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Testing swish #65 with cropping.
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@joaopauloschuler
joaopauloschuler committed Oct 14, 2021
1 parent eb602cc commit 3f88d83
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174 changes: 174 additions & 0 deletions examples/SimpleImageClassifier/SimpleImageClassifierPaddingCroppingSwish.lpi
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106 changes: 106 additions & 0 deletions examples/SimpleImageClassifier/SimpleImageClassifierPaddingCroppingSwish.lpr
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program SimpleImageClassifierPaddingCroppingSwish;
(*
Coded by Joao Paulo Schwarz Schuler.
https://github.com/joaopauloschuler/neural-api
*)
{$mode objfpc}{$H+}

uses {$IFDEF UNIX} {$IFDEF UseCThreads}
cthreads, {$ENDIF} {$ENDIF}
Classes, SysUtils, CustApp, neuralnetwork, neuralvolume,
Math, neuraldatasets, neuralfit, neuralthread;

type
TTestCNNAlgo = class(TCustomApplication)
protected
procedure DoRun; override;
end;

const
// Padding and cropping constants.
csPadding = 4;
csCropSize = csPadding * 2;

procedure TTestCNNAlgo.DoRun;
var
NN: TNNet;
NeuralFit: TNeuralImageFit;
ImgTrainingVolumes, ImgValidationVolumes, ImgTestVolumes: TNNetVolumeList;
begin
if not CheckCIFARFile() then
begin
Terminate;
exit;
end;
WriteLn('Creating Neural Network...');
NN := TNNet.Create();
NN.AddLayer([
TNNetInput.Create(32, 32, 3),
TNNetConvolutionLinear.Create({Features=}64, {FeatureSize=}5, {Padding=}2, {Stride=}1, {SuppressBias=}1),
TNNetMaxPool.Create(4),
TNNetMovingStdNormalization.Create(),
TNNetConvolutionLinear.Create({Features=}64, {FeatureSize=}3, {Padding=}1, {Stride=}1, {SuppressBias=}1),
TNNetSwish.Create(),
TNNetConvolutionLinear.Create({Features=}64, {FeatureSize=}3, {Padding=}1, {Stride=}1, {SuppressBias=}1),
TNNetSwish.Create(),
TNNetConvolutionLinear.Create({Features=}64, {FeatureSize=}3, {Padding=}1, {Stride=}1, {SuppressBias=}1),
TNNetSwish.Create(),
TNNetConvolutionLinear.Create({Features=}64, {FeatureSize=}3, {Padding=}1, {Stride=}1, {SuppressBias=}1),
TNNetSwish.Create(),
TNNetDropout.Create(0.5),
TNNetMaxPool.Create(2),
TNNetFullConnectLinear.Create(10),
TNNetSoftMax.Create()
]);
NN.DebugStructure();
CreateCifar10Volumes(ImgTrainingVolumes, ImgValidationVolumes, ImgTestVolumes);

// Add padding to dataset
WriteLn
(
'Original image size: ',
ImgTrainingVolumes[0].SizeX,',',
ImgTrainingVolumes[0].SizeY,' px.'
);
ImgTrainingVolumes.AddPadding(csPadding);
ImgValidationVolumes.AddPadding(csPadding);
ImgTestVolumes.AddPadding(csPadding);
WriteLn
(
'New image size after padding: ',
ImgTrainingVolumes[0].SizeX,',',
ImgTrainingVolumes[0].SizeY,' px.'
);

NeuralFit := TNeuralImageFit.Create;

// Enable cropping while fitting.
NeuralFit.HasImgCrop := true;
NeuralFit.MaxCropSize := csCropSize;

NeuralFit.FileNameBase := 'SimpleImageClassifierPaddingCroppingSwish-'+IntToStr(GetProcessId());
NeuralFit.InitialLearningRate := 0.001;
NeuralFit.LearningRateDecay := 0.01;
NeuralFit.StaircaseEpochs := 10;
NeuralFit.Inertia := 0.9;
NeuralFit.L2Decay := 0.00001;
NeuralFit.MaxThreadNum := 1;

NeuralFit.Fit(NN, ImgTrainingVolumes, ImgValidationVolumes, ImgTestVolumes, {NumClasses=}10, {batchsize=}64, {epochs=}50);
NeuralFit.Free;

NN.Free;
ImgTestVolumes.Free;
ImgValidationVolumes.Free;
ImgTrainingVolumes.Free;
Terminate;
end;

var
Application: TTestCNNAlgo;
begin
Application := TTestCNNAlgo.Create(nil);
Application.Title:='CIFAR-10 Classification Example';
Application.Run;
Application.Free;
end.

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