code: def _coerce_to_dict(input_arg):
      """Construct a dict from the provided arg.
  
      If input_arg is:
        dict then returns it unchanged.
  
        string or collection of Strings or Sequence[int],
        returns a dict {str(value): value, ...}
  
      Parameters
      ----------
      input_arg : String or Collection[str or Int or Sequence[Int]]
       or Dict[str, str or np.array]
          Can be of the form:
           'string'
           ['string_1', 'string_2', ...]
           list/array
           [list/array_1, list/array_2, ...]
           {'string_1': list/array1, ...}
  
      Returns
      -------
      input_args: Dict[str, np.array or str]
  
      """
      if not isinstance(input_arg, dict):
          if isinstance(input_arg, Iterable) and not isinstance(
              input_arg[0], Iterable
          ):
              input_arg = [input_arg]
          input_arg = (
              [input_arg] if isinstance(input_arg, str) else input_arg
          )
          input_arg = {
              str(contrast_): contrast_ for contrast_ in input_arg
          }
      return input_arg
  
imports: import os
  import string
  import warnings
  from collections import OrderedDict
  from collections.abc import Iterable
  from html import escape
  import numpy
  import pandas
  from matplotlib import pyplot
  from nilearn.plotting import plot_glass_brain, plot_roi, plot_stat_map
  from nilearn.plotting.img_plotting import MNI152TEMPLATE
  from nilearn.plotting.matrix_plotting import plot_contrast_matrix, plot_design_matrix
  from nilearn.reporting.html_report import HTMLReport
  from .._utils import fill_doc
  from nilearn._utils import check_niimg
  from nilearn.maskers import NiftiMasker
  from nilearn.reporting.get_clusters_table import get_clusters_table
  from nilearn.reporting.utils import figure_to_svg_quoted
label_desc: Use image node_id 3 for calling a global function with example usage: _coerce_to_dict(input_arg) and returns: input_arg