PLearn 0.1
MaxSubsamplingTest.cc
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00001 // -*- C++ -*-
00002 
00003 // MaxSubsamplingTest.cc
00004 //
00005 // Copyright (C) 2007 Pascal Lamblin
00006 //
00007 // Redistribution and use in source and binary forms, with or without
00008 // modification, are permitted provided that the following conditions are met:
00009 //
00010 //  1. Redistributions of source code must retain the above copyright
00011 //     notice, this list of conditions and the following disclaimer.
00012 //
00013 //  2. Redistributions in binary form must reproduce the above copyright
00014 //     notice, this list of conditions and the following disclaimer in the
00015 //     documentation and/or other materials provided with the distribution.
00016 //
00017 //  3. The name of the authors may not be used to endorse or promote
00018 //     products derived from this software without specific prior written
00019 //     permission.
00020 //
00021 // THIS SOFTWARE IS PROVIDED BY THE AUTHORS ``AS IS'' AND ANY EXPRESS OR
00022 // IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES
00023 // OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN
00024 // NO EVENT SHALL THE AUTHORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL,
00025 // SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED
00026 // TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR
00027 // PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF
00028 // LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING
00029 // NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
00030 // SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
00031 //
00032 // This file is part of the PLearn library. For more information on the PLearn
00033 // library, go to the PLearn Web site at www.plearn.org
00034 
00035 // Authors: Pascal Lamblin
00036 
00040 #include "MaxSubsamplingTest.h"
00041 
00042 namespace PLearn {
00043 using namespace std;
00044 
00045 PLEARN_IMPLEMENT_OBJECT(
00046     MaxSubsamplingTest,
00047     "Tests MaxSubsampling2DModule",
00048     ""
00049 );
00050 
00052 // MaxSubsamplingTest //
00054 MaxSubsamplingTest::MaxSubsamplingTest()
00055 {
00056 }
00057 
00059 // build //
00061 void MaxSubsamplingTest::build()
00062 {
00063     inherited::build();
00064     build_();
00065 }
00066 
00068 // makeDeepCopyFromShallowCopy //
00070 void MaxSubsamplingTest::makeDeepCopyFromShallowCopy(CopiesMap& copies)
00071 {
00072     inherited::makeDeepCopyFromShallowCopy(copies);
00073 
00074     deepCopyField(max_module, copies);
00075     deepCopyField(random_gen, copies);
00076 }
00077 
00079 // declareOptions //
00081 void MaxSubsamplingTest::declareOptions(OptionList& ol)
00082 {
00083     declareOption(ol, "batch_size", &MaxSubsamplingTest::batch_size,
00084                   OptionBase::buildoption,
00085                   "Size of batch");
00086 
00087     declareOption(ol, "n_input_images", &MaxSubsamplingTest::n_input_images,
00088                   OptionBase::buildoption,
00089                   "Number of images in each input vector");
00090 
00091     declareOption(ol, "input_images_length",
00092                   &MaxSubsamplingTest::input_images_length,
00093                   OptionBase::buildoption,
00094                   "Length of input images");
00095 
00096     declareOption(ol, "input_images_width",
00097                   &MaxSubsamplingTest::input_images_width,
00098                   OptionBase::buildoption,
00099                   "Width of input images");
00100 
00101     declareOption(ol, "kernel_length", &MaxSubsamplingTest::kernel_length,
00102                   OptionBase::buildoption,
00103                   "Length of the subsampling zone");
00104 
00105     declareOption(ol, "kernel_width", &MaxSubsamplingTest::kernel_width,
00106                   OptionBase::buildoption,
00107                   "Width of the subsampling zone");
00108 
00109     declareOption(ol, "output_images_length",
00110                   &MaxSubsamplingTest::output_images_length,
00111                   OptionBase::learntoption,
00112                   "Length of output images");
00113 
00114     declareOption(ol, "output_images_width",
00115                   &MaxSubsamplingTest::output_images_width,
00116                   OptionBase::learntoption,
00117                   "Width of output images");
00118 
00119     declareOption(ol, "input_images_size",
00120                   &MaxSubsamplingTest::input_images_size,
00121                   OptionBase::learntoption,
00122                   "input_images_length*input_images_width");
00123 
00124     declareOption(ol, "output_images_size",
00125                   &MaxSubsamplingTest::output_images_size,
00126                   OptionBase::learntoption,
00127                   "output_images_length*output_images_width");
00128 
00129     declareOption(ol, "input_size",
00130                   &MaxSubsamplingTest::input_size,
00131                   OptionBase::learntoption,
00132                   "n_input_images*input_images_size");
00133 
00134     declareOption(ol, "output_size",
00135                   &MaxSubsamplingTest::output_size,
00136                   OptionBase::learntoption,
00137                   "n_input_images*output_images_size");
00138 
00139     declareOption(ol, "max_module", &MaxSubsamplingTest::max_module,
00140                   OptionBase::learntoption,
00141                   "The MaxSubsampling2DModule we build and test");
00142     /*
00143     declareOption(ol, "", &MaxSubsamplingTest::,
00144                   OptionBase::buildoption,
00145                   "");
00146     */
00147 
00148     // Now call the parent class' declareOptions
00149     inherited::declareOptions(ol);
00150 }
00151 
00153 // build_ //
00155 void MaxSubsamplingTest::build_()
00156 {
00157     PLCHECK( input_images_length % kernel_length == 0 );
00158     PLCHECK( input_images_width % kernel_width == 0 );
00159 
00160     output_images_length = input_images_length / kernel_length;
00161     output_images_width = input_images_width / kernel_width;
00162 
00163     input_images_size = input_images_length * input_images_width;
00164     output_images_size = output_images_length * output_images_width;
00165 
00166     input_size = n_input_images * input_images_size;
00167     output_size = n_input_images * output_images_size;
00168 
00169     if( !max_module )
00170     {
00171         max_module = new MaxSubsampling2DModule();
00172         max_module->n_input_images = n_input_images;
00173         max_module->input_images_length = input_images_length;
00174         max_module->input_images_width = input_images_width;
00175         max_module->kernel_length = kernel_length;
00176         max_module->kernel_width = kernel_width;
00177         max_module->build();
00178     }
00179 
00180     if (!random_gen)
00181         random_gen = new PRandom();
00182     random_gen->manual_seed(42);
00183 }
00184 
00186 // perform //
00188 void MaxSubsamplingTest::perform()
00189 {
00190     Mat in_(batch_size, input_size);
00191     Mat out_(batch_size, output_size);
00192     Mat argmax_(batch_size, output_size);
00193 
00194     TMat<Mat> in(batch_size, n_input_images);
00195     TMat<Mat> out(batch_size, n_input_images);
00196     TMat<Mat> argmax(batch_size, n_input_images);
00197 
00198     for( int k=0; k<batch_size; k++ )
00199         for( int i=0; i<n_input_images; i++ )
00200         {
00201             in(k,i) = in_(k).subVec(i*input_images_size, input_images_size)
00202                 .toMat(input_images_length, input_images_width);
00203             random_gen->fill_random_uniform(in(k,i), -1, 1);
00204 
00205             out(k,i) = out_(k)
00206                 .subVec(i*output_images_size, output_images_size)
00207                 .toMat(output_images_length, output_images_width);
00208 
00209             argmax(k,i) = argmax_(k)
00210                 .subVec( i*output_images_size, output_images_size)
00211                 .toMat(output_images_length, output_images_width);
00212         }
00213 
00214     TVec<Mat*> ports_values(3);
00215     ports_values[0] = &in_;
00216     ports_values[1] = &out_;
00217     ports_values[2] = &argmax_;
00218 
00219     out_.resize(0, output_size);
00220     argmax_.resize(0, output_size);
00221     max_module->fprop(ports_values);
00222 
00223 
00224     Mat out_grad_(batch_size, output_size, 1.);
00225     Mat in_grad_(batch_size, input_size);
00226     TMat<Mat> in_grad(batch_size, n_input_images);
00227 
00228     for( int k=0; k<batch_size; k++ )
00229         for( int i=0; i<n_input_images; i++ )
00230         {
00231             in_grad(k,i) = in_grad_(k)
00232                 .subVec(i*input_images_size, input_images_size)
00233                 .toMat(input_images_length, input_images_width);
00234         }
00235 
00236     TVec<Mat*> ports_grad(3);
00237     ports_grad[0] = &in_grad_;
00238     ports_grad[1] = &out_grad_;
00239     ports_grad[2] = NULL;
00240 
00241     in_grad_.resize(0, input_size);
00242     max_module->bpropAccUpdate( ports_values, ports_grad );
00243 
00244     for( int k=0; k<batch_size; k++ )
00245         for( int i=0; i<n_input_images; i++ )
00246         {
00247             pout << "in("<<k<<","<<i<<") = " << endl << in(k,i) << endl;
00248             pout << "out("<<k<<","<<i<<") = " << endl << out(k,i) << endl;
00249             pout << "argmax("<<k<<","<<i<<") = " << endl
00250                 << argmax(k,i) << endl;
00251             pout << "in_grad("<<k<<","<<i<<") = " << endl
00252                 << in_grad(k,i) << endl;
00253         }
00254 
00255 }
00256 
00257 } // end of namespace PLearn
00258 
00259 
00260 /*
00261   Local Variables:
00262   mode:c++
00263   c-basic-offset:4
00264   c-file-style:"stroustrup"
00265   c-file-offsets:((innamespace . 0)(inline-open . 0))
00266   indent-tabs-mode:nil
00267   fill-column:79
00268   End:
00269 */
00270 // vim: filetype=cpp:expandtab:shiftwidth=4:tabstop=8:softtabstop=4:encoding=utf-8:textwidth=79 :
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