code: def train_step(self: M, inputs, labels) -> eg.TrainStepOutput[M]:
      model: M = self
  
      params = model.parameters()
      # train
      grads, (logs, model) = jax.grad(Model.loss_fn, has_aux=True)(
          params,
          model,
          inputs,
          labels,
      )
  
      assert model.optimizer is not None
  
      params = model.optimizer.update(grads, params)
      model = model.merge(params)
  
      return logs, model
  
file_path: elegy/examples/jax/linear_classifier_train_step.py
imports: import os
  import typing
  from datetime import datetime
  import jax
  import jax.numpy
  import numpy
  import optax
  import typer
  from datasets.load import load_dataset
  import elegy
label_desc: Use image node_id 6 for calling the Model obj's underlying member method code with example usage: obj.train_step(inputs, labels) and returns: logs,  model