code: def _check_input_args(scale, shape, dtype):
      """Checks the input args to the discrete Gaussian sampler."""
      if tf.as_dtype(dtype) not in (tf.int32, tf.int64):
          raise ValueError(
              f"Only tf.int32 and tf.int64 are supported. Found dtype `{dtype}`."
          )
  
      checks = [
          tf.compat.v1.assert_non_negative(scale),
          tf.compat.v1.assert_integer(scale),
      ]
      with tf.control_dependencies(checks):
          return tf.identity(scale), shape, dtype
  
imports: import tensorflow
  import tensorflow_probability
label_desc: Use image node_id 3 for calling a global function with example usage: _check_input_args(scale, shape, dtype) and returns: tf,  shape,  dtype