code: def transpose(self, axes=None, copy=False):
      if axes is not None and axes != (1, 0):
          raise ValueError(
              "Sparse arrays/matrices do not support "
              "an 'axes' parameter because swapping "
              "dimensions is the only logical permutation."
          )
  
      num_rows, num_cols = self.shape
      max_dim = max(self.shape)
  
      # flip diagonal offsets
      offsets = -self.offsets
  
      # re-align the data matrix
      r = np.arange(len(offsets), dtype=np.intc)[:, None]
      c = (
          np.arange(num_rows, dtype=np.intc)
          - (offsets % max_dim)[:, None]
      )
      pad_amount = max(0, max_dim - self.data.shape[1])
      data = np.hstack(
          (
              self.data,
              np.zeros(
                  (self.data.shape[0], pad_amount),
                  dtype=self.data.dtype,
              ),
          )
      )
      data = data[r, c]
      return self._dia_container(
          (data, offsets), shape=(num_cols, num_rows), copy=copy
      )
  
imports: import numpy
  from ._matrix import spmatrix
  from ._base import issparse, _formats, _spbase, sparray
  from ._data import _data_matrix
  from ._sputils import isshape, upcast_char, getdtype, get_sum_dtype, validateaxis, check_shape
  from ._sparsetools import dia_matvec
label_desc: Use image node_id 12 for calling the _dia_base obj's underlying member method code with example usage: obj.transpose(axes, copy) and returns: self