def test_attach_wrong_framework(sagemaker_session): rjd = { 'AlgorithmSpecification': { 'TrainingInputMode': 'File', 'TrainingImage': '1.dkr.ecr.us-west-2.amazonaws.com/sagemaker-tensorflow-py2-cpu:1.0.4'}, 'HyperParameters': { 'sagemaker_submit_directory': '"s3://some/sourcedir.tar.gz"', 'checkpoint_path': '"s3://other/1508872349"', 'sagemaker_program': '"iris-dnn-classifier.py"', 'sagemaker_enable_cloudwatch_metrics': 'false', 'sagemaker_container_log_level': '"logging.INFO"', 'training_steps': '100', 'sagemaker_region': '"us-west-2"'}, 'RoleArn': 'arn:aws:iam::366:role/SageMakerRole', 'ResourceConfig': { 'VolumeSizeInGB': 30, 'InstanceCount': 1, 'InstanceType': 'ml.c4.xlarge'}, 'StoppingCondition': {'MaxRuntimeInSeconds': 24 * 60 * 60}, 'TrainingJobName': 'neo', 'TrainingJobStatus': 'Completed', 'OutputDataConfig': {'KmsKeyId': '', 'S3OutputPath': 's3://place/output/neo'}, 'TrainingJobOutput': {'S3TrainingJobOutput': 's3://here/output.tar.gz'}} sagemaker_session.sagemaker_client.describe_training_job = Mock(name='describe_training_job', return_value=rjd) with pytest.raises(ValueError) as error: MXNet.attach(training_job_name='neo', sagemaker_session=sagemaker_session) assert "didn't use image for requested framework" in str(error)
def test_attach_wrong_framework(sagemaker_session): rjd = { "AlgorithmSpecification": { "TrainingInputMode": "File", "TrainingImage": "1.dkr.ecr.us-west-2.amazonaws.com/sagemaker-tensorflow-py2-cpu:1.0.4", }, "HyperParameters": { "sagemaker_submit_directory": '"s3://some/sourcedir.tar.gz"', "checkpoint_path": '"s3://other/1508872349"', "sagemaker_program": '"iris-dnn-classifier.py"', "sagemaker_container_log_level": '"logging.INFO"', "training_steps": "100", "sagemaker_region": '"us-west-2"', }, "RoleArn": "arn:aws:iam::366:role/SageMakerRole", "ResourceConfig": { "VolumeSizeInGB": 30, "InstanceCount": 1, "InstanceType": "ml.c4.xlarge", }, "StoppingCondition": {"MaxRuntimeInSeconds": 24 * 60 * 60}, "TrainingJobName": "neo", "TrainingJobStatus": "Completed", "TrainingJobArn": "arn:aws:sagemaker:us-west-2:336:training-job/neo", "OutputDataConfig": {"KmsKeyId": "", "S3OutputPath": "s3://place/output/neo"}, "TrainingJobOutput": {"S3TrainingJobOutput": "s3://here/output.tar.gz"}, } sagemaker_session.sagemaker_client.describe_training_job = Mock( name="describe_training_job", return_value=rjd ) with pytest.raises(ValueError) as error: MXNet.attach(training_job_name="neo", sagemaker_session=sagemaker_session) assert "didn't use image for requested framework" in str(error)
def test_attach_wrong_framework(sagemaker_session): rjd = { 'AlgorithmSpecification': { 'TrainingInputMode': 'File', 'TrainingImage': '1.dkr.ecr.us-west-2.amazonaws.com/sagemaker-tensorflow-py2-cpu:1.0.4'}, 'HyperParameters': { 'sagemaker_submit_directory': '"s3://some/sourcedir.tar.gz"', 'checkpoint_path': '"s3://other/1508872349"', 'sagemaker_program': '"iris-dnn-classifier.py"', 'sagemaker_enable_cloudwatch_metrics': 'false', 'sagemaker_container_log_level': '"logging.INFO"', 'training_steps': '100', 'sagemaker_region': '"us-west-2"'}, 'RoleArn': 'arn:aws:iam::366:role/SageMakerRole', 'ResourceConfig': { 'VolumeSizeInGB': 30, 'InstanceCount': 1, 'InstanceType': 'ml.c4.xlarge'}, 'StoppingCondition': {'MaxRuntimeInSeconds': 24 * 60 * 60}, 'TrainingJobName': 'neo', 'TrainingJobStatus': 'Completed', 'TrainingJobArn': 'arn:aws:sagemaker:us-west-2:336:training-job/neo', 'OutputDataConfig': {'KmsKeyId': '', 'S3OutputPath': 's3://place/output/neo'}, 'TrainingJobOutput': {'S3TrainingJobOutput': 's3://here/output.tar.gz'}} sagemaker_session.sagemaker_client.describe_training_job = Mock(name='describe_training_job', return_value=rjd) with pytest.raises(ValueError) as error: MXNet.attach(training_job_name='neo', sagemaker_session=sagemaker_session) assert "didn't use image for requested framework" in str(error)
def test_attach_custom_image(sagemaker_session): training_image = "ubuntu:latest" returned_job_description = { "AlgorithmSpecification": {"TrainingInputMode": "File", "TrainingImage": training_image}, "HyperParameters": { "sagemaker_submit_directory": '"s3://some/sourcedir.tar.gz"', "sagemaker_program": '"iris-dnn-classifier.py"', "sagemaker_s3_uri_training": '"sagemaker-3/integ-test-data/tf_iris"', "sagemaker_container_log_level": '"logging.INFO"', "sagemaker_job_name": '"neo"', "training_steps": "100", "sagemaker_region": '"us-west-2"', }, "RoleArn": "arn:aws:iam::366:role/SageMakerRole", "ResourceConfig": { "VolumeSizeInGB": 30, "InstanceCount": 1, "InstanceType": "ml.c4.xlarge", }, "StoppingCondition": {"MaxRuntimeInSeconds": 24 * 60 * 60}, "TrainingJobName": "neo", "TrainingJobStatus": "Completed", "TrainingJobArn": "arn:aws:sagemaker:us-west-2:336:training-job/neo", "OutputDataConfig": {"KmsKeyId": "", "S3OutputPath": "s3://place/output/neo"}, "TrainingJobOutput": {"S3TrainingJobOutput": "s3://here/output.tar.gz"}, } sagemaker_session.sagemaker_client.describe_training_job = Mock( name="describe_training_job", return_value=returned_job_description ) estimator = MXNet.attach(training_job_name="neo", sagemaker_session=sagemaker_session) assert estimator.image_uri == training_image assert estimator.training_image_uri() == training_image
def test_attach_custom_image(sagemaker_session): training_image = 'ubuntu:latest' returned_job_description = {'AlgorithmSpecification': { 'TrainingInputMode': 'File', 'TrainingImage': training_image}, 'HyperParameters': { 'sagemaker_submit_directory': '"s3://some/sourcedir.tar.gz"', 'sagemaker_program': '"iris-dnn-classifier.py"', 'sagemaker_s3_uri_training': '"sagemaker-3/integ-test-data/tf_iris"', 'sagemaker_enable_cloudwatch_metrics': 'false', 'sagemaker_container_log_level': '"logging.INFO"', 'sagemaker_job_name': '"neo"', 'training_steps': '100', 'sagemaker_region': '"us-west-2"'}, 'RoleArn': 'arn:aws:iam::366:role/SageMakerRole', 'ResourceConfig': { 'VolumeSizeInGB': 30, 'InstanceCount': 1, 'InstanceType': 'ml.c4.xlarge'}, 'StoppingCondition': {'MaxRuntimeInSeconds': 24 * 60 * 60}, 'TrainingJobName': 'neo', 'TrainingJobStatus': 'Completed', 'OutputDataConfig': {'KmsKeyId': '', 'S3OutputPath': 's3://place/output/neo'}, 'TrainingJobOutput': {'S3TrainingJobOutput': 's3://here/output.tar.gz'}} sagemaker_session.sagemaker_client.describe_training_job = Mock(name='describe_training_job', return_value=returned_job_description) estimator = MXNet.attach(training_job_name='neo', sagemaker_session=sagemaker_session) assert estimator.image_name == training_image assert estimator.train_image() == training_image
def test_attach_custom_image(sagemaker_session): training_image = 'ubuntu:latest' returned_job_description = {'AlgorithmSpecification': { 'TrainingInputMode': 'File', 'TrainingImage': training_image}, 'HyperParameters': { 'sagemaker_submit_directory': '"s3://some/sourcedir.tar.gz"', 'sagemaker_program': '"iris-dnn-classifier.py"', 'sagemaker_s3_uri_training': '"sagemaker-3/integ-test-data/tf_iris"', 'sagemaker_enable_cloudwatch_metrics': 'false', 'sagemaker_container_log_level': '"logging.INFO"', 'sagemaker_job_name': '"neo"', 'training_steps': '100', 'sagemaker_region': '"us-west-2"'}, 'RoleArn': 'arn:aws:iam::366:role/SageMakerRole', 'ResourceConfig': { 'VolumeSizeInGB': 30, 'InstanceCount': 1, 'InstanceType': 'ml.c4.xlarge'}, 'StoppingCondition': {'MaxRuntimeInSeconds': 24 * 60 * 60}, 'TrainingJobName': 'neo', 'TrainingJobStatus': 'Completed', 'TrainingJobArn': 'arn:aws:sagemaker:us-west-2:336:training-job/neo', 'OutputDataConfig': {'KmsKeyId': '', 'S3OutputPath': 's3://place/output/neo'}, 'TrainingJobOutput': {'S3TrainingJobOutput': 's3://here/output.tar.gz'}} sagemaker_session.sagemaker_client.describe_training_job = Mock(name='describe_training_job', return_value=returned_job_description) estimator = MXNet.attach(training_job_name='neo', sagemaker_session=sagemaker_session) assert estimator.image_name == training_image assert estimator.train_image() == training_image
def test_attach(sagemaker_session, mxnet_version): training_image = '1.dkr.ecr.us-west-2.amazonaws.com/sagemaker-mxnet-py2-cpu:{}-cpu-py2'.format( mxnet_version) returned_job_description = { 'AlgorithmSpecification': { 'TrainingInputMode': 'File', 'TrainingImage': training_image }, 'HyperParameters': { 'sagemaker_submit_directory': '"s3://some/sourcedir.tar.gz"', 'sagemaker_program': '"iris-dnn-classifier.py"', 'sagemaker_s3_uri_training': '"sagemaker-3/integ-test-data/tf_iris"', 'sagemaker_enable_cloudwatch_metrics': 'false', 'sagemaker_container_log_level': '"logging.INFO"', 'sagemaker_job_name': '"neo"', 'training_steps': '100', 'sagemaker_region': '"us-west-2"' }, 'RoleArn': 'arn:aws:iam::366:role/SageMakerRole', 'ResourceConfig': { 'VolumeSizeInGB': 30, 'InstanceCount': 1, 'InstanceType': 'ml.c4.xlarge' }, 'StoppingCondition': { 'MaxRuntimeInSeconds': 24 * 60 * 60 }, 'TrainingJobName': 'neo', 'TrainingJobStatus': 'Completed', 'TrainingJobArn': 'arn:aws:sagemaker:us-west-2:336:training-job/neo', 'OutputDataConfig': { 'KmsKeyId': '', 'S3OutputPath': 's3://place/output/neo' }, 'TrainingJobOutput': { 'S3TrainingJobOutput': 's3://here/output.tar.gz' } } sagemaker_session.sagemaker_client.describe_training_job = Mock( name='describe_training_job', return_value=returned_job_description) estimator = MXNet.attach(training_job_name='neo', sagemaker_session=sagemaker_session) assert estimator.latest_training_job.job_name == 'neo' assert estimator.py_version == 'py2' assert estimator.framework_version == mxnet_version assert estimator.role == 'arn:aws:iam::366:role/SageMakerRole' assert estimator.train_instance_count == 1 assert estimator.train_max_run == 24 * 60 * 60 assert estimator.input_mode == 'File' assert estimator.base_job_name == 'neo' assert estimator.output_path == 's3://place/output/neo' assert estimator.output_kms_key == '' assert estimator.hyperparameters()['training_steps'] == '100' assert estimator.source_dir == 's3://some/sourcedir.tar.gz' assert estimator.entry_point == 'iris-dnn-classifier.py' assert estimator.tags == LIST_TAGS_RESULT['Tags']
def test_attach(sagemaker_session, mxnet_version): training_image = "1.dkr.ecr.us-west-2.amazonaws.com/sagemaker-mxnet-py2-cpu:{}-cpu-py2".format( mxnet_version) returned_job_description = { "AlgorithmSpecification": { "TrainingInputMode": "File", "TrainingImage": training_image }, "HyperParameters": { "sagemaker_submit_directory": '"s3://some/sourcedir.tar.gz"', "sagemaker_program": '"iris-dnn-classifier.py"', "sagemaker_s3_uri_training": '"sagemaker-3/integ-test-data/tf_iris"', "sagemaker_enable_cloudwatch_metrics": "false", "sagemaker_container_log_level": '"logging.INFO"', "sagemaker_job_name": '"neo"', "training_steps": "100", "sagemaker_region": '"us-west-2"', }, "RoleArn": "arn:aws:iam::366:role/SageMakerRole", "ResourceConfig": { "VolumeSizeInGB": 30, "InstanceCount": 1, "InstanceType": "ml.c4.xlarge", }, "StoppingCondition": { "MaxRuntimeInSeconds": 24 * 60 * 60 }, "TrainingJobName": "neo", "TrainingJobStatus": "Completed", "TrainingJobArn": "arn:aws:sagemaker:us-west-2:336:training-job/neo", "OutputDataConfig": { "KmsKeyId": "", "S3OutputPath": "s3://place/output/neo" }, "TrainingJobOutput": { "S3TrainingJobOutput": "s3://here/output.tar.gz" }, } sagemaker_session.sagemaker_client.describe_training_job = Mock( name="describe_training_job", return_value=returned_job_description) estimator = MXNet.attach(training_job_name="neo", sagemaker_session=sagemaker_session) assert estimator.latest_training_job.job_name == "neo" assert estimator.py_version == "py2" assert estimator.framework_version == mxnet_version assert estimator.role == "arn:aws:iam::366:role/SageMakerRole" assert estimator.train_instance_count == 1 assert estimator.train_max_run == 24 * 60 * 60 assert estimator.input_mode == "File" assert estimator.base_job_name == "neo" assert estimator.output_path == "s3://place/output/neo" assert estimator.output_kms_key == "" assert estimator.hyperparameters()["training_steps"] == "100" assert estimator.source_dir == "s3://some/sourcedir.tar.gz" assert estimator.entry_point == "iris-dnn-classifier.py" assert estimator.tags == LIST_TAGS_RESULT["Tags"]
def test_attach(sagemaker_session, mxnet_version): training_image = '1.dkr.ecr.us-west-2.amazonaws.com/sagemaker-mxnet-py2-cpu:{}-cpu-py2'.format(mxnet_version) returned_job_description = { 'AlgorithmSpecification': { 'TrainingInputMode': 'File', 'TrainingImage': training_image }, 'HyperParameters': { 'sagemaker_submit_directory': '"s3://some/sourcedir.tar.gz"', 'sagemaker_program': '"iris-dnn-classifier.py"', 'sagemaker_s3_uri_training': '"sagemaker-3/integ-test-data/tf_iris"', 'sagemaker_enable_cloudwatch_metrics': 'false', 'sagemaker_container_log_level': '"logging.INFO"', 'sagemaker_job_name': '"neo"', 'training_steps': '100', 'sagemaker_region': '"us-west-2"' }, 'RoleArn': 'arn:aws:iam::366:role/SageMakerRole', 'ResourceConfig': { 'VolumeSizeInGB': 30, 'InstanceCount': 1, 'InstanceType': 'ml.c4.xlarge' }, 'StoppingCondition': {'MaxRuntimeInSeconds': 24 * 60 * 60}, 'TrainingJobName': 'neo', 'TrainingJobStatus': 'Completed', 'OutputDataConfig': { 'KmsKeyId': '', 'S3OutputPath': 's3://place/output/neo' }, 'TrainingJobOutput': {'S3TrainingJobOutput': 's3://here/output.tar.gz'} } sagemaker_session.sagemaker_client.describe_training_job = Mock(name='describe_training_job', return_value=returned_job_description) estimator = MXNet.attach(training_job_name='neo', sagemaker_session=sagemaker_session) assert estimator.latest_training_job.job_name == 'neo' assert estimator.py_version == 'py2' assert estimator.framework_version == mxnet_version assert estimator.role == 'arn:aws:iam::366:role/SageMakerRole' assert estimator.train_instance_count == 1 assert estimator.train_max_run == 24 * 60 * 60 assert estimator.input_mode == 'File' assert estimator.base_job_name == 'neo' assert estimator.output_path == 's3://place/output/neo' assert estimator.output_kms_key == '' assert estimator.hyperparameters()['training_steps'] == '100' assert estimator.source_dir == 's3://some/sourcedir.tar.gz' assert estimator.entry_point == 'iris-dnn-classifier.py'
def test_attach_no_job_name(sagemaker_session): with pytest.raises(ValueError) as error: MXNet.attach(training_job_name=None, sagemaker_session=sagemaker_session) assert "must specify training_job name" in str(error)