class_docstr: Abstract base class for PennyLane devices.
  
  Args:
      wires (int or Iterable[Number, str]]): Number of subsystems represented by the device,
          or iterable that contains unique labels for the subsystems as numbers (i.e., ``[-1, 0, 2]``)
          or strings (``['ancilla', 'q1', 'q2']``). Default 1 if not specified.
      shots (int): Number of circuit evaluations/random samples used to estimate
          expectation values of observables. Defaults to 1000 if not specified.
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docstr: Execute a batch of quantum circuits on the device.
  
  The circuits are represented by tapes, and they are executed one-by-one using the
  device's ``execute`` method. The results are collected in a list.
  
  For plugin developers: This function should be overwritten if the device can efficiently run multiple
  circuits on a backend, for example using parallel and/or asynchronous executions.
  
  Args:
      circuits (list[.tape.QuantumTape]): circuits to execute on the device
  
  Returns:
      list[array[float]]: list of measured value(s)
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code: def batch_execute(self, circuits):
      """Execute a batch of quantum circuits on the device.
  
      The circuits are represented by tapes, and they are executed one-by-one using the
      device's ``execute`` method. The results are collected in a list.
  
      For plugin developers: This function should be overwritten if the device can efficiently run multiple
      circuits on a backend, for example using parallel and/or asynchronous executions.
  
      Args:
          circuits (list[.tape.QuantumTape]): circuits to execute on the device
  
      Returns:
          list[array[float]]: list of measured value(s)
      """
      results = []
      for circuit in circuits:
          # we need to reset the device here, else it will
          # not start the next computation in the zero state
          self.reset()
  
          res = self.execute(circuit.operations, circuit.measurements)
          results.append(res)
  
      if self.tracker.active:
          self.tracker.update(batches=1, batch_len=len(circuits))
          self.tracker.record()
  
      return results
  
imports: import abc
  import copy
  import types
  import warnings
  from collections import OrderedDict
  from collections.abc import Iterable, Sequence
  from functools import lru_cache
  import numpy
  import pennylane
  from pennylane.measurements import MeasurementProcess, CountsMP, Expectation, ExpectationMP, MidMeasureMP, Probability, ProbabilityMP, Sample, SampleMP, ShadowExpvalMP, State, Variance
  from pennylane.operation import Observable, Operation, Tensor, Operator, StatePrepBase
  from pennylane.ops import Hamiltonian, Sum
  from pennylane.tape import QuantumScript, QuantumTape, expand_tape_state_prep
  from pennylane.wires import WireError, Wires
  from pennylane.queuing import QueuingManager
label_desc: Use image node_id 24 for calling the Device obj's underlying member method code with example usage: obj.batch_execute(circuits) and returns: results