tensorflow_probability/python/distributions/vector_exponential_linear_operator.py
def _mode_mean_shape(self):
    """Shape for the mode/mean Tensors."""
    shape = tensorshape_util.concatenate(self.batch_shape, self.event_shape)
    has_static_shape = tensorshape_util.is_fully_defined(shape)
    if not has_static_shape:
      shape = tf.concat([
          self.batch_shape_tensor(),
          self.event_shape_tensor(),
      ], 0)
    return shape
def _mode_mean_shape(self):
    """Shape for the mode/mean Tensors."""
    shape = tensorshape_util.concatenate(self.batch_shape, self.event_shape)
    has_static_shape = tensorshape_util.is_fully_defined(shape)
    if not has_static_shape:
      shape = tf.concat([
          self.batch_shape_tensor(),
          self.event_shape_tensor(),
      ], 0)
    return shape
def _mode_mean_shape ( self ) : shape = tensorshape_util . concatenate ( self . batch_shape , self . event_shape ) has_static_shape = tensorshape_util . is_fully_defined ( shape ) if not has_static_shape : shape = tf . concat ( [ self . batch_shape_tensor ( ) , self . event_shape_tensor ( ) , ] , 0 ) return shape
Shape for the mode/mean Tensors.
Shape for the mode / mean Tensors .