WMT_LSTM_5.py

def get_x_y_pairs(train_scaled, train_periods, prediction_periods):
    """
    train_scaled - training sequence
    train_periods - How many data points to use as inputs
    prediction_periods - How many periods to ouput as predictions
    """
    x_train = [train_scaled[i:i+train_periods] for i in range(len(train_scaled)-train_periods-prediction_periods)]
    y_train = [train_scaled[i+train_periods:i+train_periods+prediction_periods] for i in range(len(train_scaled)-train_periods-prediction_periods)]
    
    #-- use the stack function to convert the list of 1D tensors
    # into a 2D tensor where each element of the list is now a row
    x_train = torch.stack(x_train)
    y_train = torch.stack(y_train)
    
    return x_train, y_train

train_periods = 16 #-- number of quarters for input
prediction_periods = test_periods
x_train, y_train = get_x_y_pairs(train_scaled, train_periods, prediction_periods)
print(x_train.shape)
print(y_train.shape)