<SYSTEM_TASK:>
Solve the following problem using Python, implementing the functions described below, one line at a time
<END_TASK>
<USER_TASK:>
Description:
 def compile_model(self, input_model_config, output_model_config, role, job_name, stop_condition, tags):
 """Create an Amazon SageMaker Neo compilation job. Args: input_model_config (dict):
 the trained model and the Amazon S3 location where it is stored. output_model_config (dict):
 Identifies the Amazon S3 location where you want Amazon SageMaker Neo to save the results of compilation job role (str):
 An AWS IAM role (either name or full ARN). The Amazon SageMaker Neo compilation jobs use this role to access model artifacts. You must grant sufficient permissions to this role. job_name (str):
 Name of the compilation job being created. stop_condition (dict):
 Defines when compilation job shall finish. Contains entries that can be understood by the service like ``MaxRuntimeInSeconds``. tags (list[dict]):
 List of tags for labeling a compile model job. For more, see https://docs.aws.amazon.com/sagemaker/latest/dg/API_Tag.html. Returns: str: ARN of the compile model job, if it is created. """


        compilation_job_request = {
            'InputConfig': input_model_config,
            'OutputConfig': output_model_config,
            'RoleArn': role,
            'StoppingCondition': stop_condition,
            'CompilationJobName': job_name
        }

        if tags is not None:
            compilation_job_request['Tags'] = tags

        LOGGER.info('Creating compilation-job with name: {}'.format(job_name))
        self.sagemaker_client.create_compilation_job(**compilation_job_request)