code: def _nc2_cdf_jvp(primals, tangents):
      """Computes the JVP for `_nc2_cdf_abramowitz_and_stegun` (supports JAX custom derivative)."""
      x, df, noncentrality = primals
      d_x, _, d_noncentrality = tangents
  
      output = _nc2_cdf_naive(x, df, noncentrality)
  
      shape = ps.broadcast_shape(
          ps.shape(d_x), ps.shape(d_noncentrality)
      )
      d_x = tf.broadcast_to(d_x, shape)
      d_noncentrality = tf.broadcast_to(d_noncentrality, shape)
  
      # Compute tangets for `x`
      d_x = tf.math.exp(_nc2_log_prob(x, df, noncentrality)) * d_x
  
      # Compute tangents for `noncentrality`
      nc2_cdf_1 = output
      nc2_cdf_2 = _nc2_cdf_naive(x, df + 2.0, noncentrality)
  
      d_noncentrality = 0.5 * (nc2_cdf_2 - nc2_cdf_1) * d_noncentrality
  
      tangents = d_x + d_noncentrality
  
      return output, tangents
  
imports: import numpy
  import tensorflow.compat.v2
  from tensorflow_probability.python.bijectors import softplus
  from tensorflow_probability.python.distributions import chi2
  from tensorflow_probability.python.distributions import distribution
  from tensorflow_probability.python.distributions import gamma
  from tensorflow_probability.python.distributions import poisson
  from tensorflow_probability.python.internal import assert_util
  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 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 special_math
  from tensorflow_probability.python.internal import tensor_util
  from tensorflow_probability.python.math import bessel
  from tensorflow_probability.python.math import generic
  from tensorflow_probability.python.math import root_search
  import tensorflow_probability.python.random
label_desc: Use image node_id 6 for calling a global function with example usage: _nc2_cdf_jvp(primals, tangents) and returns: output,  tangents