evaluate_importance_data.py

import os.path
import sys

sys.path.append(os.path.abspath(os.path.join(
    os.path.dirname(sys.modules[__name__].__file__), '..')))  # type: ignore

if True:
    from data.mnist_data_handler import get_prepared_data
    from data.model_data import ModelData
    from evaluation.evaluator import ImportanceEvaluator
    from utility.log_handling import setup_logger


setup_logger('sample_evaluation')

name: str = 'default'
model_data: ModelData = ModelData(name)
model_data.reload_model()
importance_handler: ImportanceEvaluator = ImportanceEvaluator(model_data)
importance_handler.setup()
(x_train, y_train), (x_test, y_test), input_shape, num_classes = get_prepared_data(
    model_data.get_class_selection())
importance_handler.set_train_and_test_data(x_train, y_train, x_test, y_test)
importance_handler.create_evaluation_data(10)