tfp.sts.sample_uniform_initial_state
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Initialize from a uniform [-2, 2] distribution in unconstrained space. (deprecated)
tfp.sts.sample_uniform_initial_state(
parameter, return_constrained=True, init_sample_shape=(), seed=None
)
Deprecated: THIS FUNCTION IS DEPRECATED. It will be removed after 2022-03-01.
Instructions for updating:
Please use tf.random.stateless_uniform
or similar.
Args
parameter
sts.Parameter
named tuple instance.
return_constrained
if True
, re-applies the constraining bijector
to return initializations in the original domain. Otherwise, returns
initializations in the unconstrained space.
Default value: True
.
init_sample_shape
sample_shape
of the sampled initializations.
Default value: []
.
seed
PRNG seed; see tfp.random.sanitize_seed
for details.
Returns
uniform_initializer
Tensor
of shape concat([init_sample_shape,
parameter.prior.batch_shape, transformed_event_shape])
, where
transformed_event_shape
is parameter.prior.event_shape
, if
return_constrained=True
, and otherwise it is
parameter.bijector.inverse_event_shape(parameteter.prior.event_shape)
.
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Last updated 2023-11-21 UTC.
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