Hello. I deployed a trained model via flask on heroku. I noticed my predict method keeps failing at the point of applying a transform to an input image.
This is the error message
RuntimeError: The size of tensor a (4) must match the size of tensor b (3) at non-singleton dimension 0
This is the predict method
def transform_image(infile):
    my_transforms = transforms.Compose([transforms.Resize(256),
                                        transforms.CenterCrop(224),
                                        transforms.ToTensor(),
                                        transforms.Normalize(
                                            [0.485, 0.456, 0.406],
                                            [0.229, 0.224, 0.225])])
    image = Image.open(infile)
    timg = my_transforms(image)
    timg.unsqueeze_(0)
    return timg

It fails at
timg = my_transforms(image)

The stack trace
File “/app/application.py”, line 30, in transform_image
2020-06-14T10:18:45.253206+00:00 app[web.1]:     timg = my_transforms(image)
2020-06-14T10:18:45.253206+00:00 app[web.1]:   File “/app/.heroku/python/lib/python3.7/site-packages/torchvision/transforms/transforms.py”, line 61, in call
2020-06-14T10:18:45.253206+00:00 app[web.1]:     img = t(img)
2020-06-14T10:18:45.253207+00:00 app[web.1]:   File “/app/.heroku/python/lib/python3.7/site-packages/torchvision/transforms/transforms.py”, line 166, in call
2020-06-14T10:18:45.253207+00:00 app[web.1]:     return F.normalize(tensor, self.mean, self.std, self.inplace)
2020-06-14T10:18:45.253208+00:00 app[web.1]:   File “/app/.heroku/python/lib/python3.7/site-packages/torchvision/transforms/functional.py”, line 208, in normalize
2020-06-14T10:18:45.253208+00:00 app[web.1]:     tensor.sub_(mean).div_(std)