code: def _reverse_and_fbo_with_layer_and_opt(
      layer, optimizer, n_devices, adasum
  ):
      """Create the reverse_and_fbo function for a given layer and optimizer."""
  
      def reverse_and_fbo(
          output,
          weights,
          grads,
          state,
          new_state,
          slots,
          opt_params,
          rng,
          step,
      ):
          """Reverse and FBO of the layer."""
          # Call the reverse_and_grad method of the layer.
          inputs, (
              grads_inputs,
              grads_weights,
          ) = layer.reverse_and_grad(
              output, grads, weights, state, new_state, rng=rng
          )
  
          # For non-trainable layers, return the calculated arguments.
          if _is_empty_tuple(weights):
              return weights, slots, inputs, grads_inputs, {}
  
          # In multi-device setting, average gradients from multiple devices.
          if n_devices > 1:
              grads_weights = _average_multidevice_gradients(
                  grads_weights, adasum=adasum
              )
  
          # Run the optimizer.
          new_weights, new_slots, stats = optimizer.tree_update(
              step,
              grads_weights,
              weights,
              slots,
              opt_params,
              store_slots=False,
          )
  
          return new_weights, new_slots, inputs, grads_inputs, stats
  
      return reverse_and_fbo
  
imports: from concurrent import futures
  import functools
  import os
  import time
  from absl import logging
  import jax
  import numpy
  import psutil
  from trax import fastmath
  from trax import layers
  from trax.fastmath import numpy
  from trax.layers import base
  from trax.layers import combinators
label_desc: Use image node_id 5 for calling a global function with example usage: _reverse_and_fbo_with_layer_and_opt(layer, optimizer, n_devices, adasum) and returns: reverse_and_fbo, new_weights,  new_slots,  inputs,  grads_inputs,  stats, weights,  slots,  inputs,  grads_inputs,  dict