gistfile1.txt

def train_data_for_one_epoch():
    """
    Function for computing the gradient and updating weights in each epoch. 
    """
    losses = []
    # Iterate over batches of the dataset and call apply_gradient function
    for step, (x_batch_train, y_batch_train) in enumerate(train):
        logits, loss_value = apply_gradient(optimizer, model, x_batch_train, y_batch_train)     
        losses.append(loss_value)
        train_acc_metric(y_batch_train, logits)
    return losses