coco
152 lines
5.7 KiB
C++
152 lines
5.7 KiB
C++
// Copyright (C) 2007 Davis E. King (davis@dlib.net)
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// License: Boost Software License See LICENSE.txt for the full license.
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#ifndef DLIB_MLP_KERNEl_C_
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#define DLIB_MLP_KERNEl_C_
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#include "mlp_kernel_abstract.h"
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#include "../algs.h"
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#include "../assert.h"
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namespace dlib
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{
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template <
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typename mlp_base // is an implementation of mlp_kernel_abstract.h
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>
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class mlp_kernel_c : public mlp_base
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{
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long verify_constructor_args (
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long nodes_in_input_layer,
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long nodes_in_first_hidden_layer,
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long nodes_in_second_hidden_layer,
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long nodes_in_output_layer
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)
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{
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// make sure requires clause is not broken
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DLIB_CASSERT(nodes_in_input_layer > 0 &&
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nodes_in_first_hidden_layer > 0 &&
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nodes_in_second_hidden_layer >= 0 &&
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nodes_in_output_layer > 0,
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"\tconst mlp::constructor()"
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<< "\n\tinvalid constructor arguments"
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<< "\n\tnodes_in_input_layer: " << nodes_in_input_layer
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<< "\n\tnodes_in_first_hidden_layer: " << nodes_in_first_hidden_layer
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<< "\n\tnodes_in_second_hidden_layer: " << nodes_in_second_hidden_layer
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<< "\n\tnodes_in_output_layer: " << nodes_in_output_layer
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);
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return nodes_in_input_layer;
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}
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public:
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mlp_kernel_c (
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long nodes_in_input_layer,
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long nodes_in_first_hidden_layer,
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long nodes_in_second_hidden_layer = 0,
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long nodes_in_output_layer = 1,
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double alpha = 0.1,
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double momentum = 0.8
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) : mlp_base( verify_constructor_args(
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nodes_in_input_layer,
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nodes_in_input_layer,
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nodes_in_second_hidden_layer,
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nodes_in_output_layer),
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nodes_in_first_hidden_layer,
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nodes_in_second_hidden_layer,
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nodes_in_output_layer,
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alpha,
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momentum)
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{
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}
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template <typename EXP>
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const matrix<double> operator() (
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const matrix_exp<EXP>& in
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) const
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{
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// make sure requires clause is not broken
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DLIB_CASSERT(in.nr() == this->input_layer_nodes() &&
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in.nc() == 1,
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"\tconst matrix<double> mlp::operator()(matrix_exp)"
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<< "\n\tthe input matrix dimensions are not correct"
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<< "\n\tin.nr(): " << in.nr()
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<< "\n\tin.nc(): " << in.nc()
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<< "\n\tinput_layer_nodes(): " << this->input_layer_nodes()
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<< "\n\tthis: " << this
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);
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return mlp_base::operator()(in);
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}
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template <typename EXP1, typename EXP2>
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void train (
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const matrix_exp<EXP1>& example_in,
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const matrix_exp<EXP2>& example_out
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)
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{
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// make sure requires clause is not broken
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DLIB_CASSERT(example_in.nr() == this->input_layer_nodes() &&
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example_in.nc() == 1 &&
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example_out.nr() == this->output_layer_nodes() &&
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example_out.nc() == 1 &&
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max(example_out) <= 1.0 && min(example_out) >= 0.0,
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"\tvoid mlp::train(matrix_exp, matrix_exp)"
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<< "\n\tthe training example dimensions are not correct"
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<< "\n\texample_in.nr(): " << example_in.nr()
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<< "\n\texample_in.nc(): " << example_in.nc()
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<< "\n\texample_out.nr(): " << example_out.nr()
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<< "\n\texample_out.nc(): " << example_out.nc()
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<< "\n\tmax(example_out): " << max(example_out)
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<< "\n\tmin(example_out): " << min(example_out)
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<< "\n\tinput_layer_nodes(): " << this->input_layer_nodes()
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<< "\n\toutput_layer_nodes(): " << this->output_layer_nodes()
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<< "\n\tthis: " << this
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);
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mlp_base::train(example_in,example_out);
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}
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template <typename EXP>
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void train (
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const matrix_exp<EXP>& example_in,
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double example_out
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)
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{
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// make sure requires clause is not broken
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DLIB_CASSERT(example_in.nr() == this->input_layer_nodes() &&
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example_in.nc() == 1 &&
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this->output_layer_nodes() == 1 &&
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example_out <= 1.0 && example_out >= 0.0,
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"\tvoid mlp::train(matrix_exp, double)"
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<< "\n\tthe training example dimensions are not correct"
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<< "\n\texample_in.nr(): " << example_in.nr()
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<< "\n\texample_in.nc(): " << example_in.nc()
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<< "\n\texample_out: " << example_out
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<< "\n\tinput_layer_nodes(): " << this->input_layer_nodes()
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<< "\n\toutput_layer_nodes(): " << this->output_layer_nodes()
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<< "\n\tthis: " << this
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);
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mlp_base::train(example_in,example_out);
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}
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};
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template <
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typename mlp_base
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>
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inline void swap (
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mlp_kernel_c<mlp_base>& a,
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mlp_kernel_c<mlp_base>& b
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) { a.swap(b); }
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// ----------------------------------------------------------------------------------------
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}
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#endif // DLIB_MLP_KERNEl_C_
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