class_docstr: Inverse gamma distribution with an upper bound on sampled values.
code: def _parameter_properties(cls, dtype, num_classes=None):
      return dict(
          concentration=parameter_properties.ParameterProperties(
              default_constraining_bijector_fn=(
                  lambda: softplus_bijector.Softplus(
                      low=dtype_util.eps(dtype)
                  )
              )
          ),
          scale=parameter_properties.ParameterProperties(
              default_constraining_bijector_fn=(
                  lambda: softplus_bijector.Softplus(
                      low=dtype_util.eps(dtype)
                  )
              )
          ),
          upper_bound=parameter_properties.ParameterProperties(
              default_constraining_bijector_fn=(
                  lambda: softplus_bijector.Softplus(
                      low=dtype_util.eps(dtype)
                  )
              )
          ),
      )
  
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 InverseGammaWithSampleUpperBound obj's underlying member method code with example usage: obj._parameter_properties(cls, dtype, num_classes) and returns: dict