# Copyright (c) OpenMMLab. All rights reserved.
from argparse import ArgumentParser, Namespace
from pathlib import Path
from tempfile import TemporaryDirectory

import mmcv

try:
    from model_archiver.model_packaging import package_model
    from model_archiver.model_packaging_utils import ModelExportUtils
except ImportError:
    package_model = None


def mmgen2torchserver(config_file: str,
                      checkpoint_file: str,
                      output_folder: str,
                      model_name: str,
                      model_version: str = '1.0',
                      model_type: str = 'unconditional',
                      force: bool = False):
    """Converts MMGeneration model (config + checkpoint) to TorchServe `.mar`.

    Args:
        config_file (str): Path of config file. The config should in
            MMGeneration format.
        checkpoint_file (str): Path of checkpoint. The checkpoint should in
            MMGeneration checkpoint format.
        output_folder (str): Folder where `{model_name}.mar` will be created.
            The file created will be in TorchServe archive format.
        model_name (str): Name of the generated ``'mar'`` file. If not None,
            used for naming the `{model_name}.mar` file that will be created
            under `output_folder`. If None, `{Path(checkpoint_file).stem}`
            will be used.
        model_version (str, optional): Model's version. Defaults to '1.0'.
        model_type (str, optional): Type of the model to be convert. Handler
            named ``{model_type}_handler`` would be used to generate ``mar``
            file. Defaults to 'unconditional'.
        force (bool, optional): If True, existing `{model_name}.mar` will be
            overwritten. Default to False.
    """
    mmcv.mkdir_or_exist(output_folder)

    config = mmcv.Config.fromfile(config_file)

    with TemporaryDirectory() as tmpdir:
        config.dump(f'{tmpdir}/config.py')

        args = Namespace(
            **{
                'model_file': f'{tmpdir}/config.py',
                'serialized_file': checkpoint_file,
                'handler':
                f'{Path(__file__).parent}/mmgen_{model_type}_handler.py',
                'model_name': model_name or Path(checkpoint_file).stem,
                'version': model_version,
                'export_path': output_folder,
                'force': force,
                'requirements_file': None,
                'extra_files': None,
                'runtime': 'python',
                'archive_format': 'default'
            })
        manifest = ModelExportUtils.generate_manifest_json(args)
        package_model(args, manifest)


def parse_args():
    parser = ArgumentParser(
        description='Convert MMGeneration models to TorchServe `.mar` format.')
    parser.add_argument('config', type=str, help='config file path')
    parser.add_argument('checkpoint', type=str, help='checkpoint file path')
    parser.add_argument(
        '--output-folder',
        type=str,
        required=True,
        help='Folder where `{model_name}.mar` will be created.')
    parser.add_argument(
        '--model-name',
        type=str,
        default=None,
        help='If not None, used for naming the `{model_name}.mar`'
        'file that will be created under `output_folder`.'
        'If None, `{Path(checkpoint_file).stem}` will be used.')
    parser.add_argument(
        '--model-type',
        type=str,
        default='unconditional',
        help='Which model type and handler to be used.')
    parser.add_argument(
        '--model-version',
        type=str,
        default='1.0',
        help='Number used for versioning.')
    parser.add_argument(
        '-f',
        '--force',
        action='store_true',
        help='overwrite the existing `{model_name}.mar`')
    args = parser.parse_args()

    return args


if __name__ == '__main__':
    args = parse_args()

    if package_model is None:
        raise ImportError('`torch-model-archiver` is required.'
                          'Try: pip install torch-model-archiver')

    mmgen2torchserver(args.config, args.checkpoint, args.output_folder,
                      args.model_name, args.model_version, args.model_type,
                      args.force)