code: def __call__(self, x, deterministic=False, rng=None):
      if self.rate == 0.0:
          return x
      keep_prob = 1.0 - self.rate
  
      if deterministic:
          return x
      else:
          if rng is None:
              rng = self.scope.make_rng("dropout")
          mask = random.bernoulli(rng, p=keep_prob, shape=x.shape)
          return lax.select(mask, x / keep_prob, jnp.zeros_like(x))
  
imports: import functools
  from pprint import pprint
  from typing import Any, Callable, Optional, Sequence
  from flax.core.frozen_dict import unfreeze
  from flax.linen import initializers
  from flax.linen import Module, compact, vmap
  from flax.linen.linear import PrecisionLike
  import jax
  from jax import lax, numpy, random
label_desc: Use image node_id 1 for calling the Dropout obj's underlying member method code with example usage: obj.__call__(x, deterministic, rng) and returns: x, x, lax