TypeError: function takes exactly 1 argument (3 given)

[bigmb]

TypeError: function takes exactly 1 argument (3 given)

[yuheng222]

Solved by downgrading torch from 1.4.0 to 1.3.1, torchvision from 0.5.0 to 0.4.2, pillow from 7.0.0 to 6.2.1.

[bigmb]

I think this was caused by torch1.4.0 and its compatibility with PIL image.

[yuheng222]

Yes, I think so too. Thanks for the reply!

Just another question, if I would like to train my model with multiclass dataset, which lines do I have to change? I tried changing all the sigmoid in pytorch_run.py to softmax but it didnt work since the dice score is still low. Thanks.

[bigmb]

Did you change the input and output for the model?
And by changing the to softmax it should work.
What's the dice score?

[yuheng222]

The dice score is 0.23958333333333334.

For the input shape, I tried changing the line: model_test = model_unet(model_Inputs[0], 3, 1) to model_test = model_unet(model_Inputs[0], 3, 8) since my there are 8 classes in my dataset labels but I get this error: ValueError: Target size (torch.Size([4, 1, 96, 96])) must be the same as input size (torch.Size([4, 8, 96, 96])). Where can I change the shape of the model output? I can't seem to find the line to change output shape in pytorch_run.py. Thank you for helping!

[bigmb]

Dice score = 0.24 is not good at all.
Yes by changing it to (model_input[0],3,8 ) it should be working for 8 classes.

Also, you have to change it to softmax to make it work for all prediction line.
pred_tb = F.sigmoid(pred_tb)

Can you tell me which line you are facing this issue?