code: def forward(self, x):
      # TODO: These should be float16/bfloat16
      assert x.dtype == torch.float32
      assert torch.tensor([0.0]).dtype == torch.float32
      return self.layer(x)
  
file_path: pytorch-lightning/tests/tests_fabric/plugins/precision/test_xla_integration.py
imports: import os
  from unittest import mock
  import pytest
  import torch
  import torch.nn
  from lightning.fabric import Fabric
  from lightning.fabric.plugins import XLAPrecision
  from tests_fabric.helpers.runif import RunIf
label_desc: Use image node_id 2 for calling the BoringPrecisionModule obj's underlying member method code with example usage: obj.forward(x) and returns: self