code: def load_npz(file):
      """Load a sparse matrix from a file using ``.npz`` format.
  
      Parameters
      ----------
      file : str or file-like object
          Either the file name (string) or an open file (file-like object)
          where the data will be loaded.
  
      Returns
      -------
      result : csc_matrix, csr_matrix, bsr_matrix, dia_matrix or coo_matrix
          A sparse matrix containing the loaded data.
  
      Raises
      ------
      IOError
          If the input file does not exist or cannot be read.
  
      See Also
      --------
      scipy.sparse.save_npz: Save a sparse matrix to a file using ``.npz`` format.
      numpy.load: Load several arrays from a ``.npz`` archive.
  
      Examples
      --------
      Store sparse matrix to disk, and load it again:
  
      >>> import scipy.sparse
      >>> sparse_matrix = scipy.sparse.csc_matrix(np.array([[0, 0, 3], [4, 0, 0]]))
      >>> sparse_matrix
      <2x3 sparse matrix of type '<class 'numpy.int64'>'
         with 2 stored elements in Compressed Sparse Column format>
      >>> sparse_matrix.todense()
      matrix([[0, 0, 3],
              [4, 0, 0]], dtype=int64)
  
      >>> scipy.sparse.save_npz('/tmp/sparse_matrix.npz', sparse_matrix)
      >>> sparse_matrix = scipy.sparse.load_npz('/tmp/sparse_matrix.npz')
  
      >>> sparse_matrix
      <2x3 sparse matrix of type '<class 'numpy.int64'>'
          with 2 stored elements in Compressed Sparse Column format>
      >>> sparse_matrix.todense()
      matrix([[0, 0, 3],
              [4, 0, 0]], dtype=int64)
      """
  
      with np.load(file, **PICKLE_KWARGS) as loaded:
          try:
              matrix_format = loaded["format"]
          except KeyError as e:
              raise ValueError(
                  "The file {} does not contain a sparse matrix.".format(
                      file
                  )
              ) from e
  
          matrix_format = matrix_format.item()
  
          if not isinstance(matrix_format, str):
              # Play safe with Python 2 vs 3 backward compatibility;
              # files saved with SciPy < 1.0.0 may contain unicode or bytes.
              matrix_format = matrix_format.decode("ascii")
  
          try:
              cls = getattr(
                  scipy.sparse, "{}_matrix".format(matrix_format)
              )
          except AttributeError as e:
              raise ValueError(
                  'Unknown matrix format "{}"'.format(matrix_format)
              ) from e
  
          if matrix_format in ("csc", "csr", "bsr"):
              return cls(
                  (loaded["data"], loaded["indices"], loaded["indptr"]),
                  shape=loaded["shape"],
              )
          elif matrix_format == "dia":
              return cls(
                  (loaded["data"], loaded["offsets"]),
                  shape=loaded["shape"],
              )
          elif matrix_format == "coo":
              return cls(
                  (loaded["data"], (loaded["row"], loaded["col"])),
                  shape=loaded["shape"],
              )
          else:
              raise NotImplementedError(
                  "Load is not implemented for "
                  "sparse matrix of format {}.".format(matrix_format)
              )
  
label_desc: Use image node_id 2 for calling a global function with example usage: load_npz(file) and returns: cls, cls, cls