Error with PIL 8.3.0: __array__() takes 1 positional argument but 2 were given

🐛 Bug

The torchvision.transformer function ToTensor raise a TypeError when receiving a image loaded with PIL. The error origins from a call to np.array and contains the message: __array__() takes 1 positional argument but 2 were given

To Reproduce

Steps to reproduce the behavior:

import io
import requests
import torchvision.transforms as T
from PIL import Image

resp = requests.get('https://picsum.photos/200')
img = Image.open(io.BytesIO(resp.content))

preprocess1 = T.Compose([
   T.ToTensor(),
])

x = preprocess1(img)
print(x.shape)

Pip Freeze Log:

certifi==2021.5.30
chardet==4.0.0
idna==2.10
numpy==1.21.0
Pillow==8.3.0
requests==2.25.1
torch==1.9.0
torchvision==0.10.0
typing-extensions==3.10.0.0
urllib3==1.26.6

Full Traceback:

Traceback (most recent call last):
  File "/Users/sebastianlettner/Desktop/tmp/test.py", line 13, in <module>
    x = preprocess1(img)
  File "/Users/sebastianlettner/Desktop/tmp/.venv/lib/python3.8/site-packages/torchvision/transforms/transforms.py", line 60, in __call__
    img = t(img)
  File "/Users/sebastianlettner/Desktop/tmp/.venv/lib/python3.8/site-packages/torchvision/transforms/transforms.py", line 97, in __call__
    return F.to_tensor(pic)
  File "/Users/sebastianlettner/Desktop/tmp/.venv/lib/python3.8/site-packages/torchvision/transforms/functional.py", line 129, in to_tensor
    np.array(pic, mode_to_nptype.get(pic.mode, np.uint8), copy=True)
TypeError: __array__() takes 1 positional argument but 2 were given

Expected behavior

I expect that the conversion works and I reveive a torch.Tensor with shape (200, 200, 3)

Environment

Collecting environment information...
PyTorch version: 1.9.0
Is debug build: False
CUDA used to build PyTorch: None
ROCM used to build PyTorch: N/A

OS: macOS 10.15.7 (x86_64)
GCC version: Could not collect
Clang version: 12.0.0 (clang-1200.0.32.29)
CMake version: Could not collect
Libc version: N/A

Python version: 3.8.10 (default, May  4 2021, 03:05:50)  [Clang 12.0.0 (clang-1200.0.32.29)] (64-bit runtime)
Python platform: macOS-10.15.7-x86_64-i386-64bit
Is CUDA available: False
CUDA runtime version: No CUDA
GPU models and configuration: No CUDA
Nvidia driver version: No CUDA
cuDNN version: No CUDA
HIP runtime version: N/A
MIOpen runtime version: N/A

Versions of relevant libraries:
[pip3] numpy==1.21.0
[pip3] torch==1.9.0
[pip3] torchvision==0.10.0
[conda] Could not collect

• PyTorch / torchvision Version (e.g., 1.0 / 0.4.0): 1.9.0 / 0.10.0
• OS (e.g., Linux): macOS (10.15.7 (19H15))
• How you installed PyTorch / torchvision (conda, pip, source): pip
• Build command you used (if compiling from source): n/A
• Python version: 3.8.10
• CUDA/cuDNN version: n/A
• GPU models and configuration: n/A
• Any other relevant information:

Additional context

n/A

[pmeier]

Pillow 8.3.1 should now be released with a fix for this.

We can close this now. Unless someone explicitly specifies Pillow==8.3.0, pip install torch torchvision will now install a compatible Pillow version.

[NicolasHug]

Re-opening temporarily as other users might bump into this issue, this will hopefully help avoid duplicated entries like https://github.com/pytorch/vision/issues/4152