code: def test_amp_precision_forward_context():
      """Test to ensure that the context manager correctly is set to bfloat16 on CPU and CUDA."""
      precision = MixedPrecision(precision="16-mixed", device="cuda")
      assert precision.device == "cuda"
      assert isinstance(precision.scaler, torch.cuda.amp.GradScaler)
      assert torch.get_default_dtype() == torch.float32
      with precision.forward_context():
          assert torch.get_autocast_gpu_dtype() == torch.float16
  
      precision = MixedPrecision(precision="bf16-mixed", device="cpu")
      assert precision.device == "cpu"
      assert precision.scaler is None
      with precision.forward_context():
          assert torch.get_autocast_cpu_dtype() == torch.bfloat16
  
      context_manager = precision.forward_context()
      assert isinstance(context_manager, torch.autocast)
      assert context_manager.fast_dtype == torch.bfloat16
  
file_path: pytorch-lightning/tests/tests_fabric/plugins/precision/test_amp.py
imports: import re
  from unittest.mock import Mock
  import pytest
  import torch
  from lightning.fabric.plugins.precision.amp import MixedPrecision
label_desc: Use image node_id 3 for calling a global function with example usage: test_amp_precision_forward_context() without return types