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

// clang-format off
#ifdef ${BACKEND_NAME}_FLOAT_TOLERANCE_BITS
#define DEFAULT_FLOAT_TOLERANCE_BITS ${BACKEND_NAME}_FLOAT_TOLERANCE_BITS
#endif

#ifdef ${BACKEND_NAME}_DOUBLE_TOLERANCE_BITS
#define DEFAULT_DOUBLE_TOLERANCE_BITS ${BACKEND_NAME}_DOUBLE_TOLERANCE_BITS
#endif
// clang-format on

#include "gtest/gtest.h"
#include "ngraph/ngraph.hpp"
#include "util/all_close.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}, cosh)
{
    Shape shape{6};
    auto A = make_shared<op::v0::Parameter>(element::f32, shape);
    auto f = make_shared<Function>(make_shared<op::v0::Cosh>(A), ParameterVector{A});

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

    // Create some tensors for input/output
    auto a = backend->create_tensor(element::f32, shape);
    vector<float> input{1.0f, 0.0f, -0.0f, -1.0f, 5.0f, -5.0f};
    copy_data(a, input);
    auto result = backend->create_tensor(element::f32, shape);

    std::transform(
        input.begin(), input.end(), input.begin(), [](float x) -> float { return coshf(x); });

    auto handle = backend->compile(f);
    handle->call_with_validate({result}, {a});
    EXPECT_TRUE(test::all_close_f(input, read_vector<float>(result)));
}
