# Copyright (c) 2025 PaddlePaddle Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.

import abc

import yaml
from paddlex import create_pipeline
from paddlex.inference import load_pipeline_config

from .._abstract import CLISubcommandExecutor
from .._common_args import (
    add_common_cli_args,
    parse_common_args,
    prepare_common_init_args,
)
from .._mkldnn_blocklists import PIPELINE_MKLDNN_BLOCKLIST
from ..utils.logging import logger

_DEFAULT_ENABLE_HPI = None


def _merge_dicts(d1, d2):
    res = d1.copy()
    for k, v in d2.items():
        if k in res and isinstance(res[k], dict) and isinstance(v, dict):
            res[k] = _merge_dicts(res[k], v)
        else:
            res[k] = v
    return res


class PaddleXPipelineWrapper(metaclass=abc.ABCMeta):
    def __init__(
        self,
        *,
        paddlex_config=None,
        **common_args,
    ):
        super().__init__()
        self._paddlex_config = paddlex_config
        if (
            common_args.get("enable_mkldnn", None) is None
            and self._paddlex_pipeline_name in PIPELINE_MKLDNN_BLOCKLIST
        ):
            logger.warning(
                f"oneDNN will be disabled for the {repr(self._paddlex_pipeline_name)} pipeline."
            )
            common_args["enable_mkldnn"] = False
        self._common_args = parse_common_args(
            common_args, default_enable_hpi=_DEFAULT_ENABLE_HPI
        )
        self._merged_paddlex_config = self._get_merged_paddlex_config()
        self.paddlex_pipeline = self._create_paddlex_pipeline()

    @property
    @abc.abstractmethod
    def _paddlex_pipeline_name(self):
        raise NotImplementedError

    def export_paddlex_config_to_yaml(self, yaml_path):
        with open(yaml_path, "w", encoding="utf-8") as f:
            yaml.safe_dump(self._merged_paddlex_config, f)

    @classmethod
    @abc.abstractmethod
    def get_cli_subcommand_executor(cls):
        raise NotImplementedError

    def _get_paddlex_config_overrides(self):
        return {}

    def _get_merged_paddlex_config(self):
        if self._paddlex_config is None:
            config = load_pipeline_config(self._paddlex_pipeline_name)
        elif isinstance(self._config, str):
            config = load_pipeline_config(self._paddlex_config)
        else:
            config = self._paddlex_config

        overrides = self._get_paddlex_config_overrides()

        return _merge_dicts(config, overrides)

    def _create_paddlex_pipeline(self):
        kwargs = prepare_common_init_args(None, self._common_args)
        return create_pipeline(config=self._merged_paddlex_config, **kwargs)


class PipelineCLISubcommandExecutor(CLISubcommandExecutor):
    @property
    @abc.abstractmethod
    def subparser_name(self):
        raise NotImplementedError

    def add_subparser(self, subparsers):
        subparser = subparsers.add_parser(name=self.subparser_name)
        subparser.add_argument(
            "--paddlex_config",
            type=str,
            help="Path to PaddleX pipeline configuration file.",
        )
        add_common_cli_args(subparser, default_enable_hpi=_DEFAULT_ENABLE_HPI)
        self._update_subparser(subparser)
        return subparser

    @abc.abstractmethod
    def _update_subparser(self, subparser):
        raise NotImplementedError