/* Copyright (c) 2020 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. */

#include <string>

#include "gtest/gtest.h"
#include "paddle/fluid/framework/tensor.h"
#include "paddle/fluid/framework/operator.h"
#include "paddle/fluid/framework/scope.h"

#include "aby3_context.h"
#include "core/paddlefl_mpc/mpc_protocol/mesh_network.h"
#include "core/paddlefl_mpc/mpc_protocol/context_holder.h"
#include "fixedpoint_tensor.h"

namespace aby3 {

using g_ctx_holder = paddle::mpc::ContextHolder;
using Fix64N16 = FixedPointTensor<int64_t, 16>;
using AbstractContext = paddle::mpc::AbstractContext;

class FixedTensorTest : public ::testing::Test {
public:

    paddle::platform::CPUDeviceContext _cpu_ctx;
    std::shared_ptr<paddle::framework::ExecutionContext> _exec_ctx;
    std::shared_ptr<AbstractContext> _mpc_ctx[3];
    std::shared_ptr<gloo::rendezvous::HashStore> _store;
    std::thread _t[3];
    std::shared_ptr<TensorAdapterFactory> _s_tensor_factory;

    virtual ~FixedTensorTest() noexcept {}

    void SetUp() {

        paddle::framework::OperatorBase* op = nullptr;
        paddle::framework::Scope scope;
        paddle::framework::RuntimeContext ctx({}, {});
        // only device_ctx is needed
        _exec_ctx = std::make_shared<paddle::framework::ExecutionContext>(
            *op, scope, _cpu_ctx, ctx);

        _store = std::make_shared<gloo::rendezvous::HashStore>();

        std::thread t[3];
        for (size_t i = 0; i < 3; ++i) {
            _t[i] = std::thread(&FixedTensorTest::gen_mpc_ctx, this, i);
        }
        for (auto& ti : _t) {
            ti.join();
        }
        _s_tensor_factory = std::make_shared<PaddleTensorFactory>(&_cpu_ctx);
    }
    std::shared_ptr<paddle::mpc::MeshNetwork> gen_network(size_t idx) {
        return std::make_shared<paddle::mpc::MeshNetwork>(idx,
                                                          "127.0.0.1",
                                                          3,
                                                          "test_prefix",
                                                          _store);
    }
    void gen_mpc_ctx(size_t idx) {
        auto net = gen_network(idx);
        net->init();
        _mpc_ctx[idx] = std::make_shared<ABY3Context>(idx, net);
    }

    std::shared_ptr<TensorAdapter<int64_t>> gen(std::vector<size_t> shape) {
        return _s_tensor_factory->template create<int64_t>(shape);
    }
};

std::shared_ptr<TensorAdapter<int64_t>> gen(std::vector<size_t> shape) {
    return g_ctx_holder::tensor_factory()->template create<int64_t>(shape);
}

template<typename T, size_t N>
PaddleTensor<T> test_fixedt_gen_paddle_tensor(std::vector<float>& input,
                        std::vector<size_t>& shape,
                        paddle::platform::CPUDeviceContext& cpu_ctx) {

    PaddleTensor<T> ret(&cpu_ctx);
    ret.reshape(shape);
    T* ret_ptr = ret.data();
    for (int i = 0; i < ret.numel(); i++) {
        *(ret_ptr + i) = (T) (input[i] * pow(2, N));
    }
    return ret;
}

template<typename T>
bool test_fixedt_check_tensor_eq(const TensorAdapter<T>* in1,
                     const TensorAdapter<T>* in2, double precision = 0.0001) {
    // check shape
    std::vector<size_t> shape1, shape2;
    shape1 = in1->shape();
    shape2 = in2->shape();
    size_t scale = in1->scaling_factor();
    if (shape1.size() != shape2.size()) {
        std::cout << "shape size error: shape1.size: "<<shape1.size()<<
                     "; shape2.size: "<<shape2.size()<<std::endl;
        return false;
    }
    for (int i = 0; i < shape1.size(); i++) {
        if (shape1[i] != shape2[i]) {
            std::cout << "shape error!"<<std::endl;
            return false;
        }
    }

    // check each element
    for (int i = 0; i < in1->numel(); i++) {
        if (std::abs(*(in1->data() + i) - *(in2->data() + i)) >
            precision * pow(2, scale)) {
            std::cout << "result error: inx: "<<i<<
                        " in1[i] = "<<*(in1->data() + i)<<
                        " in2[i] = "<<*(in2->data() + i)<<std::endl;
            return false;
        }
    }
    return true;
}

void test_fixedt_gen_shares(size_t p,
                std::vector<std::shared_ptr<TensorAdapter<int64_t>>> in,
                std::vector<std::shared_ptr<TensorAdapter<int64_t>>>& out) {
    if (p == 0) {

        std::shared_ptr<TensorAdapter<int64_t>> out1_shared[3];
        std::shared_ptr<TensorAdapter<int64_t>> out2_shared[3];
        for (int i = 0; i < 3; i++) {
            out1_shared[i] = g_ctx_holder::tensor_factory()->
                                    create<int64_t>(out[0]->shape());
            out2_shared[i] = g_ctx_holder::tensor_factory()->
                                    create<int64_t>(out[0]->shape());
        }
        TensorAdapter<int64_t>* out1[3] = {out1_shared[0].get(),
                            out1_shared[1].get(), out1_shared[2].get()};
        TensorAdapter<int64_t>* out2[3] = {out2_shared[0].get(),
                            out2_shared[1].get(), out2_shared[2].get()};

        Fix64N16::share(in[0].get(), out1);
        Fix64N16::share(in[1].get(), out2);

        g_ctx_holder::mpc_ctx()->network()->template send(1, *out1[1]);
        g_ctx_holder::mpc_ctx()->network()->template send(1, *out1[2]);

        g_ctx_holder::mpc_ctx()->network()->template send(1, *out2[1]);
        g_ctx_holder::mpc_ctx()->network()->template send(1, *out2[2]);

        g_ctx_holder::mpc_ctx()->network()->template send(2, *out1[2]);
        g_ctx_holder::mpc_ctx()->network()->template send(2, *out1[0]);
        g_ctx_holder::mpc_ctx()->network()->template send(2, *out2[2]);
        g_ctx_holder::mpc_ctx()->network()->template send(2, *out2[0]);

        out1[0]->copy(out[0].get());
        out1[1]->copy(out[1].get());
        out2[0]->copy(out[2].get());
        out2[1]->copy(out[3].get());

    } else {
        std::shared_ptr<TensorAdapter<int64_t>> out3_shared[4];
        for (int i = 0; i < 4; i++) {
            out3_shared[i] = g_ctx_holder::tensor_factory()->
                                    create<int64_t>(out[0]->shape());
        }
        TensorAdapter<int64_t>* out3[4] = {out3_shared[0].get(),
                                           out3_shared[1].get(),
                                           out3_shared[2].get(),
                                           out3_shared[3].get()};
        for (int i = 0; i < 4; i++) {
            g_ctx_holder::mpc_ctx()->network()->template recv(0, *out3[i]);
            out3[i]->copy(out[i].get());
        }
    }

}

void test_fixedt_gen_shares(size_t p,
                std::shared_ptr<TensorAdapter<int64_t>> in,
                std::vector<std::shared_ptr<TensorAdapter<int64_t>>>& out) {

    if (p == 0) {

        std::shared_ptr<TensorAdapter<int64_t>> out1_shared[3];
        for (int i = 0; i < 3; i++) {
            out1_shared[i] = g_ctx_holder::tensor_factory()->
                                create<int64_t>(out[0]->shape());
        }
        TensorAdapter<int64_t>* out1[3] = {out1_shared[0].get(),
                            out1_shared[1].get(), out1_shared[2].get()};
        Fix64N16::share(in.get(), out1);

        g_ctx_holder::mpc_ctx()->network()->template send(1, *out1[1]);
        g_ctx_holder::mpc_ctx()->network()->template send(1, *out1[2]);

        g_ctx_holder::mpc_ctx()->network()->template send(2, *out1[2]);
        g_ctx_holder::mpc_ctx()->network()->template send(2, *out1[0]);

        out1[0]->copy(out[0].get());
        out1[1]->copy(out[1].get());

    } else {
        std::shared_ptr<TensorAdapter<int64_t>> out3_shared[2];
        for (int i = 0; i < 2; i++) {
            out3_shared[i] = g_ctx_holder::tensor_factory()->
                                create<int64_t>(out[0]->shape());
        }
        TensorAdapter<int64_t>* out3[2] = {out3_shared[0].get(),
                            out3_shared[1].get()};
        for (int i = 0; i < 2; i++) {
            g_ctx_holder::mpc_ctx()->network()->template recv(0, *out3[i]);
            out3[i]->copy(out[i].get());
        }
    }

}

void test_fixedt_share(size_t p, TensorAdapter<int64_t>* in,
               TensorAdapter<int64_t>* ret) {

    if (in || ret) {
        TensorAdapter<int64_t>* output[3];
        for (int i = 0; i < 3; i++) {
            output[i] = new PaddleTensor<int64_t>(g_ctx_holder::device_ctx());
            dynamic_cast<PaddleTensor<int64_t>*>(output[i])->reshape(in->shape());
        }
        Fix64N16::share(in, output);
        output[0]->add(output[1], ret);
        ret->add(output[2], ret);

        for (int i = 0; i < 3; i++) {
            delete output[i];
        }
    }
}

void test_fixedt_add_fixed(size_t p,
               std::vector<std::shared_ptr<TensorAdapter<int64_t>>> in,
               TensorAdapter<int64_t>* out) {
    std::vector<std::shared_ptr<TensorAdapter<int64_t>>> temp;
    for (int i = 0; i < 6; i++) {
        temp.emplace_back(gen(out->shape()));
    }

    test_fixedt_gen_shares(p, in, temp);
    Fix64N16* lhs = new Fix64N16(temp[0].get(), temp[1].get());
    Fix64N16* rhs = new Fix64N16(temp[2].get(), temp[3].get());
    Fix64N16* result = new Fix64N16(temp[4].get(), temp[5].get());
    lhs->add(rhs, result);
    result->reveal(out);
}

void test_fixedt_add_plain(size_t p,
               std::vector<std::shared_ptr<TensorAdapter<int64_t>>> in,
               TensorAdapter<int64_t>* out) {
    std::vector<std::shared_ptr<TensorAdapter<int64_t>>> temp;
    for (int i = 0; i < 4; i++) {
        temp.emplace_back(gen(out->shape()));
    }

    test_fixedt_gen_shares(p, in[0], temp);

    Fix64N16* lhs = new Fix64N16(temp[0].get(), temp[1].get());
    Fix64N16* result = new Fix64N16(temp[2].get(), temp[3].get());
    lhs->add(in[1].get(), result);
    result->reveal(out);
}

void test_fixedt_sub_fixed(size_t p,
               std::vector<std::shared_ptr<TensorAdapter<int64_t>>> in,
               TensorAdapter<int64_t>* out) {
    std::vector<std::shared_ptr<TensorAdapter<int64_t>>> temp;
    for (int i = 0; i < 6; i++) {
        temp.emplace_back(gen(out->shape()));
    }

    test_fixedt_gen_shares(p, in, temp);
    Fix64N16* lhs = new Fix64N16(temp[0].get(), temp[1].get());
    Fix64N16* rhs = new Fix64N16(temp[2].get(), temp[3].get());
    Fix64N16* result = new Fix64N16(temp[4].get(), temp[5].get());
    lhs->sub(rhs, result);
    result->reveal(out);
}

void test_fixedt_sub_plain(size_t p,
               std::vector<std::shared_ptr<TensorAdapter<int64_t>>> in,
               TensorAdapter<int64_t>* out) {
    std::vector<std::shared_ptr<TensorAdapter<int64_t>>> temp;
    for (int i = 0; i < 4; i++) {
        temp.emplace_back(gen(out->shape()));
    }

    test_fixedt_gen_shares(p, in[0], temp);

    Fix64N16* lhs = new Fix64N16(temp[0].get(), temp[1].get());
    Fix64N16* result = new Fix64N16(temp[2].get(), temp[3].get());
    lhs->sub(in[1].get(), result);
    result->reveal(out);
}

void test_fixedt_neg_fixed(size_t p,
               std::vector<std::shared_ptr<TensorAdapter<int64_t>>> in,
               TensorAdapter<int64_t>* out) {
    std::vector<std::shared_ptr<TensorAdapter<int64_t>>> temp;
    for (int i = 0; i < 4; i++) {
        temp.emplace_back(gen(out->shape()));
    }

    test_fixedt_gen_shares(p, in[0], temp);

    Fix64N16* lhs = new Fix64N16(temp[0].get(), temp[1].get());
    Fix64N16* result = new Fix64N16(temp[2].get(), temp[3].get());
    lhs->negative(result);
    result->reveal(out);
}

void test_fixedt_mul_fixed(size_t p,
               std::vector<std::shared_ptr<TensorAdapter<int64_t>>> in,
               TensorAdapter<int64_t>* out) {
    std::vector<std::shared_ptr<TensorAdapter<int64_t>>> temp;
    for (int i = 0; i < 6; i++) {
        temp.emplace_back(gen(out->shape()));
    }

    test_fixedt_gen_shares(p, in, temp);
    Fix64N16* lhs = new Fix64N16(temp[0].get(), temp[1].get());
    Fix64N16* rhs = new Fix64N16(temp[2].get(), temp[3].get());
    Fix64N16* result = new Fix64N16(temp[4].get(), temp[5].get());
    lhs->mul(rhs, result);
    result->reveal(out);
}

void test_fixedt_mul2_fixed(size_t p,
               std::vector<std::shared_ptr<TensorAdapter<int64_t>>> in,
               TensorAdapter<int64_t>* out) {
    std::vector<std::shared_ptr<TensorAdapter<int64_t>>> temp;
    for (int i = 0; i < 6; i++) {
        temp.emplace_back(gen(out->shape()));
    }

    test_fixedt_gen_shares(p, in, temp);
    Fix64N16* lhs = new Fix64N16(temp[0].get(), temp[1].get());
    Fix64N16* rhs = new Fix64N16(temp[2].get(), temp[3].get());
    Fix64N16* result = new Fix64N16(temp[4].get(), temp[5].get());
    lhs->mul2(rhs, result);
    result->reveal(out);
}

void test_fixedt_mul_plain(size_t p,
               std::vector<std::shared_ptr<TensorAdapter<int64_t>>> in,
               TensorAdapter<int64_t>* out) {
    std::vector<std::shared_ptr<TensorAdapter<int64_t>>> temp;
    for (int i = 0; i < 4; i++) {
        temp.emplace_back(gen(out->shape()));
    }

    test_fixedt_gen_shares(p, in[0], temp);

    Fix64N16* lhs = new Fix64N16(temp[0].get(), temp[1].get());
    Fix64N16* result = new Fix64N16(temp[2].get(), temp[3].get());
    lhs->mul(in[1].get(), result);
    result->reveal(out);
}

void test_fixedt_div_plain(size_t p,
               std::vector<std::shared_ptr<TensorAdapter<int64_t>>> in,
               TensorAdapter<int64_t>* out) {
    std::vector<std::shared_ptr<TensorAdapter<int64_t>>> temp;
    for (int i = 0; i < 4; i++) {
        temp.emplace_back(gen(out->shape()));
    }

    test_fixedt_gen_shares(p, in[0], temp);

    Fix64N16* lhs = new Fix64N16(temp[0].get(), temp[1].get());
    Fix64N16* result = new Fix64N16(temp[2].get(), temp[3].get());
    lhs->div(in[1].get(), result);
    result->reveal(out);
}

void test_fixedt_sum_fixed(size_t p,
               std::vector<std::shared_ptr<TensorAdapter<int64_t>>> in,
               TensorAdapter<int64_t>* out) {
    std::vector<std::shared_ptr<TensorAdapter<int64_t>>> temp;
    for (int i = 0; i < 2; i++) {
        temp.emplace_back(gen(in[0]->shape()));
    }

    for (int i = 2; i < 4; i++) {
        temp.emplace_back(gen(out->shape()));
    }

    test_fixedt_gen_shares(p, in[0], temp);

    Fix64N16* lhs = new Fix64N16(temp[0].get(), temp[1].get());
    Fix64N16* result = new Fix64N16(temp[2].get(), temp[3].get());
    lhs->sum(result);

    result->reveal(out);
}

void test_fixedt_poly_fixed(size_t p,
               std::vector<std::shared_ptr<TensorAdapter<int64_t>>> in,
               TensorAdapter<int64_t>* out) {
    std::vector<std::shared_ptr<TensorAdapter<int64_t>>> temp;
    for (int i = 0; i < 4; i++) {
        temp.emplace_back(gen(out->shape()));
    }

    test_fixedt_gen_shares(p, in[0], temp);

    auto c_shape = out->shape();
    c_shape.insert(c_shape.begin(), 2);
    //construct coeff
    auto coeff = gen(c_shape);
    std::vector<int64_t> w;
    w.resize(2);
    w[0] = 1 << 16;
    w[1] = 1 << 16;

    auto c_ptr = coeff->data();
    for (size_t i = 0; i < w.size(); i++) {
        for (size_t j = 0; j < in[0]->numel(); j++) {
            *(c_ptr + i * in[0]->numel() + j) = w[i];
        }
    }
    coeff->scaling_factor() = 16;

    Fix64N16* lhs = new Fix64N16(temp[0].get(), temp[1].get());
    Fix64N16* result = new Fix64N16(temp[2].get(), temp[3].get());
    lhs->polynomial(coeff.get(), result);
    result->reveal(out);
}

void test_fixedt_poly_wise_fixed(size_t p,
               std::vector<std::shared_ptr<TensorAdapter<int64_t>>> in,
               TensorAdapter<int64_t>* out) {
    std::vector<std::shared_ptr<TensorAdapter<int64_t>>> temp;
    for (int i = 0; i < 4; i++) {
        temp.emplace_back(gen(out->shape()));
    }

    test_fixedt_gen_shares(p, in[0], temp);
    Fix64N16* lhs = new Fix64N16(temp[0].get(), temp[1].get());
    Fix64N16* result = new Fix64N16(temp[2].get(), temp[3].get());

    //constrct break_point
    auto shape = in[0]->shape();
    shape.insert(shape.begin(), 1);
    auto break_point = gen(shape);
    for (size_t i = 0; i < break_point->numel(); ++i) {
        break_point->data()[i] = 0;
    }
    break_point->scaling_factor() = 16;

    //contruct coeff
    std::vector<size_t> shape_ = {2, 2};
    auto in_shape = in[0]->shape();
    shape_.insert(shape_.end(), in_shape.begin(), in_shape.end());
    auto coeff = gen(shape_);
    int64_t* c_ptr = coeff->data();
    for (size_t i = 0; i < 4 * in[0]->numel(); i++) {
        *(c_ptr + i) = 1 << 16;
    }
    for (size_t i = in[0]->numel(); i < in[0]->numel() * 2; i++) {
        *(c_ptr + i) = 0;
    }
    coeff->scaling_factor() = 16;

    lhs->polynomial_piecewise(coeff.get(), break_point.get(), result);

    result->reveal(out);
}

void test_fixedt_relu_fixed(size_t p,
               std::vector<std::shared_ptr<TensorAdapter<int64_t>>> in,
               TensorAdapter<int64_t>* out) {
    std::vector<std::shared_ptr<TensorAdapter<int64_t>>> temp;
    for (int i = 0; i < 4; i++) {
        temp.emplace_back(gen(out->shape()));
    }

    test_fixedt_gen_shares(p, in[0], temp);

    Fix64N16* lhs = new Fix64N16(temp[0].get(), temp[1].get());
    Fix64N16* result = new Fix64N16(temp[2].get(), temp[3].get());
    lhs->relu(result);
    result->reveal(out);
}

void test_fixedt_softmax_fixed(size_t p,
               std::vector<std::shared_ptr<TensorAdapter<int64_t>>> in,
               TensorAdapter<int64_t>* out) {
    std::vector<std::shared_ptr<TensorAdapter<int64_t>>> temp;
    for (int i = 0; i < 4; i++) {
        temp.emplace_back(gen(out->shape()));
    }

    test_fixedt_gen_shares(p, in[0], temp);

    Fix64N16* lhs = new Fix64N16(temp[0].get(), temp[1].get());
    Fix64N16* result = new Fix64N16(temp[2].get(), temp[3].get());
    lhs->softmax(result);
    result->reveal(out);
}

void test_fixedt_sigmoid_fixed(size_t p,
               std::vector<std::shared_ptr<TensorAdapter<int64_t>>> in,
               TensorAdapter<int64_t>* out) {
    std::vector<std::shared_ptr<TensorAdapter<int64_t>>> temp;
    for (int i = 0; i < 4; i++) {
        temp.emplace_back(gen(out->shape()));
    }

    test_fixedt_gen_shares(p, in[0], temp);

    Fix64N16* lhs = new Fix64N16(temp[0].get(), temp[1].get());
    Fix64N16* result = new Fix64N16(temp[2].get(), temp[3].get());
    lhs->sigmoid(result);
    result->reveal(out);
}

void test_fixedt_exp_fixed(size_t p,
               std::vector<std::shared_ptr<TensorAdapter<int64_t>>> in,
               TensorAdapter<int64_t>* out) {
    std::vector<std::shared_ptr<TensorAdapter<int64_t>>> temp;
    for (int i = 0; i < 4; i++) {
        temp.emplace_back(gen(out->shape()));
    }

    test_fixedt_gen_shares(p, in[0], temp);

    Fix64N16* lhs = new Fix64N16(temp[0].get(), temp[1].get());
    Fix64N16* result = new Fix64N16(temp[2].get(), temp[3].get());
    lhs->exp(result);
    result->reveal(out);
}

void test_fixedt_mat_mul_fixed(size_t p,
               std::vector<std::shared_ptr<TensorAdapter<int64_t>>> in,
               TensorAdapter<int64_t>* out) {
    std::vector<std::shared_ptr<TensorAdapter<int64_t>>> temp;
    for (int i = 0; i < 6; i++) {
        temp.emplace_back(gen(out->shape()));
    }

    test_fixedt_gen_shares(p, in, temp);
    Fix64N16* lhs = new Fix64N16(temp[0].get(), temp[1].get());
    Fix64N16* rhs = new Fix64N16(temp[2].get(), temp[3].get());
    Fix64N16* result = new Fix64N16(temp[4].get(), temp[5].get());
    lhs->mat_mul(rhs, result);
    result->reveal(out);
}

void test_fixedt_mat_mul_plain(size_t p,
               std::vector<std::shared_ptr<TensorAdapter<int64_t>>> in,
               TensorAdapter<int64_t>* out) {
    std::vector<std::shared_ptr<TensorAdapter<int64_t>>> temp;
    for (int i = 0; i < 4; i++) {
        temp.emplace_back(gen(out->shape()));
    }

    test_fixedt_gen_shares(p, in[0], temp);

    Fix64N16* lhs = new Fix64N16(temp[0].get(), temp[1].get());
    Fix64N16* result = new Fix64N16(temp[2].get(), temp[3].get());
    lhs->mat_mul(in[1].get(), result);
    result->reveal(out);
}

void test_fixedt_dot_mul_fixed(size_t p,
               std::vector<std::shared_ptr<TensorAdapter<int64_t>>> in,
               TensorAdapter<int64_t>* out) {
    std::vector<std::shared_ptr<TensorAdapter<int64_t>>> temp;
    for (int i = 0; i < 4; i++) {
        temp.emplace_back(gen(in[0]->shape()));
    }
    for (int i = 4; i < 6; i++) {
        temp.emplace_back(gen(out->shape()));
    }

    test_fixedt_gen_shares(p, in, temp);

    Fix64N16* lhs = new Fix64N16(temp[0].get(), temp[1].get());
    Fix64N16* rhs = new Fix64N16(temp[2].get(), temp[3].get());
    Fix64N16* result = new Fix64N16(temp[4].get(), temp[5].get());
    lhs->dot_mul(rhs, result);
    result->reveal(out);
}

void test_fixedt_dot_mul_plain(size_t p,
               std::vector<std::shared_ptr<TensorAdapter<int64_t>>> in,
               TensorAdapter<int64_t>* out) {
    std::vector<std::shared_ptr<TensorAdapter<int64_t>>> temp;
    for (int i = 0; i < 2; i++) {
        temp.emplace_back(gen(in[0]->shape()));
    }
    for (int i = 2; i < 4; i++) {
        temp.emplace_back(gen(out->shape()));
    }

    test_fixedt_gen_shares(p, in[0], temp);

    Fix64N16* lhs = new Fix64N16(temp[0].get(), temp[1].get());
    Fix64N16* result = new Fix64N16(temp[2].get(), temp[3].get());
    lhs->dot_mul(in[1].get(), result);
    result->reveal(out);
}

void test_fixedt_gt_plain(size_t p,
               std::vector<std::shared_ptr<TensorAdapter<int64_t>>> in,
               TensorAdapter<int64_t>* out) {
    std::vector<std::shared_ptr<TensorAdapter<int64_t>>> temp;
    for (int i = 0; i < 4; i++) {
        temp.emplace_back(gen(out->shape()));
    }

    test_fixedt_gen_shares(p, in[0], temp);

    Fix64N16* lhs = new Fix64N16(temp[0].get(), temp[1].get());

    BooleanTensor<int64_t>* result =
        new BooleanTensor<int64_t>(temp[2].get(), temp[3].get());
    lhs->gt(in[1].get(), result);
    result->reveal(out);
}

void test_fixedt_gt_fixed(size_t p,
               std::vector<std::shared_ptr<TensorAdapter<int64_t>>> in,
               TensorAdapter<int64_t>* out) {
    std::vector<std::shared_ptr<TensorAdapter<int64_t>>> temp;
    for (int i = 0; i < 6; i++) {
        temp.emplace_back(gen(out->shape()));
    }

    test_fixedt_gen_shares(p, in, temp);
    Fix64N16* lhs = new Fix64N16(temp[0].get(), temp[1].get());
    Fix64N16* rhs = new Fix64N16(temp[2].get(), temp[3].get());
    BooleanTensor<int64_t>* result =
        new BooleanTensor<int64_t>(temp[4].get(), temp[5].get());
    lhs->gt(rhs, result);
    result->reveal(out);
}

void test_fixedt_lt_plain(size_t p,
               std::vector<std::shared_ptr<TensorAdapter<int64_t>>> in,
               TensorAdapter<int64_t>* out) {
    std::vector<std::shared_ptr<TensorAdapter<int64_t>>> temp;
    for (int i = 0; i < 4; i++) {
        temp.emplace_back(gen(out->shape()));
    }

    test_fixedt_gen_shares(p, in[0], temp);

    Fix64N16* lhs = new Fix64N16(temp[0].get(), temp[1].get());

    BooleanTensor<int64_t>* result =
        new BooleanTensor<int64_t>(temp[2].get(), temp[3].get());
    lhs->lt(in[1].get(), result);
    result->reveal(out);
}

void test_fixedt_lt_fixed(size_t p,
               std::vector<std::shared_ptr<TensorAdapter<int64_t>>> in,
               TensorAdapter<int64_t>* out) {
    std::vector<std::shared_ptr<TensorAdapter<int64_t>>> temp;
    for (int i = 0; i < 6; i++) {
        temp.emplace_back(gen(out->shape()));
    }

    test_fixedt_gen_shares(p, in, temp);
    Fix64N16* lhs = new Fix64N16(temp[0].get(), temp[1].get());
    Fix64N16* rhs = new Fix64N16(temp[2].get(), temp[3].get());
    BooleanTensor<int64_t>* result =
        new BooleanTensor<int64_t>(temp[4].get(), temp[5].get());
    lhs->lt(rhs, result);
    result->reveal(out);
}

void test_fixedt_leq_plain(size_t p,
               std::vector<std::shared_ptr<TensorAdapter<int64_t>>> in,
               TensorAdapter<int64_t>* out) {
    std::vector<std::shared_ptr<TensorAdapter<int64_t>>> temp;
    for (int i = 0; i < 4; i++) {
        temp.emplace_back(gen(out->shape()));
    }

    test_fixedt_gen_shares(p, in[0], temp);

    Fix64N16* lhs = new Fix64N16(temp[0].get(), temp[1].get());

    BooleanTensor<int64_t>* result =
        new BooleanTensor<int64_t>(temp[2].get(), temp[3].get());
    lhs->leq(in[1].get(), result);
    result->reveal(out);
}

void test_fixedt_leq_fixed(size_t p,
               std::vector<std::shared_ptr<TensorAdapter<int64_t>>> in,
               TensorAdapter<int64_t>* out) {
    std::vector<std::shared_ptr<TensorAdapter<int64_t>>> temp;
    for (int i = 0; i < 6; i++) {
        temp.emplace_back(gen(out->shape()));
    }

    test_fixedt_gen_shares(p, in, temp);
    Fix64N16* lhs = new Fix64N16(temp[0].get(), temp[1].get());
    Fix64N16* rhs = new Fix64N16(temp[2].get(), temp[3].get());
    BooleanTensor<int64_t>* result =
        new BooleanTensor<int64_t>(temp[4].get(), temp[5].get());
    lhs->leq(rhs, result);
    result->reveal(out);
}

void test_fixedt_geq_plain(size_t p,
               std::vector<std::shared_ptr<TensorAdapter<int64_t>>> in,
               TensorAdapter<int64_t>* out) {
    std::vector<std::shared_ptr<TensorAdapter<int64_t>>> temp;
    for (int i = 0; i < 4; i++) {
        temp.emplace_back(gen(out->shape()));
    }

    test_fixedt_gen_shares(p, in[0], temp);

    Fix64N16* lhs = new Fix64N16(temp[0].get(), temp[1].get());

    BooleanTensor<int64_t>* result =
        new BooleanTensor<int64_t>(temp[2].get(), temp[3].get());
    lhs->geq(in[1].get(), result);
    result->reveal(out);
}

void test_fixedt_geq_fixed(size_t p,
               std::vector<std::shared_ptr<TensorAdapter<int64_t>>> in,
               TensorAdapter<int64_t>* out) {
    std::vector<std::shared_ptr<TensorAdapter<int64_t>>> temp;
    for (int i = 0; i < 6; i++) {
        temp.emplace_back(gen(out->shape()));
    }

    test_fixedt_gen_shares(p, in, temp);
    Fix64N16* lhs = new Fix64N16(temp[0].get(), temp[1].get());
    Fix64N16* rhs = new Fix64N16(temp[2].get(), temp[3].get());
    BooleanTensor<int64_t>* result =
        new BooleanTensor<int64_t>(temp[4].get(), temp[5].get());
    lhs->geq(rhs, result);
    result->reveal(out);
}

void test_fixedt_eq_plain(size_t p,
               std::vector<std::shared_ptr<TensorAdapter<int64_t>>> in,
               TensorAdapter<int64_t>* out) {
    std::vector<std::shared_ptr<TensorAdapter<int64_t>>> temp;
    for (int i = 0; i < 4; i++) {
        temp.emplace_back(gen(out->shape()));
    }

    test_fixedt_gen_shares(p, in[0], temp);

    Fix64N16* lhs = new Fix64N16(temp[0].get(), temp[1].get());

    BooleanTensor<int64_t>* result =
        new BooleanTensor<int64_t>(temp[2].get(), temp[3].get());
    lhs->eq(in[1].get(), result);
    result->reveal(out);
}

void test_fixedt_eq_fixed(size_t p,
               std::vector<std::shared_ptr<TensorAdapter<int64_t>>> in,
               TensorAdapter<int64_t>* out) {
    std::vector<std::shared_ptr<TensorAdapter<int64_t>>> temp;
    for (int i = 0; i < 6; i++) {
        temp.emplace_back(gen(out->shape()));
    }

    test_fixedt_gen_shares(p, in, temp);
    Fix64N16* lhs = new Fix64N16(temp[0].get(), temp[1].get());
    Fix64N16* rhs = new Fix64N16(temp[2].get(), temp[3].get());
    BooleanTensor<int64_t>* result =
        new BooleanTensor<int64_t>(temp[4].get(), temp[5].get());
    lhs->eq(rhs, result);
    result->reveal(out);
}

void test_fixedt_neq_plain(size_t p,
               std::vector<std::shared_ptr<TensorAdapter<int64_t>>> in,
               TensorAdapter<int64_t>* out) {
    std::vector<std::shared_ptr<TensorAdapter<int64_t>>> temp;
    for (int i = 0; i < 4; i++) {
        temp.emplace_back(gen(out->shape()));
    }

    test_fixedt_gen_shares(p, in[0], temp);

    Fix64N16* lhs = new Fix64N16(temp[0].get(), temp[1].get());

    BooleanTensor<int64_t>* result =
        new BooleanTensor<int64_t>(temp[2].get(), temp[3].get());
    lhs->neq(in[1].get(), result);
    result->reveal(out);
}

void test_fixedt_neq_fixed(size_t p,
               std::vector<std::shared_ptr<TensorAdapter<int64_t>>> in,
               TensorAdapter<int64_t>* out) {
    std::vector<std::shared_ptr<TensorAdapter<int64_t>>> temp;
    for (int i = 0; i < 6; i++) {
        temp.emplace_back(gen(out->shape()));
    }

    test_fixedt_gen_shares(p, in, temp);
    Fix64N16* lhs = new Fix64N16(temp[0].get(), temp[1].get());
    Fix64N16* rhs = new Fix64N16(temp[2].get(), temp[3].get());
    BooleanTensor<int64_t>* result =
        new BooleanTensor<int64_t>(temp[4].get(), temp[5].get());
    lhs->neq(rhs, result);
    result->reveal(out);
}

void test_fixedt_matmul_fixed(size_t p,
               std::vector<std::shared_ptr<TensorAdapter<int64_t>>> in,
               TensorAdapter<int64_t>* out) {
    std::vector<std::shared_ptr<TensorAdapter<int64_t>>> temp;
    for (int i = 0; i < 6; i++) {
        temp.emplace_back(gen(out->shape()));
    }

    test_fixedt_gen_shares(p, in, temp);
    Fix64N16* lhs = new Fix64N16(temp[0].get(), temp[1].get());
    Fix64N16* rhs = new Fix64N16(temp[2].get(), temp[3].get());
    Fix64N16* result = new Fix64N16(temp[4].get(), temp[5].get());
    lhs->mat_mul(rhs, result);
    result->reveal(out);
}

TEST_F(FixedTensorTest, matmulfixed) {

    std::vector<size_t> shape = {2, 2};
    std::vector<float> in0_val = {1.0, 1.0, 1.0, 1.0};
    std::vector<float> in1_val = {2.0, 2.0, 2.0, 2.0};
    std::vector<float> res_val = {4.0, 4.0, 4.0, 4.0};
    std::vector<std::shared_ptr<TensorAdapter<int64_t>>> in =
                            {gen(shape), gen(shape)};

    test_fixedt_gen_paddle_tensor<int64_t, 16>(in0_val,
                                shape, _cpu_ctx).copy(in[0].get());
    test_fixedt_gen_paddle_tensor<int64_t, 16>(in1_val,
                                shape, _cpu_ctx).copy(in[1].get());

    auto out0 = _s_tensor_factory->create<int64_t>(shape);
    auto out1 = _s_tensor_factory->create<int64_t>(shape);
    auto out2 = _s_tensor_factory->create<int64_t>(shape);

    PaddleTensor<int64_t> result =
            test_fixedt_gen_paddle_tensor<int64_t, 16>(res_val, shape, _cpu_ctx);

    _t[0] = std::thread([this, in, out0]() mutable {
        g_ctx_holder::template run_with_context(_exec_ctx.get(), _mpc_ctx[0], [&](){
            test_fixedt_matmul_fixed(0, in, out0.get());
        });

    });
    _t[1] = std::thread([this, in, out1]() mutable {
        g_ctx_holder::template run_with_context(_exec_ctx.get(), _mpc_ctx[1], [&](){
            test_fixedt_matmul_fixed(1, in, out1.get());
        });

    });
    _t[2] = std::thread([this, in, out2]() mutable {
        g_ctx_holder::template run_with_context(_exec_ctx.get(), _mpc_ctx[2], [&](){
            test_fixedt_matmul_fixed(2, in, out2.get());
        });

    });

    _t[0].join();
    _t[1].join();
    _t[2].join();

    EXPECT_TRUE(test_fixedt_check_tensor_eq(out0.get(), out1.get()));
    EXPECT_TRUE(test_fixedt_check_tensor_eq(out1.get(), out2.get()));
    EXPECT_TRUE(test_fixedt_check_tensor_eq(out0.get(), &result));
}

TEST_F(FixedTensorTest, share) {
    std::vector<size_t> shape = {2, 2};
    std::vector<float> in_val = {1.0, 1.0, 1.0, 1.0};
    PaddleTensor<int64_t> input =
            test_fixedt_gen_paddle_tensor<int64_t, 16>(in_val, shape, _cpu_ctx);
    auto output = _s_tensor_factory->create<int64_t>(shape);

    //test_fixedt_share(0, &input, output.get());

    _t[0] = std::thread([this, &input, output]() mutable {
        g_ctx_holder::template run_with_context(_exec_ctx.get(), _mpc_ctx[0], [&](){
            test_fixedt_share(0, &input, output.get());
        });

    });
    _t[1] = std::thread([this]() mutable {
        g_ctx_holder::template run_with_context(_exec_ctx.get(), _mpc_ctx[1], [&](){
            test_fixedt_share(1, nullptr, nullptr);
        });

    });
    _t[2] = std::thread([this]() mutable {
        g_ctx_holder::template run_with_context(_exec_ctx.get(), _mpc_ctx[2], [&](){
            test_fixedt_share(2, nullptr, nullptr);
        });

    });

    _t[0].join();
    _t[1].join();
    _t[2].join();

    EXPECT_TRUE(test_fixedt_check_tensor_eq(&input, output.get()));

}


TEST_F(FixedTensorTest, addfixed) {

    std::vector<size_t> shape = {2, 2};
    std::vector<float> in0_val = {1.0, 1.0, 1.0, 1.0};
    std::vector<float> in1_val = {2.0, 2.0, 2.0, 2.0};
    std::vector<float> res_val = {3.0, 3.0, 3.0, 3.0};
    std::vector<std::shared_ptr<TensorAdapter<int64_t>>> in =
                            {gen(shape), gen(shape)};

    test_fixedt_gen_paddle_tensor<int64_t, 16>(in0_val,
                                shape, _cpu_ctx).copy(in[0].get());
    test_fixedt_gen_paddle_tensor<int64_t, 16>(in1_val,
                                shape, _cpu_ctx).copy(in[1].get());

    auto out0 = _s_tensor_factory->create<int64_t>(shape);
    auto out1 = _s_tensor_factory->create<int64_t>(shape);
    auto out2 = _s_tensor_factory->create<int64_t>(shape);

    PaddleTensor<int64_t> result =
            test_fixedt_gen_paddle_tensor<int64_t, 16>(res_val, shape, _cpu_ctx);

    _t[0] = std::thread([this, in, out0]() mutable {
        g_ctx_holder::template run_with_context(_exec_ctx.get(), _mpc_ctx[0], [&](){
            test_fixedt_add_fixed(0, in, out0.get());
        });
    });
    _t[1] = std::thread([this, in, out1]() mutable {
        g_ctx_holder::template run_with_context(_exec_ctx.get(), _mpc_ctx[1], [&](){
            test_fixedt_add_fixed(1, in, out1.get());
        });
    });
    _t[2] = std::thread([this, in, out2]() mutable {
        g_ctx_holder::template run_with_context(_exec_ctx.get(), _mpc_ctx[2], [&](){
            test_fixedt_add_fixed(2, in, out2.get());
        });
    });

    _t[0].join();
    _t[1].join();
    _t[2].join();

    EXPECT_TRUE(test_fixedt_check_tensor_eq(out0.get(), out1.get()));
    EXPECT_TRUE(test_fixedt_check_tensor_eq(out1.get(), out2.get()));
    EXPECT_TRUE(test_fixedt_check_tensor_eq(out0.get(), &result));
}

TEST_F(FixedTensorTest, addplain) {
    std::vector<size_t> shape = {2, 2};
    std::vector<float> in0_val = {1.0, 1.0, 1.0, 1.0};
    std::vector<float> in1_val = {2.0, 2.0, 2.0, 2.0};
    std::vector<float> res_val = {3.0, 3.0, 3.0, 3.0};
    std::vector<std::shared_ptr<TensorAdapter<int64_t>>> in =
                            {gen(shape), gen(shape)};

    test_fixedt_gen_paddle_tensor<int64_t, 16>(in0_val,
                                shape, _cpu_ctx).copy(in[0].get());
    test_fixedt_gen_paddle_tensor<int64_t, 16>(in1_val,
                                shape, _cpu_ctx).copy(in[1].get());
    //not copy scaling factor in copy funtion
    dynamic_cast<PaddleTensor<int64_t>*>(in[1].get())->
                                scaling_factor() = 16;

    auto out0 = _s_tensor_factory->create<int64_t>(shape);
    auto out1 = _s_tensor_factory->create<int64_t>(shape);
    auto out2 = _s_tensor_factory->create<int64_t>(shape);
    PaddleTensor<int64_t> result =
            test_fixedt_gen_paddle_tensor<int64_t, 16>(res_val, shape, _cpu_ctx);

    _t[0] = std::thread([this, in, out0]() mutable {
        g_ctx_holder::template run_with_context(_exec_ctx.get(), _mpc_ctx[0], [&](){
            test_fixedt_add_plain(0, in, out0.get());
        });
    });
    _t[1] = std::thread([this, in, out1]() mutable {
        g_ctx_holder::template run_with_context(_exec_ctx.get(), _mpc_ctx[1], [&](){
            test_fixedt_add_plain(1, in, out1.get());
        });
    });
    _t[2] = std::thread([this, in, out2]() mutable {
        g_ctx_holder::template run_with_context(_exec_ctx.get(), _mpc_ctx[2], [&](){
            test_fixedt_add_plain(2, in, out2.get());
        });
    });

    _t[0].join();
    _t[1].join();
    _t[2].join();

    EXPECT_TRUE(test_fixedt_check_tensor_eq(out0.get(), out1.get()));
    EXPECT_TRUE(test_fixedt_check_tensor_eq(out1.get(), out2.get()));
    EXPECT_TRUE(test_fixedt_check_tensor_eq(out0.get(), &result));
}

TEST_F(FixedTensorTest, subfixed) {

    std::vector<size_t> shape = {2, 2};
    std::vector<float> in0_val = {3.0, 3.0, 3.0, 3.0};
    std::vector<float> in1_val = {2.0, 2.0, 2.0, 2.0};
    std::vector<float> res_val = {1.0, 1.0, 1.0, 1.0};
    std::vector<std::shared_ptr<TensorAdapter<int64_t>>> in =
                            {gen(shape), gen(shape)};

    test_fixedt_gen_paddle_tensor<int64_t, 16>(in0_val,
                                shape, _cpu_ctx).copy(in[0].get());
    test_fixedt_gen_paddle_tensor<int64_t, 16>(in1_val,
                                shape, _cpu_ctx).copy(in[1].get());

    auto out0 = _s_tensor_factory->create<int64_t>(shape);
    auto out1 = _s_tensor_factory->create<int64_t>(shape);
    auto out2 = _s_tensor_factory->create<int64_t>(shape);

    PaddleTensor<int64_t> result =
            test_fixedt_gen_paddle_tensor<int64_t, 16>(res_val, shape, _cpu_ctx);

    _t[0] = std::thread([this, in, out0]() mutable {
        g_ctx_holder::template run_with_context(_exec_ctx.get(), _mpc_ctx[0], [&](){
            test_fixedt_sub_fixed(0, in, out0.get());
        });
    });
    _t[1] = std::thread([this, in, out1]() mutable {
        g_ctx_holder::template run_with_context(_exec_ctx.get(), _mpc_ctx[1], [&](){
            test_fixedt_sub_fixed(1, in, out1.get());
        });
    });
    _t[2] = std::thread([this, in, out2]() mutable {
        g_ctx_holder::template run_with_context(_exec_ctx.get(), _mpc_ctx[2], [&](){
            test_fixedt_sub_fixed(2, in, out2.get());
        });
    });

    _t[0].join();
    _t[1].join();
    _t[2].join();

    EXPECT_TRUE(test_fixedt_check_tensor_eq(out0.get(), out1.get()));
    EXPECT_TRUE(test_fixedt_check_tensor_eq(out1.get(), out2.get()));
    EXPECT_TRUE(test_fixedt_check_tensor_eq(out0.get(), &result));
}

TEST_F(FixedTensorTest, subplain) {

    std::vector<size_t> shape = {2, 2};
    std::vector<float> in0_val = {3.0, 3.0, 3.0, 3.0};
    std::vector<float> in1_val = {2.0, 2.0, 2.0, 2.0};
    std::vector<float> res_val = {1.0, 1.0, 1.0, 1.0};
    std::vector<std::shared_ptr<TensorAdapter<int64_t>>> in =
                            {gen(shape), gen(shape)};

    test_fixedt_gen_paddle_tensor<int64_t, 16>(in0_val,
                                shape, _cpu_ctx).copy(in[0].get());
    test_fixedt_gen_paddle_tensor<int64_t, 16>(in1_val,
                                shape, _cpu_ctx).copy(in[1].get());
    //not copy scaling factor in copy funtion
    dynamic_cast<PaddleTensor<int64_t>*>(in[1].get())->
                                scaling_factor() = 16;

    auto out0 = _s_tensor_factory->create<int64_t>(shape);
    auto out1 = _s_tensor_factory->create<int64_t>(shape);
    auto out2 = _s_tensor_factory->create<int64_t>(shape);
    PaddleTensor<int64_t> result =
            test_fixedt_gen_paddle_tensor<int64_t, 16>(res_val, shape, _cpu_ctx);

    _t[0] = std::thread([this, in, out0]() mutable {
        g_ctx_holder::template run_with_context(_exec_ctx.get(), _mpc_ctx[0], [&](){
            test_fixedt_sub_plain(0, in, out0.get());
        });
    });
    _t[1] = std::thread([this, in, out1]() mutable {
        g_ctx_holder::template run_with_context(_exec_ctx.get(), _mpc_ctx[1], [&](){
            test_fixedt_sub_plain(1, in, out1.get());
        });
    });
    _t[2] = std::thread([this, in, out2]() mutable {
        g_ctx_holder::template run_with_context(_exec_ctx.get(), _mpc_ctx[2], [&](){
            test_fixedt_sub_plain(2, in, out2.get());
        });
    });

    _t[0].join();
    _t[1].join();
    _t[2].join();

    EXPECT_TRUE(test_fixedt_check_tensor_eq(out0.get(), out1.get()));
    EXPECT_TRUE(test_fixedt_check_tensor_eq(out1.get(), out2.get()));
    EXPECT_TRUE(test_fixedt_check_tensor_eq(out0.get(), &result));
}

TEST_F(FixedTensorTest, negfixed) {

    std::vector<size_t> shape = {2, 2};
    std::vector<float> in0_val = {1.0, 1.0, 1.0, 1.0};
    //std::vector<float> in1_val = {2.0, 2.0, 2.0, 2.0};
    std::vector<float> res_val = {-1.0, -1.0, -1.0, -1.0};
    std::vector<std::shared_ptr<TensorAdapter<int64_t>>> in = {gen(shape)};

    test_fixedt_gen_paddle_tensor<int64_t, 16>(in0_val,
                                shape, _cpu_ctx).copy(in[0].get());

    auto out0 = _s_tensor_factory->create<int64_t>(shape);
    auto out1 = _s_tensor_factory->create<int64_t>(shape);
    auto out2 = _s_tensor_factory->create<int64_t>(shape);

    PaddleTensor<int64_t> result =
            test_fixedt_gen_paddle_tensor<int64_t, 16>(res_val, shape, _cpu_ctx);

    _t[0] = std::thread([this, in, out0]() mutable {
        g_ctx_holder::template run_with_context(_exec_ctx.get(), _mpc_ctx[0], [&](){
            test_fixedt_neg_fixed(0, in, out0.get());
        });

    });
    _t[1] = std::thread([this, in, out1]() mutable {
        g_ctx_holder::template run_with_context(_exec_ctx.get(), _mpc_ctx[1], [&](){
            test_fixedt_neg_fixed(1, in, out1.get());
        });

    });
    _t[2] = std::thread([this, in, out2]() mutable {
        g_ctx_holder::template run_with_context(_exec_ctx.get(), _mpc_ctx[2], [&](){
            test_fixedt_neg_fixed(2, in, out2.get());
        });

    });

    _t[0].join();
    _t[1].join();
    _t[2].join();

    EXPECT_TRUE(test_fixedt_check_tensor_eq(out0.get(), out1.get()));
    EXPECT_TRUE(test_fixedt_check_tensor_eq(out1.get(), out2.get()));
    EXPECT_TRUE(test_fixedt_check_tensor_eq(out0.get(), &result));
}

TEST_F(FixedTensorTest, mulfixed) {

    std::vector<size_t> shape = {2, 2};
    std::vector<float> in0_val = {1.0, 1.0, 1.0, 1.0};
    std::vector<float> in1_val = {2.0, 2.0, 2.0, 2.0};
    std::vector<float> res_val = {2.0, 2.0, 2.0, 2.0};
    std::vector<std::shared_ptr<TensorAdapter<int64_t>>> in =
                            {gen(shape), gen(shape)};

    test_fixedt_gen_paddle_tensor<int64_t, 16>(in0_val,
                                shape, _cpu_ctx).copy(in[0].get());
    test_fixedt_gen_paddle_tensor<int64_t, 16>(in1_val,
                                shape, _cpu_ctx).copy(in[1].get());

    auto out0 = _s_tensor_factory->create<int64_t>(shape);
    auto out1 = _s_tensor_factory->create<int64_t>(shape);
    auto out2 = _s_tensor_factory->create<int64_t>(shape);

    PaddleTensor<int64_t> result =
            test_fixedt_gen_paddle_tensor<int64_t, 16>(res_val, shape, _cpu_ctx);

    _t[0] = std::thread([this, in, out0]() mutable {
        g_ctx_holder::template run_with_context(_exec_ctx.get(), _mpc_ctx[0], [&](){
            test_fixedt_mul_fixed(0, in, out0.get());
        });

    });
    _t[1] = std::thread([this, in, out1]() mutable {
        g_ctx_holder::template run_with_context(_exec_ctx.get(), _mpc_ctx[1], [&](){
            test_fixedt_mul_fixed(1, in, out1.get());
        });

    });
    _t[2] = std::thread([this, in, out2]() mutable {
        g_ctx_holder::template run_with_context(_exec_ctx.get(), _mpc_ctx[2], [&](){
            test_fixedt_mul_fixed(2, in, out2.get());
        });

    });

    _t[0].join();
    _t[1].join();
    _t[2].join();

    EXPECT_TRUE(test_fixedt_check_tensor_eq(out0.get(), out1.get()));
    EXPECT_TRUE(test_fixedt_check_tensor_eq(out1.get(), out2.get()));
    EXPECT_TRUE(test_fixedt_check_tensor_eq(out0.get(), &result));
}

TEST_F(FixedTensorTest, mul2fixed) {

    std::vector<size_t> shape = {2, 2};
    std::vector<float> in0_val = {1.0, 1.0, 1.0, 1.0};
    std::vector<float> in1_val = {2.0, 2.0, 2.0, 2.0};
    std::vector<float> res_val = {2.0, 2.0, 2.0, 2.0};
    std::vector<std::shared_ptr<TensorAdapter<int64_t>>> in =
                            {gen(shape), gen(shape)};

    test_fixedt_gen_paddle_tensor<int64_t, 16>(in0_val,
                                shape, _cpu_ctx).copy(in[0].get());
    test_fixedt_gen_paddle_tensor<int64_t, 16>(in1_val,
                                shape, _cpu_ctx).copy(in[1].get());

    auto out0 = _s_tensor_factory->create<int64_t>(shape);
    auto out1 = _s_tensor_factory->create<int64_t>(shape);
    auto out2 = _s_tensor_factory->create<int64_t>(shape);

    PaddleTensor<int64_t> result =
            test_fixedt_gen_paddle_tensor<int64_t, 16>(res_val, shape, _cpu_ctx);

    _t[0] = std::thread([this, in, out0]() mutable {
        g_ctx_holder::template run_with_context(_exec_ctx.get(), _mpc_ctx[0], [&](){
            test_fixedt_mul2_fixed(0, in, out0.get());
        });

    });
    _t[1] = std::thread([this, in, out1]() mutable {
        g_ctx_holder::template run_with_context(_exec_ctx.get(), _mpc_ctx[1], [&](){
            test_fixedt_mul2_fixed(1, in, out1.get());
        });

    });
    _t[2] = std::thread([this, in, out2]() mutable {
        g_ctx_holder::template run_with_context(_exec_ctx.get(), _mpc_ctx[2], [&](){
            test_fixedt_mul2_fixed(2, in, out2.get());
        });

    });

    _t[0].join();
    _t[1].join();
    _t[2].join();

    EXPECT_TRUE(test_fixedt_check_tensor_eq(out0.get(), out1.get()));
    EXPECT_TRUE(test_fixedt_check_tensor_eq(out1.get(), out2.get()));
    EXPECT_TRUE(test_fixedt_check_tensor_eq(out0.get(), &result));
}

TEST_F(FixedTensorTest, mulplain) {

    std::vector<size_t> shape = {2, 2};
    std::vector<float> in0_val = {1.0, 1.0, 1.0, 1.0};
    std::vector<float> in1_val = {2.0, 2.0, 2.0, 2.0};
    std::vector<float> res_val = {2.0, 2.0, 2.0, 2.0};
    std::vector<std::shared_ptr<TensorAdapter<int64_t>>> in =
                            {gen(shape), gen(shape)};

    test_fixedt_gen_paddle_tensor<int64_t, 16>(in0_val,
                                shape, _cpu_ctx).copy(in[0].get());
    test_fixedt_gen_paddle_tensor<int64_t, 16>(in1_val,
                                shape, _cpu_ctx).copy(in[1].get());
    //not copy scaling factor in copy funtion
    dynamic_cast<PaddleTensor<int64_t>*>(in[0].get())->
                                scaling_factor() = 16;
    dynamic_cast<PaddleTensor<int64_t>*>(in[1].get())->
                                scaling_factor() = 16;

    auto out0 = _s_tensor_factory->create<int64_t>(shape);
    auto out1 = _s_tensor_factory->create<int64_t>(shape);
    auto out2 = _s_tensor_factory->create<int64_t>(shape);
    PaddleTensor<int64_t> result =
            test_fixedt_gen_paddle_tensor<int64_t, 16>(res_val, shape, _cpu_ctx);

    _t[0] = std::thread([this, in, out0]() mutable {
        g_ctx_holder::template run_with_context(_exec_ctx.get(), _mpc_ctx[0], [&](){
            test_fixedt_mul_plain(0, in, out0.get());
        });

    });
    _t[1] = std::thread([this, in, out1]() mutable {
        g_ctx_holder::template run_with_context(_exec_ctx.get(), _mpc_ctx[1], [&](){
            test_fixedt_mul_plain(1, in, out1.get());
        });

    });
    _t[2] = std::thread([this, in, out2]() mutable {
        g_ctx_holder::template run_with_context(_exec_ctx.get(), _mpc_ctx[2], [&](){
            test_fixedt_mul_plain(2, in, out2.get());
        });

    });

    _t[0].join();
    _t[1].join();
    _t[2].join();

    EXPECT_TRUE(test_fixedt_check_tensor_eq(out0.get(), out1.get()));
    EXPECT_TRUE(test_fixedt_check_tensor_eq(out1.get(), out2.get()));
    EXPECT_TRUE(test_fixedt_check_tensor_eq(out0.get(), &result));
}

TEST_F(FixedTensorTest, divplain) {

    std::vector<size_t> shape = {2, 2};
    std::vector<float> in0_val = {1.0, 1.0, 1.0, 1.0};
    std::vector<float> in1_val = {2.0, 2.0, 2.0, 2.0};
    std::vector<float> res_val = {0.5, 0.5, 0.5, 0.5};
    std::vector<std::shared_ptr<TensorAdapter<int64_t>>> in =
                            {gen(shape), gen(shape)};

    test_fixedt_gen_paddle_tensor<int64_t, 16>(in0_val,
                                shape, _cpu_ctx).copy(in[0].get());
    test_fixedt_gen_paddle_tensor<int64_t, 16>(in1_val,
                                shape, _cpu_ctx).copy(in[1].get());
    //not copy scaling factor in copy funtion
    dynamic_cast<PaddleTensor<int64_t>*>(in[0].get())->
                                scaling_factor() = 16;
    dynamic_cast<PaddleTensor<int64_t>*>(in[1].get())->
                                scaling_factor() = 16;

    auto out0 = _s_tensor_factory->create<int64_t>(shape);
    auto out1 = _s_tensor_factory->create<int64_t>(shape);
    auto out2 = _s_tensor_factory->create<int64_t>(shape);
    PaddleTensor<int64_t> result =
            test_fixedt_gen_paddle_tensor<int64_t, 16>(res_val, shape, _cpu_ctx);

    _t[0] = std::thread([this, in, out0]() mutable {
        g_ctx_holder::template run_with_context(_exec_ctx.get(), _mpc_ctx[0], [&](){
            test_fixedt_div_plain(0, in, out0.get());
        });

    });
    _t[1] = std::thread([this, in, out1]() mutable {
        g_ctx_holder::template run_with_context(_exec_ctx.get(), _mpc_ctx[1], [&](){
            test_fixedt_div_plain(1, in, out1.get());
        });

    });
    _t[2] = std::thread([this, in, out2]() mutable {
        g_ctx_holder::template run_with_context(_exec_ctx.get(), _mpc_ctx[2], [&](){
            test_fixedt_div_plain(2, in, out2.get());
        });

    });

    _t[0].join();
    _t[1].join();
    _t[2].join();

    EXPECT_TRUE(test_fixedt_check_tensor_eq(out0.get(), out1.get()));
    EXPECT_TRUE(test_fixedt_check_tensor_eq(out1.get(), out2.get()));
    EXPECT_TRUE(test_fixedt_check_tensor_eq(out0.get(), &result));
}

TEST_F(FixedTensorTest, sum) {

    std::vector<size_t> shape = {2, 2};
    std::vector<float> in0_val = {1.0, 1.0, 1.0, 1.0};
    //std::vector<float> in1_val = {2.0, 2.0, 2.0, 2.0};
    std::vector<float> res_val = {4.0};
    std::vector<std::shared_ptr<TensorAdapter<int64_t>>> in = {gen(shape)};

    test_fixedt_gen_paddle_tensor<int64_t, 16>(in0_val,
                                shape, _cpu_ctx).copy(in[0].get());
    //not copy scaling factor in copy funtion
    dynamic_cast<PaddleTensor<int64_t>*>(in[0].get())->
                                scaling_factor() = 16;

    std::vector<size_t> ret_shape = {1};
    auto out0 = _s_tensor_factory->create<int64_t>(ret_shape);
    auto out1 = _s_tensor_factory->create<int64_t>(ret_shape);
    auto out2 = _s_tensor_factory->create<int64_t>(ret_shape);



    PaddleTensor<int64_t> result =
            test_fixedt_gen_paddle_tensor<int64_t, 16>(res_val, ret_shape, _cpu_ctx);

    _t[0] = std::thread([this, in, out0]() mutable {
        g_ctx_holder::template run_with_context(_exec_ctx.get(), _mpc_ctx[0], [&](){
            test_fixedt_sum_fixed(0, in, out0.get());
        });

    });
    _t[1] = std::thread([this, in, out1]() mutable {
        g_ctx_holder::template run_with_context(_exec_ctx.get(), _mpc_ctx[1], [&](){
            test_fixedt_sum_fixed(1, in, out1.get());
        });

    });
    _t[2] = std::thread([this, in, out2]() mutable {
        g_ctx_holder::template run_with_context(_exec_ctx.get(), _mpc_ctx[2], [&](){
            test_fixedt_sum_fixed(2, in, out2.get());
        });

    });

    _t[0].join();
    _t[1].join();
    _t[2].join();

    EXPECT_TRUE(test_fixedt_check_tensor_eq(out0.get(), out1.get()));
    EXPECT_TRUE(test_fixedt_check_tensor_eq(out1.get(), out2.get()));
    EXPECT_TRUE(test_fixedt_check_tensor_eq(out0.get(), &result));
}

TEST_F(FixedTensorTest, mat_mulfixed) {

    std::vector<size_t> shape = {2, 2};
    std::vector<float> in0_val = {1.0, 1.0, 1.0, 1.0};
    std::vector<float> in1_val = {2.0, 2.0, 2.0, 2.0};
    std::vector<float> res_val = {4.0, 4.0, 4.0, 4.0};
    std::vector<std::shared_ptr<TensorAdapter<int64_t>>> in =
                            {gen(shape), gen(shape)};

    test_fixedt_gen_paddle_tensor<int64_t, 16>(in0_val,
                                shape, _cpu_ctx).copy(in[0].get());
    test_fixedt_gen_paddle_tensor<int64_t, 16>(in1_val,
                                shape, _cpu_ctx).copy(in[1].get());

    auto out0 = _s_tensor_factory->create<int64_t>(shape);
    auto out1 = _s_tensor_factory->create<int64_t>(shape);
    auto out2 = _s_tensor_factory->create<int64_t>(shape);

    PaddleTensor<int64_t> result =
            test_fixedt_gen_paddle_tensor<int64_t, 16>(res_val, shape, _cpu_ctx);

    _t[0] = std::thread([this, in, out0]() mutable {
        g_ctx_holder::template run_with_context(_exec_ctx.get(), _mpc_ctx[0], [&](){
            test_fixedt_mat_mul_fixed(0, in, out0.get());
        });

    });
    _t[1] = std::thread([this, in, out1]() mutable {
        g_ctx_holder::template run_with_context(_exec_ctx.get(), _mpc_ctx[1], [&](){
            test_fixedt_mat_mul_fixed(1, in, out1.get());
        });

    });
    _t[2] = std::thread([this, in, out2]() mutable {
        g_ctx_holder::template run_with_context(_exec_ctx.get(), _mpc_ctx[2], [&](){
            test_fixedt_mat_mul_fixed(2, in, out2.get());
        });

    });

    _t[0].join();
    _t[1].join();
    _t[2].join();

    EXPECT_TRUE(test_fixedt_check_tensor_eq(out0.get(), out1.get()));
    EXPECT_TRUE(test_fixedt_check_tensor_eq(out1.get(), out2.get()));
    EXPECT_TRUE(test_fixedt_check_tensor_eq(out0.get(), &result));
}

TEST_F(FixedTensorTest, mat_mulplain) {

    std::vector<size_t> shape = {2, 2};
    std::vector<float> in0_val = {1.0, 1.0, 1.0, 1.0};
    std::vector<float> in1_val = {2.0, 2.0, 2.0, 2.0};
    std::vector<float> res_val = {4.0, 4.0, 4.0, 4.0};
    std::vector<std::shared_ptr<TensorAdapter<int64_t>>> in =
                            {gen(shape), gen(shape)};

    test_fixedt_gen_paddle_tensor<int64_t, 16>(in0_val,
                                shape, _cpu_ctx).copy(in[0].get());
    test_fixedt_gen_paddle_tensor<int64_t, 16>(in1_val,
                                shape, _cpu_ctx).copy(in[1].get());
    //not copy scaling factor in copy funtion
    dynamic_cast<PaddleTensor<int64_t>*>(in[0].get())->
                                scaling_factor() = 16;
    dynamic_cast<PaddleTensor<int64_t>*>(in[1].get())->
                                scaling_factor() = 16;

    auto out0 = _s_tensor_factory->create<int64_t>(shape);
    auto out1 = _s_tensor_factory->create<int64_t>(shape);
    auto out2 = _s_tensor_factory->create<int64_t>(shape);
    PaddleTensor<int64_t> result =
            test_fixedt_gen_paddle_tensor<int64_t, 16>(res_val, shape, _cpu_ctx);

    _t[0] = std::thread([this, in, out0]() mutable {
        g_ctx_holder::template run_with_context(_exec_ctx.get(), _mpc_ctx[0], [&](){
            test_fixedt_mat_mul_plain(0, in, out0.get());
        });

    });
    _t[1] = std::thread([this, in, out1]() mutable {
        g_ctx_holder::template run_with_context(_exec_ctx.get(), _mpc_ctx[1], [&](){
            test_fixedt_mat_mul_plain(1, in, out1.get());
        });

    });
    _t[2] = std::thread([this, in, out2]() mutable {
        g_ctx_holder::template run_with_context(_exec_ctx.get(), _mpc_ctx[2], [&](){
            test_fixedt_mat_mul_plain(2, in, out2.get());
        });

    });

    _t[0].join();
    _t[1].join();
    _t[2].join();

    EXPECT_TRUE(test_fixedt_check_tensor_eq(out0.get(), out1.get()));
    EXPECT_TRUE(test_fixedt_check_tensor_eq(out1.get(), out2.get()));
    EXPECT_TRUE(test_fixedt_check_tensor_eq(out0.get(), &result));
}

TEST_F(FixedTensorTest, dot_mul_fixed) {

    std::vector<size_t> shape = {2, 2};
    std::vector<float> in0_val = {1.0, 1.0, 1.0, 1.0};
    std::vector<float> in1_val = {2.0, 2.0, 2.0, 2.0};
    std::vector<float> res_val = {8.0};
    std::vector<std::shared_ptr<TensorAdapter<int64_t>>> in =
                            {gen(shape), gen(shape)};

    test_fixedt_gen_paddle_tensor<int64_t, 16>(in0_val,
                                shape, _cpu_ctx).copy(in[0].get());
    test_fixedt_gen_paddle_tensor<int64_t, 16>(in1_val,
                                shape, _cpu_ctx).copy(in[1].get());
    //not copy scaling factor in copy funtion
    dynamic_cast<PaddleTensor<int64_t>*>(in[0].get())->
                                scaling_factor() = 16;

    std::vector<size_t> ret_shape = {1};
    auto out0 = _s_tensor_factory->create<int64_t>(ret_shape);
    auto out1 = _s_tensor_factory->create<int64_t>(ret_shape);
    auto out2 = _s_tensor_factory->create<int64_t>(ret_shape);



    PaddleTensor<int64_t> result =
            test_fixedt_gen_paddle_tensor<int64_t, 16>(res_val, ret_shape, _cpu_ctx);

    _t[0] = std::thread([this, in, out0]() mutable {
        g_ctx_holder::template run_with_context(_exec_ctx.get(), _mpc_ctx[0], [&](){
            test_fixedt_dot_mul_fixed(0, in, out0.get());
        });

    });
    _t[1] = std::thread([this, in, out1]() mutable {
        g_ctx_holder::template run_with_context(_exec_ctx.get(), _mpc_ctx[1], [&](){
            test_fixedt_dot_mul_fixed(1, in, out1.get());
        });

    });
    _t[2] = std::thread([this, in, out2]() mutable {
        g_ctx_holder::template run_with_context(_exec_ctx.get(), _mpc_ctx[2], [&](){
            test_fixedt_dot_mul_fixed(2, in, out2.get());
        });

    });

    _t[0].join();
    _t[1].join();
    _t[2].join();

    EXPECT_TRUE(test_fixedt_check_tensor_eq(out0.get(), out1.get()));
    EXPECT_TRUE(test_fixedt_check_tensor_eq(out1.get(), out2.get()));
    EXPECT_TRUE(test_fixedt_check_tensor_eq(out0.get(), &result));
}

TEST_F(FixedTensorTest, dot_mul_plain) {

    std::vector<size_t> shape = {2, 2};
    std::vector<float> in0_val = {1.0, 1.0, 1.0, 1.0};
    std::vector<float> in1_val = {2.0, 2.0, 2.0, 2.0};
    std::vector<float> res_val = {8.0};
    std::vector<std::shared_ptr<TensorAdapter<int64_t>>> in =
                            {gen(shape), gen(shape)};

    test_fixedt_gen_paddle_tensor<int64_t, 16>(in0_val,
                                shape, _cpu_ctx).copy(in[0].get());
    test_fixedt_gen_paddle_tensor<int64_t, 16>(in1_val,
                                shape, _cpu_ctx).copy(in[1].get());
    //not copy scaling factor in copy funtion
    dynamic_cast<PaddleTensor<int64_t>*>(in[0].get())->
                                scaling_factor() = 16;
    dynamic_cast<PaddleTensor<int64_t>*>(in[1].get())->
                                scaling_factor() = 16;

    std::vector<size_t> ret_shape = {1};
    auto out0 = _s_tensor_factory->create<int64_t>(ret_shape);
    auto out1 = _s_tensor_factory->create<int64_t>(ret_shape);
    auto out2 = _s_tensor_factory->create<int64_t>(ret_shape);



    PaddleTensor<int64_t> result =
            test_fixedt_gen_paddle_tensor<int64_t, 16>(res_val, ret_shape, _cpu_ctx);

    _t[0] = std::thread([this, in, out0]() mutable {
        g_ctx_holder::template run_with_context(_exec_ctx.get(), _mpc_ctx[0], [&](){
            test_fixedt_dot_mul_plain(0, in, out0.get());
        });

    });
    _t[1] = std::thread([this, in, out1]() mutable {
        g_ctx_holder::template run_with_context(_exec_ctx.get(), _mpc_ctx[1], [&](){
            test_fixedt_dot_mul_plain(1, in, out1.get());
        });

    });
    _t[2] = std::thread([this, in, out2]() mutable {
        g_ctx_holder::template run_with_context(_exec_ctx.get(), _mpc_ctx[2], [&](){
            test_fixedt_dot_mul_plain(2, in, out2.get());
        });

    });

    _t[0].join();
    _t[1].join();
    _t[2].join();

    EXPECT_TRUE(test_fixedt_check_tensor_eq(out0.get(), out1.get()));
    EXPECT_TRUE(test_fixedt_check_tensor_eq(out1.get(), out2.get()));
    EXPECT_TRUE(test_fixedt_check_tensor_eq(out0.get(), &result));
}

TEST_F(FixedTensorTest, gt_plain) {

    std::vector<size_t> shape = {2, 2};
    std::vector<float> in0_val = {3.0, 3.0, 3.0, 3.0};
    std::vector<float> in1_val = {2.0, 2.0, 2.0, 2.0};
    std::vector<float> res_val = {1 / pow(2, 16), 1 / pow(2, 16), 1 / pow(2, 16), 1 / pow(2, 16)};
    std::vector<std::shared_ptr<TensorAdapter<int64_t>>> in =
                            {gen(shape), gen(shape)};

    test_fixedt_gen_paddle_tensor<int64_t, 16>(in0_val,
                                shape, _cpu_ctx).copy(in[0].get());
    test_fixedt_gen_paddle_tensor<int64_t, 16>(in1_val,
                                shape, _cpu_ctx).copy(in[1].get());
    //not copy scaling factor in copy funtion
    dynamic_cast<PaddleTensor<int64_t>*>(in[0].get())->
                                scaling_factor() = 16;
    dynamic_cast<PaddleTensor<int64_t>*>(in[1].get())->
                                scaling_factor() = 16;

    auto out0 = _s_tensor_factory->create<int64_t>(shape);
    auto out1 = _s_tensor_factory->create<int64_t>(shape);
    auto out2 = _s_tensor_factory->create<int64_t>(shape);
    PaddleTensor<int64_t> result =
            test_fixedt_gen_paddle_tensor<int64_t, 16>(res_val, shape, _cpu_ctx);

    _t[0] = std::thread([this, in, out0]() mutable {
        g_ctx_holder::template run_with_context(_exec_ctx.get(), _mpc_ctx[0], [&](){
            test_fixedt_gt_plain(0, in, out0.get());
        });

    });
    _t[1] = std::thread([this, in, out1]() mutable {
        g_ctx_holder::template run_with_context(_exec_ctx.get(), _mpc_ctx[1], [&](){
            test_fixedt_gt_plain(1, in, out1.get());
        });

    });
    _t[2] = std::thread([this, in, out2]() mutable {
        g_ctx_holder::template run_with_context(_exec_ctx.get(), _mpc_ctx[2], [&](){
            test_fixedt_gt_plain(2, in, out2.get());
        });

    });

    _t[0].join();
    _t[1].join();
    _t[2].join();

    EXPECT_TRUE(test_fixedt_check_tensor_eq(out0.get(), out1.get()));
    EXPECT_TRUE(test_fixedt_check_tensor_eq(out1.get(), out2.get()));
    EXPECT_TRUE(test_fixedt_check_tensor_eq(out0.get(), &result));
}

TEST_F(FixedTensorTest, gt_fixed) {

    std::vector<size_t> shape = {2, 2};
    std::vector<float> in0_val = {3.0, 3.0, 3.0, 3.0};
    std::vector<float> in1_val = {2.0, 2.0, 2.0, 2.0};
    std::vector<float> res_val = {1 / pow(2, 16), 1 / pow(2, 16), 1 / pow(2, 16), 1 / pow(2, 16)};
    std::vector<std::shared_ptr<TensorAdapter<int64_t>>> in =
                            {gen(shape), gen(shape)};

    test_fixedt_gen_paddle_tensor<int64_t, 16>(in0_val,
                                shape, _cpu_ctx).copy(in[0].get());
    test_fixedt_gen_paddle_tensor<int64_t, 16>(in1_val,
                                shape, _cpu_ctx).copy(in[1].get());
    //not copy scaling factor in copy funtion
    dynamic_cast<PaddleTensor<int64_t>*>(in[0].get())->
                                scaling_factor() = 16;
    dynamic_cast<PaddleTensor<int64_t>*>(in[1].get())->
                                scaling_factor() = 16;

    auto out0 = _s_tensor_factory->create<int64_t>(shape);
    auto out1 = _s_tensor_factory->create<int64_t>(shape);
    auto out2 = _s_tensor_factory->create<int64_t>(shape);
    PaddleTensor<int64_t> result =
            test_fixedt_gen_paddle_tensor<int64_t, 16>(res_val, shape, _cpu_ctx);

    _t[0] = std::thread([this, in, out0]() mutable {
        g_ctx_holder::template run_with_context(_exec_ctx.get(), _mpc_ctx[0], [&](){
            test_fixedt_gt_fixed(0, in, out0.get());
        });

    });
    _t[1] = std::thread([this, in, out1]() mutable {
        g_ctx_holder::template run_with_context(_exec_ctx.get(), _mpc_ctx[1], [&](){
            test_fixedt_gt_fixed(1, in, out1.get());
        });

    });
    _t[2] = std::thread([this, in, out2]() mutable {
        g_ctx_holder::template run_with_context(_exec_ctx.get(), _mpc_ctx[2], [&](){
            test_fixedt_gt_fixed(2, in, out2.get());
        });

    });

    _t[0].join();
    _t[1].join();
    _t[2].join();

    EXPECT_TRUE(test_fixedt_check_tensor_eq(out0.get(), out1.get()));
    EXPECT_TRUE(test_fixedt_check_tensor_eq(out1.get(), out2.get()));
    EXPECT_TRUE(test_fixedt_check_tensor_eq(out0.get(), &result));
}

TEST_F(FixedTensorTest, lt_plain) {

    std::vector<size_t> shape = {2, 2};
    std::vector<float> in0_val = {2.0, 2.0, 3.0, 3.0};
    std::vector<float> in1_val = {3.0, 3.0, 2.0, 2.0};
    std::vector<float> res_val = {1 / pow(2, 16), 1 / pow(2, 16), 0, 0};
    std::vector<std::shared_ptr<TensorAdapter<int64_t>>> in =
                            {gen(shape), gen(shape)};

    test_fixedt_gen_paddle_tensor<int64_t, 16>(in0_val,
                                shape, _cpu_ctx).copy(in[0].get());
    test_fixedt_gen_paddle_tensor<int64_t, 16>(in1_val,
                                shape, _cpu_ctx).copy(in[1].get());
    //not copy scaling factor in copy funtion
    dynamic_cast<PaddleTensor<int64_t>*>(in[0].get())->
                                scaling_factor() = 16;
    dynamic_cast<PaddleTensor<int64_t>*>(in[1].get())->
                                scaling_factor() = 16;

    auto out0 = _s_tensor_factory->create<int64_t>(shape);
    auto out1 = _s_tensor_factory->create<int64_t>(shape);
    auto out2 = _s_tensor_factory->create<int64_t>(shape);
    PaddleTensor<int64_t> result =
            test_fixedt_gen_paddle_tensor<int64_t, 16>(res_val, shape, _cpu_ctx);

    _t[0] = std::thread([this, in, out0]() mutable {
        g_ctx_holder::template run_with_context(_exec_ctx.get(), _mpc_ctx[0], [&](){
            test_fixedt_lt_plain(0, in, out0.get());
        });

    });
    _t[1] = std::thread([this, in, out1]() mutable {
        g_ctx_holder::template run_with_context(_exec_ctx.get(), _mpc_ctx[1], [&](){
            test_fixedt_lt_plain(1, in, out1.get());
        });

    });
    _t[2] = std::thread([this, in, out2]() mutable {
        g_ctx_holder::template run_with_context(_exec_ctx.get(), _mpc_ctx[2], [&](){
            test_fixedt_lt_plain(2, in, out2.get());
        });

    });

    _t[0].join();
    _t[1].join();
    _t[2].join();

    EXPECT_TRUE(test_fixedt_check_tensor_eq(out0.get(), out1.get()));
    EXPECT_TRUE(test_fixedt_check_tensor_eq(out1.get(), out2.get()));
    EXPECT_TRUE(test_fixedt_check_tensor_eq(out0.get(), &result));
}

TEST_F(FixedTensorTest, lt_fixed) {

    std::vector<size_t> shape = {2, 2};
    std::vector<float> in0_val = {2.0, 2.0, 3.0, 3.0};
    std::vector<float> in1_val = {3.0, 3.0, 2.0, 2.0};
    std::vector<float> res_val = {1 / pow(2, 16), 1 / pow(2, 16), 0, 0};
    std::vector<std::shared_ptr<TensorAdapter<int64_t>>> in =
                            {gen(shape), gen(shape)};

    test_fixedt_gen_paddle_tensor<int64_t, 16>(in0_val,
                                shape, _cpu_ctx).copy(in[0].get());
    test_fixedt_gen_paddle_tensor<int64_t, 16>(in1_val,
                                shape, _cpu_ctx).copy(in[1].get());
    //not copy scaling factor in copy funtion
    dynamic_cast<PaddleTensor<int64_t>*>(in[0].get())->
                                scaling_factor() = 16;
    dynamic_cast<PaddleTensor<int64_t>*>(in[1].get())->
                                scaling_factor() = 16;

    auto out0 = _s_tensor_factory->create<int64_t>(shape);
    auto out1 = _s_tensor_factory->create<int64_t>(shape);
    auto out2 = _s_tensor_factory->create<int64_t>(shape);
    PaddleTensor<int64_t> result =
            test_fixedt_gen_paddle_tensor<int64_t, 16>(res_val, shape, _cpu_ctx);

    _t[0] = std::thread([this, in, out0]() mutable {
        g_ctx_holder::template run_with_context(_exec_ctx.get(), _mpc_ctx[0], [&](){
            test_fixedt_lt_fixed(0, in, out0.get());
        });

    });
    _t[1] = std::thread([this, in, out1]() mutable {
        g_ctx_holder::template run_with_context(_exec_ctx.get(), _mpc_ctx[1], [&](){
            test_fixedt_lt_fixed(1, in, out1.get());
        });

    });
    _t[2] = std::thread([this, in, out2]() mutable {
        g_ctx_holder::template run_with_context(_exec_ctx.get(), _mpc_ctx[2], [&](){
            test_fixedt_lt_fixed(2, in, out2.get());
        });

    });

    _t[0].join();
    _t[1].join();
    _t[2].join();

    EXPECT_TRUE(test_fixedt_check_tensor_eq(out0.get(), out1.get()));
    EXPECT_TRUE(test_fixedt_check_tensor_eq(out1.get(), out2.get()));
    EXPECT_TRUE(test_fixedt_check_tensor_eq(out0.get(), &result));
}

TEST_F(FixedTensorTest, leq_plain) {

    std::vector<size_t> shape = {2, 2};
    std::vector<float> in0_val = {2.0, 3.0, 3.0, 3.0};
    std::vector<float> in1_val = {3.0, 3.0, 2.0, 2.0};
    std::vector<float> res_val = {1 / pow(2, 16), 1 / pow(2, 16), 0, 0};
    std::vector<std::shared_ptr<TensorAdapter<int64_t>>> in =
                            {gen(shape), gen(shape)};

    test_fixedt_gen_paddle_tensor<int64_t, 16>(in0_val,
                                shape, _cpu_ctx).copy(in[0].get());
    test_fixedt_gen_paddle_tensor<int64_t, 16>(in1_val,
                                shape, _cpu_ctx).copy(in[1].get());
    //not copy scaling factor in copy funtion
    dynamic_cast<PaddleTensor<int64_t>*>(in[0].get())->
                                scaling_factor() = 16;
    dynamic_cast<PaddleTensor<int64_t>*>(in[1].get())->
                                scaling_factor() = 16;

    auto out0 = _s_tensor_factory->create<int64_t>(shape);
    auto out1 = _s_tensor_factory->create<int64_t>(shape);
    auto out2 = _s_tensor_factory->create<int64_t>(shape);
    PaddleTensor<int64_t> result =
            test_fixedt_gen_paddle_tensor<int64_t, 16>(res_val, shape, _cpu_ctx);

    _t[0] = std::thread([this, in, out0]() mutable {
        g_ctx_holder::template run_with_context(_exec_ctx.get(), _mpc_ctx[0], [&](){
            test_fixedt_leq_plain(0, in, out0.get());
        });

    });
    _t[1] = std::thread([this, in, out1]() mutable {
        g_ctx_holder::template run_with_context(_exec_ctx.get(), _mpc_ctx[1], [&](){
            test_fixedt_leq_plain(1, in, out1.get());
        });

    });
    _t[2] = std::thread([this, in, out2]() mutable {
        g_ctx_holder::template run_with_context(_exec_ctx.get(), _mpc_ctx[2], [&](){
            test_fixedt_leq_plain(2, in, out2.get());
        });

    });

    _t[0].join();
    _t[1].join();
    _t[2].join();

    EXPECT_TRUE(test_fixedt_check_tensor_eq(out0.get(), out1.get()));
    EXPECT_TRUE(test_fixedt_check_tensor_eq(out1.get(), out2.get()));
    EXPECT_TRUE(test_fixedt_check_tensor_eq(out0.get(), &result));
}

TEST_F(FixedTensorTest, leq_fixed) {

    std::vector<size_t> shape = {2, 2};
    std::vector<float> in0_val = {2.0, 3.0, 3.0, 3.0};
    std::vector<float> in1_val = {3.0, 3.0, 2.0, 2.0};
    std::vector<float> res_val = {1 / pow(2, 16), 1 / pow(2, 16), 0, 0};
    std::vector<std::shared_ptr<TensorAdapter<int64_t>>> in =
                            {gen(shape), gen(shape)};

    test_fixedt_gen_paddle_tensor<int64_t, 16>(in0_val,
                                shape, _cpu_ctx).copy(in[0].get());
    test_fixedt_gen_paddle_tensor<int64_t, 16>(in1_val,
                                shape, _cpu_ctx).copy(in[1].get());
    //not copy scaling factor in copy funtion
    dynamic_cast<PaddleTensor<int64_t>*>(in[0].get())->
                                scaling_factor() = 16;
    dynamic_cast<PaddleTensor<int64_t>*>(in[1].get())->
                                scaling_factor() = 16;

    auto out0 = _s_tensor_factory->create<int64_t>(shape);
    auto out1 = _s_tensor_factory->create<int64_t>(shape);
    auto out2 = _s_tensor_factory->create<int64_t>(shape);
    PaddleTensor<int64_t> result =
            test_fixedt_gen_paddle_tensor<int64_t, 16>(res_val, shape, _cpu_ctx);

    _t[0] = std::thread([this, in, out0]() mutable {
        g_ctx_holder::template run_with_context(_exec_ctx.get(), _mpc_ctx[0], [&](){
            test_fixedt_leq_fixed(0, in, out0.get());
        });

    });
    _t[1] = std::thread([this, in, out1]() mutable {
        g_ctx_holder::template run_with_context(_exec_ctx.get(), _mpc_ctx[1], [&](){
            test_fixedt_leq_fixed(1, in, out1.get());
        });

    });
    _t[2] = std::thread([this, in, out2]() mutable {
        g_ctx_holder::template run_with_context(_exec_ctx.get(), _mpc_ctx[2], [&](){
            test_fixedt_leq_fixed(2, in, out2.get());
        });

    });

    _t[0].join();
    _t[1].join();
    _t[2].join();

    EXPECT_TRUE(test_fixedt_check_tensor_eq(out0.get(), out1.get()));
    EXPECT_TRUE(test_fixedt_check_tensor_eq(out1.get(), out2.get()));
    EXPECT_TRUE(test_fixedt_check_tensor_eq(out0.get(), &result));
}

TEST_F(FixedTensorTest, geq_plain) {

    std::vector<size_t> shape = {2, 2};
    std::vector<float> in0_val = {3.0, 3.0, 2.0, 2.0};
    std::vector<float> in1_val = {2.0, 3.0, 3.0, 3.0};
    std::vector<float> res_val = {1 / pow(2, 16), 1 / pow(2, 16), 0, 0};
    std::vector<std::shared_ptr<TensorAdapter<int64_t>>> in =
                            {gen(shape), gen(shape)};

    test_fixedt_gen_paddle_tensor<int64_t, 16>(in0_val,
                                shape, _cpu_ctx).copy(in[0].get());
    test_fixedt_gen_paddle_tensor<int64_t, 16>(in1_val,
                                shape, _cpu_ctx).copy(in[1].get());
    //not copy scaling factor in copy funtion
    dynamic_cast<PaddleTensor<int64_t>*>(in[0].get())->
                                scaling_factor() = 16;
    dynamic_cast<PaddleTensor<int64_t>*>(in[1].get())->
                                scaling_factor() = 16;

    auto out0 = _s_tensor_factory->create<int64_t>(shape);
    auto out1 = _s_tensor_factory->create<int64_t>(shape);
    auto out2 = _s_tensor_factory->create<int64_t>(shape);
    PaddleTensor<int64_t> result =
            test_fixedt_gen_paddle_tensor<int64_t, 16>(res_val, shape, _cpu_ctx);

    _t[0] = std::thread([this, in, out0]() mutable {
        g_ctx_holder::template run_with_context(_exec_ctx.get(), _mpc_ctx[0], [&](){
            test_fixedt_geq_plain(0, in, out0.get());
        });

    });
    _t[1] = std::thread([this, in, out1]() mutable {
        g_ctx_holder::template run_with_context(_exec_ctx.get(), _mpc_ctx[1], [&](){
            test_fixedt_geq_plain(1, in, out1.get());
        });

    });
    _t[2] = std::thread([this, in, out2]() mutable {
        g_ctx_holder::template run_with_context(_exec_ctx.get(), _mpc_ctx[2], [&](){
            test_fixedt_geq_plain(2, in, out2.get());
        });

    });

    _t[0].join();
    _t[1].join();
    _t[2].join();

    EXPECT_TRUE(test_fixedt_check_tensor_eq(out0.get(), out1.get()));
    EXPECT_TRUE(test_fixedt_check_tensor_eq(out1.get(), out2.get()));
    EXPECT_TRUE(test_fixedt_check_tensor_eq(out0.get(), &result));
}

TEST_F(FixedTensorTest, geq_fixed) {

    std::vector<size_t> shape = {2, 2};
    std::vector<float> in0_val = {3.0, 3.0, 2.0, 2.0};
    std::vector<float> in1_val = {2.0, 3.0, 3.0, 3.0};
    std::vector<float> res_val = {1 / pow(2, 16), 1 / pow(2, 16), 0, 0};
    std::vector<std::shared_ptr<TensorAdapter<int64_t>>> in =
                            {gen(shape), gen(shape)};

    test_fixedt_gen_paddle_tensor<int64_t, 16>(in0_val,
                                shape, _cpu_ctx).copy(in[0].get());
    test_fixedt_gen_paddle_tensor<int64_t, 16>(in1_val,
                                shape, _cpu_ctx).copy(in[1].get());
    //not copy scaling factor in copy funtion
    dynamic_cast<PaddleTensor<int64_t>*>(in[0].get())->
                                scaling_factor() = 16;
    dynamic_cast<PaddleTensor<int64_t>*>(in[1].get())->
                                scaling_factor() = 16;

    auto out0 = _s_tensor_factory->create<int64_t>(shape);
    auto out1 = _s_tensor_factory->create<int64_t>(shape);
    auto out2 = _s_tensor_factory->create<int64_t>(shape);
    PaddleTensor<int64_t> result =
            test_fixedt_gen_paddle_tensor<int64_t, 16>(res_val, shape, _cpu_ctx);

    _t[0] = std::thread([this, in, out0]() mutable {
        g_ctx_holder::template run_with_context(_exec_ctx.get(), _mpc_ctx[0], [&](){
            test_fixedt_geq_fixed(0, in, out0.get());
        });

    });
    _t[1] = std::thread([this, in, out1]() mutable {
        g_ctx_holder::template run_with_context(_exec_ctx.get(), _mpc_ctx[1], [&](){
            test_fixedt_geq_fixed(1, in, out1.get());
        });

    });
    _t[2] = std::thread([this, in, out2]() mutable {
        g_ctx_holder::template run_with_context(_exec_ctx.get(), _mpc_ctx[2], [&](){
            test_fixedt_geq_fixed(2, in, out2.get());
        });

    });

    _t[0].join();
    _t[1].join();
    _t[2].join();

    EXPECT_TRUE(test_fixedt_check_tensor_eq(out0.get(), out1.get()));
    EXPECT_TRUE(test_fixedt_check_tensor_eq(out1.get(), out2.get()));
    EXPECT_TRUE(test_fixedt_check_tensor_eq(out0.get(), &result));
}

TEST_F(FixedTensorTest, eq_plain) {

    std::vector<size_t> shape = {2, 2};
    std::vector<float> in0_val = {3.0, 3.0, 2.0, 3.0};
    std::vector<float> in1_val = {3.0, 3.0, 3.0, 2.0};
    std::vector<float> res_val = {1 / pow(2, 16), 1 / pow(2, 16), 0, 0};
    std::vector<std::shared_ptr<TensorAdapter<int64_t>>> in =
                            {gen(shape), gen(shape)};

    test_fixedt_gen_paddle_tensor<int64_t, 16>(in0_val,
                                shape, _cpu_ctx).copy(in[0].get());
    test_fixedt_gen_paddle_tensor<int64_t, 16>(in1_val,
                                shape, _cpu_ctx).copy(in[1].get());
    //not copy scaling factor in copy funtion
    dynamic_cast<PaddleTensor<int64_t>*>(in[0].get())->
                                scaling_factor() = 16;
    dynamic_cast<PaddleTensor<int64_t>*>(in[1].get())->
                                scaling_factor() = 16;

    auto out0 = _s_tensor_factory->create<int64_t>(shape);
    auto out1 = _s_tensor_factory->create<int64_t>(shape);
    auto out2 = _s_tensor_factory->create<int64_t>(shape);
    PaddleTensor<int64_t> result =
            test_fixedt_gen_paddle_tensor<int64_t, 16>(res_val, shape, _cpu_ctx);

    _t[0] = std::thread([this, in, out0]() mutable {
        g_ctx_holder::template run_with_context(_exec_ctx.get(), _mpc_ctx[0], [&](){
            test_fixedt_eq_plain(0, in, out0.get());
        });

    });
    _t[1] = std::thread([this, in, out1]() mutable {
        g_ctx_holder::template run_with_context(_exec_ctx.get(), _mpc_ctx[1], [&](){
            test_fixedt_eq_plain(1, in, out1.get());
        });

    });
    _t[2] = std::thread([this, in, out2]() mutable {
        g_ctx_holder::template run_with_context(_exec_ctx.get(), _mpc_ctx[2], [&](){
            test_fixedt_eq_plain(2, in, out2.get());
        });

    });

    _t[0].join();
    _t[1].join();
    _t[2].join();

    EXPECT_TRUE(test_fixedt_check_tensor_eq(out0.get(), out1.get()));
    EXPECT_TRUE(test_fixedt_check_tensor_eq(out1.get(), out2.get()));
    EXPECT_TRUE(test_fixedt_check_tensor_eq(out0.get(), &result));
}

TEST_F(FixedTensorTest, eq_fixed) {

    std::vector<size_t> shape = {2, 2};
    std::vector<float> in0_val = {3.0, 3.0, 2.0, 3.0};
    std::vector<float> in1_val = {3.0, 3.0, 3.0, 2.0};
    std::vector<float> res_val = {1 / pow(2, 16), 1 / pow(2, 16), 0, 0};
    std::vector<std::shared_ptr<TensorAdapter<int64_t>>> in =
                            {gen(shape), gen(shape)};

    test_fixedt_gen_paddle_tensor<int64_t, 16>(in0_val,
                                shape, _cpu_ctx).copy(in[0].get());
    test_fixedt_gen_paddle_tensor<int64_t, 16>(in1_val,
                                shape, _cpu_ctx).copy(in[1].get());
    //not copy scaling factor in copy funtion
    dynamic_cast<PaddleTensor<int64_t>*>(in[0].get())->
                                scaling_factor() = 16;
    dynamic_cast<PaddleTensor<int64_t>*>(in[1].get())->
                                scaling_factor() = 16;

    auto out0 = _s_tensor_factory->create<int64_t>(shape);
    auto out1 = _s_tensor_factory->create<int64_t>(shape);
    auto out2 = _s_tensor_factory->create<int64_t>(shape);
    PaddleTensor<int64_t> result =
            test_fixedt_gen_paddle_tensor<int64_t, 16>(res_val, shape, _cpu_ctx);

    _t[0] = std::thread([this, in, out0]() mutable {
        g_ctx_holder::template run_with_context(_exec_ctx.get(), _mpc_ctx[0], [&](){
            test_fixedt_eq_fixed(0, in, out0.get());
        });

    });
    _t[1] = std::thread([this, in, out1]() mutable {
        g_ctx_holder::template run_with_context(_exec_ctx.get(), _mpc_ctx[1], [&](){
            test_fixedt_eq_fixed(1, in, out1.get());
        });

    });
    _t[2] = std::thread([this, in, out2]() mutable {
        g_ctx_holder::template run_with_context(_exec_ctx.get(), _mpc_ctx[2], [&](){
            test_fixedt_eq_fixed(2, in, out2.get());
        });

    });

    _t[0].join();
    _t[1].join();
    _t[2].join();

    EXPECT_TRUE(test_fixedt_check_tensor_eq(out0.get(), out1.get()));
    EXPECT_TRUE(test_fixedt_check_tensor_eq(out1.get(), out2.get()));
    EXPECT_TRUE(test_fixedt_check_tensor_eq(out0.get(), &result));
}

TEST_F(FixedTensorTest, neq_plain) {

    std::vector<size_t> shape = {2, 2};
    std::vector<float> in0_val = {2.0, 3.0, 3.0, 3.0};
    std::vector<float> in1_val = {3.0, 2.0, 3.0, 3.0};
    std::vector<float> res_val = {1 / pow(2, 16), 1 / pow(2, 16), 0, 0};
    std::vector<std::shared_ptr<TensorAdapter<int64_t>>> in =
                            {gen(shape), gen(shape)};

    test_fixedt_gen_paddle_tensor<int64_t, 16>(in0_val,
                                shape, _cpu_ctx).copy(in[0].get());
    test_fixedt_gen_paddle_tensor<int64_t, 16>(in1_val,
                                shape, _cpu_ctx).copy(in[1].get());
    //not copy scaling factor in copy funtion
    dynamic_cast<PaddleTensor<int64_t>*>(in[0].get())->
                                scaling_factor() = 16;
    dynamic_cast<PaddleTensor<int64_t>*>(in[1].get())->
                                scaling_factor() = 16;

    auto out0 = _s_tensor_factory->create<int64_t>(shape);
    auto out1 = _s_tensor_factory->create<int64_t>(shape);
    auto out2 = _s_tensor_factory->create<int64_t>(shape);
    PaddleTensor<int64_t> result =
            test_fixedt_gen_paddle_tensor<int64_t, 16>(res_val, shape, _cpu_ctx);

    _t[0] = std::thread([this, in, out0]() mutable {
        g_ctx_holder::template run_with_context(_exec_ctx.get(), _mpc_ctx[0], [&](){
            test_fixedt_neq_plain(0, in, out0.get());
        });

    });
    _t[1] = std::thread([this, in, out1]() mutable {
        g_ctx_holder::template run_with_context(_exec_ctx.get(), _mpc_ctx[1], [&](){
            test_fixedt_neq_plain(1, in, out1.get());
        });

    });
    _t[2] = std::thread([this, in, out2]() mutable {
        g_ctx_holder::template run_with_context(_exec_ctx.get(), _mpc_ctx[2], [&](){
            test_fixedt_neq_plain(2, in, out2.get());
        });

    });

    _t[0].join();
    _t[1].join();
    _t[2].join();

    EXPECT_TRUE(test_fixedt_check_tensor_eq(out0.get(), out1.get()));
    EXPECT_TRUE(test_fixedt_check_tensor_eq(out1.get(), out2.get()));
    EXPECT_TRUE(test_fixedt_check_tensor_eq(out0.get(), &result));
}

TEST_F(FixedTensorTest, neq_fixed) {

    std::vector<size_t> shape = {2, 2};
    std::vector<float> in0_val = {3.0, 2.0, 3.0, 3.0};
    std::vector<float> in1_val = {2.0, 3.0, 3.0, 3.0};
    std::vector<float> res_val = {1 / pow(2, 16), 1 / pow(2, 16), 0, 0};
    std::vector<std::shared_ptr<TensorAdapter<int64_t>>> in =
                            {gen(shape), gen(shape)};

    test_fixedt_gen_paddle_tensor<int64_t, 16>(in0_val,
                                shape, _cpu_ctx).copy(in[0].get());
    test_fixedt_gen_paddle_tensor<int64_t, 16>(in1_val,
                                shape, _cpu_ctx).copy(in[1].get());
    //not copy scaling factor in copy funtion
    dynamic_cast<PaddleTensor<int64_t>*>(in[0].get())->
                                scaling_factor() = 16;
    dynamic_cast<PaddleTensor<int64_t>*>(in[1].get())->
                                scaling_factor() = 16;

    auto out0 = _s_tensor_factory->create<int64_t>(shape);
    auto out1 = _s_tensor_factory->create<int64_t>(shape);
    auto out2 = _s_tensor_factory->create<int64_t>(shape);
    PaddleTensor<int64_t> result =
            test_fixedt_gen_paddle_tensor<int64_t, 16>(res_val, shape, _cpu_ctx);

    _t[0] = std::thread([this, in, out0]() mutable {
        g_ctx_holder::template run_with_context(_exec_ctx.get(), _mpc_ctx[0], [&](){
            test_fixedt_neq_fixed(0, in, out0.get());
        });

    });
    _t[1] = std::thread([this, in, out1]() mutable {
        g_ctx_holder::template run_with_context(_exec_ctx.get(), _mpc_ctx[1], [&](){
            test_fixedt_neq_fixed(1, in, out1.get());
        });

    });
    _t[2] = std::thread([this, in, out2]() mutable {
        g_ctx_holder::template run_with_context(_exec_ctx.get(), _mpc_ctx[2], [&](){
            test_fixedt_neq_fixed(2, in, out2.get());
        });

    });

    _t[0].join();
    _t[1].join();
    _t[2].join();

    EXPECT_TRUE(test_fixedt_check_tensor_eq(out0.get(), out1.get()));
    EXPECT_TRUE(test_fixedt_check_tensor_eq(out1.get(), out2.get()));
    EXPECT_TRUE(test_fixedt_check_tensor_eq(out0.get(), &result));
}

TEST_F(FixedTensorTest, exp_fixed) {

    std::vector<size_t> shape = {2, 2};
    std::vector<float> in0_val = {0.0, 0.0, 1.0, 1.0};
    //std::vector<float> in1_val = {2.0, 2.0, 2.0, 2.0};
    std::vector<float> res_val = {1.0, 1.0, 2.7183, 2.7183};
    std::vector<std::shared_ptr<TensorAdapter<int64_t>>> in = {gen(shape)};

    test_fixedt_gen_paddle_tensor<int64_t, 16>(in0_val,
                                shape, _cpu_ctx).copy(in[0].get());
    //not copy scaling factor in copy funtion
    dynamic_cast<PaddleTensor<int64_t>*>(in[0].get())->
                                scaling_factor() = 16;

    auto out0 = _s_tensor_factory->create<int64_t>(shape);
    auto out1 = _s_tensor_factory->create<int64_t>(shape);
    auto out2 = _s_tensor_factory->create<int64_t>(shape);

    PaddleTensor<int64_t> result =
            test_fixedt_gen_paddle_tensor<int64_t, 16>(res_val, shape, _cpu_ctx);

    _t[0] = std::thread([this, in, out0]() mutable {
        g_ctx_holder::template run_with_context(_exec_ctx.get(), _mpc_ctx[0], [&](){
            test_fixedt_exp_fixed(0, in, out0.get());
        });

    });
    _t[1] = std::thread([this, in, out1]() mutable {
        g_ctx_holder::template run_with_context(_exec_ctx.get(), _mpc_ctx[1], [&](){
            test_fixedt_exp_fixed(1, in, out1.get());
        });

    });
    _t[2] = std::thread([this, in, out2]() mutable {
        g_ctx_holder::template run_with_context(_exec_ctx.get(), _mpc_ctx[2], [&](){
            test_fixedt_exp_fixed(2, in, out2.get());
        });

    });

    _t[0].join();
    _t[1].join();
    _t[2].join();

    EXPECT_TRUE(test_fixedt_check_tensor_eq(out0.get(), out1.get(), 0.1));
    EXPECT_TRUE(test_fixedt_check_tensor_eq(out1.get(), out2.get(), 0.1));
    EXPECT_TRUE(test_fixedt_check_tensor_eq(out0.get(), &result, 0.1));
}

TEST_F(FixedTensorTest, polynomial) {
    // y = 1 + x
    std::vector<size_t> shape = {2, 2};
    std::vector<float> in0_val = {-1.0, 2.0, 2.0, 2.0};
    //std::vector<float> in1_val = {2.0, 2.0, 2.0, 2.0};
    std::vector<float> res_val = {0.0, 3.0, 3.0, 3.0};
    std::vector<std::shared_ptr<TensorAdapter<int64_t>>> in = {gen(shape)};

    test_fixedt_gen_paddle_tensor<int64_t, 16>(in0_val,
                                shape, _cpu_ctx).copy(in[0].get());
    //not copy scaling factor in copy funtion
    dynamic_cast<PaddleTensor<int64_t>*>(in[0].get())->
                                scaling_factor() = 16;

    auto out0 = _s_tensor_factory->create<int64_t>(shape);
    auto out1 = _s_tensor_factory->create<int64_t>(shape);
    auto out2 = _s_tensor_factory->create<int64_t>(shape);

    PaddleTensor<int64_t> result =
            test_fixedt_gen_paddle_tensor<int64_t, 16>(res_val, shape, _cpu_ctx);

    _t[0] = std::thread([this, in, out0]() mutable {
        g_ctx_holder::template run_with_context(_exec_ctx.get(), _mpc_ctx[0], [&](){
            test_fixedt_poly_fixed(0, in, out0.get());
        });

    });
    _t[1] = std::thread([this, in, out1]() mutable {
        g_ctx_holder::template run_with_context(_exec_ctx.get(), _mpc_ctx[1], [&](){
            test_fixedt_poly_fixed(1, in, out1.get());
        });

    });
    _t[2] = std::thread([this, in, out2]() mutable {
        g_ctx_holder::template run_with_context(_exec_ctx.get(), _mpc_ctx[2], [&](){
            test_fixedt_poly_fixed(2, in, out2.get());
        });

    });

    _t[0].join();
    _t[1].join();
    _t[2].join();

    EXPECT_TRUE(test_fixedt_check_tensor_eq(out0.get(), out1.get()));
    EXPECT_TRUE(test_fixedt_check_tensor_eq(out1.get(), out2.get()));
    EXPECT_TRUE(test_fixedt_check_tensor_eq(out0.get(), &result));
}

TEST_F(FixedTensorTest, polynomial_wise) {
    // y = x + 1 (x >= 0)
    // y = 1 (x < 0)
    std::vector<size_t> shape = {2, 2};
    std::vector<float> in0_val = {-1.0, 1.0, 2.0, 2.0};
    //std::vector<float> in1_val = {2.0, 2.0, 2.0, 2.0};
    std::vector<float> res_val = {1.0, 2.0, 3.0, 3.0};
    std::vector<std::shared_ptr<TensorAdapter<int64_t>>> in = {gen(shape)};

    test_fixedt_gen_paddle_tensor<int64_t, 16>(in0_val,
                                shape, _cpu_ctx).copy(in[0].get());
    //not copy scaling factor in copy funtion
    dynamic_cast<PaddleTensor<int64_t>*>(in[0].get())->
                                scaling_factor() = 16;

    auto out0 = _s_tensor_factory->create<int64_t>(shape);
    auto out1 = _s_tensor_factory->create<int64_t>(shape);
    auto out2 = _s_tensor_factory->create<int64_t>(shape);

    PaddleTensor<int64_t> result =
            test_fixedt_gen_paddle_tensor<int64_t, 16>(res_val, shape, _cpu_ctx);

    _t[0] = std::thread([this, in, out0]() mutable {
        g_ctx_holder::template run_with_context(_exec_ctx.get(), _mpc_ctx[0], [&](){
            test_fixedt_poly_wise_fixed(0, in, out0.get());
        });

    });
    _t[1] = std::thread([this, in, out1]() mutable {
        g_ctx_holder::template run_with_context(_exec_ctx.get(), _mpc_ctx[1], [&](){
            test_fixedt_poly_wise_fixed(1, in, out1.get());
        });

    });
    _t[2] = std::thread([this, in, out2]() mutable {
        g_ctx_holder::template run_with_context(_exec_ctx.get(), _mpc_ctx[2], [&](){
            test_fixedt_poly_wise_fixed(2, in, out2.get());
        });

    });

    _t[0].join();
    _t[1].join();
    _t[2].join();

    EXPECT_TRUE(test_fixedt_check_tensor_eq(out0.get(), out1.get()));
    EXPECT_TRUE(test_fixedt_check_tensor_eq(out1.get(), out2.get()));
    EXPECT_TRUE(test_fixedt_check_tensor_eq(out0.get(), &result));
}

TEST_F(FixedTensorTest, relu) {

    std::vector<size_t> shape = {2, 2};
    std::vector<float> in0_val = {1.0, -1.0, -2, 2};
    //std::vector<float> in1_val = {2.0, 2.0, 2.0, 2.0};
    std::vector<float> res_val = {1.0, 0.0, 0.0, 2};
    std::vector<std::shared_ptr<TensorAdapter<int64_t>>> in = {gen(shape)};

    test_fixedt_gen_paddle_tensor<int64_t, 16>(in0_val,
                                shape, _cpu_ctx).copy(in[0].get());
    //not copy scaling factor in copy funtion
    dynamic_cast<PaddleTensor<int64_t>*>(in[0].get())->
                                scaling_factor() = 16;

    auto out0 = _s_tensor_factory->create<int64_t>(shape);
    auto out1 = _s_tensor_factory->create<int64_t>(shape);
    auto out2 = _s_tensor_factory->create<int64_t>(shape);

    PaddleTensor<int64_t> result =
            test_fixedt_gen_paddle_tensor<int64_t, 16>(res_val, shape, _cpu_ctx);

    _t[0] = std::thread([this, in, out0]() mutable {
        g_ctx_holder::template run_with_context(_exec_ctx.get(), _mpc_ctx[0], [&](){
            test_fixedt_relu_fixed(0, in, out0.get());
        });

    });
    _t[1] = std::thread([this, in, out1]() mutable {
        g_ctx_holder::template run_with_context(_exec_ctx.get(), _mpc_ctx[1], [&](){
            test_fixedt_relu_fixed(1, in, out1.get());
        });

    });
    _t[2] = std::thread([this, in, out2]() mutable {
        g_ctx_holder::template run_with_context(_exec_ctx.get(), _mpc_ctx[2], [&](){
            test_fixedt_relu_fixed(2, in, out2.get());
        });

    });

    _t[0].join();
    _t[1].join();
    _t[2].join();

    EXPECT_TRUE(test_fixedt_check_tensor_eq(out0.get(), out1.get()));
    EXPECT_TRUE(test_fixedt_check_tensor_eq(out1.get(), out2.get()));
    EXPECT_TRUE(test_fixedt_check_tensor_eq(out0.get(), &result));
}

TEST_F(FixedTensorTest, softmax) {

    std::vector<size_t> shape = {2, 2};
    std::vector<float> in0_val = {1.0, 1.0, 1, 1};
    //std::vector<float> in1_val = {2.0, 2.0, 2.0, 2.0};
    std::vector<float> res_val = {0.5, 0.5, 0.5, 0.5};
    std::vector<std::shared_ptr<TensorAdapter<int64_t>>> in = {gen(shape)};

    test_fixedt_gen_paddle_tensor<int64_t, 16>(in0_val,
                                shape, _cpu_ctx).copy(in[0].get());
    //not copy scaling factor in copy funtion
    dynamic_cast<PaddleTensor<int64_t>*>(in[0].get())->
                                scaling_factor() = 16;

    auto out0 = _s_tensor_factory->create<int64_t>(shape);
    auto out1 = _s_tensor_factory->create<int64_t>(shape);
    auto out2 = _s_tensor_factory->create<int64_t>(shape);

    PaddleTensor<int64_t> result =
            test_fixedt_gen_paddle_tensor<int64_t, 16>(res_val, shape, _cpu_ctx);

    _t[0] = std::thread([this, in, out0]() mutable {
        g_ctx_holder::template run_with_context(_exec_ctx.get(), _mpc_ctx[0], [&](){
            test_fixedt_softmax_fixed(0, in, out0.get());
        });

    });
    _t[1] = std::thread([this, in, out1]() mutable {
        g_ctx_holder::template run_with_context(_exec_ctx.get(), _mpc_ctx[1], [&](){
            test_fixedt_softmax_fixed(1, in, out1.get());
        });

    });
    _t[2] = std::thread([this, in, out2]() mutable {
        g_ctx_holder::template run_with_context(_exec_ctx.get(), _mpc_ctx[2], [&](){
            test_fixedt_softmax_fixed(2, in, out2.get());
        });

    });

    _t[0].join();
    _t[1].join();
    _t[2].join();

    EXPECT_TRUE(test_fixedt_check_tensor_eq(out0.get(), out1.get()));
    EXPECT_TRUE(test_fixedt_check_tensor_eq(out1.get(), out2.get()));
    EXPECT_TRUE(test_fixedt_check_tensor_eq(out0.get(), &result));
}

TEST_F(FixedTensorTest, sigmoid) {

    std::vector<size_t> shape = {2, 2};
    std::vector<float> in0_val = {0.0, 0.0, -0.5, 0.5};
    //std::vector<float> in1_val = {2.0, 2.0, 2.0, 2.0};
    std::vector<float> res_val = {0.5, 0.5, 0.3775, 0.6225};
    std::vector<std::shared_ptr<TensorAdapter<int64_t>>> in = {gen(shape)};

    test_fixedt_gen_paddle_tensor<int64_t, 16>(in0_val,
                                shape, _cpu_ctx).copy(in[0].get());
    //not copy scaling factor in copy funtion
    dynamic_cast<PaddleTensor<int64_t>*>(in[0].get())->
                                scaling_factor() = 16;

    auto out0 = _s_tensor_factory->create<int64_t>(shape);
    auto out1 = _s_tensor_factory->create<int64_t>(shape);
    auto out2 = _s_tensor_factory->create<int64_t>(shape);

    PaddleTensor<int64_t> result =
            test_fixedt_gen_paddle_tensor<int64_t, 16>(res_val, shape, _cpu_ctx);

    _t[0] = std::thread([this, in, out0]() mutable {
        g_ctx_holder::template run_with_context(_exec_ctx.get(), _mpc_ctx[0], [&](){
            test_fixedt_sigmoid_fixed(0, in, out0.get());
        });

    });
    _t[1] = std::thread([this, in, out1]() mutable {
        g_ctx_holder::template run_with_context(_exec_ctx.get(), _mpc_ctx[1], [&](){
            test_fixedt_sigmoid_fixed(1, in, out1.get());
        });

    });
    _t[2] = std::thread([this, in, out2]() mutable {
        g_ctx_holder::template run_with_context(_exec_ctx.get(), _mpc_ctx[2], [&](){
            test_fixedt_sigmoid_fixed(2, in, out2.get());
        });

    });

    _t[0].join();
    _t[1].join();
    _t[2].join();

    EXPECT_TRUE(test_fixedt_check_tensor_eq(out0.get(), out1.get(), 0.1));
    EXPECT_TRUE(test_fixedt_check_tensor_eq(out1.get(), out2.get(), 0.1));
    EXPECT_TRUE(test_fixedt_check_tensor_eq(out0.get(), &result, 0.1));
}

} // namespace aby3