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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 transformer(self, instance_count, instance_type, strategy=None, assemble_with=None, output_path=None, output_kms_key=None, accept=None, env=None, max_concurrent_transforms=None, max_payload=None, tags=None, volume_kms_key=None):
 """Return a ``Transformer`` that uses this Model. Args: instance_count (int):
 Number of EC2 instances to use. instance_type (str):
 Type of EC2 instance to use, for example, 'ml.c4.xlarge'. strategy (str):
 The strategy used to decide how to batch records in a single request (default: None). Valid values: 'MULTI_RECORD' and 'SINGLE_RECORD'. assemble_with (str):
 How the output is assembled (default: None). Valid values: 'Line' or 'None'. output_path (str):
 S3 location for saving the transform result. If not specified, results are stored to a default bucket. output_kms_key (str):
 Optional. KMS key ID for encrypting the transform output (default: None). accept (str):
 The content type accepted by the endpoint deployed during the transform job. env (dict):
 Environment variables to be set for use during the transform job (default: None). 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. tags (list[dict]):
 List of tags for labeling a transform job. If none specified, then the tags used for the training job are used for the transform job. volume_kms_key (str):
 Optional. KMS key ID for encrypting the volume attached to the ML compute instance (default: None). """

        self._create_sagemaker_model(instance_type)
        if self.enable_network_isolation():
            env = None

        return Transformer(self.name, instance_count, instance_type, strategy=strategy, assemble_with=assemble_with,
                           output_path=output_path, output_kms_key=output_kms_key, accept=accept,
                           max_concurrent_transforms=max_concurrent_transforms, max_payload=max_payload,
                           env=env, tags=tags, base_transform_job_name=self.name,
                           volume_kms_key=volume_kms_key, sagemaker_session=self.sagemaker_session)