def test_learning_rate(self):
"""Test learning rate with wrong value."""
config_dict = deepcopy(self._config_dict)
config_dict['parameters']['learning_rate']['bounds'] = [-0.1, 1]
expected_err = {
'parameters': {
'learning_rate': {
'bounds': 'The value(s) should be positive number.'
}
}
}
err = OptimizerConfig().validate(config_dict)
assert expected_err == err
config_dict['parameters']['learning_rate']['bounds'] = [0.1, 1.1]
expected_err = {
'parameters': {
'learning_rate': {
'bounds': 'The upper bound should be less than and equal to 1.'
}
}
}
err = OptimizerConfig().validate(config_dict)
assert expected_err == err
def test_config_dict_with_wrong_value(self):
"""Test config dict with wrong value."""
config_dict = deepcopy(self._config_dict)
init_list = ['a']
init_str = 'a'
config_dict['target']['group'] = init_str
config_dict['target']['goal'] = init_str
config_dict['tuner']['name'] = init_str
config_dict['parameters']['learning_rate']['bounds'] = init_list
config_dict['parameters']['learning_rate']['choice'] = init_list
config_dict['parameters']['learning_rate']['type'] = init_str
expected_err = {
'parameters': {
'learning_rate': {
'type': "The value(s) should be float number, please config its type as 'float'."
}
},
'target': {
'goal': ["Value should be in ['maximize', 'minimize']. Current value is 'a'."],
'group': ["Value should be in ['system_defined', 'metric']. Current value is 'a'."]
},
'tuner': {
'name': ['Must be one of: gp.']
}
}
err = OptimizerConfig().validate(config_dict)
assert expected_err == err
def test_config_dict_with_wrong_type(self):
"""Test config dict with wrong type."""
config_dict = deepcopy(self._config_dict)
init_list = ['a']
init_str = 'a'
config_dict['command'] = init_list
config_dict['summary_base_dir'] = init_list
config_dict['target']['name'] = init_list
config_dict['target']['goal'] = init_list
config_dict['parameters']['learning_rate']['bounds'] = init_str
config_dict['parameters']['learning_rate']['choice'] = init_str
config_dict['parameters']['learning_rate']['type'] = init_list
expected_err = {
'command': ['Value should be a string.'],
'parameters': {
'learning_rate': {
'type': "The value(s) should be float number, please config its type as 'float'."
}
},
'summary_base_dir': ['Value should be a string.'],
'target': {
'goal': ['Value should be a string.'],
'name': ['Value should be a string.']
}
}
err = OptimizerConfig().validate(config_dict)
assert expected_err == err
def test_batch_size_and_epoch(self, param_name):
"""Test parameters combination."""
config_dict = deepcopy(self._config_dict)
config_dict['parameters'] = {
param_name: {'choice': [-1, 1]}
}
expected_err = {
'parameters': {
param_name: {
'choice': 'The value(s) should be positive number.'
}
}
}
err = OptimizerConfig().validate(config_dict)
assert expected_err == err
expected_err['parameters'][param_name]['choice'] = 'The value(s) should be integer.'
config_dict['parameters'][param_name]['choice'] = [1, 'hello']
err = OptimizerConfig().validate(config_dict)
assert expected_err == err
# test bool
expected_err['parameters'][param_name]['choice'] = 'The value(s) should be integer.'
config_dict['parameters'][param_name]['choice'] = [1, True]
err = OptimizerConfig().validate(config_dict)
assert expected_err == err
config_dict['parameters'][param_name] = {'choice': [0.1, 0.2]}
err = OptimizerConfig().validate(config_dict)
assert expected_err == err
config_dict['parameters'] = {}
config_dict['parameters'][param_name] = {
'bounds': [1, 22],
'type': 'float'
}
expected_err = {
'parameters': {
param_name: {
'type': "The value(s) should be integer, please config its type as 'int'."
}
}
}
err = OptimizerConfig().validate(config_dict)
assert expected_err == err
def test_learning_rate_type(self):
"""Test learning rate with wrong type."""
config_dict = deepcopy(self._config_dict)
config_dict['parameters']['learning_rate']['type'] = 'int'
expected_err = {
'parameters': {
'learning_rate': {
'type': "The value(s) should be float number, please config its type as 'float'."
}
}
}
err = OptimizerConfig().validate(config_dict)
assert expected_err == err
def test_target_combination(self):
"""Test target combination."""
config_dict = deepcopy(self._config_dict)
config_dict['target']['group'] = TargetGroup.SYSTEM_DEFINED.value
config_dict['target']['name'] = 'a'
expected_err = {
'target': {
'group': "This target is not system defined. Current group is 'system_defined'."
}
}
err = OptimizerConfig().validate(config_dict)
assert expected_err == err
def test_parameters_combination2(self):
"""Test parameters combination."""
config_dict = deepcopy(self._config_dict)
config_dict['parameters']['decay_step']['bounds'] = [1, 40]
expected_err = {
'parameters': {
'decay_step': {
'_schema': ["Only one of ['bounds', 'choice'] should be specified."]
}
}
}
err = OptimizerConfig().validate(config_dict)
assert expected_err == err
def test_parameters_combination1(self):
"""Test parameters combination."""
config_dict = deepcopy(self._config_dict)
config_dict['parameters']['decay_step']['source'] = HyperParamSource.SYSTEM_DEFINED.value
expected_err = {
'parameters': {
'decay_step': {
'source': "This param is not system defined. Current source is 'system_defined'."
}
}
}
err = OptimizerConfig().validate(config_dict)
assert expected_err == err
def _validate_config_schema(self, config_info):
error = OptimizerConfig().validate(config_info)
if error:
err_msg = get_nested_message(error)
raise ConfigParamError(err_msg)