b1e4247e6f2fba4da8ad305f2e04d4f81cce9525,qiskit_aqua/algorithms/adaptive/qsvm/svm_variational.py,SVM_Variational,init_params,#SVM_Variational#Any#Any#,67

Before Change

        optimizer = get_optimizer_instance(opt_params["name"])
        // hard-coded params if SPSA is used.
        if opt_params["name"] == "SPSA" and opt_params["parameters"] is None:
            opt_params["parameters"] = np.asarray([4.0, 0.1, 0.602, 0.101, 0.0])
        optimizer.init_params(opt_params)

        // Set up variational form
        fea_map_params = params.get(QuantumAlgorithm.SECTION_KEY_FEATURE_MAP)

After Change

        self._ret = {}

    def init_params(self, params, algo_input):
        algo_params = params.get(QuantumAlgorithm.SECTION_KEY_ALGORITHM)
        override_spsa_params = algo_params.get("override_SPSA_params")

        // Set up optimizer
        opt_params = params.get(QuantumAlgorithm.SECTION_KEY_OPTIMIZER)

Instances