class_docstr: Tangent space of M for Spherical distributions in R^n.
code: def _transform_general(self, x, f, **kwargs):
      basis = self.compute_spherical_basis(x)
      new_basis = spaces.compute_new_basis_tensor(f, x, basis)
      new_log_volume = spaces.volume_coefficient(
          distribution_util.move_dimension(new_basis, 0, -2)
      )
      # The original basis has 0 log_volume.
      return new_log_volume, spaces.GeneralSpace(
          spaces.DenseBasis(new_basis),
          computed_log_volume=new_log_volume,
      )
  
file_path: probability/tensorflow_probability/python/experimental/tangent_spaces/spherical.py
imports: import tensorflow.compat.v2
  from tensorflow_probability.python.experimental.linalg import linear_operator_row_block
  from tensorflow_probability.python.experimental.tangent_spaces import spaces
  from tensorflow_probability.python.internal import distribution_util
  from tensorflow_probability.python.internal import prefer_static
label_desc: Use image node_id 2 for calling the SphericalSpace obj's underlying member method code with example usage: obj._transform_general(x, f) and returns: new_log_volume,  spaces