Trouble compiling for QPU #123

genos · 2023-02-13T19:07:17Z

Introduction

Sorry to trouble y'all again, but I've got another issue.

I'm trying to run a tree tensor network on Aspen-M-2, but I hit a compilation issue.
Trying to sidestep the issue gets me a little further, but then quilc has trouble with the number of MEASURE calls—especially when I only need one.
Any ideas or help you can provide would be greatly appreciated!

Setup

Here's the code for creating the circuit given a specific device:

Setup code

import pennylane as qml
from pennylane import numpy as np

NUM_QUBITS, PARAM_SHAPE = 8, (7, 2)

def block(weights, wires):
    qml.RX(weights[0], wires=wires[0])
    qml.RX(weights[1], wires=wires[1])
    qml.CNOT(wires=wires)

def make_circuit(device, wires=None):
    if wires is None:
        wires = range(NUM_QUBITS)

    @qml.qnode(device)
    def circuit(X, parameters):
        qml.AngleEmbedding(X, wires=wires, rotation="Z")
        qml.TTN(
            wires=wires,
            n_block_wires=2,
            block=block,
            n_params_block=2,
            template_weights=parameters,
        )
        return qml.expval(qml.PauliZ(NUM_QUBITS - 1))

    return circuit

This looks like it builds the circuit I want:

Circuit drawing code

fig, ax = qml.draw_mpl(
    make_circuit(qml.device("default.qubit", wires=NUM_QUBITS)),
    expansion_strategy="device",
    style="solarized_light",
)(np.zeros(NUM_QUBITS), np.zeros(PARAM_SHAPE))
fig.set_size_inches(5, 4);

And this works fine with the default.qubit device:

circuit = make_circuit(qml.device("default.qubit", wires=NUM_QUBITS))
print(circuit(np.zeros(NUM_QUBITS), np.zeros(PARAM_SHAPE)))
# tensor(1., requires_grad=True)

First Problem

Running quilc -S and attempting to compile this for Aspen-M-2, we encounter our first problem. Attempting to build the circuit with 8 specific qubits chosen due to their connectivity on the QPU, we have:

aspen_m_2 = qml.device("rigetti.qpu", device="Aspen-M-2", active_reset=True, compiler_timeout=100)
circuit = make_circuit(aspen_m_2, wires=[113, 114, 116, 115, 100, 101, 103, 102])
circuit(np.zeros(NUM_QUBITS), np.zeros(PARAM_SHAPE))

However, this throws a WireError:

WireError from above code

WireError                                 Traceback (most recent call last)
File REPO/.venv/lib/python3.10/site-packages/pennylane/_device.py:385, in Device.map_wires(self, wires)
    384 try:
--> 385     mapped_wires = wires.map(self.wire_map)
    386 except WireError as e:

File REPO/.venv/lib/python3.10/site-packages/pennylane/wires.py:278, in Wires.map(self, wire_map)
    277     if w not in wire_map:
--> 278         raise WireError(f"No mapping for wire label {w} specified in wire map {wire_map}.")
    280 new_wires = [wire_map[w] for w in self]

WireError: No mapping for wire label 113 specified in wire map OrderedDict([(0, 0), (1, 1), (2, 2), (3, 3), (4, 4), (5, 5), (6, 6), (7, 7), (8, 8), (9, 9), (10, 10), (11, 11), (12, 12), (13, 13), (14, 14), (15, 15), (16, 16), (17, 17), (18, 18), (19, 19), (20, 20), (21, 21), (22, 22), (23, 23), (24, 24), (25, 25), (26, 26), (27, 27), (28, 28), (29, 29), (30, 30), (31, 31), (32, 32), (33, 33), (34, 34), (35, 35), (36, 36), (37, 37), (38, 38), (39, 39), (40, 40), (41, 41), (42, 42), (43, 43), (44, 44), (45, 45), (46, 46), (47, 47), (48, 48), (49, 49), (50, 50), (51, 51), (52, 52), (53, 53), (54, 54), (55, 55), (56, 56), (57, 57), (58, 58), (59, 59), (60, 60), (61, 61), (62, 62), (63, 63), (64, 64), (65, 65), (66, 66), (67, 67), (68, 68), (69, 69), (70, 70), (71, 71), (72, 72), (73, 73), (74, 74), (75, 75), (76, 76), (77, 77), (78, 78), (79, 79)]).

The above exception was the direct cause of the following exception:

WireError                                 Traceback (most recent call last)
Cell In[4], line 3
      1 aspen_m_2 = qml.device("rigetti.qpu", device="Aspen-M-2", active_reset=True, compiler_timeout=100)
      2 circuit = make_circuit(aspen_m_2, wires=[113, 114, 116, 115, 100, 101, 103, 102])
----> 3 circuit(np.zeros(NUM_QUBITS), np.zeros(PARAM_SHAPE))

File REPO/.venv/lib/python3.10/site-packages/pennylane/qnode.py:847, in QNode.__call__(self, *args, **kwargs)
    843     self._update_original_device()
    845     return res
--> 847 res = qml.execute(
    848     [self.tape],
    849     device=self.device,
    850     gradient_fn=self.gradient_fn,
    851     interface=self.interface,
    852     gradient_kwargs=self.gradient_kwargs,
    853     override_shots=override_shots,
    854     **self.execute_kwargs,
    855 )
    857 if old_interface == "auto":
    858     self.interface = "auto"

File REPO/.venv/lib/python3.10/site-packages/pennylane/interfaces/execution.py:724, in execute(tapes, device, gradient_fn, interface, mode, gradient_kwargs, cache, cachesize, max_diff, override_shots, expand_fn, max_expansion, device_batch_transform)
    718 except ImportError as e:
    719     raise qml.QuantumFunctionError(
    720         f"{mapped_interface} not found. Please install the latest "
    721         f"version of {mapped_interface} to enable the '{mapped_interface}' interface."
    722     ) from e
--> 724 res = _execute(
    725     tapes, device, execute_fn, gradient_fn, gradient_kwargs, _n=1, max_diff=max_diff, mode=_mode
    726 )
    728 return batch_fn(res)

File REPO/.venv/lib/python3.10/site-packages/pennylane/interfaces/autograd.py:81, in execute(tapes, device, execute_fn, gradient_fn, gradient_kwargs, _n, max_diff, mode)
     75 # pylint misidentifies autograd.builtins as a dict
     76 # pylint: disable=no-member
     77 parameters = autograd.builtins.tuple(
     78     [autograd.builtins.list(t.get_parameters()) for t in tapes]
     79 )
---> 81 return _execute(
     82     parameters,
     83     tapes=tapes,
     84     device=device,
     85     execute_fn=execute_fn,
     86     gradient_fn=gradient_fn,
     87     gradient_kwargs=gradient_kwargs,
     88     _n=_n,
     89     max_diff=max_diff,
     90 )[0]

File REPO/.venv/lib/python3.10/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 REPO/.venv/lib/python3.10/site-packages/pennylane/interfaces/autograd.py:125, in _execute(parameters, tapes, device, execute_fn, gradient_fn, gradient_kwargs, _n, max_diff)
    104 """Autodifferentiable wrapper around ``Device.batch_execute``.
    105 
    106 The signature of this function is designed to work around Autograd restrictions.
   (...)
    122 understand the consequences!
    123 """
    124 with qml.tape.Unwrap(*tapes):
--> 125     res, jacs = execute_fn(tapes, **gradient_kwargs)
    127 for i, r in enumerate(res):
    128     if any(isinstance(m, CountsMP) for m in tapes[i].measurements):

File REPO/.venv/lib/python3.10/site-packages/pennylane/interfaces/execution.py:206, in cache_execute.<locals>.wrapper(tapes, **kwargs)
    202         return (res, []) if return_tuple else res
    204 else:
    205     # execute all unique tapes that do not exist in the cache
--> 206     res = fn(execution_tapes.values(), **kwargs)
    208 final_res = []
    210 for i, tape in enumerate(tapes):

File REPO/.venv/lib/python3.10/site-packages/pennylane/interfaces/execution.py:131, in cache_execute.<locals>.fn(tapes, **kwargs)
    129 def fn(tapes: Sequence[QuantumTape], **kwargs):  # pylint: disable=function-redefined
    130     tapes = [expand_fn(tape) for tape in tapes]
--> 131     return original_fn(tapes, **kwargs)

File ~/.pyenv/versions/3.10.7/lib/python3.10/contextlib.py:79, in ContextDecorator.__call__.<locals>.inner(*args, **kwds)
     76 @wraps(func)
     77 def inner(*args, **kwds):
     78     with self._recreate_cm():
---> 79         return func(*args, **kwds)

File REPO/.venv/lib/python3.10/site-packages/pennylane/_qubit_device.py:656, in QubitDevice.batch_execute(self, circuits)
    653     self.reset()
    655     # TODO: Insert control on value here
--> 656     res = self.execute(circuit)
    657     results.append(res)
    659 if self.tracker.active:

File REPO/.venv/lib/python3.10/site-packages/pennylane_rigetti/qpu.py:198, in QPUDevice.execute(self, circuit, **kwargs)
    192 def execute(self, circuit: QuantumTape, **kwargs):
    193     self._skip_generate_samples = (
    194         all(obs.return_type == Expectation for obs in circuit.observables)
    195         and not self.parametric_compilation
    196     )
--> 198     return super().execute(circuit, **kwargs)

File REPO/.venv/lib/python3.10/site-packages/pennylane_rigetti/qc.py:259, in QuantumComputerDevice.execute(self, circuit, **kwargs)
    257 if self.parametric_compilation:
    258     self._circuit_hash = circuit.graph.hash
--> 259 return super().execute(circuit, **kwargs)

File REPO/.venv/lib/python3.10/site-packages/pennylane/_qubit_device.py:432, in QubitDevice.execute(self, circuit, **kwargs)
    429 self.check_validity(circuit.operations, circuit.observables)
    431 # apply all circuit operations
--> 432 self.apply(circuit.operations, rotations=circuit.diagonalizing_gates, **kwargs)
    434 # generate computational basis samples
    435 if self.shots is not None or circuit.is_sampled:

File REPO/.venv/lib/python3.10/site-packages/pennylane_rigetti/qc.py:189, in QuantumComputerDevice.apply(self, operations, **kwargs)
    186 self.prog = prag + self.prog
    188 if self.parametric_compilation:
--> 189     self.prog += self.apply_parametric_operations(operations)
    190 else:
    191     self.prog += self.apply_circuit_operations(operations)

File REPO/.venv/lib/python3.10/site-packages/pennylane_rigetti/qc.py:216, in QuantumComputerDevice.apply_parametric_operations(self, operations)
    213 # Apply the circuit operations
    214 for i, operation in enumerate(operations):
    215     # map the operation wires to the physical device qubits
--> 216     device_wires = self.map_wires(operation.wires)
    218     if i > 0 and operation.name in ("QubitStateVector", "BasisState"):
    219         raise DeviceError(
    220             f"Operation {operation.name} cannot be used after other Operations have already been applied "
    221             f"on a {self.short_name} device."
    222         )

File REPO/.venv/lib/python3.10/site-packages/pennylane/_device.py:387, in Device.map_wires(self, wires)
    385     mapped_wires = wires.map(self.wire_map)
    386 except WireError as e:
--> 387     raise WireError(
    388         f"Did not find some of the wires {wires} on device with wires {self.wires}."
    389     ) from e
    391 return mapped_wires

WireError: Did not find some of the wires <Wires = [113]> on device with wires <Wires = [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79]>.

Workaround and Second Problem

We can sidestep the above WireError if we overwrite the wire map for our device—though of course, I'd prefer to not have to.
However, doing so leads to a different error: quilc has trouble compiling the resulting Program, I think because there are too many MEASURE calls in it.

aspen_m_2._wire_map = {q: q for q in aspen_m_2.qc.qubits()}
circuit = make_circuit(aspen_m_2, wires=[113, 114, 116, 115, 100, 101, 103, 102])
circuit(np.zeros(NUM_QUBITS), np.zeros(PARAM_SHAPE))

QCSHTTPStatusError from the above code

QCSHTTPStatusError                        Traceback (most recent call last)
Cell In[10], line 3
      1 aspen_m_2._wire_map = {q: q for q in aspen_m_2.qc.qubits()}
      2 circuit = make_circuit(aspen_m_2, wires=[113, 114, 116, 115, 100, 101, 103, 102])
----> 3 circuit(np.zeros(NUM_QUBITS), np.zeros(PARAM_SHAPE))

File REPO/.venv/lib/python3.10/site-packages/pennylane/qnode.py:847, in QNode.__call__(self, *args, **kwargs)
    843     self._update_original_device()
    845     return res
--> 847 res = qml.execute(
    848     [self.tape],
    849     device=self.device,
    850     gradient_fn=self.gradient_fn,
    851     interface=self.interface,
    852     gradient_kwargs=self.gradient_kwargs,
    853     override_shots=override_shots,
    854     **self.execute_kwargs,
    855 )
    857 if old_interface == "auto":
    858     self.interface = "auto"

File REPO/.venv/lib/python3.10/site-packages/pennylane/interfaces/execution.py:724, in execute(tapes, device, gradient_fn, interface, mode, gradient_kwargs, cache, cachesize, max_diff, override_shots, expand_fn, max_expansion, device_batch_transform)
    718 except ImportError as e:
    719     raise qml.QuantumFunctionError(
    720         f"{mapped_interface} not found. Please install the latest "
    721         f"version of {mapped_interface} to enable the '{mapped_interface}' interface."
    722     ) from e
--> 724 res = _execute(
    725     tapes, device, execute_fn, gradient_fn, gradient_kwargs, _n=1, max_diff=max_diff, mode=_mode
    726 )
    728 return batch_fn(res)

File REPO/.venv/lib/python3.10/site-packages/pennylane/interfaces/autograd.py:81, in execute(tapes, device, execute_fn, gradient_fn, gradient_kwargs, _n, max_diff, mode)
     75 # pylint misidentifies autograd.builtins as a dict
     76 # pylint: disable=no-member
     77 parameters = autograd.builtins.tuple(
     78     [autograd.builtins.list(t.get_parameters()) for t in tapes]
     79 )
---> 81 return _execute(
     82     parameters,
     83     tapes=tapes,
     84     device=device,
     85     execute_fn=execute_fn,
     86     gradient_fn=gradient_fn,
     87     gradient_kwargs=gradient_kwargs,
     88     _n=_n,
     89     max_diff=max_diff,
     90 )[0]

File REPO/.venv/lib/python3.10/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 REPO/.venv/lib/python3.10/site-packages/pennylane/interfaces/autograd.py:125, in _execute(parameters, tapes, device, execute_fn, gradient_fn, gradient_kwargs, _n, max_diff)
    104 """Autodifferentiable wrapper around ``Device.batch_execute``.
    105 
    106 The signature of this function is designed to work around Autograd restrictions.
   (...)
    122 understand the consequences!
    123 """
    124 with qml.tape.Unwrap(*tapes):
--> 125     res, jacs = execute_fn(tapes, **gradient_kwargs)
    127 for i, r in enumerate(res):
    128     if any(isinstance(m, CountsMP) for m in tapes[i].measurements):

File REPO/.venv/lib/python3.10/site-packages/pennylane/interfaces/execution.py:206, in cache_execute.<locals>.wrapper(tapes, **kwargs)
    202         return (res, []) if return_tuple else res
    204 else:
    205     # execute all unique tapes that do not exist in the cache
--> 206     res = fn(execution_tapes.values(), **kwargs)
    208 final_res = []
    210 for i, tape in enumerate(tapes):

File REPO/.venv/lib/python3.10/site-packages/pennylane/interfaces/execution.py:131, in cache_execute.<locals>.fn(tapes, **kwargs)
    129 def fn(tapes: Sequence[QuantumTape], **kwargs):  # pylint: disable=function-redefined
    130     tapes = [expand_fn(tape) for tape in tapes]
--> 131     return original_fn(tapes, **kwargs)

File ~/.pyenv/versions/3.10.7/lib/python3.10/contextlib.py:79, in ContextDecorator.__call__.<locals>.inner(*args, **kwds)
     76 @wraps(func)
     77 def inner(*args, **kwds):
     78     with self._recreate_cm():
---> 79         return func(*args, **kwds)

File REPO/.venv/lib/python3.10/site-packages/pennylane/_qubit_device.py:656, in QubitDevice.batch_execute(self, circuits)
    653     self.reset()
    655     # TODO: Insert control on value here
--> 656     res = self.execute(circuit)
    657     results.append(res)
    659 if self.tracker.active:

File REPO/.venv/lib/python3.10/site-packages/pennylane_rigetti/qpu.py:198, in QPUDevice.execute(self, circuit, **kwargs)
    192 def execute(self, circuit: QuantumTape, **kwargs):
    193     self._skip_generate_samples = (
    194         all(obs.return_type == Expectation for obs in circuit.observables)
    195         and not self.parametric_compilation
    196     )
--> 198     return super().execute(circuit, **kwargs)

File REPO/.venv/lib/python3.10/site-packages/pennylane_rigetti/qc.py:259, in QuantumComputerDevice.execute(self, circuit, **kwargs)
    257 if self.parametric_compilation:
    258     self._circuit_hash = circuit.graph.hash
--> 259 return super().execute(circuit, **kwargs)

File REPO/.venv/lib/python3.10/site-packages/pennylane/_qubit_device.py:436, in QubitDevice.execute(self, circuit, **kwargs)
    434 # generate computational basis samples
    435 if self.shots is not None or circuit.is_sampled:
--> 436     self._samples = self.generate_samples()
    438 measurements = circuit.measurements
    439 counts_exist = any(isinstance(m, CountsMP) for m in measurements)

File REPO/.venv/lib/python3.10/site-packages/pennylane_rigetti/qpu.py:201, in QPUDevice.generate_samples(self)
    200 def generate_samples(self):
--> 201     return None if self._skip_generate_samples else super().generate_samples()

File REPO/.venv/lib/python3.10/site-packages/pennylane_rigetti/qc.py:271, in QuantumComputerDevice.generate_samples(self)
    269     self._compiled_program = self._compiled_program_dict.get(self.circuit_hash, None)
    270     if self._compiled_program is None:
--> 271         self._compiled_program = self.compile()
    272         self._compiled_program_dict[self.circuit_hash] = self._compiled_program
    273 else:
    274     # Parametric compilation is disabled, just compile the program

File REPO/.venv/lib/python3.10/site-packages/pennylane_rigetti/qc.py:253, in QuantumComputerDevice.compile(self)
    251 def compile(self) -> QuantumExecutable:
    252     """Compiles the program for the target device"""
--> 253     return self.qc.compile(self.prog)

File REPO/.venv/lib/python3.10/site-packages/pyquil/api/_quantum_computer.py:403, in QuantumComputer.compile(self, program, to_native_gates, optimize, protoquil)
    400 else:
    401     nq_program = program
--> 403 return self.compiler.native_quil_to_executable(nq_program)

File REPO/.venv/lib/python3.10/site-packages/pyquil/api/_compiler.py:119, in QPUCompiler.native_quil_to_executable(self, nq_program)
    111 request = TranslateNativeQuilToEncryptedBinaryRequest(
    112     quil=arithmetic_response.quil, num_shots=nq_program.num_shots
    113 )
    114 with self._qcs_client() as qcs_client:  # type: httpx.Client
    115     response = translate_native_quil_to_encrypted_binary(
    116         client=qcs_client,
    117         quantum_processor_id=self.quantum_processor_id,
    118         json_body=request,
--> 119     ).parsed
    121 ro_sources = cast(List[List[str]], [] if response.ro_sources == UNSET else response.ro_sources)
    123 def to_expression(rule: str) -> ExpressionDesignator:
    124     # We can only parse complete lines of Quil, so we wrap the arithmetic expression
    125     # in a valid Quil instruction to parse it.
    126     # TODO: This hack should be replaced after #687

File REPO/.venv/lib/python3.10/site-packages/qcs_api_client/types.py:67, in Response.parsed(self)
     61 """
     62 Return the response body parsed into an API model.
     63 
     64 Value is memoized after the first successful call.
     65 """
     66 if self._parsed is None:
---> 67     self._parsed = self._parse_function(response=self)
     69 return self._parsed

File REPO/.venv/lib/python3.10/site-packages/qcs_api_client/api/translation/translate_native_quil_to_encrypted_binary.py:39, in _parse_response(response)
     38 def _parse_response(*, response: httpx.Response) -> TranslateNativeQuilToEncryptedBinaryResponse:
---> 39     raise_for_status(response)
     40     if response.status_code == 200:
     41         response_200 = TranslateNativeQuilToEncryptedBinaryResponse.from_dict(response.json())

File REPO/.venv/lib/python3.10/site-packages/qcs_api_client/util/errors.py:33, in raise_for_status(res)
     30 except (JSONDecodeError, KeyError):
     31     pass
---> 33 raise QCSHTTPStatusError(message, error=error, response=res)

QCSHTTPStatusError: QCS API call POST https://api.qcs.rigetti.com/v1/quantumProcessors/Aspen-M-2:translateNativeQuilToEncryptedBinary failed with status 400: {"code":"translation_error","message":"Memory-region re-declared: q24_unclassified","requestId":"<SNIP>"}

However, if we take the pyQuil program from the device and clean up unused MEASURE instructions, the resulting program compiles without issue:

p = Program()
for i in aspen_m_2.prog.instructions:
    if not i.out().startswith("MEASURE") or i.get_qubits() == {102}:
        p += i
print(p)

Program with only one MEASURE

PRAGMA INITIAL_REWIRING "PARTIAL"
RESET
RZ(0) 113
RZ(0) 114
RZ(0) 116
RZ(0) 115
RZ(0) 100
RZ(0) 101
RZ(0) 103
RZ(0) 102
RX(0) 113
RX(0) 114
CNOT 113 114
RX(0) 116
RX(0) 115
CNOT 116 115
RX(0) 100
RX(0) 101
CNOT 100 101
RX(0) 103
RX(0) 102
CNOT 103 102
RX(0) 114
RX(0) 115
CNOT 114 115
RX(0) 101
RX(0) 102
CNOT 101 102
RX(0) 115
RX(0) 102
CNOT 115 102
DECLARE ro BIT[80]
MEASURE 102 ro[42]

print(aspen_m_2.qc.compile(p))
# EncryptedProgram(
#  program=<SNIP>,
#  memory_descriptors={'ro': ParameterSpec(length=80, type='BIT')},
#  ro_sources={<MRef q10_unclassified[0]>: 'q10_unclassified', <MRef ro[42]>: 'q10'},
#  recalculation_table={}, _memory=Memory(values={})
# )

The text was updated successfully, but these errors were encountered:

CatalinaAlbornoz · 2023-02-17T00:39:06Z

Thank you for opening this issue @genos !

MarquessV mentioned this issue Feb 16, 2023

Fix default wire mapping and QPU program compilation and add support for parallel execution #124

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Trouble compiling for QPU #123

Trouble compiling for QPU #123

genos commented Feb 13, 2023 •

edited

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CatalinaAlbornoz commented Feb 17, 2023

Trouble compiling for QPU #123

Trouble compiling for QPU #123

Comments

genos commented Feb 13, 2023 • edited Loading

Introduction

Setup

First Problem

Workaround and Second Problem

CatalinaAlbornoz commented Feb 17, 2023

genos commented Feb 13, 2023 •

edited

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