// Copyright (c) 2023 Huawei Technologies Co., Ltd
// Copyright (c) 2019, Facebook CORPORATION.
// 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/OpApiInterface.h"
#include "op_plugin/utils/op_api_common.h"

namespace op_api {
using npu_preparation = at_npu::native::OpPreparation;
at::Tensor& gt_out(const at::Tensor& self, const at::Scalar& other, at::Tensor& result)
{
    DO_COMPATIBILITY(aclnnGtScalar, acl_op::gt_out(self, other, result));
    auto output_size = self.sizes();
    npu_preparation::check_tensor({self}, result, output_size);
    EXEC_NPU_CMD(aclnnGtScalar, self, other, result);
    return result;
}

at::Tensor gt(const at::Tensor& self, const at::Scalar& other)
{
    DO_COMPATIBILITY(aclnnGtScalar, acl_op::gt(self, other));
    // calculate the output size
    auto output_size = op_infer::input_same_output_size(self);

    // construct the output tensor of the NPU
    at::Tensor result = npu_preparation::apply_tensor_without_format(output_size, self.options().dtype(at::kBool));

    // calculate the output result of the NPU
    EXEC_NPU_CMD(aclnnGtScalar, self, other, result);
    return result;
}

at::Tensor& gt_(at::Tensor& self, const at::Scalar& other)
{
    DO_COMPATIBILITY(aclnnInplaceGtScalar, acl_op::gt_(self, other));
    EXEC_NPU_CMD(aclnnInplaceGtScalar, self, other);
    return self;
}

at::Tensor& gt_out(const at::Tensor& self, const at::Tensor& other, at::Tensor& result)
{
    DO_COMPATIBILITY(aclnnGtTensor, acl_op::gt_out(self, other, result));
    auto output_size = op_infer::broadcast_ops_npu_output_size(self, other);

    npu_preparation::check_tensor({self, other}, result, output_size);

    if (npu_preparation::IsCPUScalar(self)) {
        const at::Scalar self_scalar = self.item();
        EXEC_NPU_CMD(aclnnLtScalar, other, self_scalar, result);
    } else if (npu_preparation::IsCPUScalar(other)) {
        const at::Scalar other_scalar = other.item();
        EXEC_NPU_CMD(aclnnGtScalar, self, other_scalar, result);
    } else {
        EXEC_NPU_CMD(aclnnGtTensor, self, other, result);
    }
    return result;
}

at::Tensor gt(const at::Tensor& self, const at::Tensor& other)
{
    DO_COMPATIBILITY(aclnnGtTensor, acl_op::gt(self, other));
    // calculate the output size
    auto output_size = op_infer::broadcast_ops_npu_output_size(self, other);

    // construct the output tensor of the NPU
    at::Tensor result = npu_preparation::apply_tensor_without_format(output_size, self.options().dtype(at::kBool));

    // calculate the output result of the NPU
    if (npu_preparation::IsCPUScalar(self)) {
        const at::Scalar self_scalar = self.item();
        EXEC_NPU_CMD(aclnnLtScalar, other, self_scalar, result);
    } else if (npu_preparation::IsCPUScalar(other)) {
        const at::Scalar other_scalar = other.item();
        EXEC_NPU_CMD(aclnnGtScalar, self, other_scalar, result);
    } else {
        EXEC_NPU_CMD(aclnnGtTensor, self, other, result);
    }
    return result;
}

at::Tensor& gt_(at::Tensor &self, const at::Tensor &other)
{
    DO_COMPATIBILITY(aclnnInplaceGtTensor, acl_op::gt_(self, other));
    if (other.dim() == 0 && !torch_npu::utils::is_npu(other)) {
        return op_api::gt_(self, other.item());
    } else {
        TORCH_CHECK(self.device() == other.device(),
            "Expected all tensors to be on the same device, but found at least two devices", OPS_ERROR(ErrCode::INTERNAL));
        npu_preparation::CheckMemory({self, other}, {self});
        EXEC_NPU_CMD(aclnnInplaceGtTensor, self, other);
        return self;
    }
}
}