code: def _stability_limit_tensor(total_count, dtype):
      limit = tf.cast(BATES_TOTAL_COUNT_STABILITY_LIMITS[dtype], dtype)
      return tf.cond(
          tf.math.reduce_any(total_count > limit),
          # pylint: disable=g-long-lambda
          lambda: tf.print(
              "WARNING: Bates PDF/CDF is unstable for `total_count` >",
              limit,
              output_stream=sys.stderr,
          ),
          tf.no_op,
      )
  
imports: import sys
  import numpy
  import tensorflow.compat.v2
  from tensorflow_probability.python.bijectors import sigmoid
  from tensorflow_probability.python.distributions import distribution
  from tensorflow_probability.python.internal import assert_util
  from tensorflow_probability.python.internal import distribution_util
  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 reparameterization
  from tensorflow_probability.python.internal import samplers
  from tensorflow_probability.python.internal import tensor_util
  from tensorflow_probability.python.math import special
label_desc: Use image node_id 3 for calling a global function with example usage: _stability_limit_tensor(total_count, dtype) and returns: tf