class_docstr: Multivariate normal that forces some sample dimensions to zero.
  
  This is equivalent to setting `loc[d] = 0.` and `precision_factor[d, d]=`inf`
  in the zeroed dimensions, but is numerically better behaved.
class_docstr_tok: ["Multivariate","normal","that","forces","some","sample","dimensions","to","zero",".","This","is","equivalent","to","setting","`","loc","[","d","]","=","0.","`","and","`","precision_factor","[","d",",","d","]","=","`","inf","`","in","the","zeroed","dimensions",",","but","is","numerically","better","behaved","."]
code: def _parameter_properties(cls, dtype, num_classes=None):
      return dict(
          loc=parameter_properties.ParameterProperties(event_ndims=1),
          precision_factor=parameter_properties.BatchedComponentProperties(),
          precision=parameter_properties.BatchedComponentProperties(),
          nonzeros=parameter_properties.BatchedComponentProperties(
              event_ndims=1
          ),
      )
  
imports: import collections
  import tensorflow.compat.v2
  from tensorflow_probability.python.bijectors import softplus
  from tensorflow_probability.python.distributions import bernoulli
  from tensorflow_probability.python.distributions import inverse_gamma
  from tensorflow_probability.python.distributions import joint_distribution_auto_batched
  from tensorflow_probability.python.distributions import sample
  from tensorflow_probability.python.experimental.distributions.mvn_precision_factor_linop import MultivariateNormalPrecisionFactorLinearOperator
  from tensorflow_probability.python.internal import broadcast_util
  from tensorflow_probability.python.internal import dtype_util
  from tensorflow_probability.python.internal import parameter_properties
  from tensorflow_probability.python.internal import prefer_static
  from tensorflow_probability.python.internal import samplers
  from tensorflow_probability.python.internal import vectorization_util
  from tensorflow_probability.python.math import linalg
  from tensorflow_probability.python.mcmc.internal import util
label_desc: Use image node_id 4 for calling the MVNPrecisionFactorHardZeros obj's underlying member method code with example usage: obj._parameter_properties(cls, dtype, num_classes) and returns: dict