code: def sample_discrete_gaussian(scale, shape, dtype=tf.int32):
      """Draws (possibly inexact) samples from the discrete Gaussian distribution.
  
      We relax some integer constraints to use vectorized implementations of
      Bernoulli and discrete Laplace sampling. Integer operations are done in
      tf.int64 as TF does not have direct support for fractions.
  
      Args:
        scale: The scale of the discrete Gaussian distribution.
        shape: The shape of the output tensor.
        dtype: The type of the output.
  
      Returns:
        A tensor of the specified shape filled with random values.
      """
      scale, shape, dtype = _check_input_args(scale, shape, dtype)
      return tf.cond(
          tf.equal(scale, 0),
          lambda: tf.zeros(shape, dtype),
          lambda: _sample_discrete_gaussian_helper(scale, shape, dtype),
      )
  
imports: import tensorflow
  import tensorflow_probability
label_desc: Use image node_id 6 for calling a global function with example usage: sample_discrete_gaussian(scale, shape, dtype) and returns: tf