# 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 __future__ import annotations

from typing import TYPE_CHECKING

from paddle import _C_ops

# from ....framework import LayerHelper, in_dynamic_or_pir_mode
from paddle.base.framework import in_dynamic_or_pir_mode
from paddle.base.layer_helper import LayerHelper

if TYPE_CHECKING:
    from paddle import Tensor


def expand_modality_expert_id(
    expert_id: Tensor,
    num_expert_per_modality: int,
    group_size: int,
    modality_offset: int,
    is_group_expert: bool,
    name: str | None = None,
) -> Tensor:
    """
    Args:
        expert_id:
        num_expert_per_modality:
        group_size:
        modality_offset:
        is_group_expert:

    Returns:
    """
    if in_dynamic_or_pir_mode():
        return _C_ops.expand_modality_expert_id(
            expert_id,
            num_expert_per_modality,
            group_size,
            modality_offset,
            is_group_expert,
        )
    helper = LayerHelper('expand_modality_expert_id', **locals())
    expert_id_out = helper.create_variable_for_type_inference(
        dtype=expert_id.dtype
    )
    inputs = {'expert_id': expert_id}
    attrs = {
        'num_expert_per_modality': num_expert_per_modality,
        'group_size': group_size,
        'modality_offset': modality_offset,
        'is_group_expert': is_group_expert,
    }
    helper.append_op(
        type='expand_modality_expert_id',
        inputs=inputs,
        attrs=attrs,
        outputs={'expert_id_out': expert_id_out},
    )
    return expert_id_out