Something like this ?
import torch
import kornia
import numpy as np
from PIL import Image
import matplotlib.pyplot as plt

img = np.array(Image.open('pepper.png'))

img_tensor = torch.tensor(img.transpose([2, 0, 1])).float()

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 = kornia.random_affine(
          img_tensor,
          degrees=0,
          translate=(0.3, 0.3)
      )
      ax.imshow(img_translated.squeeze().permute(1, 2, 0).byte())

Output:
image882×809 154 KB