class_docstr: Tangent space of M for distributions supported on all of R^n.
  
  This subclass covers full-rank distributions on n-dimensional
  manifolds. In this common case we can take the basis to be the
  standard basis for R^n, so we need not explicitly represent it
  at all.
class_docstr_tok: ["Tangent","space","of","M","for","distributions","supported","on","all","of","R^n",".","This","subclass","covers","full-rank","distributions","on","n-dimensional","manifolds",".","In","this","common","case","we","can","take","the","basis","to","be","the","standard","basis","for","R^n",",","so","we","need","not","explicitly","represent","it","at","all","."]
code: def _transform_projection(self, x, f, **kwargs):
      return AxisAlignedSpace(tf.ones_like(x)).transform_projection(
          x, f, **kwargs
      )
  
imports: import tensorflow.compat.v2
  from tensorflow_probability.python.internal import distribution_util
  from tensorflow_probability.python.internal import nest_util
  from tensorflow_probability.python.internal import prefer_static
  from tensorflow_probability.python.internal import tensor_util
  from tensorflow_probability.python.internal import tensorshape_util
label_desc: Use image node_id 3 for calling the FullSpace obj's underlying member method code with example usage: obj._transform_projection(x, f) and returns: AxisAlignedSpace