// Copyright (c) 2023 Huawei Technologies Co., Ltd
// All rights reserved.
//
// Licensed under the BSD 3-Clause License  (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
// https://opensource.org/licenses/BSD-3-Clause
//
// 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.

#include "op_plugin/AclOpsInterface.h"
#include "op_plugin/utils/OpAdapter.h"
#include "op_plugin/utils/custom_functions/aclops/inner_compute.h"

namespace acl_op {
using npu_preparation = at_npu::native::OpPreparation;
using npu_utils = at_npu::native::NpuUtils;

at::Tensor& softplus_backward_out(
    const at::Tensor& grad_output,
    const at::Tensor& self,
    const at::Scalar& beta,
    const at::Scalar& threshold,
    at::Tensor& grad_input)
{
    npu_preparation::CheckOut(
        {grad_output, self},
        grad_input,
        self);
    if (!npu_utils::check_match(&grad_input)) {
        at::Tensor contiguous_result = npu_utils::format_contiguous(grad_input);
        softplus_backward_out_common_nocheck(contiguous_result, grad_output, self, beta, threshold);
        npu_utils::format_fresh_view(grad_input, contiguous_result);
    } else {
        softplus_backward_out_common_nocheck(grad_input, grad_output, self, beta, threshold);
    }
    return grad_input;
}
} // namespace acl_op