def _get_keras_utils()

in horovod/spark/keras/estimator.py [0:0]

• 35 lines of code
• 14 McCabe index (conditional complexity)

    def _get_keras_utils(self):
        # This function determines the keras package type of the Estimator based on the passed
        # optimizer and model and updates _keras_pkg_type parameter.

        model_type = None
        model = self.getModel()
        if model:
            if isinstance(model, tf.keras.Model):
                model_type = TF_KERAS
            elif is_instance_of_bare_keras_model(model):
                model_type = BARE_KERAS
            else:
                raise ValueError(
                    "model has to be an instance of tensorflow.keras.Model or keras.Model")

        optimizer_type = None
        optimizer = self.getOptimizer()
        if optimizer:
            if isinstance(optimizer, str):
                optimizer_type = None
            elif isinstance(optimizer, tf.keras.optimizers.Optimizer):
                optimizer_type = TF_KERAS
            elif is_instance_of_bare_keras_optimizer(optimizer):
                optimizer_type = BARE_KERAS
            else:
                raise ValueError("invalid optimizer type")

        types = set([model_type, optimizer_type])
        types.discard(None)

        if len(types) > 1:
            raise ValueError('mixed keras and tf.keras values for optimizers and model')
        elif len(types) == 1:
            pkg_type = types.pop()
            super(KerasEstimator, self)._set(_keras_pkg_type=pkg_type)

            if pkg_type == TF_KERAS:
                return TFKerasUtil
            elif pkg_type == BARE_KERAS:
                return BareKerasUtil
            else:
                raise ValueError("invalid keras type")