[Python] RuntimeError: all elements of target should be between 0 and 1. Please help my...

I use the BCELoss(),and it show up RuntimeError: all elements of target should be between 0 and 1, but I already use sigmoid, I can't understand why it still not working...


# Build CustomDataset for loading data from Google Drive
class CustomDataset(Dataset):
def __init__(self,image_dir,mask_dir,transform):
super().__init__()
self.image_dir=image_dir
self.mask_dir=mask_dir
self.transform=transform
self.images=os.listdir(image_dir)
def __len__(self):
return len(self.images)
def __getitem__(self, index):
img_path=os.path.join(self.image_dir,self.images[index])
mask_path=os.path.join(self.mask_dir,self.images[index])
image=np.array(Image.open(img_path).convert('L'))
mask=np.array(Image.open(mask_path).convert('L'))
return self.transform(image),self.transform(mask)


# Load data
all_data = CustomDataset('images', 'masks', T.Compose([T.ToTensor(), T.Resize((IMG_HEIGHT, IMG_WIDTH))]))

# Split data into train and val
train_data, val_data = torch.utils.data.random_split(all_data, [0.7, 0.3])

# Create loader for mini-batch gradient descent
from torch.utils.data import DataLoader
train_loader = DataLoader(train_data, batch_size=BATCH_SIZE, shuffle=True)
val_loader = DataLoader(val_data, batch_size=BATCH_SIZE, shuffle=False)


# The loss function for bianry classification
# loss_function = nn.BCELoss()
loss_function = nn.BCEWithLogitsLoss()



I want to finish training this model...I use this model to do Semantic Segmentation on spinal X-ray photo.

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