//*****************************************************************************
// Copyright 2017-2020 Intel Corporation
//
// 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 "gtest/gtest.h"
#include "ngraph/ngraph.hpp"
#include "ngraph/runtime/tensor.hpp"
#include "runtime/backend.hpp"
#include "util/all_close_f.hpp"
#include "util/ndarray.hpp"
#include "util/test_control.hpp"
#include "util/test_tools.hpp"

using namespace std;
using namespace ngraph;

static string s_manifest = "${MANIFEST}";

NGRAPH_TEST(${BACKEND_NAME}, abc)
{
    Shape shape{2, 2};
    auto A = make_shared<op::Parameter>(element::f32, shape);
    auto B = make_shared<op::Parameter>(element::f32, shape);
    auto C = make_shared<op::Parameter>(element::f32, shape);
    auto f = make_shared<Function>((A + B) * C, ParameterVector{A, B, C});

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

    // Create some tensors for input/output
    shared_ptr<runtime::Tensor> a = backend->create_tensor(element::f32, shape);
    shared_ptr<runtime::Tensor> b = backend->create_tensor(element::f32, shape);
    shared_ptr<runtime::Tensor> c = backend->create_tensor(element::f32, shape);
    shared_ptr<runtime::Tensor> result = backend->create_tensor(element::f32, shape);

    copy_data(a, test::NDArray<float, 2>({{1, 2}, {3, 4}}).get_vector());
    copy_data(b, test::NDArray<float, 2>({{5, 6}, {7, 8}}).get_vector());
    copy_data(c, test::NDArray<float, 2>({{9, 10}, {11, 12}}).get_vector());

    auto handle = backend->compile(f);
    handle->call_with_validate({result}, {a, b, c});
    EXPECT_TRUE(test::all_close_f(read_vector<float>(result),
                                  (test::NDArray<float, 2>({{54, 80}, {110, 144}})).get_vector()));

    handle->call_with_validate({result}, {b, a, c});
    EXPECT_TRUE(test::all_close_f(read_vector<float>(result),
                                  (test::NDArray<float, 2>({{54, 80}, {110, 144}})).get_vector()));

    handle->call_with_validate({result}, {a, c, b});
    EXPECT_TRUE(test::all_close_f(read_vector<float>(result),
                                  (test::NDArray<float, 2>({{50, 72}, {98, 128}})).get_vector()));
}

NGRAPH_TEST(${BACKEND_NAME}, abc_int64)
{
    Shape shape{2, 2};
    auto A = make_shared<op::Parameter>(element::i64, shape);
    auto B = make_shared<op::Parameter>(element::i64, shape);
    auto C = make_shared<op::Parameter>(element::i64, shape);
    auto f = make_shared<Function>((A + B) * C, ParameterVector{A, B, C});

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

    // Create some tensors for input/output
    auto a = backend->create_tensor(element::i64, shape);
    copy_data(a, vector<int64_t>{1, 2, 3, 4});
    auto b = backend->create_tensor(element::i64, shape);
    copy_data(b, vector<int64_t>{5, 6, 7, 8});
    auto c = backend->create_tensor(element::i64, shape);
    copy_data(c, vector<int64_t>{9, 10, 11, 12});
    auto result = backend->create_tensor(element::i64, shape);

    auto handle = backend->compile(f);
    handle->call_with_validate({result}, {a, b, c});
    EXPECT_EQ((vector<int64_t>{54, 80, 110, 144}), read_vector<int64_t>(result));

    handle->call_with_validate({result}, {b, a, c});
    EXPECT_EQ((vector<int64_t>{54, 80, 110, 144}), read_vector<int64_t>(result));

    handle->call_with_validate({result}, {a, c, b});
    EXPECT_EQ((vector<int64_t>{50, 72, 98, 128}), read_vector<int64_t>(result));
}
