def tf_step(self, time, variables, **kwargs):
fn_loss = kwargs["<STR_LIT>"]<EOL>if variables is None:<EOL><INDENT>variables = tf.trainable_variables<EOL><DEDENT>return tf.gradients(fn_loss, variables)<EOL>
Creates the TensorFlow operations for performing an optimization step on the given variables, including
actually changing the values of the variables.

Args:
    time: Time tensor. Not used for this optimizer.
    variables: List of variables to optimize.
    **kwargs: 
        fn_loss : loss function tensor to differentiate.

Returns:
    List of delta tensors corresponding to the updates for each optimized variable.