src/autotrain/trainers/image_classification/__main__.py [44:87]:
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    valid_data = None
    if config.data_path == f"{config.project_name}/autotrain-data":
        train_data = load_from_disk(config.data_path)[config.train_split]
    else:
        if ":" in config.train_split:
            dataset_config_name, split = config.train_split.split(":")
            train_data = load_dataset(
                config.data_path,
                name=dataset_config_name,
                split=split,
                token=config.token,
                trust_remote_code=ALLOW_REMOTE_CODE,
            )
        else:
            train_data = load_dataset(
                config.data_path,
                split=config.train_split,
                token=config.token,
                trust_remote_code=ALLOW_REMOTE_CODE,
            )

    if config.valid_split is not None:
        if config.data_path == f"{config.project_name}/autotrain-data":
            valid_data = load_from_disk(config.data_path)[config.valid_split]
        else:
            if ":" in config.valid_split:
                dataset_config_name, split = config.valid_split.split(":")
                valid_data = load_dataset(
                    config.data_path,
                    name=dataset_config_name,
                    split=split,
                    token=config.token,
                    trust_remote_code=ALLOW_REMOTE_CODE,
                )
            else:
                valid_data = load_dataset(
                    config.data_path,
                    split=config.valid_split,
                    token=config.token,
                    trust_remote_code=ALLOW_REMOTE_CODE,
                )

    logger.info(f"Train data: {train_data}")
    logger.info(f"Valid data: {valid_data}")
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src/autotrain/trainers/image_regression/__main__.py [44:87]:
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    valid_data = None
    if config.data_path == f"{config.project_name}/autotrain-data":
        train_data = load_from_disk(config.data_path)[config.train_split]
    else:
        if ":" in config.train_split:
            dataset_config_name, split = config.train_split.split(":")
            train_data = load_dataset(
                config.data_path,
                name=dataset_config_name,
                split=split,
                token=config.token,
                trust_remote_code=ALLOW_REMOTE_CODE,
            )
        else:
            train_data = load_dataset(
                config.data_path,
                split=config.train_split,
                token=config.token,
                trust_remote_code=ALLOW_REMOTE_CODE,
            )

    if config.valid_split is not None:
        if config.data_path == f"{config.project_name}/autotrain-data":
            valid_data = load_from_disk(config.data_path)[config.valid_split]
        else:
            if ":" in config.valid_split:
                dataset_config_name, split = config.valid_split.split(":")
                valid_data = load_dataset(
                    config.data_path,
                    name=dataset_config_name,
                    split=split,
                    token=config.token,
                    trust_remote_code=ALLOW_REMOTE_CODE,
                )
            else:
                valid_data = load_dataset(
                    config.data_path,
                    split=config.valid_split,
                    token=config.token,
                    trust_remote_code=ALLOW_REMOTE_CODE,
                )

    logger.info(f"Train data: {train_data}")
    logger.info(f"Valid data: {valid_data}")
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