# -*- coding: utf-8 -*-
# enpheeph - Neural Fault Injection Framework
# Copyright (C) 2020-2023 Alessio "Alexei95" Colucci
#
# This program is free software: you can redistribute it and/or modify
# it under the terms of the GNU Affero General Public License as published by
# the Free Software Foundation, either version 3 of the License, or
# (at your option) any later version.
#
# This program is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
# GNU Affero General Public License for more details.
#
# You should have received a copy of the GNU Affero General Public License
# along with this program.  If not, see <https://www.gnu.org/licenses/>.

# enpheeph - Neural Fault Injection Framework
# Copyright (C) 2020-2022 Alessio "Alexei95" Colucci
#
# This program is free software: you can redistribute it and/or modify
# it under the terms of the GNU Affero General Public License as published by
# the Free Software Foundation, either version 3 of the License, or
# (at your option) any later version.
#
# This program is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
# GNU Affero General Public License for more details.
#
# You should have received a copy of the GNU Affero General Public License
# along with this program.  If not, see <https://www.gnu.org/licenses/>.

import abc

# import typing

# import enpheeph.utils.enums
# import enpheeph.utils.typings

# while 3rd party library should be before custom libraries, we move it down to avoid
# flake8 complaining, since it is a conditional import
# if typing.TYPE_CHECKING:
#     import torch


class PyTorchSparseInterfacePluginABC(abc.ABC):
    # @abc.abstractmethod
    # def to_torch(
    #     self, array: enpheeph.utils.typings.LowLevelMaskArrayType
    # ) -> "torch.Tensor":
    #     pass

    # @abc.abstractmethod
    # def from_torch(
    #     self, tensor: "torch.Tensor"
    # ) -> enpheeph.utils.typings.LowLevelMaskArrayType:
    #     pass

    # @abc.abstractmethod
    # def to_bitwise_type(
    #     self, array: enpheeph.utils.typings.LowLevelMaskArrayType
    # ) -> enpheeph.utils.typings.LowLevelMaskArrayType:
    #     pass

    # @abc.abstractmethod
    # def to_target_type(
    #     self,
    #     array: enpheeph.utils.typings.LowLevelMaskArrayType,
    #     target: enpheeph.utils.typings.LowLevelMaskArrayType,
    # ) -> enpheeph.utils.typings.LowLevelMaskArrayType:
    #     pass

    # @abc.abstractmethod
    # def make_mask_array(
    #     self,
    #     int_mask: int,
    #     # this fill value is already final, as is the int mask
    #     int_fill_value: int,
    #     shape: typing.Sequence[int],
    #     torch_placeholder: "torch.Tensor",
    #     mask: typing.Optional[enpheeph.utils.typings.AnyMaskType] = None,
    #     mask_index: typing.Optional[enpheeph.utils.typings.AnyIndexType] = None,
    # ) -> enpheeph.utils.typings.LowLevelMaskArrayType:
    #     pass
    pass
