code: def read_annotations(
      fname, sfreq="auto", uint16_codec=None, encoding="utf8"
  ) -> Annotations:
      r"""Read annotations from a file.
  
      This function reads a ``.fif``, ``.fif.gz``, ``.vmrk``, ``.amrk``,
      ``.edf``, ``.txt``, ``.csv``, ``.cnt``, ``.cef``, or ``.set`` file and
      makes an :class:`mne.Annotations` object.
  
      Parameters
      ----------
      fname : path-like
          The filename.
      sfreq : float | ``'auto'``
          The sampling frequency in the file. This parameter is necessary for
          \*.vmrk, \*.amrk, and \*.cef files as Annotations are expressed in
          seconds and \*.vmrk/\*.amrk/\*.cef files are in samples. For any other
          file format, ``sfreq`` is omitted. If set to 'auto' then the ``sfreq``
          is taken from the respective info file of the same name with according
          file extension (\*.vhdr/\*.ahdr for brainvision; \*.dap for Curry 7;
          \*.cdt.dpa for Curry 8). So data.vmrk/amrk looks for sfreq in
          data.vhdr/ahdr, data.cef looks in data.dap and data.cdt.cef looks in
          data.cdt.dpa.
      uint16_codec : str | None
          This parameter is only used in EEGLAB (\*.set) and omitted otherwise.
          If your \*.set file contains non-ascii characters, sometimes reading
          it may fail and give rise to error message stating that "buffer is
          too small". ``uint16_codec`` allows to specify what codec (for example:
          ``'latin1'`` or ``'utf-8'``) should be used when reading character
          arrays and can therefore help you solve this problem.
      %(encoding_edf)s
          Only used when reading EDF annotations.
  
      Returns
      -------
      annot : instance of Annotations
          The annotations.
  
      Notes
      -----
      The annotations stored in a ``.csv`` require the onset columns to be
      timestamps. If you have onsets as floats (in seconds), you should use the
      ``.txt`` extension.
      """
      from .io.brainvision.brainvision import (
          _read_annotations_brainvision,
      )
      from .io.cnt.cnt import _read_annotations_cnt
      from .io.ctf.markers import _read_annotations_ctf
      from .io.curry.curry import _read_annotations_curry
      from .io.edf.edf import _read_annotations_edf
      from .io.eeglab.eeglab import _read_annotations_eeglab
  
      fname = str(
          _check_fname(
              fname,
              overwrite="read",
              must_exist=True,
              need_dir=str(fname).endswith(".ds"),  # for CTF
              name="fname",
          )
      )
      name = op.basename(fname)
      if name.endswith(("fif", "fif.gz")):
          # Read FiF files
          ff, tree, _ = fiff_open(fname, preload=False)
          with ff as fid:
              annotations = _read_annotations_fif(fid, tree)
      elif name.endswith("txt"):
          annotations = _read_annotations_txt(fname)
  
      elif name.endswith(("vmrk", "amrk")):
          annotations = _read_annotations_brainvision(
              fname, sfreq=sfreq
          )
  
      elif name.endswith("csv"):
          annotations = _read_annotations_csv(fname)
  
      elif name.endswith("cnt"):
          annotations = _read_annotations_cnt(fname)
  
      elif name.endswith("ds"):
          annotations = _read_annotations_ctf(fname)
  
      elif name.endswith("cef"):
          annotations = _read_annotations_curry(fname, sfreq=sfreq)
  
      elif name.endswith("set"):
          annotations = _read_annotations_eeglab(
              fname, uint16_codec=uint16_codec
          )
  
      elif name.endswith(("edf", "bdf", "gdf")):
          annotations = _read_annotations_edf(fname, encoding=encoding)
  
      elif name.startswith("events_") and fname.endswith("mat"):
          annotations = _read_brainstorm_annotations(fname)
      else:
          raise OSError('Unknown annotation file format "%s"' % fname)
  
      if annotations is None:
          raise OSError('No annotation data found in file "%s"' % fname)
      return annotations
  
imports: import json
  import os.path
  import re
  import warnings
  from collections import Counter, OrderedDict
  from collections.abc import Iterable
  from copy import deepcopy
  from datetime import datetime, timedelta, timezone
  from itertools import takewhile
  from textwrap import shorten
  import numpy
  from scipy.io import loadmat
  from ._fiff.constants import FIFF
  from ._fiff.open import fiff_open
  from ._fiff.tag import read_tag
  from ._fiff.tree import dir_tree_find
  from ._fiff.write import _safe_name_list, end_block, start_and_end_file, start_block, write_double, write_float, write_name_list_sanitized, write_string
  from .utils import _check_dict_keys, _check_dt, _check_fname, _check_option, _check_pandas_installed, _check_time_format, _convert_times, _DefaultEventParser, _dt_to_stamp, _is_numeric, _mask_to_onsets_offsets, _on_missing, _pl, _stamp_to_dt, _validate_type, check_fname, fill_doc, int_like, logger, verbose, warn
label_desc: Use image node_id 10 for calling a global function with example usage: read_annotations(fname, sfreq, uint16_codec, encoding) and returns: annotations