code: def full_suite(
      n_samples: Optional[int] = 5000,
      image_properties: List[Dict[str, Any]] = None,
      label_properties: List[Dict[str, Any]] = None,
      prediction_properties: List[Dict[str, Any]] = None,
      scorers: Union[Dict[str, Union[Callable, str]], List[Any]] = None,
      area_range: Tuple[float, float] = (32**2, 96**2),
      **kwargs,
  ) -> Suite:
      """Create a suite that includes many of the implemented checks, for a quick overview of your model and data.
  
      Parameters
      ----------
      n_samples : Optional[int] , default : 5000
          Number of samples to use for the checks in the suite. If None, all samples will be used.
      image_properties : List[Dict[str, Any]], default: None
          List of properties. Replaces the default deepchecks properties.
          Each property is a dictionary with keys ``'name'`` (str), ``method`` (Callable) and ``'output_type'`` (str),
          representing attributes of said method. 'output_type' must be one of:
  
          - ``'numerical'`` - for continuous ordinal outputs.
          - ``'categorical'`` - for discrete, non-ordinal outputs. These can still be numbers,
            but these numbers do not have inherent value.
  
          For more on image / label properties, see the guide about :ref:`vision__properties_guide`.
      label_properties : List[Dict[str, Any]], default: None
          List of properties. Replaces the default deepchecks properties.
          Each property is a dictionary with keys ``'name'`` (str), ``method`` (Callable) and ``'output_type'`` (str),
          representing attributes of said method. 'output_type' must be one of:
  
          - ``'numerical'`` - for continuous ordinal outputs.
          - ``'categorical'`` - for discrete, non-ordinal outputs. These can still be numbers,
            but these numbers do not have inherent value.
          - ``'class_id'`` - for properties that return the class_id. This is used because these
            properties are later matched with the ``VisionData.label_map``, if one was given.
  
          For more on image / label properties, see the guide about :ref:`vision__properties_guide`.
  
      scorers: Union[Dict[str, Union[Callable, str]], List[Any]], default: None
          Scorers to override the default scorers (metrics), find more about the supported formats at
          https://docs.deepchecks.com/stable/user-guide/general/metrics_guide.html
      area_range: tuple, default: (32**2, 96**2)
          Slices for small/medium/large buckets. (For object detection tasks only)
      image_properties : List[Dict[str, Any]], default: None
          List of properties. Replaces the default deepchecks properties.
          Each property is a dictionary with keys ``'name'`` (str), ``method`` (Callable) and ``'output_type'`` (str),
          representing attributes of said method. 'output_type' must be one of:
  
          - ``'numerical'`` - for continuous ordinal outputs.
          - ``'categorical'`` - for discrete, non-ordinal outputs. These can still be numbers,
            but these numbers do not have inherent value.
  
          For more on image / label properties, see the guide about :ref:`vision__properties_guide`.
      prediction_properties : List[Dict[str, Any]], default: None
          List of properties. Replaces the default deepchecks properties.
          Each property is a dictionary with keys ``'name'`` (str), ``method`` (Callable) and ``'output_type'`` (str),
          representing attributes of said method. 'output_type' must be one of:
  
          - ``'numerical'`` - for continuous ordinal outputs.
          - ``'categorical'`` - for discrete, non-ordinal outputs. These can still be numbers,
            but these numbers do not have inherent value.
          - ``'class_id'`` - for properties that return the class_id. This is used because these
            properties are later matched with the ``VisionData.label_map``, if one was given.
  
          For more on image / label properties, see the guide about :ref:`vision__properties_guide`.
      Returns
      -------
      Suite
          A suite that includes integrity checks.
      """
      args = locals()
      args.pop("kwargs")
      non_none_args = {k: v for k, v in args.items() if v is not None}
      kwargs = {**non_none_args, **kwargs}
      return Suite(
          "Full Suite",
          model_evaluation(**kwargs),
          train_test_validation(**kwargs),
          data_integrity(**kwargs),
      )
  
imports: from typing import Any, Callable, Dict, List, Optional, Tuple, Union
  from deepchecks.vision import Suite
  from deepchecks.vision.checks import ClassPerformance, ConfusionMatrixReport, HeatmapComparison, ImageDatasetDrift, ImagePropertyDrift, ImagePropertyOutliers, LabelDrift, LabelPropertyOutliers, MeanAveragePrecisionReport, MeanAverageRecallReport, NewLabels, PredictionDrift, PropertyLabelCorrelation, PropertyLabelCorrelationChange, SimpleModelComparison, WeakSegmentsPerformance
label_desc: Use image node_id 4 for calling a global function with example usage: full_suite(n_samples, image_properties, label_properties, prediction_properties, scorers, area_range) and returns: Suite