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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def transform(self, job_name, model_name, strategy, max_concurrent_transforms, max_payload, env, input_config, output_config, resource_config, tags):
 """Create an Amazon SageMaker transform job. Args: job_name (str):
 Name of the transform job being created. model_name (str):
 Name of the SageMaker model being used for the transform job. strategy (str):
 The strategy used to decide how to batch records in a single request. Possible values are 'MULTI_RECORD' and 'SINGLE_RECORD'. max_concurrent_transforms (int):
 The maximum number of HTTP requests to be made to each individual transform container at one time. max_payload (int):
 Maximum size of the payload in a single HTTP request to the container in MB. env (dict):
 Environment variables to be set for use during the transform job. input_config (dict):
 A dictionary describing the input data (and its location) for the job. output_config (dict):
 A dictionary describing the output location for the job. resource_config (dict):
 A dictionary describing the resources to complete the job. tags (list[dict]):
 List of tags for labeling a training job. For more, see https://docs.aws.amazon.com/sagemaker/latest/dg/API_Tag.html. """

        transform_request = {
            'TransformJobName': job_name,
            'ModelName': model_name,
            'TransformInput': input_config,
            'TransformOutput': output_config,
            'TransformResources': resource_config,
        }

        if strategy is not None:
            transform_request['BatchStrategy'] = strategy

        if max_concurrent_transforms is not None:
            transform_request['MaxConcurrentTransforms'] = max_concurrent_transforms

        if max_payload is not None:
            transform_request['MaxPayloadInMB'] = max_payload

        if env is not None:
            transform_request['Environment'] = env

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

        LOGGER.info('Creating transform job with name: {}'.format(job_name))
        LOGGER.debug('Transform request: {}'.format(json.dumps(transform_request, indent=4)))
        self.sagemaker_client.create_transform_job(**transform_request)