code: def _prevent_2nd_derivative(x):
      """Disables computation of the second derivatives for a tensor.
  
      NB: you need to apply a non-identity function to the output tensor for the
      exception to be raised.
  
      Args:
        x: A tensor.
  
      Returns:
        A tensor with the same value and the same derivative as x, but that raises
        LookupError when trying to compute the second derivatives.
      """
      return tf.identity(x)
  
imports: import warnings
  import tensorflow.compat.v2
  from tensorflow_probability.python.distributions import batch_broadcast
  from tensorflow_probability.python.distributions import categorical
  from tensorflow_probability.python.distributions import distribution
  from tensorflow_probability.python.distributions import independent
  from tensorflow_probability.python.internal import assert_util
  from tensorflow_probability.python.internal import auto_composite_tensor
  from tensorflow_probability.python.internal import custom_gradient
  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 tensorshape_util
  from tensorflow_probability.python.math.gradient import value_and_batch_jacobian
label_desc: Use image node_id 2 for calling a global function with example usage: _prevent_2nd_derivative(x) and returns: tf