def get_model_overview()

in src/responsibleai/rai_analyse/_score_card/common_components.py [0:0]

• 80 lines of code
• 5 McCabe index (conditional complexity)

def get_model_overview(data):
    model_left_items = []

    if "ModelSummary" not in data:
        raise UserConfigValidationException(
            "Invalid model config data, expecting key ModelSummary to exist in the model config data."
        )
    else:
        model_left_items.append(div(h3("Purpose"), p(data["ModelSummary"])))

    if data["ModelType"] == "binary_classification":
        model_left_items.append(
            div(
                p(
                    "Classification: {} vs {}".format(
                        data["classes"][0], data["classes"][1]
                    )
                )
            )
        )
    else:
        model_left_items.append(
            div(p("This is a {} model.".format(data["ModelType"].lower())))
        )

    model_left_items.append(
        div(
            h3("Model evaluation"),
            p(
                "This model is evaluated on a test set with {} datapoints.".format(
                    len(data["y_test"])
                )
            ),
        )
    )

    model_overview_left_container = div(model_left_items, _class="left_model_overview")

    model_main_items = []
    model_main_items.extend(
        [
            h3("Target values"),
            p(
                "Here are your defined target values for your model "
                "performance and/or other model assessment parameters:"
            ),
        ]
    )

    metric_targets_elems = []
    for item in data["metrics_targets"]:
        metric_targets_elems.append(li(item))

    model_main_items.append(
        div(
            ul(metric_targets_elems),
            _style="border: 2px solid black; border-radius: 5px;",
        )
    )

    model_overview_main_container = div(model_main_items, _class="main_model_overview")

    heading = [h1(data["ModelName"])]
    if data["runinfo"]:
        heading.append(
            p(
                "Generated by {} on {}".format(
                    data["runinfo"]["submittedBy"], data["runinfo"]["startTimeUtc"]
                )
            )
        )
        heading.append(
            p(
                "Source RAI dashboard: ",
                a(
                    data["runinfo"]["dashboard_title"],
                    _href=data["runinfo"]["dashboard_link"],
                ),
            )
        )
        heading.append(p(f"Model id: {data['runinfo']['model_id']}"))

    model_overview_container = div(
        div(heading, _class="header"),
        get_page_divider("Model Summary"),
        model_overview_left_container,
        model_overview_main_container,
        _class="container",
    )

    return model_overview_container