//*****************************************************************************
// 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 <memory>

#include "ngraph/op/add.hpp"
#include "ngraph/op/constant.hpp"
#include "ngraph/op/fused/hard_sigmoid.hpp"
#include "ngraph/op/maximum.hpp"
#include "ngraph/op/minimum.hpp"
#include "ngraph/op/multiply.hpp"
#include "ngraph/shape.hpp"

using namespace std;
using namespace ngraph;

constexpr NodeTypeInfo op::HardSigmoid::type_info;

op::HardSigmoid::HardSigmoid(const Output<Node>& data,
                             const Output<Node>& alpha,
                             const Output<Node>& beta)
    : FusedOp({data, alpha, beta})
{
    constructor_validate_and_infer_types();
}

bool ngraph::op::v0::HardSigmoid::visit_attributes(AttributeVisitor& visitor)
{
    return true;
}

void op::HardSigmoid::pre_validate_and_infer_types()
{
    const auto& alpha_pshape = get_input_partial_shape(1);
    const auto& beta_pshape = get_input_partial_shape(2);

    if (alpha_pshape.is_static())
    {
        const auto alpha_shape = alpha_pshape.to_shape();
        NODE_VALIDATION_CHECK(this,
                              is_scalar(alpha_shape),
                              "A scalar is expected for the 'alpha' input. Got: ",
                              alpha_shape);
    }

    if (beta_pshape.is_static())
    {
        const auto beta_shape = beta_pshape.to_shape();
        NODE_VALIDATION_CHECK(this,
                              is_scalar(beta_shape),
                              "A scalar is expected for the 'beta' input. Got: ",
                              beta_shape);
    }

    const auto& data_et = get_input_element_type(0);
    const auto& alpha_et = get_input_element_type(1);
    const auto& beta_et = get_input_element_type(2);

    NODE_VALIDATION_CHECK(
        this,
        data_et == alpha_et && data_et == beta_et,
        "The element types of both alpha and beta inputs must match the data input type.");
}

NodeVector op::HardSigmoid::decompose_op() const
{
    const auto data = input_value(0);

    const auto one_node =
        ngraph::op::Constant::create<float>(data.get_element_type(), data.get_shape(), {1.0f});

    const auto zero_node =
        ngraph::op::Constant::create<float>(data.get_element_type(), data.get_shape(), {0.0f});

    const auto alpha_node = input_value(1).get_node_shared_ptr();
    const auto beta_node = input_value(2).get_node_shared_ptr();

    std::shared_ptr<Node> alpha_x_plus_beta =
        std::make_shared<op::v1::Multiply>(alpha_node, data, AutoBroadcastType::NUMPY);

    alpha_x_plus_beta =
        std::make_shared<op::v1::Add>(alpha_x_plus_beta, beta_node, AutoBroadcastType::NUMPY);

    return {std::make_shared<op::v1::Minimum>(
        std::make_shared<op::v1::Maximum>(alpha_x_plus_beta, zero_node), one_node)};
}

shared_ptr<Node> op::HardSigmoid::clone_with_new_inputs(const OutputVector& new_args) const
{
    check_new_args_count(this, new_args);

    return make_shared<HardSigmoid>(new_args.at(0), new_args.at(1), new_args.at(2));
}
