"""
# 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.
"""

from abc import ABC, abstractmethod
from typing import Any, Optional


class QuantMethodBase(ABC):
    """Base class for different quantized methods."""

    @abstractmethod
    def create_weights(self, layer, *weight_args, **extra_weight_attrs):
        """Create weights for a layer.

        The weights will be set as attributes of the layer."""
        raise NotImplementedError

    @abstractmethod
    def apply(self, layer, *args, **kwargs):
        """Apply the weights in layer to the input tensor.

        Expects create_weights to have been called before on the layer."""
        raise NotImplementedError

    def process_loaded_weights(self, layer, weights):
        """Process the weight after loading.

        This can be used for example, to transpose weights for computation.
        """
        return


class QuantConfigBase(ABC):
    """Base class for quantization configs."""

    def __init__(self):
        super().__init__()

    @abstractmethod
    def name(self) -> str:
        """Name of the quantization method."""
        raise NotImplementedError

    @classmethod
    @abstractmethod
    def from_config(cls, config: dict) -> "QuantConfigBase":
        """Create a config class from the model's quantization config."""
        raise NotImplementedError

    @staticmethod
    def get_from_keys(config: dict[str, Any], keys: list[str]) -> Any:
        """Get a value from the model's quantization config."""
        for key in keys:
            if key in config:
                return config[key]
        raise ValueError(f"Cannot find any of {keys} in the model's " "quantization config.")

    @abstractmethod
    def get_quant_method(self, layer, prefix) -> Optional[QuantMethodBase]:
        """Get the quantize method to use for the quantized layer.

        Args:
            layer: The layer for the quant method.
            prefix: The full name of the layer in the state dict
        Returns:
            The quantize method. None if the given layer doesn't support quant
            method.
        """
        raise NotImplementedError