def addFILTER_INC(self):
operator = Operator('FILTER_INC', 1)
def func(node):
node.filter_count *= 2
return node
operator.set_pheno_func(func)
self.operators.append(operator)
def addSOFTSIGN(self):
operator = Operator('SOFTSIGN', 1)
def func(node):
node.set_activation('softsign')
return node
operator.set_pheno_func(func)
self.operators.append(operator)
def addMAX_P(self):
operator = Operator('MAX_P', 1)
def func(node):
node.maxPooling = True
return node
operator.set_pheno_func(func)
self.operators.append(operator)
def addHALF(self):
operator = Operator('HALF', 1)
def func(node):
node.divide_neuron_count(2)
return node
operator.set_pheno_func(func)
self.operators.append(operator)
def addHSIGMOID(self):
operator = Operator('HSIGMOID', 1)
def func(node):
node.set_activation('hard_sigmoid')
return node
operator.set_pheno_func(func)
self.operators.append(operator)
def addDOUB(self):
operator = Operator('DOUB', 1)
def func(node):
node.multiply_neuron_count(2)
return node
operator.set_pheno_func(func)
self.operators.append(operator)
def addRELU(self):
operator = Operator('RELU', 1)
def func(node):
node.set_activation('relu')
return node
operator.set_pheno_func(func)
self.operators.append(operator)
def addTANH(self):
operator = Operator('TANH', 1)
def func(node):
node.set_activation('tanh')
return node
operator.set_pheno_func(func)
self.operators.append(operator)
def addSOFTPLUS(self):
operator = Operator('SOFTPLUS', 1)
def func(node):
node.set_activation('softplus')
return node
operator.set_pheno_func(func)
self.operators.append(operator)
def addDROP_DEC(self):
operator = Operator('DROP_DEC', 1)
def func(node):
if node.dropout > 0.1: # make sure that it never reaches 0%
node.dropout -= 0.1
return node
operator.set_pheno_func(func)
self.operators.append(operator)
def addDROP_INC(self):
operator = Operator('DROP_INC', 1)
def func(node):
if node.dropout < 0.9: # make sure that it never reaches 100%
node.dropout += 0.1
return node
operator.set_pheno_func(func)
self.operators.append(operator)
def addPOOL_SIZE_DEC(self):
operator = Operator('POOL_SIZE_DEC', 1)
def func(node):
if node.pool_size > constants.POOL_SIZE_MIN: # make sure it always stays at least POOL_SIZE_MIN
node.pool_size -= 1
return node
operator.set_pheno_func(func)
self.operators.append(operator)
def addPOOL_SIZE_INC(self):
operator = Operator('POOL_SIZE_INC', 1)
def func(node):
if node.pool_size < constants.IMG_DIMENSION: # prevent out of bounds
node.pool_size += 1
return node
operator.set_pheno_func(func)
self.operators.append(operator)
def addKER_SIZE_DEC(self):
operator = Operator('KER_SIZE_DEC', 1)
def func(node):
if node.kernel_size > constants.KERNEL_SIZE_MIN: # make sure kernel stays at least KERNEL_SIZE_MIN
node.kernel_size -= 2 # make sure it always stays uneven (e.g. 3, 5, 7 etc.) for convolution to work
return node
operator.set_pheno_func(func)
self.operators.append(operator)
def addFILTER_DEC(self):
operator = Operator('FILTER_DEC', 1)
def func(node):
if node.filter_count > constants.FILTER_COUNT_MIN: # make sure that it stays at least FILTER_COUNT_MIN
node.filter_count = int(node.filter_count / 2)
return node
operator.set_pheno_func(func)
self.operators.append(operator)
def addPAR(self):
operator = Operator('PAR', 2)
def func(node, index):
next = Phenotype(index, node.neurons)
next.copy_inputs(node)
next.copy_outputs(node)
return node, next # return LEFT, RIGHT
operator.set_pheno_func(func)
self.operators.append(operator)
def addKER_SIZE_INC(self):
operator = Operator('KER_SIZE_INC', 1)
def func(node):
if node.kernel_size < constants.IMG_DIMENSION:
node.kernel_size += 2 # make sure kernel always stays uneven (e.g. 3, 5, 7 etc.) for convolution to work
if node.kernel_size > constants.IMG_DIMENSION: # addition could lead to out of bounds
node.kernel_size -= 2
return node
operator.set_pheno_func(func)
self.operators.append(operator)
def addSEQ(self):
operator = Operator('SEQ', 2)
def func(node, index):
next = Phenotype(index, node.neurons)
next.add_input(node)
next.copy_outputs(node)
for n in node.outputs:
n.inputs.remove(node)
node.outputs = []
node.add_output(next)
return node, next # return LEFT, RIGHT
operator.set_pheno_func(func)
self.operators.append(operator)
