code: def __call__(self, inputs):
      x = inputs
      for layer_size in self.layer_sizes[:-1]:
          x = nn.Dense(
              features=layer_size,
              kernel_init=nn.initializers.ones_init(),
          )(x)
          if self.activation is not None:
              x = self.activation(x)
      x = nn.Dense(
          features=self.layer_sizes[-1],
          kernel_init=nn.initializers.ones_init(),
      )(x)
      if self.activation_final is None:
          return x
      return self.activation_final(x)
  
imports: from typing import Any, Optional, Sequence
  import jax
  import numpy
  from absl.testing import absltest
  from jax import numpy
  from jax import random
  from flax import linen
label_desc: Use image node_id 1 for calling the MLP obj's underlying member method code with example usage: obj.__call__(inputs) and returns: self, x