// Copyright 2016, Tobias Hermann.
// https://github.com/Dobiasd/frugally-deep
// Distributed under the MIT License.
// (See accompanying LICENSE file or at
//  https://opensource.org/licenses/MIT)

#pragma once

#include "fdeep/convolution.hpp"
#include "fdeep/filter.hpp"
#include "fdeep/layers/layer.hpp"
#include "fdeep/shape2.hpp"
#include "fdeep/tensor_shape.hpp"

#include <fplus/fplus.hpp>

#include <cstddef>
#include <vector>

namespace fdeep {
namespace internal {

    // Convolve depth slices separately first.
    // Then convolve normally with kernel_size = (1, 1)
    class separable_conv_2d_layer : public layer {
    public:
        explicit separable_conv_2d_layer(
            const std::string& name, std::size_t input_depth,
            const tensor_shape& filter_shape,
            std::size_t k, const shape2& strides, padding p,
            const shape2& dilation_rate,
            const float_vec& depthwise_weights,
            const float_vec& pointwise_weights,
            const float_vec& bias_0,
            const float_vec& bias)
            : layer(name)
            , depthwise_layer_(name + "_depthwise_part", input_depth,
                  filter_shape, strides, p, dilation_rate,
                  depthwise_weights, bias_0)
            , filters_pointwise_(generate_im2col_filter_matrix(
                  generate_filters(shape2(1, 1),
                      tensor_shape(input_depth), k, pointwise_weights, bias)))
        {
        }

    protected:
        tensors apply_impl(const tensors& inputs) const override
        {
            const auto temp = depthwise_layer_.apply(inputs);
            const auto temp_single = single_tensor_from_tensors(temp);
            return { convolve(shape2(1, 1), padding::valid, filters_pointwise_, temp_single) };
        }

        depthwise_conv_2d_layer depthwise_layer_;
        convolution_filter_matrices filters_pointwise_;
    };

}
}
