#!/usr/bin/env python3
# -*- coding: utf-8 -*-
# ----------------------------------------------------------------------------
# Copyright (c) 2025 Huawei Technologies Co., Ltd.
# This program is free software, you can redistribute it and/or modify it under the terms and conditions of
# CANN Open Software License Agreement Version 2.0 (the "License").
# Please refer to the License for details. You may not use this file except in compliance with the License.
# THIS SOFTWARE IS PROVIDED ON AN "AS IS" BASIS, WITHOUT WARRANTIES OF ANY KIND, EITHER EXPRESS OR IMPLIED,
# INCLUDING BUT NOT LIMITED TO NON-INFRINGEMENT, MERCHANTABILITY, OR FITNESS FOR A PARTICULAR PURPOSE.
# See LICENSE in the root of the software repository for the full text of the License.
# ----------------------------------------------------------------------------
# Copyright (c) Huawei Technologies Co., Ltd. 2023. All rights reserved.
import torch
from atk.configs.dataset_config import InputDataset
from atk.configs.results_config import TaskResult
from atk.tasks.api_execute import register
from atk.tasks.api_execute.base_api import BaseApi
from atk.tasks.dataset.base_dataset import OpsDataset
import numpy as np

@register("ascend_method_torch_expand")
class MethodTorchExpand(BaseApi):
    def __init__(self, task_result: TaskResult):
        super(MethodTorchExpand, self).__init__(task_result)
        OpsDataset.seed_everything()
        self.change_flag = None

    def __call__(self, input_data: InputDataset, with_output: bool = False):

        input_self = input_data.kwargs["self"]
        input_size = np.array(input_data.kwargs["size"], dtype=np.int64)
        input_size = tuple(input_size.tolist())

        golden = torch.ops.aten.expand(input_self, input_size, implicit=False)

        return golden