def get_trained_model(config, experiment_name):
model = get_new_model(config)
file_controller = FileController(experiment_name)
assert file_controller.trained_model_exists(
), ' ! Unable to load trained model. Invalid experiment name.'
trained_model_path = file_controller.get_model_filepath()
trained_model = model.load_weights(trained_model_path)
return model
class UIController():
def __init__(self, config, experiment_name):
self.config = config
self.file_controller = FileController(experiment_name)
self.skip_training = False
self.new_training = False
self.continue_training = True
self.skip_testing = False
self.new_testing = False
self.continue_testing = True
def ask_retrain(self):
if self.file_controller.trained_model_exists() == False:
print(' - Trained model not found. Model will be trained.')
self.continue_training = False
self.skip_training = False
self.new_training = True
return
message = 'A trained model already exists, would you like to retrain it?'
choices = [
'skip training', 'continue training existing model',
'new training (discard existing)'
]
question = inquirer.List('retrain', message, choices)
answer = inquirer.prompt([question])
self.skip_training = answer['retrain'] == 'skip training'
self.new_training = answer[
'retrain'] == 'new training (discard existing)'
self.continue_training = answer[
'retrain'] == 'continue training existing model'
def ask_retest(self):
if self.file_controller.testing_result_exists() == False:
print(' - Testing results not found. Model will be tested.')
self.continue_testing = False
self.skip_testing = False
self.new_testing = True
return
message = 'Model testing results already exist, what would you like to do?'
choices = self.get_retest_choices()
question = inquirer.List('retest', message, choices)
answer = inquirer.prompt([question])
self.skip_testing = answer['retest'] == 'skip testing'
self.new_testing = answer['retest'] == 'new testing (discard existing)'
self.continue_testing = answer[
'retest'] == 'append to existing results'
def get_retest_choices(self):
if self.new_training or self.continue_training:
return [
'skip testing', 'new testing (discard existing)'
] # Do not allow to append testing analysis if model is retrained or improved
else:
return [
'skip testing', 'append to existing results',
'new testing (discard existing)'
]
def ask_parameters(self):
message = 'Continue with these experiment parameters?'
choices = ['yes', 'no']
question = inquirer.List('parameters', message, choices)
answer = inquirer.prompt([question])
if answer['parameters'] == 'no':
sys.exit()
def print_parameters(self, key):
print(f' - Verify {key} parameters')
print(json.dumps(self.config[key], indent=4, sort_keys=True))