PyTorch Training Function: TrainWithFeatureLabel

The function 'TrainWithFeatureLabel' takes in the following parameters:

• 'dev': The device on which the model and data should be loaded (e.g. 'cuda' or 'cpu').
• 'feature': The input features for training the model.
• 'label': The corresponding labels for the input features.
• 'batchsize': The batch size to use during training.
• 'model': The model to be trained.
• 'opt': The optimizer used for training the model.
• 'loss_func': The loss function used for calculating the loss during training.

The function first creates a 'TensorDataset' object from the input features and labels. Then, it calls the 'TrainWithDataset' function to train the model using this dataset. Finally, it returns the average loss calculated during training.