code: def Dropout(rate, mode="train"):
      """Layer construction function for a dropout layer with given rate."""
  
      def init_fun(rng, input_shape):
          return input_shape, ()
  
      def apply_fun(params, inputs, **kwargs):
          rng = kwargs.get("rng", None)
          if rng is None:
              msg = (
                  "Dropout layer requires apply_fun to be called with a PRNG key "
                  "argument. That is, instead of `apply_fun(params, inputs)`, call "
                  "it like `apply_fun(params, inputs, rng)` where `rng` is a "
                  "jax.random.PRNGKey value."
              )
              raise ValueError(msg)
          if mode == "train":
              keep = random.bernoulli(rng, rate, inputs.shape)
              return jnp.where(keep, inputs / rate, 0)
          else:
              return inputs
  
      return init_fun, apply_fun
  
imports: import functools
  import operator
  from jax import lax
  from jax import random
  import jax.numpy
  from jax.nn import relu, log_softmax, softmax, softplus, sigmoid, elu, leaky_relu, selu, gelu, standardize
  from jax.nn.initializers import glorot_normal, normal, ones, zeros
label_desc: Use image node_id 13 for calling a global function with example usage: Dropout(rate, mode) and returns: init_fun,  apply_fun, input_shape,  , jnp, inputs