class_docstr: The log-logistic distribution.
class_docstr_tok: ["The","log-logistic","distribution","."]
code: def _parameter_properties(cls, dtype, num_classes=None):
      # pylint: disable=g-long-lambda
      return dict(
          loc=parameter_properties.ParameterProperties(),
          scale=parameter_properties.ParameterProperties(
              default_constraining_bijector_fn=(
                  lambda: softplus_bijector.Softplus(
                      low=dtype_util.eps(dtype)
                  )
              )
          ),
      )
  
imports: import numpy
  import tensorflow.compat.v2
  from tensorflow_probability.python.bijectors import exp
  from tensorflow_probability.python.bijectors import softplus
  from tensorflow_probability.python.distributions import logistic
  from tensorflow_probability.python.distributions import transformed_distribution
  from tensorflow_probability.python.internal import assert_util
  from tensorflow_probability.python.internal import dtype_util
  from tensorflow_probability.python.internal import parameter_properties
label_desc: Use image node_id 2 for calling the LogLogistic obj's underlying member method code with example usage: obj._parameter_properties(cls, dtype, num_classes) and returns: dict