ca0aca8a9219b0ef5382cdf88c2aa5343cf0d954,deeppavlov/models/classifiers/keras_classification_model.py,KerasClassificationModel,__init__,#KerasClassificationModel#Any#Any#Any#Any#Any#Any#Any#Any#Any#Any#Any#Any#,82

Before Change

        if restore_lr:
            learning_rate = self.opt.get("final_learning_rate", learning_rate)

        self.model = self.compile(self.model, optimizer_name=optimizer, loss_name=loss,
                                  learning_rate=learning_rate, learning_rate_decay=learning_rate_decay)

        self._change_not_fixed_params(**given_opt)

        summary = ["Model was successfully initialized!", "Model summary:"]

After Change

        Initialize model using parameters
        from opt dictionary (from config), if model is being initialized from saved.
        
        if learning_rate is None and isinstance(learning_rate_decay, float):
            learning_rate = 0.01
        elif learning_rate is None and learning_rate_decay is None:
            learning_rate = 0.01
            learning_rate_decay = 0.
        elif isinstance(learning_rate, float) and "learning_rate_drop_patience" in kwargs:
            learning_rate_decay = "no"

        if classes is not None:
            classes = list(classes)

        given_opt = {"embedding_size": embedding_size,

Instances