import json from abc import ABCMeta, abstractmethod from moto.sts.models import ACCOUNT_ID class TestConfig(metaclass=ABCMeta): """Provides the interface to use for creating test configurations. This class will provide the interface for what information will be needed for the SageMaker CloudFormation tests. Ultimately, this will improve the readability of the tests in `test_sagemaker_cloudformation.py` because it will reduce the amount of information we pass through the `pytest.mark.parametrize` decorator. """ @property @abstractmethod def resource_name(self): pass @property @abstractmethod def describe_function_name(self): pass @property @abstractmethod def name_parameter(self): pass @property @abstractmethod def arn_parameter(self): pass @abstractmethod def get_cloudformation_template(self, include_outputs=True, **kwargs): pass def run_setup_procedure(self, sagemaker_client): """Provides a method to set up resources with a SageMaker client. Note: This procedure should be called while within a `mock_sagemaker` context so that no actual resources are created with the sagemaker_client. """ pass class NotebookInstanceTestConfig(TestConfig): """Test configuration for SageMaker Notebook Instances.""" @property def resource_name(self): return "TestNotebook" @property def describe_function_name(self): return "describe_notebook_instance" @property def name_parameter(self): return "NotebookInstanceName" @property def arn_parameter(self): return "NotebookInstanceArn" def get_cloudformation_template(self, include_outputs=True, **kwargs): instance_type = kwargs.get("instance_type", "ml.c4.xlarge") role_arn = kwargs.get( "role_arn", "arn:aws:iam::{}:role/FakeRole".format(ACCOUNT_ID) ) template = { "AWSTemplateFormatVersion": "2010-09-09", "Resources": { self.resource_name: { "Type": "AWS::SageMaker::NotebookInstance", "Properties": {"InstanceType": instance_type, "RoleArn": role_arn}, }, }, } if include_outputs: template["Outputs"] = { "Arn": {"Value": {"Ref": self.resource_name}}, "Name": { "Value": { "Fn::GetAtt": [self.resource_name, "NotebookInstanceName"] } }, } return json.dumps(template) class NotebookInstanceLifecycleConfigTestConfig(TestConfig): """Test configuration for SageMaker Notebook Instance Lifecycle Configs.""" @property def resource_name(self): return "TestNotebookLifecycleConfig" @property def describe_function_name(self): return "describe_notebook_instance_lifecycle_config" @property def name_parameter(self): return "NotebookInstanceLifecycleConfigName" @property def arn_parameter(self): return "NotebookInstanceLifecycleConfigArn" def get_cloudformation_template(self, include_outputs=True, **kwargs): on_create = kwargs.get("on_create") on_start = kwargs.get("on_start") template = { "AWSTemplateFormatVersion": "2010-09-09", "Resources": { self.resource_name: { "Type": "AWS::SageMaker::NotebookInstanceLifecycleConfig", "Properties": {}, }, }, } if on_create is not None: template["Resources"][self.resource_name]["Properties"]["OnCreate"] = [ {"Content": on_create} ] if on_start is not None: template["Resources"][self.resource_name]["Properties"]["OnStart"] = [ {"Content": on_start} ] if include_outputs: template["Outputs"] = { "Arn": {"Value": {"Ref": self.resource_name}}, "Name": { "Value": { "Fn::GetAtt": [ self.resource_name, "NotebookInstanceLifecycleConfigName", ] } }, } return json.dumps(template) class ModelTestConfig(TestConfig): """Test configuration for SageMaker Models.""" @property def resource_name(self): return "TestModel" @property def describe_function_name(self): return "describe_model" @property def name_parameter(self): return "ModelName" @property def arn_parameter(self): return "ModelArn" def get_cloudformation_template(self, include_outputs=True, **kwargs): execution_role_arn = kwargs.get( "execution_role_arn", "arn:aws:iam::{}:role/FakeRole".format(ACCOUNT_ID) ) image = kwargs.get( "image", "404615174143.dkr.ecr.us-east-2.amazonaws.com/linear-learner:1" ) template = { "AWSTemplateFormatVersion": "2010-09-09", "Resources": { self.resource_name: { "Type": "AWS::SageMaker::Model", "Properties": { "ExecutionRoleArn": execution_role_arn, "PrimaryContainer": {"Image": image}, }, }, }, } if include_outputs: template["Outputs"] = { "Arn": {"Value": {"Ref": self.resource_name}}, "Name": {"Value": {"Fn::GetAtt": [self.resource_name, "ModelName"]}}, } return json.dumps(template) class EndpointConfigTestConfig(TestConfig): """Test configuration for SageMaker Endpoint Configs.""" @property def resource_name(self): return "TestEndpointConfig" @property def describe_function_name(self): return "describe_endpoint_config" @property def name_parameter(self): return "EndpointConfigName" @property def arn_parameter(self): return "EndpointConfigArn" def get_cloudformation_template(self, include_outputs=True, **kwargs): num_production_variants = kwargs.get("num_production_variants", 1) production_variants = [ { "InitialInstanceCount": 1, "InitialVariantWeight": 1, "InstanceType": "ml.c4.xlarge", "ModelName": self.resource_name, "VariantName": "variant-name-{}".format(i), } for i in range(num_production_variants) ] template = { "AWSTemplateFormatVersion": "2010-09-09", "Resources": { self.resource_name: { "Type": "AWS::SageMaker::EndpointConfig", "Properties": {"ProductionVariants": production_variants}, }, }, } if include_outputs: template["Outputs"] = { "Arn": {"Value": {"Ref": self.resource_name}}, "Name": { "Value": {"Fn::GetAtt": [self.resource_name, "EndpointConfigName"]} }, } return json.dumps(template) def run_setup_procedure(self, sagemaker_client): """Adds Model that can be referenced in the CloudFormation template.""" sagemaker_client.create_model( ModelName=self.resource_name, ExecutionRoleArn="arn:aws:iam::{}:role/FakeRole".format(ACCOUNT_ID), PrimaryContainer={ "Image": "404615174143.dkr.ecr.us-east-2.amazonaws.com/linear-learner:1", }, ) class EndpointTestConfig(TestConfig): """Test configuration for SageMaker Endpoints.""" @property def resource_name(self): return "TestEndpoint" @property def describe_function_name(self): return "describe_endpoint" @property def name_parameter(self): return "EndpointName" @property def arn_parameter(self): return "EndpointArn" def get_cloudformation_template(self, include_outputs=True, **kwargs): endpoint_config_name = kwargs.get("endpoint_config_name", self.resource_name) template = { "AWSTemplateFormatVersion": "2010-09-09", "Resources": { self.resource_name: { "Type": "AWS::SageMaker::Endpoint", "Properties": {"EndpointConfigName": endpoint_config_name}, }, }, } if include_outputs: template["Outputs"] = { "Arn": {"Value": {"Ref": self.resource_name}}, "Name": {"Value": {"Fn::GetAtt": [self.resource_name, "EndpointName"]}}, } return json.dumps(template) def run_setup_procedure(self, sagemaker_client): """Adds Model and Endpoint Config that can be referenced in the CloudFormation template.""" sagemaker_client.create_model( ModelName=self.resource_name, ExecutionRoleArn="arn:aws:iam::{}:role/FakeRole".format(ACCOUNT_ID), PrimaryContainer={ "Image": "404615174143.dkr.ecr.us-east-2.amazonaws.com/linear-learner:1", }, ) sagemaker_client.create_endpoint_config( EndpointConfigName=self.resource_name, ProductionVariants=[ { "InitialInstanceCount": 1, "InitialVariantWeight": 1, "InstanceType": "ml.c4.xlarge", "ModelName": self.resource_name, "VariantName": "variant-name-1", }, ], )