tf.contrib.distributions.bijectors.ConditionalBijector

Conditional Bijector is a Bijector that allows intrinsic conditioning.

Inherits From: Bijector

@abc.abstractmethod
tf.contrib.distributions.bijectors.ConditionalBijector(
    graph_parents=None, is_constant_jacobian=False, validate_args=False, dtype=None,
    forward_min_event_ndims=None, inverse_min_event_ndims=None, name=None
)

Args
graph_parents	Python list of graph prerequisites of this Bijector.
is_constant_jacobian	Python bool indicating that the Jacobian matrix is not a function of the input.
validate_args	Python bool, default False. Whether to validate input with asserts. If validate_args is False, and the inputs are invalid, correct behavior is not guaranteed.
dtype	tf.dtype supported by this Bijector. None means dtype is not enforced.
forward_min_event_ndims	Python integer indicating the minimum number of dimensions forward operates on.
inverse_min_event_ndims	Python integer indicating the minimum number of dimensions inverse operates on. Will be set to forward_min_event_ndims by default, if no value is provided.
name	The name to give Ops created by the initializer.

Raises
ValueError	If neither forward_min_event_ndims and inverse_min_event_ndims are specified, or if either of them is negative.
ValueError	If a member of graph_parents is not a Tensor.

Attributes
dtype	dtype of Tensors transformable by this distribution.
forward_min_event_ndims	Returns the minimal number of dimensions bijector.forward operates on.
graph_parents	Returns this Bijector's graph_parents as a Python list.
inverse_min_event_ndims	Returns the minimal number of dimensions bijector.inverse operates on.
is_constant_jacobian	Returns true iff the Jacobian matrix is not a function of x. Note: Jacobian matrix is either constant for both forward and inverse or neither.
name	Returns the string name of this Bijector.
validate_args	Returns True if Tensor arguments will be validated.

Methods

forward

View source

forward(
    x, name='forward', **condition_kwargs
)

kwargs:

• **condition_kwargs: Named arguments forwarded to subclass implementation.

forward_event_shape

View source

forward_event_shape(
    input_shape
)

Shape of a single sample from a single batch as a TensorShape.

Same meaning as forward_event_shape_tensor. May be only partially defined.

Args
input_shape	TensorShape indicating event-portion shape passed into forward function.

Returns
forward_event_shape_tensor	TensorShape indicating event-portion shape after applying forward. Possibly unknown.

forward_event_shape_tensor

View source

forward_event_shape_tensor(
    input_shape, name='forward_event_shape_tensor'
)

Shape of a single sample from a single batch as an int32 1D Tensor.

Args
input_shape	Tensor, int32 vector indicating event-portion shape passed into forward function.
name	name to give to the op

Returns
forward_event_shape_tensor	Tensor, int32 vector indicating event-portion shape after applying forward.

forward_log_det_jacobian

View source

forward_log_det_jacobian(
    x, event_ndims, name='forward_log_det_jacobian', **condition_kwargs
)

kwargs:

• **condition_kwargs: Named arguments forwarded to subclass implementation.

inverse

View source

inverse(
    y, name='inverse', **condition_kwargs
)

kwargs:

• **condition_kwargs: Named arguments forwarded to subclass implementation.

inverse_event_shape

View source

inverse_event_shape(
    output_shape
)

Shape of a single sample from a single batch as a TensorShape.

Same meaning as inverse_event_shape_tensor. May be only partially defined.

Args
output_shape	TensorShape indicating event-portion shape passed into inverse function.

Returns
inverse_event_shape_tensor	TensorShape indicating event-portion shape after applying inverse. Possibly unknown.

inverse_event_shape_tensor

View source

inverse_event_shape_tensor(
    output_shape, name='inverse_event_shape_tensor'
)

Shape of a single sample from a single batch as an int32 1D Tensor.

Args
output_shape	Tensor, int32 vector indicating event-portion shape passed into inverse function.
name	name to give to the op

Returns
inverse_event_shape_tensor	Tensor, int32 vector indicating event-portion shape after applying inverse.

inverse_log_det_jacobian

View source

inverse_log_det_jacobian(
    y, event_ndims, name='inverse_log_det_jacobian', **condition_kwargs
)

kwargs:

• **condition_kwargs: Named arguments forwarded to subclass implementation.