class_docstr: Apply an arbitrary fixed quantum channel.
  
  Kraus matrices that represent the fixed channel are provided
  as a list of NumPy arrays.
  
  **Details:**
  
  * Number of wires: Any (the operation can act on any number of wires)
  * Number of parameters: 1
  * Gradient recipe: None
  
  Args:
      K_list (list[array[complex]]): list of Kraus matrices
      wires (Union[Wires, Sequence[int], or int]): the wire(s) the operation acts on
      id (str or None): String representing the operation (optional)
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docstr: Kraus matrices representing the QubitChannel channel.
  
  Args:
      *K_list (list[array[complex]]): list of Kraus matrices
  
  Returns:
      list (array): list of Kraus matrices
  
  **Example**
  
  >>> K_list = qml.PhaseFlip(0.5, wires=0).kraus_matrices()
  >>> res = qml.QubitChannel.compute_kraus_matrices(K_list)
  >>> all(np.allclose(r, k) for r, k  in zip(res, K_list))
  True
code: def compute_kraus_matrices(
      *kraus_matrices,
  ):  # pylint:disable=arguments-differ
      """Kraus matrices representing the QubitChannel channel.
  
      Args:
          *K_list (list[array[complex]]): list of Kraus matrices
  
      Returns:
          list (array): list of Kraus matrices
  
      **Example**
  
      >>> K_list = qml.PhaseFlip(0.5, wires=0).kraus_matrices()
      >>> res = qml.QubitChannel.compute_kraus_matrices(K_list)
      >>> all(np.allclose(r, k) for r, k  in zip(res, K_list))
      True
      """
      return list(kraus_matrices)
  
imports: import warnings
  import pennylane.math
  from pennylane.operation import AnyWires, Channel
label_desc: Use image node_id 3 for calling the QubitChannel obj's underlying member method code with example usage: obj.compute_kraus_matrices() and returns: list