I am trying to train a Transformer model using (Transformer — PyTorch 1.9.0 documentation) which will take in an input of shape (batch_size, 73, 640) and output a sequence of shape (batch_size, 2, 640). I have initialized the transformer with d_model to 640 and kept the rest at default. Now while training, the model requires two inputs: src and tgt. I can safely assume src is the input that I have (batch_size, 73, 640) and the tgt would be the ground truths that I have (batch_size, 2, 640). However, while in the validation/test phase of the model, I may not have ground truths for prediction. What should be done in this case? Or am I understanding the tgt incorrectly?
Any help would be greatly appreciated.