def gradient_helper(optimizer, loss, var_list=None):
    '''A helper to get the gradients out at each step.

    Args:
      optimizer: the optimizer op.
      loss: the op that computes your loss value.

    Returns: the gradient tensors and the train_step op.
    '''
    if var_list is None:
      var_list = tf.compat.v1.trainable_variables()

    grads_and_vars = optimizer.compute_gradients(loss, var_list=var_list)
    grads = [pair[0] for pair in grads_and_vars]

    return grads, optimizer.apply_gradients(grads_and_vars)
A helper to get the gradients out at each step.

    Args:
      optimizer: the optimizer op.
      loss: the op that computes your loss value.

    Returns: the gradient tensors and the train_step op.