code: def loss_fn(
      params: M, model: M, inputs, labels
  ) -> eg.LossStepOutput[M]:
      model = model.merge(params)
      loss, logs, model = model.test_step(inputs, labels)
      return loss, (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 5 for calling the Model obj's underlying member method code with example usage: obj.loss_fn(params, model, inputs, labels) and returns: loss,  logs,  model