Builds a variational distribution from a location-scale family.
tfp.experimental.vi.build_trainable_location_scale_distribution(
initial_loc, initial_scale, event_ndims,
distribution_fn=tfp.distributions.Normal, validate_args=False, name=None
)
Args |
initial_loc
|
Float Tensor initial location.
|
initial_scale
|
Float Tensor initial scale.
|
event_ndims
|
Integer Tensor number of event dimensions in initial_loc .
|
distribution_fn
|
Optional constructor for a tfd.Distribution instance
in a location-scale family. This should have signature dist =
distribution_fn(loc, scale, validate_args) .
Default value: tfd.Normal .
|
validate_args
|
Python bool . Whether to validate input with asserts. This
imposes a runtime cost. If validate_args is False , and the inputs are
invalid, correct behavior is not guaranteed.
Default value: False .
|
name
|
Python str name prefixed to ops created by this function.
Default value: None (i.e.,
'build_trainable_location_scale_distribution').
|
Returns |
posterior_dist
|
A tfd.Distribution instance.
|