code: def squeeze_output_dim_1(
      result, in_shapes, input_types, is_scal=True
  ):
      """Determine if the output needs to be squeezed on dim 1.
  
      This happens if the user represents scalars as array of shapes:
      [n_samples,] instead of [n_samples, 1]
      Dimension 1 is squeezed by default if input_type is 'scalar'.
      Dimension 1 is not squeezed if the user inputs at least one scalar with
      a singleton in dimension 1.
  
      Parameters
      ----------
      result: array-like
          Result output by the function, before reshaping.
      in_shapes : list
          Initial shapes of input parameters, as entered by the user.
      input_types : list
          Associated list of input_type of input parameters.
  
      Returns
      -------
      squeeze : bool
          Boolean deciding whether to squeeze dim 1 of the output.
      """
      if not is_scal:
          return False
      if not is_scalar(result):
          return False
  
      for shape, input_type in zip(in_shapes, input_types):
          if input_type == "scalar":
              ndim = len(shape)
              if ndim > 2:
                  raise ValueError(
                      "The ndim of a scalar cannot be > 2."
                  )
              if ndim == 2:
                  return False
      return True
  
file_path: geomstats/geomstats/vectorization.py
imports: import math
  import geomstats.backend
label_desc: Use image node_id 15 for calling a global function with example usage: squeeze_output_dim_1(result, in_shapes, input_types, is_scal) and returns: True, False, False, False