Module: contrib.distributions.bijectors
Module: tf.contrib.distributions.bijectors
Module tf.contrib.distributions.bijectors
Defined in tensorflow/contrib/distributions/python/ops/bijectors/__init__.py
.
Bijector Ops.
Classes
class Affine
: Compute Y = g(X; shift, scale) = scale @ X + shift
.
class AffineLinearOperator
: Compute Y = g(X; shift, scale) = scale @ X + shift
.
class Bijector
: Interface for invertible transformations of a Distribution
sample.
class Chain
: Bijector which applies a sequence of bijectors.
class CholeskyOuterProduct
: Compute g(X) = X @ X.T
; X is lower-triangular, positive-diagonal matrix.
class ConditionalBijector
: Conditional Bijector is a Bijector that allows intrinsic conditioning.
class Exp
: Compute Y = g(X) = exp(X)
.
class Identity
: Compute Y = g(X) = X.
class Inline
: Bijector constructed from custom callables.
class Invert
: Bijector which inverts another Bijector.
class PowerTransform
: Compute Y = g(X) = (1 + X * c)**(1 / c), X >= -1 / c
.
class Sigmoid
: Bijector which computes Y = g(X) = 1 / (1 + exp(-X))
.
class SigmoidCentered
: Bijector which computes Y = g(X) = exp([X 0]) / (1 + exp(-X)).
class SoftmaxCentered
: Bijector which computes Y = g(X) = exp([X 0]) / sum(exp([X 0]))
.
class Softplus
: Bijector which computes Y = g(X) = Log[1 + exp(X)]
.
© 2017 The TensorFlow Authors. All rights reserved.
Licensed under the Creative Commons Attribution License 3.0.
Code samples licensed under the Apache 2.0 License.
https://www.tensorflow.org/api_docs/python/tf/contrib/distributions/bijectors