src/sagemaker/model_monitor/model_monitoring.py [2787:2833]:
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        if output_s3_uri is not None:
            normalized_monitoring_output = self._normalize_monitoring_output(
                monitoring_schedule_name, output_s3_uri
            )
            job_output["MonitoringOutputs"] = [normalized_monitoring_output._to_request_dict()]
        if output_kms_key is not None:
            job_output["KmsKeyId"] = output_kms_key

        # cluster config
        if instance_count is not None:
            cluster_config["InstanceCount"] = instance_count
        if instance_type is not None:
            cluster_config["InstanceType"] = instance_type
        if volume_size_in_gb is not None:
            cluster_config["VolumeSizeInGB"] = volume_size_in_gb
        if volume_kms_key is not None:
            cluster_config["VolumeKmsKeyId"] = volume_kms_key

        # stop condition
        if max_runtime_in_seconds is not None:
            stop_condition["MaxRuntimeInSeconds"] = max_runtime_in_seconds

        request_dict = {
            "JobDefinitionName": job_definition_name,
            "{}AppSpecification".format(self.monitoring_type()): app_specification,
            "{}JobInput".format(self.monitoring_type()): job_input,
            "{}JobOutputConfig".format(self.monitoring_type()): job_output,
            "JobResources": dict(ClusterConfig=cluster_config),
            "RoleArn": self.sagemaker_session.expand_role(role),
        }

        if baseline_config:
            request_dict["{}BaselineConfig".format(self.monitoring_type())] = baseline_config

        if network_config is not None:
            network_config_dict = network_config._to_request_dict()
            request_dict["NetworkConfig"] = network_config_dict
        elif existing_network_config is not None:
            request_dict["NetworkConfig"] = existing_network_config

        if stop_condition:
            request_dict["StoppingCondition"] = stop_condition

        if tags is not None:
            request_dict["Tags"] = format_tags(tags)

        return request_dict
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src/sagemaker/model_monitor/model_monitoring.py [3565:3611]:
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        if output_s3_uri is not None:
            normalized_monitoring_output = self._normalize_monitoring_output(
                monitoring_schedule_name, output_s3_uri
            )
            job_output["MonitoringOutputs"] = [normalized_monitoring_output._to_request_dict()]
        if output_kms_key is not None:
            job_output["KmsKeyId"] = output_kms_key

        # cluster config
        if instance_count is not None:
            cluster_config["InstanceCount"] = instance_count
        if instance_type is not None:
            cluster_config["InstanceType"] = instance_type
        if volume_size_in_gb is not None:
            cluster_config["VolumeSizeInGB"] = volume_size_in_gb
        if volume_kms_key is not None:
            cluster_config["VolumeKmsKeyId"] = volume_kms_key

        # stop condition
        if max_runtime_in_seconds is not None:
            stop_condition["MaxRuntimeInSeconds"] = max_runtime_in_seconds

        request_dict = {
            "JobDefinitionName": job_definition_name,
            "{}AppSpecification".format(self.monitoring_type()): app_specification,
            "{}JobInput".format(self.monitoring_type()): job_input,
            "{}JobOutputConfig".format(self.monitoring_type()): job_output,
            "JobResources": dict(ClusterConfig=cluster_config),
            "RoleArn": self.sagemaker_session.expand_role(role),
        }

        if baseline_config:
            request_dict["{}BaselineConfig".format(self.monitoring_type())] = baseline_config

        if network_config is not None:
            network_config_dict = network_config._to_request_dict()
            request_dict["NetworkConfig"] = network_config_dict
        elif existing_network_config is not None:
            request_dict["NetworkConfig"] = existing_network_config

        if stop_condition:
            request_dict["StoppingCondition"] = stop_condition

        if tags is not None:
            request_dict["Tags"] = format_tags(tags)

        return request_dict
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