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// 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/depthwise_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 <algorithm>
#include <cstddef>
#include <string>
#include <vector>
namespace fdeep {
namespace internal {
// Convolve depth slices separately.
class depthwise_conv_2d_layer : public layer {
public:
explicit depthwise_conv_2d_layer(
const std::string& name, std::size_t input_depth,
const tensor_shape& filter_shape,
const shape2& strides, padding p,
const shape2& dilation_rate,
const float_vec& depthwise_weights,
const float_vec& bias)
: layer(name)
, filters_(generate_im2col_filter_matrix(
generate_filters(dilation_rate, filter_shape,
input_depth, depthwise_weights, bias, false)))
, strides_(strides)
, padding_(p)
{
assertion(filter_shape.volume() > 0, "filter must have volume");
assertion(strides.area() > 0, "invalid strides");
assertion(filters_.filter_count_ == input_depth,
"invalid number of filters");
assertion(filters_.filter_shape_.depth_ == 1,
"invalid filter shape");
}
protected:
tensors apply_impl(const tensors& inputs) const override
{
const auto& input = single_tensor_from_tensors(inputs);
const auto result = depthwise_convolve(strides_, padding_, filters_, input);
assertion(result.shape().depth_ == input.shape().depth_,
"Invalid output shape");
return { result };
}
convolution_filter_matrices filters_;
shape2 strides_;
padding padding_;
};
}
}
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