b1756fd255d0f921cd30537d55d0dfb2a6c8ad32,auto_ml/utils_models.py,,load_ml_model,#Any#,479

Before Change

def load_ml_model(file_name):
    from keras.models import load_model as keras_load_model

    print("file_name")
    print(file_name)
    with open(file_name, "rb") as read_file:
        base_pipeline = dill.load(read_file)

After Change

    with open(file_name, "rb") as read_file:
        base_pipeline = dill.load(read_file)

    if isinstance(base_pipeline, utils_categorical_ensembling.CategoricalEnsembler):
        for step in base_pipeline.transformation_pipeline.named_steps:
            pipeline_step = base_pipeline.transformation_pipeline.named_steps[step]

            try:
                if pipeline_step.get("model_name", "reallylongnonsensicalstring")[:12] == "DeepLearning":
                    pipeline_step.model = insert_deep_learning_model(pipeline_step, file_name)
            except AttributeError:
                pass

        for step in base_pipeline.trained_models:
            pipeline_step = base_pipeline.trained_models[step]

            try:
                if pipeline_step.get("model_name", "reallylongnonsensicalstring")[:12] == "DeepLearning":
                    pipeline_step.model = insert_deep_learning_model(pipeline_step, file_name)
            except AttributeError:
                pass

    else:

        for step in base_pipeline.named_steps:
            pipeline_step = base_pipeline.named_steps[step]
            try:
                if pipeline_step.get("model_name", "reallylongnonsensicalstring")[:12] == "DeepLearning":
                    pipeline_step.model = insert_deep_learning_model(pipeline_step, file_name)
            except AttributeError:
                pass

    return base_pipeline

    // if isinstance(base_pipeline, utils_categorical_ensembling.CategoricalEnsembler):

Instances