class_docstr: TFX infra validator executor.
class_docstr_tok: ["TFX","infra","validator","executor","."]
code: def _CreateWarmupModel(
      self,
      blessing: types.Artifact,
      model_path: str,
      warmup_requests: List[iv_types.Request],
  ):
      output_model_path = path_utils.stamped_model_path(blessing.uri)
      io_utils.copy_dir(src=model_path, dst=output_model_path)
      io_utils.write_tfrecord_file(
          path_utils.warmup_file_path(output_model_path),
          *[_convert_to_prediction_log(r) for r in warmup_requests],
      )
      blessing.set_int_custom_property(_MODEL_FLAG_KEY, 1)
  
imports: import contextlib
  import functools
  import os
  import signal
  import threading
  import time
  from typing import Any, Dict, List, Optional
  from absl import logging
  from tfx import types
  from tfx.components.infra_validator import error_types
  from tfx.components.infra_validator import request_builder
  from tfx.components.infra_validator import serving_bins
  from tfx.components.infra_validator import types
  from tfx.components.infra_validator.model_server_runners import kubernetes_runner
  from tfx.components.infra_validator.model_server_runners import local_docker_runner
  from tfx.dsl.components.base import base_executor
  from tfx.proto import infra_validator_pb2
  from tfx.types import artifact_utils
  from tfx.types import standard_component_specs
  from tfx.utils import io_utils
  from tfx.utils import path_utils
  from tfx.utils import proto_utils
  from tfx.utils.model_paths import tf_serving_flavor
  from tensorflow_serving.apis import classification_pb2
  from tensorflow_serving.apis import predict_pb2
  from tensorflow_serving.apis import prediction_log_pb2
  from tensorflow_serving.apis import regression_pb2
label_desc: Use image node_id 7 for calling the Executor obj's underlying member method code with example usage: obj._CreateWarmupModel(blessing, model_path, warmup_requests) without return types