code: def test_fabric_log():
      logger = Mock()
      module = BoringModel()
      fabric = Fabric(loggers=[logger])
      wrapped_module = fabric.setup(module)
  
      # unsupported data type
      with pytest.raises(
          ValueError, match="`list` values cannot be logged"
      ):
          wrapped_module.log("invalid", [])
  
      # supported data types
      wrapped_module.log("int", 1)
      logger.log_metrics.assert_called_with(
          metrics={"int": 1}, step=None
      )
      wrapped_module.log("float", 0.1)
      logger.log_metrics.assert_called_with(
          metrics={"float": 0.1}, step=None
      )
      wrapped_module.log("tensor", torch.tensor(0.1))
      logger.log_metrics.assert_called_with(
          metrics={"tensor": torch.tensor(0.1)}, step=None
      )
  
      # logger=False
      logger.reset_mock()
      wrapped_module.log("nothing", 1, logger=False)
      logger.log_metrics.assert_not_called()
  
imports: import sys
  import weakref
  from unittest.mock import Mock
  import pytest
  import torch
  from lightning.fabric import Fabric
  from lightning.fabric.utilities.imports import _TORCH_GREATER_EQUAL_1_13, _TORCH_GREATER_EQUAL_2_0
  from lightning.pytorch import LightningModule, Trainer
  from lightning.pytorch.core.module import _TrainerFabricShim
  from lightning.pytorch.demos.boring_classes import BoringModel
  from lightning.pytorch.loggers import TensorBoardLogger
  from lightning.pytorch.utilities.exceptions import MisconfigurationException
  from torch import nn
  from torch.optim import SGD, Adam
  from tests_pytorch.helpers.runif import RunIf
label_desc: Use image node_id 21 for calling a global function with example usage: test_fabric_log() without return types