class_docstr: Measure model average inference time (in seconds) per sample.
  
  Parameters
  ----------
  n_samples : int , default: 1_000
      number of samples to use for this check.
  random_state : int, default: 42
      random seed for all check internals.
code: def __init__(
      self, n_samples: int = 1_000, random_state: int = 42, **kwargs
  ):
      super().__init__(**kwargs)
      self.n_samples = n_samples
      self.random_state = random_state
      if n_samples == 0 or n_samples < 0:
          raise DeepchecksValueError("n_samples cannot be le than 0!")
  
file_path: deepchecks/deepchecks/tabular/checks/model_evaluation/model_inference_time.py
imports: import timeit
  import typing
  from deepchecks.core import CheckResult, ConditionResult
  from deepchecks.core.condition import ConditionCategory
  from deepchecks.core.errors import DeepchecksValueError
  from deepchecks.tabular import Context, SingleDatasetCheck
  from deepchecks.utils.strings import format_number
label_desc: Use image node_id 1 to create a new ModelInferenceTime object from inherited base classes: SingleDatasetCheck with example: obj = ModelInferenceTime(n_samples, random_state)