Resolved: Change of Tensor Dimension Cause an Error

import numpy as np
import torch
from torchvision import transforms

tim = np.array([[[1, 2, 3],
                 [1, 2, 3],
                 [1, 2, 3]],
                [[1, 2, 3],
                 [1, 2, 3],
                 [1, 2, 3]]]) # (2, 3, 3)

tim = torch.from_numpy(tim)

tf = transforms.Compose([  # Principle?
     transforms.ToPILImage(),
     transforms.Resize((6, 6)), # HW
     transforms.ToTensor()
])

mask = tf(tim)
squ = mask.squeeze()

Traceback (most recent call last):
  File "C:/Users/Tim/Desktop/U-Net/test.py", line 62, in <module>
    mask = tf(tim)
  File "C:\Users\Tim\.conda\envs\Segment\lib\site-packages\torchvision\transforms\transforms.py", line 95, in __call__
    img = t(img)
  File "C:\Users\Tim\.conda\envs\Segment\lib\site-packages\torchvision\transforms\transforms.py", line 227, in __call__
    return F.to_pil_image(pic, self.mode)
  File "C:\Users\Tim\.conda\envs\Segment\lib\site-packages\torchvision\transforms\functional.py", line 315, in to_pil_image
    raise TypeError(f"Input type {npimg.dtype} is not supported")
TypeError: Input type int32 is not supported

tim = np.array([[[1, 2, 3],
                 [1, 2, 3],
                 [1, 2, 3]]]) # (1, 3, 3)

tim = np.array([[[1, 2, 3],
                 [1, 2, 3],
                 [1, 2, 3]],
                [[1, 2, 3],
                 [1, 2, 3],
                 [1, 2, 3]]], dtype=np.float32) # (2, 3, 3)