code: def plot_latent_traversal(
      explainer,
      input_images,
      args,
      dataset_obj,
      image_id_to_plot=0,
      num_sweeps=15,
      max_abs_edit_value=10.0,
      epoch=0,
      batch_id=0,
      save_dir="results",
  ):
      edit_dim_values = np.linspace(
          -1.0 * max_abs_edit_value, max_abs_edit_value, num_sweeps
      )
  
      f, axarr = plt.subplots(
          args.latent_dim,
          len(edit_dim_values),
          sharex=True,
          sharey=True,
      )
      f.set_size_inches(10, 10 * args.latent_dim / len(edit_dim_values))
  
      for i in range(args.latent_dim):
          for j in range(len(edit_dim_values)):
              edited_images = convert_and_reshape(
                  explainer.explain(
                      input_images=input_images,
                      edit_dim_id=i,
                      edit_dim_value=edit_dim_values[j],
                      edit_z_sample=False,
                  ),
                  dataset_obj,
              )
              if edited_images.shape[2] == 1:
                  axarr[i][j].imshow(
                      edited_images[image_id_to_plot, :, :, 0],
                      cmap="gray",
                      aspect="auto",
                  )
              else:
                  axarr[i][j].imshow(
                      edited_images[image_id_to_plot] * 0.5 + 0.5,
                      aspect="auto",
                  )
              # axarr[j][i].axis('off')
              if i == len(axarr) - 1:
                  axarr[i][j].set_xlabel(
                      "z:" + str(np.round(edit_dim_values[j], 1))
                  )
              if j == 0:
                  axarr[i][j].set_ylabel("l:" + str(i))
              axarr[i][j].set_yticks([])
              axarr[i][j].set_xticks([])
      plt.subplots_adjust(hspace=0, wspace=0)
  
      if not os.path.isdir(save_dir):
          os.makedirs(save_dir)
  
      f.savefig(
          os.path.join(
              save_dir,
              "traversal_epoch_{}_batch_id_{}.png".format(
                  epoch, batch_id
              ),
          )
      )
      plt.close(fig=f)
  
imports: import matplotlib
  import matplotlib.pyplot
  import numpy
  import torch
  import torch.nn
  import torch.nn.functional
  from torch.autograd import Variable
  from torch.nn import Linear
  import os
label_desc: Use image node_id 3 for calling a global function with example usage: plot_latent_traversal(explainer, input_images, args, dataset_obj, image_id_to_plot, num_sweeps, max_abs_edit_value, epoch, batch_id, save_dir) without return types