class_docstr: Logs a validation batch and their predictions to wandb.
  Example adapted from:
      https://wandb.ai/wandb/wandb-lightning/reports/Image-Classification-using-PyTorch-Lightning--VmlldzoyODk1NzY
class_docstr_tok: ["Logs","a","validation","batch","and","their","predictions","to","wandb",".","Example","adapted","from",":","https",":","\/\/wandb.ai\/wandb\/wandb-lightning\/reports\/Image-Classification-using-PyTorch-Lightning","--","VmlldzoyODk1NzY"]
code: def __init__(self, num_samples: int = 8):
      super().__init__()
      self.num_samples = num_samples
      self.ready = True
  
imports: import subprocess
  from pathlib import Path
  from typing import List
  import matplotlib.pyplot
  import seaborn
  import torch
  import wandb
  from pytorch_lightning import Callback, Trainer
  from pytorch_lightning.loggers import LoggerCollection, WandbLogger
  from pytorch_lightning.utilities import rank_zero_only
  from sklearn import metrics
  from sklearn.metrics import f1_score, precision_score, recall_score
label_desc: Use image node_id 1 to create a new LogImagePredictions object from inherited base classes: Callback with example: obj = LogImagePredictions(num_samples)