class_docstr: This device provides derivatives via parameter shift.
class_docstr_tok: ["This","device","provides","derivatives","via","parameter","shift","."]
code: def compute_jvp(
      self,
      circuits,
      tangents,
      execution_config=qml.devices.DefaultExecutionConfig,
  ):
      is_single_circuit = False
      if isinstance(circuits, qml.tape.QuantumScript):
          is_single_circuit = True
          circuits = (circuits,)
          tangents = (tangents,)
  
      if self.tracker.active:
          self.tracker.update(jvp_batches=1, jvps=len(circuits))
          self.tracker.record()
  
      batch, fn = qml.gradients.batch_jvp(
          circuits, tangents, qml.gradients.param_shift
      )
      results = self.execute(batch)
      return fn(results)[0] if is_single_circuit else fn(results)
  
file_path: pennylane/tests/param_shift_dev.py
imports: import dataclasses
  import pennylane
label_desc: Use image node_id 5 for calling the ParamShiftDerivativesDevice obj's underlying member method code with example usage: obj.compute_jvp(circuits, tangents, execution_config) and returns: unknown