def __init__()

in use-cases/model-fine-tuning-pipeline/model-eval/src/validate_fine_tuned_model.py [0:0]

• 20 lines of code
• 1 McCabe index (conditional complexity)

    def __init__(self):  # Constructor
        self.api_endpoint = os.environ["ENDPOINT"]
        self.model_name = os.environ["MODEL_PATH"]
        self.output_file = os.environ["PREDICTIONS_FILE"]
        self.gcs_bucket = os.environ["BUCKET"]
        self.dataset_output_path = os.environ["DATASET_OUTPUT_PATH"]
        training_dataset = load_from_disk(
            f"gs://{self.gcs_bucket}/{self.dataset_output_path}/training"
        )
        validation_dataset = load_from_disk(
            f"gs://{self.gcs_bucket}/{self.dataset_output_path}/validation"
        )
        test_dataset = load_from_disk(
            f"gs://{self.gcs_bucket}/{self.dataset_output_path}/test"
        )
        # convert output to pandas dataframe
        self.training_df = training_dataset.to_pandas()
        self.validation_df = validation_dataset.to_pandas()
        self.test_df = test_dataset.to_pandas()
        # Concatenate vertically (stack rows)
        self.df = pd.concat([self.validation_df, self.test_df], axis=0)
        self.df.reset_index(drop=True, inplace=True)