class_docstr: Weights and Biases logger.
  
  The `WandBLogger` provides an easy integration with
  Weights & Biases logging. Each monitored metric is automatically
  logged to a dedicated Weights & Biases project dashboard.
  
  External storage for W&B Artifacts (for instance - AWS S3 and GCS
  buckets) uri are supported.
  
  The wandb log files are placed by default in "./wandb/" unless specified.
  
  .. note::
  
      TensorBoard can be synced on to the W&B dedicated dashboard.
code: def __getstate__(self):
      state = self.__dict__.copy()
      if "wandb" in state:
          del state["wandb"]
      return state
  
imports: import re
  from typing import Optional, Union, List, TYPE_CHECKING
  from pathlib import Path
  import os
  import warnings
  import numpy
  from numpy import array
  from torch import Tensor
  from PIL.Image import Image
  from matplotlib.pyplot import Figure
  from avalanche.core import SupervisedPlugin
  from avalanche.evaluation.metric_results import AlternativeValues, MetricValue, TensorImage
  from avalanche.logging import BaseLogger
label_desc: Use image node_id 8 for calling the WandBLogger obj's underlying member method code with example usage: obj.__getstate__() and returns: state