chunk_content: uation
  method with the 🤗 Evaluate library. For this task, use
  the mean Intersection over Union (IoU) metric (see the 🤗 Evaluate
  quick tour to learn more about how to load and compute a metric):
  
  
  	Copied
  import torch
  from torch import nn
  import evaluate
  
  metric = evaluate.load("mean_iou")
  
  
  def compute_metrics(eval_pred):
      with torch.no_grad():
          logits, labels = eval_pred
          logits_tensor = torch.from_numpy(logits)
          logits