docstr: Compute the p-value resulting from a permutation test using the maximum mean discrepancy
  as a distance measure between the reference data and the data to be tested.
  
  Parameters
  ----------
  x
      Batch of instances.
  
  Returns
  -------
  p-value obtained from the permutation test, the MMD^2 between the reference and test set,         and the MMD^2 threshold above which drift is flagged.
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code: def score(
      self, x: Union[np.ndarray, list]
  ) -> Tuple[float, float, float]:
      """
          Compute the p-value resulting from a permutation test using the maximum mean discrepancy
          as a distance measure between the reference data and the data to be tested.
  
          Parameters
          ----------
          x
              Batch of instances.
  
          Returns
          -------
          p-value obtained from the permutation test, the MMD^2 between the reference and test set, \
          and the MMD^2 threshold above which drift is flagged.
          """
      return self._detector.score(x)
  
file_path: alibi-detect/alibi_detect/cd/mmd.py
imports: import logging
  import numpy
  from typing import Callable, Dict, Optional, Union, Tuple
  from alibi_detect.utils.frameworks import has_pytorch, has_tensorflow, has_keops, BackendValidator, Framework
  from alibi_detect.utils.warnings import deprecated_alias
  from alibi_detect.base import DriftConfigMixin
  from alibi_detect.utils._types import TorchDeviceType
label_desc: Use image node_id 3 for calling the MMDDrift obj's underlying member method code with example usage: obj.score(x) and returns: self