def _individual_to_json(individual):
return {
'id': individual.id,
'parameters': individual.genome.encoded_parameters,
'learning_rate': individual.learning_rate,
'optimizer_state': StateEncoder.encode(individual.optimizer_state)
}
def _parse_individual(json, create_genome):
return Individual.decode(create_genome,
json['parameters'],
is_local=False,
learning_rate=json['learning_rate'],
optimizer_state=StateEncoder.decode(
json['optimizer_state']),
source=json['source'],
id=json['id'])
def _individual_to_json(individual):
json_response = {
'id': individual.id,
'parameters': individual.genome.encoded_parameters,
'learning_rate': individual.learning_rate,
'optimizer_state': StateEncoder.encode(individual.optimizer_state)
}
if individual.iteration is not None:
json_response['iteration'] = individual.iteration
return json_response
def individual_to_dict(individual):
individual_dict = {
'id': individual.id,
'parameters': individual.genome.encoded_parameters,
'learning_rate': individual.learning_rate,
'optimizer_state': StateEncoder.encode(individual.optimizer_state)
}
if individual.iteration is not None:
individual_dict['iteration'] = individual.iteration
return individual_dict
def encoded_parameters(self, value):
"""
:param value: base64 encoded representation of the networks state dictionary
"""
self.net.load_state_dict(StateEncoder.decode(value))
def encoded_parameters(self):
"""
:return: base64 encoded representation of the networks state dictionary
"""
return StateEncoder.encode(self.net.state_dict())