code: def _fix_zero_samples(s):
      # We use `tf.where` instead of `tf.maximum` because we need to allow for
      # `samples` to be `nan`, but `tf.maximum(nan, x) == x`.
      return tf.where(
          tf.equal(s, 0),
          np.finfo(dtype_util.as_numpy_dtype(s.dtype)).tiny,
          s,
      )
  
imports: import numpy
  import tensorflow.compat.v2
  from tensorflow_probability.python.bijectors import softplus
  from tensorflow_probability.python.distributions import distribution
  from tensorflow_probability.python.distributions import kullback_leibler
  from tensorflow_probability.python.internal import assert_util
  from tensorflow_probability.python.internal import batched_rejection_sampler
  from tensorflow_probability.python.internal import custom_gradient
  from tensorflow_probability.python.internal import distribution_util
  from tensorflow_probability.python.internal import dtype_util
  from tensorflow_probability.python.internal import implementation_selection
  from tensorflow_probability.python.internal import parameter_properties
  from tensorflow_probability.python.internal import prefer_static
  from tensorflow_probability.python.internal import reparameterization
  from tensorflow_probability.python.internal import samplers
  from tensorflow_probability.python.internal import tensor_util
  from tensorflow_probability.python.internal import tensorshape_util
  from tensorflow_probability.python.math import generic
  from tensorflow_probability.python.math import special
  from tensorflow_probability.python.util.deferred_tensor import DeferredTensor
label_desc: Use image node_id 12 for calling a global function with example usage: _fix_zero_samples(s) and returns: tf