Thank you for your help, it was very helpful 
I have another problem:
Each input is a computed embedding of a graph and as I said before, each input is 1215x1519 matrix.
On the other hand, since we do not have any labels for our data, the original  9x1215x1519 (9 is number of inputs) data considered as label and then considered a noisy version of original data with same shape for model input, in this way we’re trying to reconstruct input according to the labels.
In another implementation of this case with tensorflow and keras, developer fit the model with keras fit() function:

For fitting the model
history = model.fit(X_train_noisy, X_train, epochs=epochs, batch_size=batch_size, shuffle=True,
                    validation_data=(X_test_noisy, X_test),
                    callbacks=[EarlyStopping(monitor='val_loss', min_delta=0.0001, patience=5)])

Both X_train_noisy and X_train are 9x1215x1519.
Now I’m really confused about how to do this with pytorch!
Thank you again
@anantguptadbl