code: import os
  import torch
  from torchvision.utils import make_grid
  from tensorboardX import SummaryWriter
  from dataloaders.utils import decode_seg_map_sequence
  
  class TensorboardSummary(object):
      def __init__(self, directory):
          self.directory = directory
  
      def create_summary(self):
          writer = SummaryWriter(log_dir=os.path.join(self.directory))
          return writer
  
      def visualize_image(self, writer, dataset, image, target, output, global_step):
          grid_image = make_grid(image[:3].clone().cpu().data, 3, normalize=True)
          writer.add_image('Image', grid_image, global_step)
          grid_image = make_grid(decode_seg_map_sequence(torch.max(output[:3], 1)[1].detach().cpu().numpy(),
                                                         dataset=dataset), 3, normalize=False, range=(0, 255))
          writer.add_image('Predicted label', grid_image, global_step)
          grid_image = make_grid(decode_seg_map_sequence(torch.squeeze(target[:3], 1).detach().cpu().numpy(),
                                                         dataset=dataset), 3, normalize=False, range=(0, 255))
          writer.add_image('Groundtruth label', grid_image, global_step)
apis: torch.squeeze torch.max