Pytorch ResNet152 Model Not Predicting - machine-learning

Question

I have a Pytorch resnet152 model, initialized with the following:
model = torchvision.models.resnet152()
model.load_state_dict(torch.load("resnet152_weights.pth"))
for parameter in model.parameters():
parameter.requires_grad = False
model.fc = torch.nn.Linear(2048, 10)
And "resnet152_weights.pth" contains the weights of the model, which is the exact same as torchvision.models.ResNet152_Weights.IMAGENET1K_V2. I downloaded it because my IDE (Pycharm) could not find the URL.
When my model is trained, the code output = model(images) returns the following error:
Traceback (most recent call last):
File "deep_learning_model.py", line 184, in <module>
main()
File "deep_learning_model.py", line 168, in main
model = train(model, 2)
File "deep_learning_model.py", line 141, in train
output = model(images)
File "torch\nn\modules\module.py", line 1194, in _call_impl
return forward_call(*input, **kwargs)
File "torchvision\models\resnet.py", line 285, in forward
return self._forward_impl(x)
File "torchvision\models\resnet.py", line 268, in _forward_impl
x = self.conv1(x)
File "torch\nn\modules\module.py", line 1194, in _call_impl
return forward_call(*input, **kwargs)
File "torch\nn\modules\conv.py", line 463, in forward
return self._conv_forward(input, self.weight, self.bias)
File "torch\nn\modules\conv.py", line 459, in _conv_forward
return F.conv2d(input, weight, bias, self.stride,
RuntimeError: expected scalar type Byte but found Float
Can you please help me fix this bug (if you want me to send more code, please specify which block).