class_docstr: Stores info about the input example collection before it is needed.
  
  For example, in xgboost and lightgbm, an InputExampleInfo object is attached to the dataset,
  where its value is read later by the train method.
  
  Exactly one of input_example or error_msg should be populated.
class_docstr_tok: ["Stores","info","about","the","input","example","collection","before","it","is","needed",".","For","example",",","in","xgboost","and","lightgbm",",","an","InputExampleInfo","object","is","attached","to","the","dataset",",","where","its","value","is","read","later","by","the","train","method",".","Exactly","one","of","input_example","or","error_msg","should","be","populated","."]
code: def __init__(self, input_example=None, error_msg=None):
      self.input_example = input_example
      self.error_msg = error_msg
  
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 1 to create a new InputExampleInfo object  with example: obj = InputExampleInfo(input_example, error_msg)