def execute(self, context):
sagemaker = SageMakerHook(
sagemaker_conn_id=self.sagemaker_conn_id,
use_db_config=self.use_db_config,
region_name=self.region_name,
check_interval=self.check_interval,
max_ingestion_time=self.max_ingestion_time
)
if self.model_config:
self.log.info(
"Creating SageMaker Model %s for transform job"
% self.model_config['ModelName']
)
sagemaker.create_model(self.model_config)
self.log.info(
"Creating SageMaker transform Job %s."
% self.transform_job_config['TransformJobName']
)
response = sagemaker.create_transform_job(
self.transform_job_config,
wait_for_completion=self.wait_for_completion)
if not response['ResponseMetadata']['HTTPStatusCode'] \
== 200:
raise AirflowException(
'Sagemaker transform Job creation failed: %s' % response)
else:
return response
def test_training_with_logs(self, mock_describe, mock_client, mock_log_client, mock_check_training):
mock_check_training.return_value = True
mock_describe.side_effect = \
[(LogState.WAIT_IN_PROGRESS, DESCRIBE_TRAINING_INPROGRESS_RETURN, 0),
(LogState.JOB_COMPLETE, DESCRIBE_TRAINING_STOPPING_RETURN, 0),
(LogState.COMPLETE, DESCRIBE_TRAINING_COMPELETED_RETURN, 0)]
mock_session = mock.Mock()
mock_log_session = mock.Mock()
attrs = {'create_training_job.return_value':
test_arn_return,
'describe_training_job.return_value':
DESCRIBE_TRAINING_COMPELETED_RETURN
}
log_attrs = {'describe_log_streams.side_effect':
LIFECYCLE_LOG_STREAMS,
'get_log_events.side_effect':
STREAM_LOG_EVENTS
}
mock_session.configure_mock(**attrs)
mock_log_session.configure_mock(**log_attrs)
mock_client.return_value = mock_session
mock_log_client.return_value = mock_log_session
hook = SageMakerHook(aws_conn_id='sagemaker_test_conn_id_1')
hook.create_training_job(create_training_params, wait_for_completion=True,
print_log=True, check_interval=1)
self.assertEqual(mock_describe.call_count, 3)
self.assertEqual(mock_session.describe_training_job.call_count, 1)
def test_configure_s3_resources(self, mock_load_file, mock_create_bucket):
hook = SageMakerHook()
evaluation_result = {'Image': image, 'Role': role}
hook.configure_s3_resources(test_evaluation_config)
self.assertEqual(test_evaluation_config, evaluation_result)
mock_create_bucket.assert_called_once_with(bucket_name=bucket)
mock_load_file.assert_called_once_with(path, key, bucket)
def test_describe_training_job_with_logs_complete(self, mock_client,
mock_log_client):
mock_session = mock.Mock()
mock_log_session = mock.Mock()
attrs = {
'describe_training_job.return_value':
DESCRIBE_TRAINING_COMPELETED_RETURN
}
log_attrs = {
'describe_log_streams.side_effect': LIFECYCLE_LOG_STREAMS,
'get_log_events.side_effect': STREAM_LOG_EVENTS
}
mock_session.configure_mock(**attrs)
mock_client.return_value = mock_session
mock_log_session.configure_mock(**log_attrs)
mock_log_client.return_value = mock_log_session
hook = SageMakerHook(aws_conn_id='sagemaker_test_conn_id')
response = hook.describe_training_job_with_log(
job_name=job_name,
positions={},
stream_names=[],
instance_count=1,
state=LogState.COMPLETE,
last_description={},
last_describe_job_call=0)
self.assertEqual(response, (LogState.COMPLETE, {}, 0))
def test_training_with_logs(self, mock_describe, mock_client,
mock_log_client, mock_check_training):
mock_check_training.return_value = True
mock_describe.side_effect = \
[(LogState.WAIT_IN_PROGRESS, DESCRIBE_TRAINING_INPROGRESS_RETURN, 0),
(LogState.JOB_COMPLETE, DESCRIBE_TRAINING_STOPPING_RETURN, 0),
(LogState.COMPLETE, DESCRIBE_TRAINING_COMPELETED_RETURN, 0)]
mock_session = mock.Mock()
mock_log_session = mock.Mock()
attrs = {
'create_training_job.return_value':
test_arn_return,
'describe_training_job.return_value':
DESCRIBE_TRAINING_COMPELETED_RETURN
}
log_attrs = {
'describe_log_streams.side_effect': LIFECYCLE_LOG_STREAMS,
'get_log_events.side_effect': STREAM_LOG_EVENTS
}
mock_session.configure_mock(**attrs)
mock_log_session.configure_mock(**log_attrs)
mock_client.return_value = mock_session
mock_log_client.return_value = mock_log_session
hook = SageMakerHook(aws_conn_id='sagemaker_test_conn_id_1')
hook.create_training_job(create_training_params,
wait_for_completion=True,
print_log=True,
check_interval=1)
self.assertEqual(mock_describe.call_count, 3)
self.assertEqual(mock_session.describe_training_job.call_count, 1)
def test_describe_training_job_with_logs_in_progress(self, mock_time, mock_client, mock_log_client):
mock_session = mock.Mock()
mock_log_session = mock.Mock()
attrs = {'describe_training_job.return_value':
DESCRIBE_TRAINING_COMPELETED_RETURN
}
log_attrs = {'describe_log_streams.side_effect':
LIFECYCLE_LOG_STREAMS,
'get_log_events.side_effect':
STREAM_LOG_EVENTS
}
mock_time.return_value = 50
mock_session.configure_mock(**attrs)
mock_client.return_value = mock_session
mock_log_session.configure_mock(**log_attrs)
mock_log_client.return_value = mock_log_session
hook = SageMakerHook(aws_conn_id='sagemaker_test_conn_id')
response = hook.describe_training_job_with_log(job_name=job_name,
positions={},
stream_names=[],
instance_count=1,
state=LogState.WAIT_IN_PROGRESS,
last_description={},
last_describe_job_call=0)
self.assertEqual(response, (LogState.JOB_COMPLETE, {}, 50))
def get_sagemaker_response(self):
sagemaker_hook = SageMakerHook(aws_conn_id=self.aws_conn_id)
if self.print_log:
if not self.log_resource_inited:
self.init_log_resource(sagemaker_hook)
self.state, self.last_description, self.last_describe_job_call = \
sagemaker_hook.describe_training_job_with_log(self.job_name,
self.positions, self.stream_names,
self.instance_count, self.state,
self.last_description,
self.last_describe_job_call)
else:
self.last_description = sagemaker_hook.describe_training_job(
self.job_name)
status = self.state_from_response(self.last_description)
if status not in self.non_terminal_states(
) and status not in self.failed_states():
billable_time = \
(self.last_description['TrainingEndTime'] - self.last_description['TrainingStartTime']) * \
self.last_description['ResourceConfig']['InstanceCount']
self.log.info('Billable seconds: %s',
int(billable_time.total_seconds()) + 1)
return self.last_description
def get_sagemaker_response(self):
sagemaker = SageMakerHook(
aws_conn_id=self.aws_conn_id,
region_name=self.region_name
)
self.log.info('Poking Sagemaker Training Job %s', self.job_name)
return sagemaker.describe_training_job(self.job_name)
def get_sagemaker_response(self):
sagemaker = SageMakerHook(
aws_conn_id=self.aws_conn_id,
region_name=self.region_name
)
self.log.info('Poking Sagemaker Tuning Job %s', self.job_name)
return sagemaker.describe_tuning_job(self.job_name)
def test_check_for_url(self, mock_check_bucket, mock_check_key,
mock_client):
mock_client.return_value = None
hook = SageMakerHook()
mock_check_bucket.side_effect = [False, True, True]
mock_check_key.side_effect = [False, True]
self.assertRaises(AirflowException, hook.check_for_url, data_url)
self.assertRaises(AirflowException, hook.check_for_url, data_url)
self.assertEqual(hook.check_for_url(data_url), True)
def test_create_model(self, mock_client):
mock_session = mock.Mock()
attrs = {'create_model.return_value':
test_arn_return}
mock_session.configure_mock(**attrs)
mock_client.return_value = mock_session
hook = SageMakerHook(aws_conn_id='sagemaker_test_conn_id')
response = hook.create_model(create_model_params)
mock_session.create_model.assert_called_once_with(**create_model_params)
self.assertEqual(response, test_arn_return)
def test_describe_endpoint(self, mock_client):
mock_session = mock.Mock()
attrs = {'describe_endpoint.return_value': 'InProgress'}
mock_session.configure_mock(**attrs)
mock_client.return_value = mock_session
hook = SageMakerHook(aws_conn_id='sagemaker_test_conn_id')
response = hook.describe_endpoint(endpoint_name)
mock_session.describe_endpoint.\
assert_called_once_with(EndpointName=endpoint_name)
self.assertEqual(response, 'InProgress')
def test_create_endpoint_config(self, mock_client):
mock_session = mock.Mock()
attrs = {'create_endpoint_config.return_value': test_arn_return}
mock_session.configure_mock(**attrs)
mock_client.return_value = mock_session
hook = SageMakerHook(aws_conn_id='sagemaker_test_conn_id')
response = hook.create_endpoint_config(create_endpoint_config_params)
mock_session.create_endpoint_config\
.assert_called_once_with(**create_endpoint_config_params)
self.assertEqual(response, test_arn_return)
def test_describe_model(self, mock_client):
mock_session = mock.Mock()
attrs = {'describe_model.return_value': model_name}
mock_session.configure_mock(**attrs)
mock_client.return_value = mock_session
hook = SageMakerHook(aws_conn_id='sagemaker_test_conn_id')
response = hook.describe_model(model_name)
mock_session.describe_model.\
assert_called_once_with(ModelName=model_name)
self.assertEqual(response, model_name)
def test_configure_s3_resources(self, mock_load_file, mock_create_bucket):
hook = SageMakerHook()
evaluation_result = {
'Image': image,
'Role': role
}
hook.configure_s3_resources(test_evaluation_config)
self.assertEqual(test_evaluation_config, evaluation_result)
mock_create_bucket.assert_called_once_with(bucket_name=bucket)
mock_load_file.assert_called_once_with(path, key, bucket)
def test_describe_training_job(self, mock_client):
mock_session = mock.Mock()
attrs = {'describe_training_job.return_value': 'InProgress'}
mock_session.configure_mock(**attrs)
mock_client.return_value = mock_session
hook = SageMakerHook(aws_conn_id='sagemaker_test_conn_id')
response = hook.describe_training_job(job_name)
mock_session.describe_training_job.\
assert_called_once_with(TrainingJobName=job_name)
self.assertEqual(response, 'InProgress')
def test_describe_transform_job(self, mock_client):
mock_session = mock.Mock()
attrs = {'describe_transform_job.return_value': 'InProgress'}
mock_session.configure_mock(**attrs)
mock_client.return_value = mock_session
hook = SageMakerHook(aws_conn_id='sagemaker_test_conn_id')
response = hook.describe_transform_job(job_name)
mock_session.describe_transform_job.\
assert_called_once_with(TransformJobName=job_name)
self.assertEqual(response, 'InProgress')
def test_describe_endpoint_config(self, mock_client):
mock_session = mock.Mock()
attrs = {'describe_endpoint_config.return_value':
config_name}
mock_session.configure_mock(**attrs)
mock_client.return_value = mock_session
hook = SageMakerHook(aws_conn_id='sagemaker_test_conn_id')
response = hook.describe_endpoint_config(config_name)
mock_session.describe_endpoint_config.\
assert_called_once_with(EndpointConfigName=config_name)
self.assertEqual(response, config_name)
def test_describe_model(self, mock_client):
mock_session = mock.Mock()
attrs = {'describe_model.return_value':
model_name}
mock_session.configure_mock(**attrs)
mock_client.return_value = mock_session
hook = SageMakerHook(aws_conn_id='sagemaker_test_conn_id')
response = hook.describe_model(model_name)
mock_session.describe_model.\
assert_called_once_with(ModelName=model_name)
self.assertEqual(response, model_name)
def test_update_endpoint(self, mock_client):
mock_session = mock.Mock()
attrs = {'update_endpoint.return_value': test_arn_return}
mock_session.configure_mock(**attrs)
mock_client.return_value = mock_session
hook = SageMakerHook(aws_conn_id='sagemaker_test_conn_id')
response = hook.update_endpoint(update_endpoint_params,
wait_for_completion=False)
mock_session.update_endpoint\
.assert_called_once_with(**update_endpoint_params)
self.assertEqual(response, test_arn_return)
def test_create_transform_job(self, mock_client, mock_check_url):
mock_check_url.return_value = True
mock_session = mock.Mock()
attrs = {'create_transform_job.return_value': test_arn_return}
mock_session.configure_mock(**attrs)
mock_client.return_value = mock_session
hook = SageMakerHook(aws_conn_id='sagemaker_test_conn_id')
response = hook.create_transform_job(create_transform_params,
wait_for_completion=False)
mock_session.create_transform_job.assert_called_once_with(
**create_transform_params)
self.assertEqual(response, test_arn_return)
def test_create_tuning_job(self, mock_client, mock_check_tuning):
mock_session = mock.Mock()
attrs = {'create_hyper_parameter_tuning_job.return_value':
test_arn_return}
mock_session.configure_mock(**attrs)
mock_client.return_value = mock_session
hook = SageMakerHook(aws_conn_id='sagemaker_test_conn_id')
response = hook.create_tuning_job(create_tuning_params,
wait_for_completion=False)
mock_session.create_hyper_parameter_tuning_job.\
assert_called_once_with(**create_tuning_params)
self.assertEqual(response, test_arn_return)
def test_create_tuning_job(self, mock_client, mock_check_tuning):
mock_session = mock.Mock()
attrs = {
'create_hyper_parameter_tuning_job.return_value': test_arn_return
}
mock_session.configure_mock(**attrs)
mock_client.return_value = mock_session
hook = SageMakerHook(sagemaker_conn_id='sagemaker_test_conn_id')
response = hook.create_tuning_job(create_tuning_params)
mock_session.create_hyper_parameter_tuning_job.\
assert_called_once_with(**create_tuning_params)
self.assertEqual(response, test_arn_return)
def test_update_endpoint(self, mock_client):
mock_session = mock.Mock()
attrs = {'update_endpoint.return_value':
test_arn_return}
mock_session.configure_mock(**attrs)
mock_client.return_value = mock_session
hook = SageMakerHook(aws_conn_id='sagemaker_test_conn_id')
response = hook.update_endpoint(update_endpoint_params,
wait_for_completion=False)
mock_session.update_endpoint\
.assert_called_once_with(**update_endpoint_params)
self.assertEqual(response, test_arn_return)
def test_list_tuning_job(self, mock_client):
mock_session = mock.Mock()
attrs = {'list_hyper_parameter_tuning_job.return_value':
test_list_tuning_job_return}
mock_session.configure_mock(**attrs)
mock_client.return_value = mock_session
hook = SageMakerHook(sagemaker_conn_id='sagemaker_test_conn_id')
response = hook.list_tuning_job(name_contains=job_name,
status_equals='InProgress')
mock_session.list_hyper_parameter_tuning_job. \
assert_called_once_with(NameContains=job_name,
StatusEquals='InProgress')
self.assertEqual(response, test_list_tuning_job_return)
def test_list_training_job(self, mock_client):
mock_session = mock.Mock()
attrs = {
'list_training_jobs.return_value': test_list_training_job_return
}
mock_session.configure_mock(**attrs)
mock_client.return_value = mock_session
hook = SageMakerHook(sagemaker_conn_id='sagemaker_test_conn_id')
response = hook.list_training_job(name_contains=job_name,
status_equals='InProgress')
mock_session.list_training_jobs. \
assert_called_once_with(NameContains=job_name,
StatusEquals='InProgress')
self.assertEqual(response, test_list_training_job_return)
def preprocess_config(self):
self.log.info(
'Preprocessing the config and doing required s3_operations'
)
self.hook = SageMakerHook(aws_conn_id=self.aws_conn_id)
self.hook.configure_s3_resources(self.config)
self.parse_config_integers()
self.expand_role()
self.log.info(
'After preprocessing the config is:\n {}'.format(
json.dumps(self.config, sort_keys=True, indent=4, separators=(',', ': ')))
)
def test_create_training_job_db_config(self, mock_client, mock_check_training):
mock_check_training.return_value = True
mock_session = mock.Mock()
attrs = {'create_training_job.return_value':
test_arn_return}
mock_session.configure_mock(**attrs)
mock_client.return_value = mock_session
hook_use_db_config = SageMakerHook(sagemaker_conn_id='sagemaker_test_conn_id',
use_db_config=True)
response = hook_use_db_config.create_training_job(create_training_params,
wait_for_completion=False)
updated_config = copy.deepcopy(create_training_params)
updated_config.update(db_config)
mock_session.create_training_job.assert_called_once_with(**updated_config)
self.assertEqual(response, test_arn_return)
def test_create_transform_job_db_config(self, mock_client, mock_check_url):
mock_check_url.return_value = True
mock_session = mock.Mock()
attrs = {'create_transform_job.return_value': test_arn_return}
mock_session.configure_mock(**attrs)
mock_client.return_value = mock_session
hook_use_db_config = SageMakerHook(
sagemaker_conn_id='sagemaker_test_conn_id', use_db_config=True)
response = hook_use_db_config.create_transform_job(
create_transform_params, wait_for_completion=False)
updated_config = copy.deepcopy(create_transform_params)
updated_config.update(db_config)
mock_session.create_transform_job.assert_called_once_with(
**updated_config)
self.assertEqual(response, test_arn_return)
def test_check_s3_url(self,
mock_check_prefix,
mock_check_bucket,
mock_check_key,
mock_client):
mock_client.return_value = None
hook = SageMakerHook()
mock_check_bucket.side_effect = [False, True, True, True]
mock_check_key.side_effect = [False, True, False]
mock_check_prefix.side_effect = [False, True, True]
self.assertRaises(AirflowException,
hook.check_s3_url, data_url)
self.assertRaises(AirflowException,
hook.check_s3_url, data_url)
self.assertEqual(hook.check_s3_url(data_url), True)
self.assertEqual(hook.check_s3_url(data_url), True)
def test_training_ends_with_wait_on(self, mock_client, mock_check_training):
mock_check_training.return_value = True
mock_session = mock.Mock()
attrs = {'create_training_job.return_value':
test_arn_return,
'describe_training_job.side_effect':
[DESCRIBE_TRAINING_INPROGRESS_RETURN,
DESCRIBE_TRAINING_STOPPING_RETURN,
DESCRIBE_TRAINING_STOPPED_RETURN,
DESCRIBE_TRAINING_COMPELETED_RETURN]
}
mock_session.configure_mock(**attrs)
mock_client.return_value = mock_session
hook = SageMakerHook(sagemaker_conn_id='sagemaker_test_conn_id_1')
hook.create_training_job(create_training_params, wait_for_completion=True)
self.assertEqual(mock_session.describe_training_job.call_count, 4)
def test_create_tuning_job_db_config(self, mock_client, mock_check_tuning):
mock_check_tuning.return_value = True
mock_session = mock.Mock()
attrs = {
'create_hyper_parameter_tuning_job.return_value': test_arn_return
}
mock_session.configure_mock(**attrs)
mock_client.return_value = mock_session
hook = SageMakerHook(sagemaker_conn_id='sagemaker_test_conn_id',
use_db_config=True)
response = hook.create_tuning_job(create_tuning_params)
updated_config = copy.deepcopy(create_tuning_params)
updated_config.update(db_config)
mock_session.create_hyper_parameter_tuning_job. \
assert_called_once_with(**updated_config)
self.assertEqual(response, test_arn_return)
def test_training_ends_with_wait(self, mock_client, mock_check_training):
mock_check_training.return_value = True
mock_session = mock.Mock()
attrs = {'create_training_job.return_value':
test_arn_return,
'describe_training_job.side_effect':
[DESCRIBE_TRAINING_INPROGRESS_RETURN,
DESCRIBE_TRAINING_STOPPING_RETURN,
DESCRIBE_TRAINING_COMPELETED_RETURN,
DESCRIBE_TRAINING_COMPELETED_RETURN]
}
mock_session.configure_mock(**attrs)
mock_client.return_value = mock_session
hook = SageMakerHook(aws_conn_id='sagemaker_test_conn_id_1')
hook.create_training_job(create_training_params, wait_for_completion=True,
print_log=False, check_interval=1)
self.assertEqual(mock_session.describe_training_job.call_count, 4)
def execute(self, context):
sagemaker = SageMakerHook(sagemaker_conn_id=self.sagemaker_conn_id,
use_db_config=self.use_db_config,
region_name=self.region_name,
check_interval=self.check_interval,
max_ingestion_time=self.max_ingestion_time)
self.log.info("Creating SageMaker Training Job %s." %
self.training_job_config['TrainingJobName'])
response = sagemaker.create_training_job(
self.training_job_config,
wait_for_completion=self.wait_for_completion)
if not response['ResponseMetadata']['HTTPStatusCode'] \
== 200:
raise AirflowException(
'Sagemaker Training Job creation failed: %s' % response)
else:
return response
def get_sagemaker_response(self):
sagemaker_hook = SageMakerHook(aws_conn_id=self.aws_conn_id)
if self.print_log:
if not self.log_resource_inited:
self.init_log_resource(sagemaker_hook)
self.state, self.last_description, self.last_describe_job_call = \
sagemaker_hook.describe_training_job_with_log(self.job_name,
self.positions, self.stream_names,
self.instance_count, self.state,
self.last_description,
self.last_describe_job_call)
else:
self.last_description = sagemaker_hook.describe_training_job(self.job_name)
status = self.state_from_response(self.last_description)
if status not in self.non_terminal_states() and status not in self.failed_states():
billable_time = \
(self.last_description['TrainingEndTime'] - self.last_description['TrainingStartTime']) * \
self.last_description['ResourceConfig']['InstanceCount']
self.log.info('Billable seconds: %s', int(billable_time.total_seconds()) + 1)
return self.last_description
def preprocess_config(self):
self.log.info(
'Preprocessing the config and doing required s3_operations'
)
self.hook = SageMakerHook(aws_conn_id=self.aws_conn_id)
self.hook.configure_s3_resources(self.config)
self.parse_config_integers()
self.expand_role()
self.log.info(
'After preprocessing the config is:\n {}'.format(
json.dumps(self.config, sort_keys=True, indent=4, separators=(',', ': ')))
)
def execute(self, context):
sagemaker = SageMakerHook(sagemaker_conn_id=self.sagemaker_conn_id,
region_name=self.region_name,
use_db_config=self.use_db_config,
check_interval=self.check_interval,
max_ingestion_time=self.max_ingestion_time
)
self.log.info(
"Creating SageMaker Hyper Parameter Tunning Job %s"
% self.tuning_job_config['HyperParameterTuningJobName']
)
response = sagemaker.create_tuning_job(
self.tuning_job_config,
wait_for_completion=self.wait_for_completion
)
if not response['ResponseMetadata']['HTTPStatusCode'] \
== 200:
raise AirflowException(
"Sagemaker Tuning Job creation failed: %s" % response)
else:
return response
def test_check_valid_training(self, mock_check_url, mock_client):
mock_client.return_value = None
hook = SageMakerHook()
hook.check_training_config(create_training_params)
mock_check_url.assert_called_once_with(data_url)
# InputDataConfig is optional, verify if check succeeds without InputDataConfig
create_training_params_no_inputdataconfig = create_training_params.copy()
create_training_params_no_inputdataconfig.pop("InputDataConfig")
hook.check_training_config(create_training_params_no_inputdataconfig)
def test_training_throws_error_when_failed_with_wait_on(
self, mock_client, mock_check_training):
mock_check_training.return_value = True
mock_session = mock.Mock()
attrs = {
'create_training_job.return_value':
test_arn_return,
'describe_training_job.side_effect': [
DESCRIBE_TRAINING_INPROGRESS_RETURN,
DESCRIBE_TRAINING_STOPPING_RETURN,
DESCRIBE_TRAINING_STOPPED_RETURN,
DESCRIBE_TRAINING_FAILED_RETURN
]
}
mock_session.configure_mock(**attrs)
mock_client.return_value = mock_session
hook = SageMakerHook(sagemaker_conn_id='sagemaker_test_conn_id_1')
self.assertRaises(AirflowException,
hook.create_training_job,
create_training_params,
wait_for_completion=True)
self.assertEqual(mock_session.describe_training_job.call_count, 4)
def get_sagemaker_response(self):
sagemaker = SageMakerHook(aws_conn_id=self.aws_conn_id)
self.log.info('Poking Sagemaker Transform Job %s', self.job_name)
return sagemaker.describe_transform_job(self.job_name)
def get_sagemaker_response(self):
sagemaker = SageMakerHook(aws_conn_id=self.aws_conn_id)
self.log.info('Poking Sagemaker Endpoint %s', self.endpoint_name)
return sagemaker.describe_endpoint(self.endpoint_name)
def get_sagemaker_response(self):
sagemaker = SageMakerHook(aws_conn_id=self.aws_conn_id)
self.log.info('Poking Sagemaker Endpoint %s', self.endpoint_name)
return sagemaker.describe_endpoint(self.endpoint_name)
def test_multi_stream_iter(self, mock_log_stream):
event = {'timestamp': 1}
mock_log_stream.side_effect = [iter([event]), iter([]), None]
hook = SageMakerHook()
event_iter = hook.multi_stream_iter('log', [None, None, None])
self.assertEqual(next(event_iter), (0, event))
class SageMakerBaseOperator(BaseOperator):
"""
This is the base operator for all SageMaker operators.
:param config: The configuration necessary to start a training job (templated)
:type config: dict
:param aws_conn_id: The AWS connection ID to use.
:type aws_conn_id: str
"""
template_fields = ['config']
template_ext = ()
ui_color = '#ededed'
integer_fields = [] # type: Iterable[Iterable[str]]
@apply_defaults
def __init__(self,
config,
aws_conn_id='aws_default',
*args, **kwargs):
super().__init__(*args, **kwargs)
self.aws_conn_id = aws_conn_id
self.config = config
self.hook = None
def parse_integer(self, config, field):
if len(field) == 1:
if isinstance(config, list):
for sub_config in config:
self.parse_integer(sub_config, field)
return
head = field[0]
if head in config:
config[head] = int(config[head])
return
if isinstance(config, list):
for sub_config in config:
self.parse_integer(sub_config, field)
return
head, tail = field[0], field[1:]
if head in config:
self.parse_integer(config[head], tail)
return
def parse_config_integers(self):
# Parse the integer fields of training config to integers
# in case the config is rendered by Jinja and all fields are str
for field in self.integer_fields:
self.parse_integer(self.config, field)
def expand_role(self):
pass
def preprocess_config(self):
self.log.info(
'Preprocessing the config and doing required s3_operations'
)
self.hook = SageMakerHook(aws_conn_id=self.aws_conn_id)
self.hook.configure_s3_resources(self.config)
self.parse_config_integers()
self.expand_role()
self.log.info(
'After preprocessing the config is:\n {}'.format(
json.dumps(self.config, sort_keys=True, indent=4, separators=(',', ': ')))
)
def execute(self, context):
raise NotImplementedError('Please implement execute() in sub class!')
def test_check_valid_tuning(self, mock_check_url, mock_client):
mock_client.return_value = None
hook = SageMakerHook()
hook.check_tuning_config(create_tuning_params)
mock_check_url.assert_called_once_with(data_url)
def get_sagemaker_response(self):
sagemaker = SageMakerHook(aws_conn_id=self.aws_conn_id)
self.log.info('Poking Sagemaker Transform Job %s', self.job_name)
return sagemaker.describe_transform_job(self.job_name)
class SageMakerBaseOperator(BaseOperator):
"""
This is the base operator for all SageMaker operators.
:param config: The configuration necessary to start a training job (templated)
:type config: dict
:param aws_conn_id: The AWS connection ID to use.
:type aws_conn_id: str
"""
template_fields = ['config']
template_ext = ()
ui_color = '#ededed'
integer_fields = []
@apply_defaults
def __init__(self,
config,
aws_conn_id='aws_default',
*args, **kwargs):
super(SageMakerBaseOperator, self).__init__(*args, **kwargs)
self.aws_conn_id = aws_conn_id
self.config = config
self.hook = None
def parse_integer(self, config, field):
if len(field) == 1:
if isinstance(config, list):
for sub_config in config:
self.parse_integer(sub_config, field)
return
head = field[0]
if head in config:
config[head] = int(config[head])
return
if isinstance(config, list):
for sub_config in config:
self.parse_integer(sub_config, field)
return
head, tail = field[0], field[1:]
if head in config:
self.parse_integer(config[head], tail)
return
def parse_config_integers(self):
# Parse the integer fields of training config to integers
# in case the config is rendered by Jinja and all fields are str
for field in self.integer_fields:
self.parse_integer(self.config, field)
def expand_role(self):
pass
def preprocess_config(self):
self.log.info(
'Preprocessing the config and doing required s3_operations'
)
self.hook = SageMakerHook(aws_conn_id=self.aws_conn_id)
self.hook.configure_s3_resources(self.config)
self.parse_config_integers()
self.expand_role()
self.log.info(
'After preprocessing the config is:\n {}'.format(
json.dumps(self.config, sort_keys=True, indent=4, separators=(',', ': ')))
)
def execute(self, context):
raise NotImplementedError('Please implement execute() in sub class!')
def test_multi_stream_iter(self, mock_log_stream):
event = {'timestamp': 1}
mock_log_stream.side_effect = [iter([event]), iter([]), None]
hook = SageMakerHook()
event_iter = hook.multi_stream_iter('log', [None, None, None])
self.assertEqual(next(event_iter), (0, event))
def test_conn(self, mock_get_client_type):
hook = SageMakerHook(aws_conn_id='sagemaker_test_conn_id')
self.assertEqual(hook.aws_conn_id, 'sagemaker_test_conn_id')
def test_check_valid_tuning(self, mock_check_url, mock_client):
mock_client.return_value = None
hook = SageMakerHook()
hook.check_tuning_config(create_tuning_params)
mock_check_url.assert_called_once_with(data_url)
def test_conn(self, mock_get_client):
hook = SageMakerHook(sagemaker_conn_id='sagemaker_test_conn_id',
region_name='us-east-1')
self.assertEqual(hook.sagemaker_conn_id, 'sagemaker_test_conn_id')
mock_get_client.assert_called_once_with('sagemaker',
region_name='us-east-1')