def predictions()

in ludwig/models/ecd.py [0:0]

• 38 lines of code
• 9 McCabe index (conditional complexity)

    def predictions(self, inputs, output_features=None):
        # check validity of output_features
        if output_features is None:
            of_list = self.output_features
        elif isinstance(output_features, str):
            if output_features == 'all':
                of_list = set(self.output_features.keys())
            elif output_features in self.output_features:
                of_list = [output_features]
            else:
                raise ValueError(
                    "'output_features' {} is not a valid for this model. "
                    "Available ones are: {}".format(
                        output_features, set(self.output_features.keys())
                    )
                )
        elif isinstance(output_features, list or set):
            if output_features.issubset(self.output_features):
                of_list = output_features
            else:
                raise ValueError(
                    "'output_features' {} must be a subset of "
                    "available features {}".format(
                        output_features, set(self.output_features.keys())
                    )
                )
        else:
            raise ValueError(
                "'output_features' must be None or a string or a list "
                "of output features"
            )

        outputs = self.call(inputs, training=False)

        predictions = {}
        for of_name in of_list:
            predictions[of_name] = self.output_features[of_name].predictions(
                outputs[of_name],
                training=False
            )

        return predictions