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OpenNN 8.0.0 RC-2
1 parent 4a97e59 commit 52a99c1

11 files changed

Lines changed: 14 additions & 61 deletions

‎blank/data/neural_network.xml‎

Lines changed: 3 additions & 1 deletion
Original file line numberDiff line numberDiff line change
@@ -38,13 +38,15 @@
3838
<NeuronsNumber>1</NeuronsNumber>
3939
<Activation>HyperbolicTangent</Activation>
4040
<BatchNormalization>false</BatchNormalization>
41+
<DropoutRate>0.000000</DropoutRate>
4142
</Dense2d>
4243
<Dense2d>
4344
<Label>approximation_layer</Label>
4445
<InputsNumber>1</InputsNumber>
4546
<NeuronsNumber>3</NeuronsNumber>
4647
<Activation>Linear</Activation>
4748
<BatchNormalization>false</BatchNormalization>
49+
<DropoutRate>0.000000</DropoutRate>
4850
</Dense2d>
4951
<Unscaling>
5052
<NeuronsNumber>3</NeuronsNumber>
@@ -92,5 +94,5 @@
9294
<Output Index="3">output_3</Output>
9395
</Outputs>
9496
<Display>1</Display>
95-
<Parameters>0 0 0 0 0 0 0 0 0.3812433481216431 -0.7486003637313843 -0.01747423410415649 -0.259113609790802 -0.005976319313049316 0 0 0 0 0 0 0 0 0 0 0 -0.1103723049163818 0.6025896072387695 -0.8747032880783081 0 0 0 0 0 </Parameters>
97+
<Parameters>0 0 0 0 0 0 0 0 0.6431425809860229 0.1926859617233276 -0.3346401453018188 -0.1273961663246155 0.3503750562667847 0 0 0 0 0 0 0 0 0 0 0 0.2720129489898682 -0.2607494592666626 -0.5467162728309631 0 0 0 0 0 </Parameters>
9698
</NeuralNetwork>

‎examples/melanoma_cancer/main.cpp‎

Lines changed: 1 addition & 2 deletions
Original file line numberDiff line numberDiff line change
@@ -53,11 +53,10 @@ int main()
5353
AdaptiveMomentEstimation* adam = dynamic_cast<AdaptiveMomentEstimation*>(training_strategy.get_optimization_algorithm());
5454
adam->set_display_period(1);
5555
adam->set_batch_size(16);
56-
adam->set_maximum_epochs(10);
56+
adam->set_maximum_epochs(25);
5757

5858
training_strategy.train_cuda();
5959

60-
6160
// Testing analysis
6261

6362
cout << "Calculating Binary classification tests..." << endl;

‎opennn/adaptive_moment_estimation.cpp‎

Lines changed: 0 additions & 3 deletions
Original file line numberDiff line numberDiff line change
@@ -229,9 +229,6 @@ TrainingResults AdaptiveMomentEstimation::train()
229229

230230
for(Index epoch = 0; epoch <= maximum_epochs; epoch++)
231231
{
232-
cout << "Epoch: " << epoch << endl;
233-
234-
235232
if(display && epoch%display_period == 0) cout << "Epoch: " << epoch << endl;
236233

237234
training_batches = dataset->get_batches(training_sample_indices, training_batch_size, shuffle);

‎opennn/convolutional_layer.cpp‎

Lines changed: 0 additions & 2 deletions
Original file line numberDiff line numberDiff line change
@@ -684,10 +684,8 @@ void Convolutional::from_XML(const XMLDocument& document)
684684
throw runtime_error("Convolutional layer element is nullptr.\n");
685685

686686
const string inputDimsStr = read_xml_string(convolutional_layer_element, "InputDimensions");
687-
cout << "[Convolutional::from_XML] InputDimensions='" << inputDimsStr << "'" << endl;
688687

689688
const string strideStr = read_xml_string(convolutional_layer_element, "StrideDimensions");
690-
cout << "[Convolutional::from_XML] StrideDimensions='" << strideStr << "'" << endl;
691689

692690
set_label(read_xml_string(convolutional_layer_element, "Label"));
693691
set_input_shape(string_to_shape(inputDimsStr));

‎opennn/flatten_layer.h‎

Lines changed: 0 additions & 2 deletions
Original file line numberDiff line numberDiff line change
@@ -82,8 +82,6 @@ class Flatten final : public Layer
8282

8383
void set(const Shape& new_input_shape)
8484
{
85-
cout<<"Rank"<<Rank<<endl;
86-
cout<<"new_input_shape"<<new_input_shape.size()<<endl;
8785
if (new_input_shape.size() != Rank - 1)
8886
throw runtime_error("Error: Input shape size must match layer Rank in FlattenLayer::set().");
8987

‎opennn/image_dataset.cpp‎

Lines changed: 4 additions & 8 deletions
Original file line numberDiff line numberDiff line change
@@ -259,7 +259,6 @@ void ImageDataset::set_random_vertical_translation_maximum(const type new_random
259259

260260
void ImageDataset::to_XML(XMLPrinter& printer) const
261261
{
262-
cout<<"1a"<<endl;
263262
printer.OpenElement("ImageDataset");
264263

265264
printer.OpenElement("DataSource");
@@ -282,17 +281,14 @@ void ImageDataset::to_XML(XMLPrinter& printer) const
282281
add_xml_element(printer, "Codification", get_codification_string());
283282

284283
printer.CloseElement();
285-
cout<<"2a"<<endl;
284+
286285
variables_to_XML(printer);
287-
cout<<"3a"<<endl;
286+
288287
samples_to_XML(printer);
289-
cout<<"4a"<<endl;
290-
add_xml_element(printer, "Display", to_string(display));
291-
cout<<"5a"<<endl;
292-
printer.CloseElement();
293-
cout<<"6a"<<endl;
294288

289+
add_xml_element(printer, "Display", to_string(display));
295290

291+
printer.CloseElement();
296292
}
297293

298294

‎opennn/neural_network.cpp‎

Lines changed: 2 additions & 36 deletions
Original file line numberDiff line numberDiff line change
@@ -410,10 +410,7 @@ Index NeuralNetwork::get_inputs_number() const
410410

411411

412412
const Shape input_shape = layers[0]->get_input_shape();
413-
cout << "input_shape rank: " << input_shape.rank << endl;
414-
for(size_t i = 0; i < input_shape.rank; i++)
415-
cout << "input_shape[" << i << "] = " << input_shape.shape[i] << endl;
416-
cout << "count: " << input_shape.count() << endl;
413+
417414
return input_shape.count();
418415
}
419416

@@ -971,19 +968,12 @@ Tensor<string, 2> NeuralNetwork::get_dense2d_layers_information() const
971968
}
972969

973970

974-
975971
void NeuralNetwork::to_XML(XMLPrinter& printer) const
976972
{
977-
cout << "[to_XML] ENTER" << endl;
978-
979973
const Index inputs_number = get_inputs_number();
980974
const Index layers_number = get_layers_number();
981975
const Index outputs_number = get_outputs_number();
982976

983-
cout << "[to_XML] inputs=" << inputs_number
984-
<< " layers=" << layers_number
985-
<< " outputs=" << outputs_number << endl;
986-
987977
vector<string> input_names = get_input_feature_names();
988978
while (input_names.size() < static_cast<size_t>(inputs_number))
989979
input_names.push_back("input_" + to_string(input_names.size() + 1));
@@ -992,9 +982,6 @@ void NeuralNetwork::to_XML(XMLPrinter& printer) const
992982
while (output_names.size() < static_cast<size_t>(outputs_number))
993983
output_names.push_back("output_" + to_string(output_names.size() + 1));
994984

995-
cout << "[to_XML] input_names.size=" << input_names.size()
996-
<< " output_names.size=" << output_names.size() << endl;
997-
998985
printer.OpenElement("NeuralNetwork");
999986

1000987
// Inputs
@@ -1003,64 +990,43 @@ void NeuralNetwork::to_XML(XMLPrinter& printer) const
1003990
for(Index i = 0; i < inputs_number; i++)
1004991
add_xml_element_attribute(printer, "Input", input_names[i], "Index", to_string(i + 1));
1005992
printer.CloseElement();
1006-
cout << "[to_XML] Inputs section done" << endl;
1007993

1008994
// Layers
1009995
printer.OpenElement("Layers");
1010996
add_xml_element(printer, "LayersNumber", to_string(layers_number));
1011997

1012-
cout << "[to_XML] Starting layers loop, layers_number=" << layers_number << endl;
1013998
for(Index i = 0; i < layers_number; i++)
1014-
{
1015-
cout << "[to_XML] Layer " << i
1016-
<< " name=" << layers[i]->get_name();
1017999
layers[i]->to_XML(printer);
1018-
cout << "[to_XML] Layer " << i << " serialized OK" << endl;
1019-
}
1020-
cout << "[to_XML] Layers loop done" << endl;
1021-
1022-
// LayerInputIndices
1023-
cout << "[to_XML] layer_input_indices.size=" << layer_input_indices.size()
1024-
<< " layers_number=" << layers_number << endl;
1025-
1026-
if(Index(layer_input_indices.size()) != layers_number)
1027-
cout << "[to_XML] *** WARNING MISMATCH layer_input_indices vs layers_number ***" << endl;
10281000

10291001
printer.OpenElement("LayerInputIndices");
10301002
for(Index i = 0; i < Index(layer_input_indices.size()); i++)
10311003
{
1032-
cout << "[to_XML] indices[" << i << "]="
1033-
<< vector_to_string(layer_input_indices[i]) << endl;
10341004
add_xml_element_attribute(printer, "LayerInputsIndices",
10351005
vector_to_string(layer_input_indices[i]), "LayerIndex", to_string(i));
10361006
}
10371007
printer.CloseElement();
10381008
printer.CloseElement(); // Layers
1039-
cout << "[to_XML] LayerInputIndices done" << endl;
10401009

10411010
// Outputs
10421011
printer.OpenElement("Outputs");
10431012
const Index outputs_count = has("Embedding") ? outputs_number : output_names.size();
1044-
cout << "[to_XML] outputs_count=" << outputs_count << endl;
10451013
add_xml_element(printer, "OutputsNumber", to_string(outputs_count));
10461014
for(Index i = 0; i < outputs_count; i++)
10471015
add_xml_element_attribute(printer, "Output", output_names[i], "Index", to_string(i + 1));
10481016
printer.CloseElement();
1049-
cout << "[to_XML] Outputs done" << endl;
10501017

10511018
add_xml_element(printer, "Display", to_string(display));
10521019

10531020
// Parameters
10541021
printer.OpenElement("Parameters");
1055-
cout << "[to_XML] parameters_number=" << get_parameters_number() << endl;
10561022
if(get_parameters_number() > 0)
10571023
printer.PushText(vector_to_string(parameters, " ").c_str());
10581024
printer.CloseElement();
10591025

10601026
printer.CloseElement(); // NeuralNetwork
1061-
cout << "[to_XML] EXIT OK" << endl;
10621027
}
10631028

1029+
10641030
void NeuralNetwork::from_XML(const XMLDocument& document)
10651031
{
10661032
const XMLElement* neural_network_element = document.FirstChildElement("NeuralNetwork");

‎opennn/pooling_layer.cpp‎

Lines changed: 0 additions & 2 deletions
Original file line numberDiff line numberDiff line change
@@ -541,8 +541,6 @@ void Pooling::from_XML(const XMLDocument& document)
541541
throw runtime_error("Pooling layer element is nullptr.\batch_index");
542542

543543
const string inputDimsStr = read_xml_string(pooling_layer_element, "InputDimensions");
544-
cout << "[Pooling::from_XML] InputDimensions='" << inputDimsStr << "'" << endl;
545-
546544

547545
set_label(read_xml_string(pooling_layer_element, "Label"));
548546
set_input_shape(string_to_shape(read_xml_string(pooling_layer_element, "InputDimensions")));

‎opennn/standard_networks.cpp‎

Lines changed: 2 additions & 1 deletion
Original file line numberDiff line numberDiff line change
@@ -210,7 +210,8 @@ ImageClassificationNetwork::ImageClassificationNetwork(const Shape& input_shape,
210210

211211
add_layer(make_unique<Flatten<4>>(get_output_shape()));
212212

213-
const Shape hidden_shape = { get_output_shape()[0] };
213+
const Index flatten_size = get_output_shape()[0];
214+
const Shape hidden_shape = { min(flatten_size, Index(128)) };
214215
add_layer(make_unique<Dense<2>>(get_output_shape(),
215216
hidden_shape,
216217
"RectifiedLinear",

‎opennn/variable.cpp‎

Lines changed: 0 additions & 3 deletions
Original file line numberDiff line numberDiff line change
@@ -100,16 +100,13 @@ Index Variable::get_categories_number() const
100100
// XML Serialization
101101
void Variable::from_XML(const XMLDocument& document)
102102
{
103-
cout<<"FROM_XML CML SERIALIZATION)"<<endl;
104103
name = read_xml_string(document.FirstChildElement(), "Name");
105104
set_scaler(read_xml_string(document.FirstChildElement(), "Scaler"));
106105
set_role(read_xml_string(document.FirstChildElement(), "Role"));
107106
set_type(read_xml_string(document.FirstChildElement(), "Type"));
108107

109108
if (type == VariableType::Categorical)
110109
{
111-
cout<<"ENTRA en CATEGORICAL"<<endl;
112-
113110
const string categories_text = read_xml_string(document.FirstChildElement(), "Categories");
114111
categories = get_tokens(categories_text, ";");
115112
}

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