5c42053fcd6821eb39eded56526cfe5f2070418a,sandbox/rocky/tf/optimizers/conjugate_gradient_optimizer.py,ConjugateGradientOptimizer,update_opt,#ConjugateGradientOptimizer#Any#Any#Any#Any#Any#Any#,166

Before Change

        params = target.get_params(trainable=True)
        grads = tf.gradients(loss, xs=params)
        for idx, (grad, param) in enumerate(zip(grads, params)):
            if grad is None:
                grads[idx] = tf.zeros_like(param)
        flat_grad = tensor_utils.flatten_tensor_variables(grads)

        self._hvp_approach.update_opt(f=constraint_term, target=target, inputs=inputs + extra_inputs,
                                      reg_coeff=self._reg_coeff)

After Change

            self.opt_fun = ext.lazydict(
                f_Hx_plain=lambda: tensor_utils.compile_function(
                    inputs=inputs + xs,
                    outputs=Hx_plain(),
                    log_name="f_Hx_plain",
                ),
            )

    def build_eval(self, inputs):

Instances