/*******************************************************************************
* Copyright 2020-2024 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 <cstdint>

#include <gtest/gtest.h>

#include "oneapi/dnnl/dnnl_graph.hpp"

TEST(APIGraph, SetAndGetFloatingPointMathMode) {
    using namespace dnnl::graph;
    using fpmath_mode = dnnl::fpmath_mode;

    dnnl::engine::kind engine_kind = dnnl::engine::kind::cpu;
    graph g(engine_kind);
    g.set_fpmath_mode(fpmath_mode::bf16, true);

    fpmath_mode mode;
    bool apply_to_int;
    g.get_fpmath_mode(mode, apply_to_int);

    EXPECT_EQ(mode, fpmath_mode::bf16);
    EXPECT_EQ(apply_to_int, 1U);
}

TEST(APIGraph, GetPartitions) {
    using namespace dnnl::graph;
    dnnl::engine::kind engine_kind = dnnl::engine::kind::cpu;
    graph g(engine_kind);
    op relu_op(0, op::kind::ReLU, "relu");
    logical_tensor lt1 {0, logical_tensor::data_type::f32,
            logical_tensor::layout_type::strided};
    logical_tensor lt2 {1, logical_tensor::data_type::f32,
            logical_tensor::layout_type::strided};
    relu_op.add_input(lt1);
    relu_op.add_output(lt2);
    g.add_op(relu_op);
    g.finalize();
    // with default policy: partition::policy::fusion
    auto partitions = g.get_partitions();

    EXPECT_EQ(partitions.size(), 1U);
}

TEST(APIGraph, GetPartitionsReentrant) {
    using namespace dnnl::graph;
    engine::kind engine_kind = engine::kind::cpu;
    graph g(engine_kind);

    op matmul_op(0, op::kind::MatMul, "matmul");
    op relu_op(1, op::kind::ReLU, "relu");
    logical_tensor matmul_src {0, logical_tensor::data_type::f32,
            logical_tensor::layout_type::strided};
    logical_tensor matmul_wei {1, logical_tensor::data_type::f32,
            logical_tensor::layout_type::strided};
    logical_tensor matmul_dst {2, logical_tensor::data_type::f32,
            logical_tensor::layout_type::strided};
    logical_tensor relu_dst {3, logical_tensor::data_type::f32,
            logical_tensor::layout_type::strided};

    matmul_op.add_input(matmul_src);
    matmul_op.add_input(matmul_wei);
    matmul_op.add_output(matmul_dst);
    relu_op.add_input(matmul_dst);
    relu_op.add_output(relu_dst);
    g.add_op(matmul_op);
    g.add_op(relu_op);
    g.finalize();

    // with default policy: partition::policy::fusion
    auto partitions = g.get_partitions();

    EXPECT_EQ(partitions.size(), 1U);

    // reenter the function with different policy
    auto debug_partitions = g.get_partitions(partition::policy::debug);
    EXPECT_EQ(debug_partitions.size(), 2U);
}

TEST(APIGraph, AddOp) {
    using namespace dnnl::graph;
    dnnl::engine::kind engine_kind = dnnl::engine::kind::cpu;
    graph g(engine_kind);

    op conv(0, op::kind::Convolution, "conv");

    const bool allow_exception = false;
    ASSERT_NE(g.add_op(conv, allow_exception), status::success);
    EXPECT_THROW(g.add_op(conv), dnnl::error);
}
