That function does not seem to have padding_mode, but one can instantiate a RandomAffine class to get the padding mode like this
affine = kornia.augmentation.RandomAffine(degrees=0, translate=(0.3, 0.3), padding_mode='border')  
fig = plt.figure(figsize=(15, 15))
for i in range(4):
  for j in range(4):
      ax = plt.subplot(4, 4, i*4 + j +1)
      img_translated = affine(img_tensor)
      ax.imshow(img_translated.squeeze().permute(1, 2, 0).byte())