from typing import Iterable, Union
label_desc: Use image node_id 1 to create a new GlobGroup object  with example: obj = GlobGroup(include)