code: def _safe_value_for_distribution(dist):
      """Returns an x for which it is safe to differentiate dist.logprob(x)."""
      return dist.sample(seed=samplers.zeros_seed())
  
imports: import inspect
  import warnings
  import tensorflow.compat.v2
  from tensorflow_probability.python.bijectors import sigmoid
  from tensorflow_probability.python.distributions import categorical
  from tensorflow_probability.python.distributions import deterministic
  from tensorflow_probability.python.distributions import distribution
  from tensorflow_probability.python.distributions import mixture
  from tensorflow_probability.python.distributions import negative_binomial
  from tensorflow_probability.python.internal import auto_composite_tensor
  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 tensor_util
  from tensorflow_probability.python.util.deferred_tensor import DeferredTensor
label_desc: Use image node_id 1 for calling a global function with example usage: _safe_value_for_distribution(dist) and returns: dist