// Copyright (C) 2018-2021 Intel Corporation
// SPDX-License-Identifier: Apache-2.0
//

#include <algorithm>
#include <cinttypes>
#include <cmath>
#include <cstdlib>
#include <random>
#include <string>

#include "engines_util/test_case.hpp"
#include "engines_util/test_engines.hpp"
#include "gtest/gtest.h"
#include "ngraph/ngraph.hpp"
#include "util/test_control.hpp"

using namespace std;
using namespace ngraph;

static string s_manifest = "${MANIFEST}";
using TestEngine = test::ENGINE_CLASS_NAME(${BACKEND_NAME});

NGRAPH_TEST(${BACKEND_NAME}, one_hot_scalar_2_in_3) {
    Shape shape_a{};
    auto A = make_shared<op::Parameter>(element::i32, shape_a);
    int axis = 0;
    Shape shape_r{3};
    auto depth = op::Constant::create(element::i32, {}, {shape_r[axis]});
    auto on_value = op::Constant::create(element::i32, {}, {1});
    auto off_value = op::Constant::create(element::i32, {}, {0});
    auto r = make_shared<op::v1::OneHot>(A, depth, on_value, off_value, axis);
    auto f = make_shared<Function>(r, ParameterVector{A});

    auto test_case = test::TestCase<TestEngine>(f);
    test_case.add_input<int32_t>({2});
    test_case.add_expected_output<int32_t>(shape_r, {0, 0, 1});
    test_case.run();
}

NGRAPH_TEST(${BACKEND_NAME}, one_hot_scalar_1_in_3) {
    Shape shape_a{};
    auto A = make_shared<op::Parameter>(element::i32, shape_a);
    int axis = 0;
    Shape shape_r{3};
    auto depth = op::Constant::create(element::i32, {}, {shape_r[axis]});
    auto on_value = op::Constant::create(element::i32, {}, {1});
    auto off_value = op::Constant::create(element::i32, {}, {0});
    auto r = make_shared<op::v1::OneHot>(A, depth, on_value, off_value, axis);
    auto f = make_shared<Function>(r, ParameterVector{A});

    auto test_case = test::TestCase<TestEngine>(f);
    test_case.add_input<int32_t>({1});
    test_case.add_expected_output<int32_t>(shape_r, {0, 1, 0});
    test_case.run();
}

NGRAPH_TEST(${BACKEND_NAME}, one_hot_scalar_0_in_3) {
    Shape shape_a{};
    auto A = make_shared<op::Parameter>(element::i32, shape_a);
    Shape shape_r{3};
    int axis = 0;
    auto depth = op::Constant::create(element::i32, {}, {shape_r[axis]});
    auto on_value = op::Constant::create(element::i32, {}, {1});
    auto off_value = op::Constant::create(element::i32, {}, {0});
    auto r = make_shared<op::v1::OneHot>(A, depth, on_value, off_value, axis);
    auto f = make_shared<Function>(r, ParameterVector{A});

    auto test_case = test::TestCase<TestEngine>(f);
    test_case.add_input<int32_t>({0});
    test_case.add_expected_output<int32_t>(shape_r, {1, 0, 0});
    test_case.run();
}

NGRAPH_TEST(${BACKEND_NAME}, one_hot_vector_0) {
    Shape shape_a{8};
    auto A = make_shared<op::Parameter>(element::i32, shape_a);
    Shape shape_r{3, 8};
    int axis = 0;
    auto depth = op::Constant::create(element::i32, {}, {shape_r[axis]});
    auto on_value = op::Constant::create(element::i32, {}, {1});
    auto off_value = op::Constant::create(element::i32, {}, {0});
    auto r = make_shared<op::v1::OneHot>(A, depth, on_value, off_value, axis);
    auto f = make_shared<Function>(r, ParameterVector{A});

    auto test_case = test::TestCase<TestEngine>(f);
    test_case.add_input<int32_t>({2, 1, 0, 0, 2, 2, 1, 0});
    test_case.add_expected_output<int32_t>(shape_r,
                                           {0, 0, 1, 1, 0, 0, 0, 1, 0, 1, 0, 0, 0, 0, 1, 0, 1, 0, 0, 0, 1, 1, 0, 0});
    test_case.run();
}

NGRAPH_TEST(${BACKEND_NAME}, one_hot_vector_1) {
    Shape shape_a{8};
    auto A = make_shared<op::Parameter>(element::i32, shape_a);
    Shape shape_r{8, 3};
    int axis = 1;
    auto depth = op::Constant::create(element::i32, {}, {shape_r[axis]});
    auto on_value = op::Constant::create(element::i32, {}, {1});
    auto off_value = op::Constant::create(element::i32, {}, {0});
    auto r = make_shared<op::v1::OneHot>(A, depth, on_value, off_value, axis);
    auto f = make_shared<Function>(r, ParameterVector{A});

    auto test_case = test::TestCase<TestEngine>(f);
    test_case.add_input<int32_t>({2, 1, 0, 0, 2, 2, 1, 0});
    test_case.add_expected_output<int32_t>(shape_r,
                                           {0, 0, 1, 0, 1, 0, 1, 0, 0, 1, 0, 0, 0, 0, 1, 0, 0, 1, 0, 1, 0, 1, 0, 0});
    test_case.run();
}

NGRAPH_TEST(${BACKEND_NAME}, one_hot_vector_1_barely_oob) {
    Shape shape_a{8};
    auto A = make_shared<op::Parameter>(element::i32, shape_a);
    Shape shape_r{8, 3};
    int axis = 1;
    auto depth = op::Constant::create(element::i32, {}, {shape_r[axis]});
    auto on_value = op::Constant::create(element::i32, {}, {1});
    auto off_value = op::Constant::create(element::i32, {}, {0});
    auto r = make_shared<op::v1::OneHot>(A, depth, on_value, off_value, axis);
    auto f = make_shared<Function>(r, ParameterVector{A});

    auto test_case = test::TestCase<TestEngine>(f);
    test_case.add_input<int32_t>({2, 1, 0, 0, 3, 2, 1, 0});
    // elements 12, 13, 14 are zeroed as out of bound
    test_case.add_expected_output<int32_t>(shape_r,
                                           {0, 0, 1, 0, 1, 0, 1, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 1, 0, 1, 0, 1, 0, 0});
    test_case.run();
}

NGRAPH_TEST(${BACKEND_NAME}, one_hot_matrix_0) {
    Shape shape_a{3, 3};
    auto A = make_shared<op::Parameter>(element::i32, shape_a);
    Shape shape_r{3, 3, 3};
    int axis = 0;
    auto depth = op::Constant::create(element::i32, {}, {shape_r[axis]});
    auto on_value = op::Constant::create(element::i32, {}, {1});
    auto off_value = op::Constant::create(element::i32, {}, {0});
    auto r = make_shared<op::v1::OneHot>(A, depth, on_value, off_value, axis);
    auto f = make_shared<Function>(r, ParameterVector{A});

    auto test_case = test::TestCase<TestEngine>(f);
    test_case.add_input<int32_t>({0, 1, 1, 2, 1, 0, 0, 2, 1});
    test_case.add_expected_output<int32_t>(shape_r, {1, 0, 0, 0, 0, 1, 1, 0, 0, 0, 1, 1, 0, 1,
                                                     0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 1, 0});
    test_case.run();
}

NGRAPH_TEST(${BACKEND_NAME}, one_hot_vector_many_categories) {
    // Imagenet has roughly 20,000 categories
    constexpr uint32_t category_count = 20000;
    Shape shape_a{6};
    auto A = make_shared<op::Parameter>(element::i32, shape_a);
    Shape shape_r{6, category_count};
    int axis = 1;
    auto depth = op::Constant::create(element::i32, {}, {shape_r[axis]});
    auto on_value = op::Constant::create(element::i32, {}, {1});
    auto off_value = op::Constant::create(element::i32, {}, {0});
    auto r = make_shared<op::v1::OneHot>(A, depth, on_value, off_value, axis);
    auto f = make_shared<Function>(r, ParameterVector{A});

    vector<int32_t> input{0, 11, 101, 1001, 10001, static_cast<int32_t>(category_count - 1)};
    vector<int32_t> output(shape_size(shape_r), 0);
    for (size_t i = 0; i < input.size(); ++i) {
        output[i * category_count + input[i]] = 1;
    }

    auto test_case = test::TestCase<TestEngine>(f);
    test_case.add_input<int32_t>(input);
    test_case.add_expected_output<int32_t>(shape_r, output);
    test_case.run();
}

NGRAPH_TEST(${BACKEND_NAME}, one_hot_on_off_float) {
    Shape shape_a{3, 3};
    auto A = make_shared<op::Parameter>(element::i32, shape_a);
    Shape shape_r{3, 3, 3};
    int axis = 0;
    auto depth = op::Constant::create(element::i32, {}, {shape_r[axis]});
    auto on_value = op::Constant::create(element::f32, {}, {2.5});
    auto off_value = op::Constant::create(element::f32, {}, {0.5});
    auto r = make_shared<op::v1::OneHot>(A, depth, on_value, off_value, axis);
    auto f = make_shared<Function>(r, ParameterVector{A});

    auto backend = runtime::Backend::create("${BACKEND_NAME}");

    // Create some tensors for input/output
    auto a = backend->create_tensor(element::i32, shape_a);
    copy_data(a, vector<int32_t>{0, 1, 1, 2, 1, 0, 0, 2, 1});
    auto result = backend->create_tensor(element::f32, shape_r);

    auto handle = backend->compile(f);
    handle->call_with_validate({result}, {a});
    EXPECT_EQ((vector<float>{2.5, 0.5, 0.5, 0.5, 0.5, 2.5, 2.5, 0.5, 0.5, 0.5, 2.5, 2.5, 0.5, 2.5,
                             0.5, 0.5, 0.5, 2.5, 0.5, 0.5, 0.5, 2.5, 0.5, 0.5, 0.5, 2.5, 0.5}),
              read_vector<float>(result));
}
