def populate_defaults()

in ludwig/features/category_feature.py [0:0]

• 33 lines of code
• 3 McCabe index (conditional complexity)

    def populate_defaults(output_feature):
        # If Loss is not defined, set an empty dictionary
        set_default_value(output_feature, LOSS, {})

        # Populate the default values for LOSS if they aren't defined already
        set_default_values(
            output_feature[LOSS],
            {
                'type': 'softmax_cross_entropy',
                'labels_smoothing': 0,
                'class_weights': 1,
                'robust_lambda': 0,
                'confidence_penalty': 0,
                'class_similarities_temperature': 0,
                'weight': 1
            }
        )

        if output_feature[LOSS][TYPE] == 'sampled_softmax_cross_entropy':
            set_default_values(
                output_feature[LOSS],
                {
                    'sampler': 'log_uniform',
                    'unique': False,
                    'negative_samples': 25,
                    'distortion': 0.75
                }
            )

        set_default_values(
            output_feature,
            {
                'top_k': 3,
                'dependencies': [],
                'reduce_input': SUM,
                'reduce_dependencies': SUM
            }
        )