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.
  
   This class is meant to work specifically with the DynamicSpikeSlabSampler,
   and so does not conform to a TensorFlow probability distribution API. In
   particular, the loc and precision_factor are expected to be the nonzero
   entries, and samples are broadcast back out to a full shape. This means:
   - Querying the `event_shape` will give a wrong answer.
   - Sampling for more than 1 element will throw an exception.
code: def _call_sample_n(self, *args, **kwargs):
      xs = super()._call_sample_n(*args, **kwargs)
      return tf.scatter_nd(
          indices=self._indices, updates=xs, shape=[self._size]
      )
  
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 gamma
  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 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.mcmc.internal import util
label_desc: Use image node_id 2 for calling the MVNPrecisionFactorHardZeros obj's underlying member method code with example usage: obj._call_sample_n() and returns: tf