Hi, I tried running the code from this video. When I tried to run it on a IBM device it gave me an error. The error seems to be because of the controlled Z gate that the program uses. It works fine on the pennylane simulator but when I try to use the qiskit one it breaks. Could use some help debugging.
# Put code here
import pennylane as qml
from pennylane import numpy as np
property_prices = [4, 8, 6, 3, 12, 15] # total 48
variables_wires = [0, 1, 2, 3, 4, 5]
aux_oracle_wires = [6, 7, 8 ,9 ,10, 11]
def oracle(variables_wires, aux_oracle_wires):
def add_k_fourier(k, wires):
for j in range(len(wires)):
qml.RZ(k * np.pi / (2**j), wires=wires[j])
def value_second_sibling():
qml.QFT(wires = aux_oracle_wires)
for wire in variables_wires:
qml.ctrl(add_k_fourier, control = wire)(property_prices[wire], wires = aux_oracle_wires)
qml.adjoint(qml.QFT)(wires = aux_oracle_wires)
value_second_sibling()
qml.FlipSign(sum(property_prices) // 2, wires = aux_oracle_wires)
qml.adjoint(value_second_sibling)()
dev = qml.device('qiskit.ibmq', wires=12, backend='ibmq_qasm_simulator')
@qml.qnode(dev)
def circuit():
# step 1
for wire in variables_wires:
qml.Hadamard(wires = wire)
# step 2
oracle(variables_wires, aux_oracle_wires)
# step 3
qml.GroverOperator(wires = variables_wires)
return qml.probs(wires = variables_wires)
import matplotlib.pyplot as plt
values = circuit()
plt.bar(range(len(values)), values)
If you want help with diagnosing an error, please put the full error message below:
# Put full error message here
---------------------------------------------------------------------------
KeyError Traceback (most recent call last)
Cell In[5], line 3
1 import matplotlib.pyplot as plt
----> 3 values = circuit()
4 plt.bar(range(len(values)), values)
File ~\anaconda3\Lib\site-packages\pennylane\qnode.py:989, in QNode.__call__(self, *args, **kwargs)
986 self.execute_kwargs.pop("mode")
988 # pylint: disable=unexpected-keyword-arg
--> 989 res = qml.execute(
990 (self._tape,),
991 device=self.device,
992 gradient_fn=self.gradient_fn,
993 interface=self.interface,
994 transform_program=self.transform_program,
995 gradient_kwargs=self.gradient_kwargs,
996 override_shots=override_shots,
997 **self.execute_kwargs,
998 )
1000 res = res[0]
1002 # convert result to the interface in case the qfunc has no parameters
File ~\anaconda3\Lib\site-packages\pennylane\interfaces\execution.py:757, in execute(tapes, device, gradient_fn, interface, transform_program, grad_on_execution, gradient_kwargs, cache, cachesize, max_diff, override_shots, expand_fn, max_expansion, device_batch_transform)
754 raise ValueError("Gradient transforms cannot be used with grad_on_execution=True")
756 ml_boundary_execute = _get_ml_boundary_execute(interface, _grad_on_execution)
--> 757 results = ml_boundary_execute(
758 tapes, device, execute_fn, gradient_fn, gradient_kwargs, _n=1, max_diff=max_diff
759 )
761 results = batch_fn(results)
762 return program_post_processing(results)
File ~\anaconda3\Lib\site-packages\pennylane\interfaces\autograd.py:317, in execute(tapes, device, execute_fn, gradient_fn, gradient_kwargs, _n, max_diff)
312 # pylint misidentifies autograd.builtins as a dict
313 # pylint: disable=no-member
314 parameters = autograd.builtins.tuple(
315 [autograd.builtins.list(t.get_parameters()) for t in tapes]
316 )
--> 317 return _execute(
318 parameters,
319 tapes=tapes,
320 device=device,
321 execute_fn=execute_fn,
322 gradient_fn=gradient_fn,
323 gradient_kwargs=gradient_kwargs,
324 _n=_n,
325 max_diff=max_diff,
326 )[0]
File ~\anaconda3\Lib\site-packages\autograd\tracer.py:48, in primitive.<locals>.f_wrapped(*args, **kwargs)
46 return new_box(ans, trace, node)
47 else:
---> 48 return f_raw(*args, **kwargs)
File ~\anaconda3\Lib\site-packages\pennylane\interfaces\autograd.py:378, in _execute(parameters, tapes, device, execute_fn, gradient_fn, gradient_kwargs, _n, max_diff)
360 if logger.isEnabledFor(logging.DEBUG):
361 logger.debug(
362 "Entry with args=(parameters=%s, tapes=%s, device=%s, execute_fn=%s, gradient_fn=%s, gradient_kwargs=%s, _n=%s, max_diff=%s) called by=%s",
363 parameters,
(...)
375 "::L".join(str(i) for i in inspect.getouterframes(inspect.currentframe(), 2)[1][1:3]),
376 )
--> 378 res, jacs = execute_fn(tapes, **gradient_kwargs)
380 return res, jacs
File ~\anaconda3\Lib\site-packages\pennylane\interfaces\execution.py:623, in execute.<locals>.inner_execute_with_empty_jac(tapes, **_)
622 def inner_execute_with_empty_jac(tapes, **_):
--> 623 return (inner_execute(tapes), [])
File ~\anaconda3\Lib\site-packages\pennylane\interfaces\execution.py:255, in _make_inner_execute.<locals>.inner_execute(tapes, **_)
253 if numpy_only:
254 tapes = tuple(qml.transforms.convert_to_numpy_parameters(t) for t in tapes)
--> 255 return cached_device_execution(tapes)
File ~\anaconda3\Lib\site-packages\pennylane\interfaces\execution.py:377, in cache_execute.<locals>.wrapper(tapes, **kwargs)
372 return (res, []) if return_tuple else res
374 else:
375 # execute all unique tapes that do not exist in the cache
376 # convert to list as new device interface returns a tuple
--> 377 res = list(fn(tuple(execution_tapes.values()), **kwargs))
379 final_res = []
381 for i, tape in enumerate(tapes):
File ~\anaconda3\Lib\contextlib.py:81, in ContextDecorator.__call__.<locals>.inner(*args, **kwds)
78 @wraps(func)
79 def inner(*args, **kwds):
80 with self._recreate_cm():
---> 81 return func(*args, **kwds)
File ~\anaconda3\Lib\site-packages\pennylane_qiskit\ibmq.py:91, in IBMQDevice.batch_execute(self, circuits)
90 def batch_execute(self, circuits): # pragma: no cover, pylint:disable=arguments-differ
---> 91 res = super().batch_execute(circuits, timeout=self.timeout_secs)
92 if self.tracker.active:
93 self._track_run()
File ~\anaconda3\Lib\site-packages\pennylane_qiskit\qiskit_device.py:473, in QiskitDevice.batch_execute(self, circuits, timeout)
470 def batch_execute(self, circuits, timeout: int = None):
471 # pylint: disable=missing-function-docstring
--> 473 compiled_circuits = self.compile_circuits(circuits)
475 # Send the batch of circuit objects using backend.run
476 self._current_job = self.backend.run(compiled_circuits, shots=self.shots, **self.run_args)
File ~\anaconda3\Lib\site-packages\pennylane_qiskit\qiskit_device.py:462, in QiskitDevice.compile_circuits(self, circuits)
458 for circuit in circuits:
459 # We need to reset the device here, else it will
460 # not start the next computation in the zero state
461 self.reset()
--> 462 self.create_circuit_object(circuit.operations, rotations=circuit.diagonalizing_gates)
464 compiled_circ = self.compile()
465 compiled_circ.name = f"circ{len(compiled_circuits)}"
File ~\anaconda3\Lib\site-packages\pennylane_qiskit\qiskit_device.py:273, in QiskitDevice.create_circuit_object(self, operations, **kwargs)
261 """Builds the circuit objects based on the operations and measurements
262 specified to apply.
263
(...)
269 pre-measurement into the eigenbasis of the observables.
270 """
271 rotations = kwargs.get("rotations", [])
--> 273 applied_operations = self.apply_operations(operations)
275 # Rotating the state for measurement in the computational basis
276 rotation_circuits = self.apply_operations(rotations)
File ~\anaconda3\Lib\site-packages\pennylane_qiskit\qiskit_device.py:322, in QiskitDevice.apply_operations(self, operations)
318 par[idx] = p.tolist()
320 operation = operation.name
--> 322 mapped_operation = self._operation_map[operation]
324 self.qubit_state_vector_check(operation)
326 qregs = [self._reg[i] for i in device_wires.labels]
KeyError: 'C(RZ)'
And, finally, make sure to include the versions of your packages. Specifically, show us the output of qml.about().
Name: PennyLane
Version: 0.32.0
Summary: PennyLane is a Python quantum machine learning library by Xanadu Inc.
Home-page: GitHub - PennyLaneAI/pennylane: PennyLane is a cross-platform Python library for differentiable programming of quantum computers. Train a quantum computer the same way as a neural network.
Author:
Author-email:
License: Apache License 2.0
Location: C:\Users\Carter\anaconda3\Lib\site-packages
Requires: appdirs, autograd, autoray, cachetools, networkx, numpy, pennylane-lightning, requests, rustworkx, scipy, semantic-version, toml, typing-extensions
Required-by: PennyLane-Lightning, PennyLane-qiskit
Platform info: Windows-10-10.0.22621-SP0
Python version: 3.11.5
Numpy version: 1.23.5
Scipy version: 1.11.1
Installed devices:
- default.gaussian (PennyLane-0.32.0)
- default.mixed (PennyLane-0.32.0)
- default.qubit (PennyLane-0.32.0)
- default.qubit.autograd (PennyLane-0.32.0)
- default.qubit.jax (PennyLane-0.32.0)
- default.qubit.tf (PennyLane-0.32.0)
- default.qubit.torch (PennyLane-0.32.0)
- default.qutrit (PennyLane-0.32.0)
- null.qubit (PennyLane-0.32.0)
- lightning.qubit (PennyLane-Lightning-0.32.0)
- qiskit.aer (PennyLane-qiskit-0.32.0)
- qiskit.basicaer (PennyLane-qiskit-0.32.0)
- qiskit.ibmq (PennyLane-qiskit-0.32.0)
- qiskit.ibmq.circuit_runner (PennyLane-qiskit-0.32.0)
- qiskit.ibmq.sampler (PennyLane-qiskit-0.32.0)
- qiskit.remote (PennyLane-qiskit-0.32.0)
.
… are you using this to ensure that things get decomposed in an ibmq-friendly way?