Type Affine
Namespace tensorflow.contrib.distributions.bijectors
Parent Bijector
Interfaces IAffine
Compute `Y = g(X; shift, scale) = scale @ X + shift`. Here `scale = c * I + diag(D1) + tril(L) + V @ diag(D2) @ V.T`. In TF parlance, the `scale` term is logically equivalent to:
The `scale` term is applied without necessarily materializing constituent
matrices, i.e., the matmul is [matrix-free](
https://en.wikipedia.org/wiki/Matrix-free_methods) when possible. #### Examples
Show Example
scale = ( scale_identity_multiplier * tf.linalg.tensor_diag(tf.ones(d)) + tf.linalg.tensor_diag(scale_diag) + scale_tril + scale_perturb_factor @ diag(scale_perturb_diag) @ tf.transpose([scale_perturb_factor]) )
Properties
Public properties
object dtype get;
object dtype_dyn get;
object forward_min_event_ndims get;
object forward_min_event_ndims_dyn get;
IList<object> graph_parents get;
object graph_parents_dyn get;
object inverse_min_event_ndims get;
object inverse_min_event_ndims_dyn get;
bool is_constant_jacobian get;
object is_constant_jacobian_dyn get;
object name get;
object name_dyn get;
object PythonObject get;
object scale get;
The `scale` `LinearOperator` in `Y = scale @ X + shift`.
object scale_dyn get;
The `scale` `LinearOperator` in `Y = scale @ X + shift`.
object shift get;
The `shift` `Tensor` in `Y = scale @ X + shift`.
object shift_dyn get;
The `shift` `Tensor` in `Y = scale @ X + shift`.