# Copyright 2023 The HuggingFace Team. 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 typing import Tuple, Union

import torch


def apply_rotary_emb(
    x: torch.Tensor,
    freqs_cis: Union[torch.Tensor, Tuple[torch.Tensor]],
) -> Tuple[torch.Tensor, torch.Tensor]:
    """
    Adapted from: https://github.com/huggingface/diffusers/blob/v0.31.0/src/diffusers/models/embeddings.py#L697
    """
    cos_, sin_ = freqs_cis  # [S, D]

    cos = cos_[None, None]
    sin = sin_[None, None]
    cos, sin = cos.to(x.device), sin.to(x.device)

    x = torch.ops.hpu.rotary_pos_embedding(x, sin, cos, None, 0, 1)

    return x