class_docstr: Tangent space of M for a distribution with axis-aligned subspace support.
  
  This subclass covers cases where the support of the distribution is
  on an axis-aligned subspace, such as lower-triangular matrices. In
  this special case we can represent the standard basis of the
  subspace with a mask. The subclass is designed to support axis-aligned
  injections like the `FillTriangular` `Bijector`.
  
  Any Bijector calling the `transform_projection` method is expected
  to define an `experimental_update_live_dimensions` method.
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docstr: Constructs an AxisAlignedSpace with a set of live dimensions.
  
  Args:
    axis_mask: `Tensor`. A bit-mask of the live dimensions of the space.
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code: def __init__(self, axis_mask):
      """Constructs an AxisAlignedSpace with a set of live dimensions.
  
      Args:
        axis_mask: `Tensor`. A bit-mask of the live dimensions of the space.
      """
      self._axis_mask = axis_mask
  
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 1 to create a new AxisAlignedSpace object from inherited base classes: TangentSpace with example: obj = AxisAlignedSpace(axis_mask)