code: def semi_explicit_mlp(scope, x, sizes=(3, 1)):
      for i, size in enumerate(sizes):
          dense = scope.child(
              ExplicitDense.create_in_scope, prefix="dense_"
          )(x.shape[-1], size)
          x = dense(x)
          if i + 1 < len(sizes):
              x = nn.relu(x)
      return x
  
imports: from dataclasses import dataclass
  from typing import Any, Optional
  import jax
  from absl.testing import absltest
  from jax import numpy
  from jax import random
  from flax import struct
  from flax.core import Array, init, nn, unfreeze
label_desc: Use image node_id 2 for calling a global function with example usage: semi_explicit_mlp(scope, x, sizes) and returns: x