code: def resolve_input_example_and_signature(
      get_input_example,
      infer_model_signature,
      log_input_example,
      log_model_signature,
      logger,
  ):
      """Handles the logic of calling functions to gather the input example and infer the model
      signature.
  
      Args:
          get_input_example: Function which returns an input example, usually sliced from a
              dataset. This function can raise an exception, its message will be
              shown to the user in a warning in the logs.
          infer_model_signature: Function which takes an input example and returns the signature
              of the inputs and outputs of the model. This function can raise
              an exception, its message will be shown to the user in a warning
              in the logs.
          log_input_example: Whether to log errors while collecting the input example, and if it
              succeeds, whether to return the input example to the user. We collect
              it even if this parameter is False because it is needed for inferring
              the model signature.
          log_model_signature: Whether to infer and return the model signature.
          logger: The logger instance used to log warnings to the user during input example
              collection and model signature inference.
  
      Returns:
          A tuple of input_example and signature. Either or both could be None based on the
          values of log_input_example and log_model_signature.
  
      """
  
      input_example = None
      input_example_user_msg = None
      input_example_failure_msg = None
      if log_input_example or log_model_signature:
          try:
              input_example = get_input_example()
          except Exception as e:
              input_example_failure_msg = str(e)
              input_example_user_msg = (
                  "Failed to gather input example: " + str(e)
              )
  
      model_signature = None
      model_signature_user_msg = None
      if log_model_signature:
          try:
              if input_example is None:
                  raise Exception(
                      "could not sample data to infer model signature: "
                      + input_example_failure_msg
                  )
              model_signature = infer_model_signature(input_example)
          except Exception as e:
              model_signature_user_msg = (
                  "Failed to infer model signature: " + str(e)
              )
  
      # disable input_example signature inference in model logging if `log_model_signature`
      # is set to `False` or signature inference in autologging fails
      if (
          model_signature is None
          and input_example is not None
          and (
              not log_model_signature
              or model_signature_user_msg is not None
          )
      ):
          model_signature = False
  
      if log_input_example and input_example_user_msg is not None:
          logger.warning(input_example_user_msg)
      if log_model_signature and model_signature_user_msg is not None:
          logger.warning(model_signature_user_msg)
  
      return (
          input_example if log_input_example else None,
          model_signature,
      )
  
imports: import contextlib
  import inspect
  import logging
  import time
  from typing import List
  import mlflow
  from mlflow.entities import Metric
  from mlflow.tracking.client import MlflowClient
  from mlflow.utils.validation import MAX_METRICS_PER_BATCH
  from mlflow.utils.autologging_utils.client import MlflowAutologgingQueueingClient
  from mlflow.utils.autologging_utils.events import AutologgingEventLogger
  from mlflow.utils.autologging_utils.logging_and_warnings import set_mlflow_events_and_warnings_behavior_globally, set_non_mlflow_warnings_behavior_for_current_thread
  from mlflow.utils.autologging_utils.safety import ExceptionSafeAbstractClass, ExceptionSafeClass, PatchFunction, exception_safe_function_for_class, is_testing, picklable_exception_safe_function, revert_patches, safe_patch, update_wrapper_extended, with_managed_run
  from mlflow.utils.autologging_utils.versioning import FLAVOR_TO_MODULE_NAME_AND_VERSION_INFO_KEY, get_min_max_version_and_pip_release, is_flavor_supported_for_associated_package_versions
label_desc: Use image node_id 3 for calling a global function with example usage: resolve_input_example_and_signature(get_input_example, infer_model_signature, log_input_example, log_model_signature, logger) and returns: unknown,  model_signature