def recoverNeuralNetwork():
name = input('Input NeuralNetwork\'s name to be recovered.\n>>>')
nn = NeuralNetwork.DFF()
nn.loadfromFile(name + '_backup')
nn.Name = name
IO.setValuetoConfigfile('setting.json', 'latestNN', nn.Name)
return nn
def editBackproprogation(MyNeuralNetwork):
speed = float(input('Input speed value.\n>>>'))
# targeterr = input('Input target error value.\n>>>')
IO.setValuetoConfigfile(
p.SAVED_PATH + MyNeuralNetwork.Name + '_profile.json',
'LearningAlgorithm', 'BackPropagation')
IO.setValuetoConfigfile(
p.SAVED_PATH + MyNeuralNetwork.Name + '_profile.json', 'Speed', speed)
def createNeuralNetwork():
name = input('Input NeuralNetwork\'s name to be created.\n>>>')
layerscount = int(input('Input "'+name+'" NeuralNetwork\'s layers count.\n>>>'))
layerneuronscount = []
for layer in range(0, layerscount):
layerneuronscount.append(int(input('Input layer('+str(layer+1)+'\\'+str(layerscount)+')\'s neurons count.\n>>>')))
nn = NeuralNetwork.DFF(layerscount, layerneuronscount, name)
nn.savetoFile()
IO.setValuetoConfigfile('setting.json', 'latestNN', nn.Name)
return nn
def editAdam(MyNeuralNetwork):
speed = float(input('Input speed value('+str(p.PROFILE_DEFAULT['Speed'])+').\n>>>'))
beta1 = float(input('Input Beta1(decay rate)('+str(p.PROFILE_DEFAULT['Beta1'])+').\n>>>'))
beta2 = float(input('Input Beta2(decay rate)('+str(p.PROFILE_DEFAULT['Beta2'])+').\n>>>'))
# targeterr = input('Input target error value.\n>>>')
IO.setValuetoConfigfile(p.SAVED_PATH+MyNeuralNetwork.Name+'_profile.json', 'LearningAlgorithm', 'Adam')
IO.setValuetoConfigfile(p.SAVED_PATH+MyNeuralNetwork.Name+'_profile.json', 'Speed', speed)
IO.setValuetoConfigfile(p.SAVED_PATH+MyNeuralNetwork.Name+'_profile.json', 'Beta1', beta1)
IO.setValuetoConfigfile(p.SAVED_PATH+MyNeuralNetwork.Name+'_profile.json', 'Beta2', beta2)
IO.setValuetoConfigfile(p.SAVED_PATH+MyNeuralNetwork.Name+'_profile.json', 'Epsilon', p.PROFILE_DEFAULT['Epsilon'])
def editRMSprop(MyNeuralNetwork):
speed = float(input('Input speed value('+str(p.PROFILE_DEFAULT['Speed'])+').\n>>>'))
decayrate = float(input('Input decay rate('+str(p.PROFILE_DEFAULT['DecayRate'])+').\n>>>'))
# targeterr = input('Input target error value.\n>>>')
IO.setValuetoConfigfile(p.SAVED_PATH+MyNeuralNetwork.Name+'_profile.json', 'LearningAlgorithm', 'RMSprop')
IO.setValuetoConfigfile(p.SAVED_PATH+MyNeuralNetwork.Name+'_profile.json', 'Speed', speed)
IO.setValuetoConfigfile(p.SAVED_PATH+MyNeuralNetwork.Name+'_profile.json', 'DecayRate', decayrate)
IO.setValuetoConfigfile(p.SAVED_PATH+MyNeuralNetwork.Name+'_profile.json', 'Epsilon', p.PROFILE_DEFAULT['Epsilon'])
def editNesterovMomentum(MyNeuralNetwork):
speed = float(input('Input speed value.\n>>>'))
momentumrate = float(input('Input momentum rate.\n>>>'))
# targeterr = input('Input target error value.\n>>>')
IO.setValuetoConfigfile(p.SAVED_PATH+MyNeuralNetwork.Name+'_profile.json', 'LearningAlgorithm', 'NesterovMomentum')
IO.setValuetoConfigfile(p.SAVED_PATH+MyNeuralNetwork.Name+'_profile.json', 'Speed', speed)
IO.setValuetoConfigfile(p.SAVED_PATH+MyNeuralNetwork.Name+'_profile.json', 'Momentum_Rate', momentumrate)
def editAdaGrad(MyNeuralNetwork):
speed = float(input('Input speed value.\n>>>'))
# targeterr = input('Input target error value.\n>>>')
IO.setValuetoConfigfile(
p.SAVED_PATH + MyNeuralNetwork.Name + '_profile.json',
'LearningAlgorithm', 'AdaGrad')
IO.setValuetoConfigfile(
p.SAVED_PATH + MyNeuralNetwork.Name + '_profile.json', 'Speed', speed)
IO.setValuetoConfigfile(
p.SAVED_PATH + MyNeuralNetwork.Name + '_profile.json', 'Epsilon',
p.PROFILE_DEFAULT['Epsilon'])
def loadNeuralNetwork():
name = input('Input NeuralNetwork\'s name to be loaded.\n>>>')
nn = NeuralNetwork.DFF()
nn.loadfromFile(name)
IO.setValuetoConfigfile('setting.json', 'latestNN', nn.Name)
return nn
def editTest1(MyNeuralNetwork):
# targeterr = input('Input target error value.\n>>>')
IO.setValuetoConfigfile(
p.SAVED_PATH + MyNeuralNetwork.Name + '_profile.json',
'LearningAlgorithm', 'Test1')
def setValuetoConfigfile():
listConfigfileValues()
name = input('Name Code:\n>>>')
value = input('Value:\n>>>')
IO.setValuetoConfigfile('setting.json', ConfigDict[str(name)], value)