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diff --git a/.github/workflows/interface-unit-tests.yml b/.github/workflows/interface-unit-tests.yml index 2dfee7df77b..8c60c2f7f35 100644 --- a/.github/workflows/interface-unit-tests.yml +++ b/.github/workflows/interface-unit-tests.yml @@ -81,20 +81,20 @@ jobs: cat >matrix_max_parallel.json <<-EOF { "default": 1, - "tf-tests": 3, - "core-tests": 3, + "core-tests": 5, + "gradients-tests": 2, "jax-tests": 5, - "gradients-tests": 2 + "tf-tests": 3 } EOF else cat >matrix_max_parallel.json <<-EOF { "default": 1, - "torch-tests": 2, - "tf-tests": 6, + "core-tests": 5, "jax-tests": 10, - "core-tests": 3 + "tf-tests": 6, + "torch-tests": 2 } EOF fi @@ -264,9 +264,7 @@ jobs: || fromJSON(needs.setup-ci-load.outputs.matrix-max-parallel).default }} matrix: - group: - - '1' - - '2' + group: [1, 2, 3, 4, 5] python-version: >- ${{ fromJSON(needs.setup-ci-load.outputs.python-version).core-tests @@ -286,7 +284,7 @@ jobs: install_pennylane_lightning_master: true pytest_coverage_flags: ${{ inputs.pytest_coverage_flags }} pytest_markers: core and not qcut and not finite-diff and not param-shift - pytest_additional_args: --splits 2 --group ${{ matrix.group }} + pytest_additional_args: --splits 5 --group ${{ matrix.group }} --durations-path='.github/workflows/core_tests_durations.json' additional_pip_packages: pytest-split requirements_file: ${{ strategy.job-index == 0 && 'core.txt' || '' }} diff --git a/doc/releases/changelog-dev.md b/doc/releases/changelog-dev.md index e6585fb3150..eb5c9e116f9 100644 --- a/doc/releases/changelog-dev.md +++ b/doc/releases/changelog-dev.md @@ -118,9 +118,9 @@ ```pycon >>> circuit() array([[0, 1, 1, 0, 0], - [1, 0, 1, 1, 1], - [0, 0, 0, 1, 0], - [1, 0, 0, 1, 1]]) + [1, 0, 1, 1, 1], + [0, 0, 0, 1, 0], + [1, 0, 0, 1, 1]]) ``` * A function called `apply_operation` has been added to the new `qutrit_mixed` module found in `qml.devices` that applies operations to device-compatible states. @@ -146,7 +146,7 @@ * PennyLane can now use lightning provided VJPs by selecting `device_vjp=True` on the QNode. [(#4914)](https://github.com/PennyLaneAI/pennylane/pull/4914) -* Remove queuing (`AnnotatedQueue`) from `qml.cut_circuit` and `qml.cut_circuit_mc` to improve performance +* Remove queuing (`AnnotatedQueue`) from `qml.cut_circuit` and `qml.cut_circuit_mc` to improve performance for large workflows. [(#5108)](https://github.com/PennyLaneAI/pennylane/pull/5108) @@ -156,27 +156,35 @@

Community contributions 🥳

* `parity_transform` is added for parity mapping of a fermionic Hamiltonian. - [(#4928)](https://github.com/PennyLaneAI/pennylane/pull/4928) - It is now possible to transform a fermionic Hamiltonian to a qubit Hamiltonian with parity mapping. + [(#4928)](https://github.com/PennyLaneAI/pennylane/pull/4928) + It is now possible to transform a fermionic Hamiltonian to a qubit Hamiltonian with parity mapping. - ```python - import pennylane as qml - fermi_ham = qml.fermi.FermiWord({(0, 0) : '+', (1, 1) : '-'}) + ```python + import pennylane as qml + fermi_ham = qml.fermi.FermiWord({(0, 0) : '+', (1, 1) : '-'}) + + qubit_ham = qml.fermi.parity_transform(fermi_ham, n=6) + ``` + + ```pycon + >>> print(qubit_ham) + (-0.25j*(PauliY(wires=[0]))) + ((-0.25+0j)*(PauliX(wires=[0]) @ PauliZ(wires=[1]))) + + ((0.25+0j)*(PauliX(wires=[0]))) + (0.25j*(PauliY(wires=[0]) @ PauliZ(wires=[1]))) + ``` - qubit_ham = qml.fermi.parity_transform(fermi_ham, n=6) - ``` +

Improvements 🛠

- ```pycon - >>> print(qubit_ham) - (-0.25j*(PauliY(wires=[0]))) + ((-0.25+0j)*(PauliX(wires=[0]) @ PauliZ(wires=[1]))) + - ((0.25+0j)*(PauliX(wires=[0]))) + (0.25j*(PauliY(wires=[0]) @ PauliZ(wires=[1]))) - ``` +* The `default.qubit` device now supports mid-circuit measurements without using the deferred measurement + principle when using finite shots. The native execution mode comprises all features supported with `qml.defer_measurements`, including + classical control, collecting statistics, and post-selection. This PR notably introduces support for + post-selection, measurement value lists, and composite measurements. + [(#5120)](https://github.com/PennyLaneAI/pennylane/pull/5120) * The transform `split_non_commuting` now accepts measurements of type `probs`, `sample` and `counts` which accept both wires and observables. [(#4972)](https://github.com/PennyLaneAI/pennylane/pull/4972) * Improve efficiency of matrix calculation when operator is symmetric over wires - [(#3601)](https://github.com/PennyLaneAI/pennylane/pull/3601) + [(#3601)](https://github.com/PennyLaneAI/pennylane/pull/3601) * The module `pennylane/math/quantum.py` has now support for the min-entropy. [(#3959)](https://github.com/PennyLaneAI/pennylane/pull/3959/) @@ -342,13 +350,14 @@ (with potentially negative eigenvalues) has been implemented. [(#5048)](https://github.com/PennyLaneAI/pennylane/pull/5048) -* Controlled operators with a custom controlled version decomposes like how their - controlled counterpart decomposes, as opposed to decomposing into their controlled version. +* Controlled operators with a custom controlled version decomposes like how their controlled + counterpart decomposes, as opposed to decomposing into their controlled version. [(#5069)](https://github.com/PennyLaneAI/pennylane/pull/5069) [(#5125)](https://github.com/PennyLaneAI/pennylane/pull/5125/) - + For example: - ``` + + ```pycon >>> qml.ctrl(qml.RX(0.123, wires=1), control=0).decomposition() [ RZ(1.5707963267948966, wires=[1]), @@ -486,16 +495,16 @@ * `PauliSentence.wires` no longer imposes a false order. [(#5041)](https://github.com/PennyLaneAI/pennylane/pull/5041) -* `qml.qchem.import_state` now applies the chemist-to-physicist +* `qml.qchem.import_state` now applies the chemist-to-physicist sign convention when initializing a PennyLane state vector from - classically pre-computed wavefunctions. That is, it interleaves + classically pre-computed wavefunctions. That is, it interleaves spin-up/spin-down operators for the same spatial orbital index, - as standard in PennyLane (instead of commuting all spin-up - operators to the left, as is standard in quantum chemistry). + as standard in PennyLane (instead of commuting all spin-up + operators to the left, as is standard in quantum chemistry). [(#5114)](https://github.com/PennyLaneAI/pennylane/pull/5114) * Multi-wire controlled `CNOT` and `PhaseShift` can now be decomposed correctly. - [(#5125)](https://github.com/PennyLaneAI/pennylane/pull/5125/) + [(#5125)](https://github.com/PennyLaneAI/pennylane/pull/5125/) [(#5148)](https://github.com/PennyLaneAI/pennylane/pull/5148) * `draw_mpl` no longer raises an error when drawing a circuit containing an adjoint of a controlled operation. diff --git a/pennylane/devices/qubit/apply_operation.py b/pennylane/devices/qubit/apply_operation.py index a55bc57f367..4c6e2c6bc12 100644 --- a/pennylane/devices/qubit/apply_operation.py +++ b/pennylane/devices/qubit/apply_operation.py @@ -231,7 +231,7 @@ def apply_conditional( Returns: ndarray: output state """ - if mid_measurements[op.meas_val.measurements[0]]: + if op.meas_val.concretize(mid_measurements): return apply_operation( op.then_op, state, @@ -260,17 +260,20 @@ def apply_mid_measure( """ if is_state_batched: raise ValueError("MidMeasureMP cannot be applied to batched states.") + if not np.allclose(np.linalg.norm(state), 1.0): + mid_measurements[op] = 0 + return np.zeros_like(state) wire = op.wires probs = qml.devices.qubit.measure(qml.probs(wire), state) sample = np.random.binomial(1, probs[1]) mid_measurements[op] = sample + if op.postselect is not None and sample != op.postselect: + return np.zeros_like(state) axis = wire.toarray()[0] slices = [slice(None)] * qml.math.ndim(state) slices[axis] = int(not sample) state[tuple(slices)] = 0.0 state_norm = np.linalg.norm(state) - if state_norm < 1.0e-15: - raise ValueError("Cannot normalize projected state.") state = state / state_norm if op.reset and sample == 1: state = apply_operation( diff --git a/pennylane/devices/qubit/simulate.py b/pennylane/devices/qubit/simulate.py index 5b2d00fad92..b90a49baa93 100644 --- a/pennylane/devices/qubit/simulate.py +++ b/pennylane/devices/qubit/simulate.py @@ -14,8 +14,8 @@ """Simulate a quantum script.""" # pylint: disable=protected-access from collections import Counter -from functools import singledispatch -from typing import Optional +from typing import Optional, Sequence +import warnings from numpy.random import default_rng import numpy as np @@ -300,22 +300,29 @@ def simulate_native_mcm( results.append(simulate_native_mcm(aux_circuit, rng, prng_key, debugger, interface)) return tuple(results) aux_circuit = init_auxiliary_circuit(circuit) - all_shot_meas, list_mcm_values_dict = None, [] + all_shot_meas, list_mcm_values_dict, valid_shots = None, [], 0 for _ in range(circuit.shots.total_shots): one_shot_meas, mcm_values_dict = simulate_one_shot_native_mcm( aux_circuit, rng, prng_key, debugger, interface ) + if one_shot_meas is None: + continue + valid_shots += 1 all_shot_meas = accumulate_native_mcm(aux_circuit, all_shot_meas, one_shot_meas) list_mcm_values_dict.append(mcm_values_dict) + if not valid_shots: + warnings.warn( + "All shots were thrown away as invalid. This can happen for example when post-selecting the 1-branch of a 0-state. Make sure your circuit has some probability of producing a valid shot.", + UserWarning, + ) return parse_native_mid_circuit_measurements(circuit, all_shot_meas, list_mcm_values_dict) def init_auxiliary_circuit(circuit: qml.tape.QuantumScript): """Creates an auxiliary circuit to perform one-shot mid-circuit measurement calculations. - Measurements with non-trivial measurement values are removed from the script. VarianceMP - measurements are also replaced by SampleMP measurements, which are necessary to evaluate - the variance. + Measurements are replaced by SampleMP measurements on wires and observables found in the + original measurements. Args: circuit (QuantumTape): The original QuantumScript @@ -363,6 +370,8 @@ def simulate_one_shot_native_mcm( state, is_state_batched = get_final_state( circuit, debugger=debugger, interface=interface, mid_measurements=mcm_dict ) + if not np.allclose(np.linalg.norm(state), 1.0): + return None, mcm_dict return ( measure_final_state(circuit, state, is_state_batched, rng=rng, prng_key=prng_key), mcm_dict, @@ -383,7 +392,7 @@ def accumulate_native_mcm(circuit: qml.tape.QuantumScript, all_shot_meas, one_sh if len(circuit.measurements) == 1: one_shot_meas = [one_shot_meas] if all_shot_meas is None: - new_shot_meas = one_shot_meas + new_shot_meas = list(one_shot_meas) for i, (m, s) in enumerate(zip(circuit.measurements, new_shot_meas)): if isinstance(m, SampleMP) and isinstance(s, np.ndarray): new_shot_meas[i] = [s] @@ -394,10 +403,12 @@ def accumulate_native_mcm(circuit: qml.tape.QuantumScript, all_shot_meas, one_sh tmp = Counter(all_shot_meas[i]) tmp.update(Counter(one_shot_meas[i])) new_shot_meas[i] = tmp + elif isinstance(m, (ExpectationMP, ProbabilityMP)): + new_shot_meas[i] = all_shot_meas[i] + one_shot_meas[i] elif isinstance(m, SampleMP): new_shot_meas[i].append(one_shot_meas[i]) else: - new_shot_meas[i] = all_shot_meas[i] + one_shot_meas[i] + raise TypeError(f"Unsupported measurement of {type(m).__name__}.") return new_shot_meas @@ -415,34 +426,6 @@ def has_mid_circuit_measurements( return any(isinstance(op, MidMeasureMP) for op in circuit.operations) -def find_measurement_values( - circuit: qml.tape.QuantumScript, -): - """Returns the indices of measurements with a non-trivial measurement value. - - Args: - circuit (QuantumTape): A QuantumScript - - Returns: - List[int]: Indices of measurements with a non-trivial measurement value. - """ - return [i for i, m in enumerate(circuit.measurements) if m.mv] - - -def find_not_measurement_values( - circuit: qml.tape.QuantumScript, -): - """Returns the indices of measurements with a trivial measurement value. - - Args: - circuit (QuantumTape): A QuantumScript - - Returns: - List[int]: Indices of measurements with a trivial measurement value. - """ - return [i for i, m in enumerate(circuit.measurements) if not m.mv] - - def parse_native_mid_circuit_measurements( circuit: qml.tape.QuantumScript, all_shot_meas, mcm_shot_meas ): @@ -456,20 +439,32 @@ def parse_native_mid_circuit_measurements( Returns: tuple(TensorLike): The results of the simulation """ - idx_one_shot = find_not_measurement_values(circuit) - normalized_meas = [None] * len(circuit.measurements) - for i, m in zip(idx_one_shot, all_shot_meas): - normalized_meas[i] = gather_non_mcm(circuit.measurements[i], m, mcm_shot_meas) - - idx_sample = find_measurement_values(circuit) - counter = Counter() - if any(isinstance(m, (CountsMP, ProbabilityMP)) for m in circuit.measurements): - for d in mcm_shot_meas: - counter.update(d) - for i in idx_sample: - normalized_meas[i] = gather_mcm( - circuit.measurements[i], circuit.measurements[i].mv, mcm_shot_meas, counter + + def measurement_with_no_shots(measurement): + return ( + np.nan * np.ones_like(measurement.eigvals()) + if isinstance(measurement, ProbabilityMP) + else np.nan ) + + normalized_meas = [] + for i, m in enumerate(circuit.measurements): + if not isinstance(m, (CountsMP, ExpectationMP, ProbabilityMP, SampleMP, VarianceMP)): + raise ValueError( + f"Native mid-circuit measurement mode does not support {type(m).__name__} measurements." + ) + if m.mv and not mcm_shot_meas: + meas = measurement_with_no_shots(m) + elif m.mv: + meas = gather_mcm(m, mcm_shot_meas) + elif not all_shot_meas: + meas = measurement_with_no_shots(m) + else: + meas = gather_non_mcm(m, all_shot_meas[i], mcm_shot_meas) + if isinstance(m, SampleMP): + meas = qml.math.squeeze(meas) + normalized_meas.append(meas) + return tuple(normalized_meas) if len(normalized_meas) > 1 else normalized_meas[0] @@ -484,65 +479,49 @@ def gather_non_mcm(circuit_measurement, measurement, samples): Returns: TensorLike: The combined measurement outcome """ + if isinstance(circuit_measurement, CountsMP): + return dict(sorted(measurement.items())) if isinstance(circuit_measurement, (ExpectationMP, ProbabilityMP)): - new_meas = measurement / len(samples) - elif isinstance(circuit_measurement, SampleMP): - new_meas = np.concatenate(tuple(s.ravel() for s in measurement)) - elif isinstance(circuit_measurement, CountsMP): - new_meas = dict(sorted(measurement.items())) - elif isinstance(circuit_measurement, VarianceMP): - new_meas = qml.math.var(np.concatenate(tuple(s.ravel() for s in measurement))) - else: - raise ValueError( - f"Native mid-circuit measurement mode does not support {circuit_measurement.__class__.__name__} measurements." - ) - return new_meas + return measurement / len(samples) + if isinstance(circuit_measurement, SampleMP): + return np.squeeze(np.concatenate(tuple(s.reshape(1, -1) for s in measurement))) + # VarianceMP + return qml.math.var(np.concatenate(tuple(s.ravel() for s in measurement))) -@singledispatch -def gather_mcm(measurement, mv, samples, counter): # pylint: disable=unused-argument +def gather_mcm(measurement, samples): """Combines, gathers and normalizes several measurements with non-trivial measurement values. Args: measurement (MeasurementProcess): measurement - mv (MeasurementValue): measurement value samples (List[dict]): Mid-circuit measurement samples - counter (Counter): Measurement value counts Returns: TensorLike: The combined measurement outcome """ - raise ValueError( - f"Native mid-circuit measurement mode does not support {measurement.__class__.__name__} measurements." - ) - - -@gather_mcm.register -def _(measurement: CountsMP, mv, samples, counter): # pylint: disable=unused-argument - new_samples = {} - if len(samples) - counter[mv.measurements[0]] > 0: - new_samples[0] = len(samples) - counter[mv.measurements[0]] - if counter[mv.measurements[0]] > 0: - new_samples[1] = counter[mv.measurements[0]] - return new_samples - - -@gather_mcm.register -def _(measurement: ExpectationMP, mv, samples, counter): # pylint: disable=unused-argument - return np.mean(np.array([dct[mv.measurements[0]] for dct in samples])) - - -@gather_mcm.register -def _(measurement: ProbabilityMP, mv, samples, counter): # pylint: disable=unused-argument - p1 = counter[mv.measurements[0]] / float(len(samples)) - return np.array([1 - p1, p1]) - - -@gather_mcm.register -def _(measurement: SampleMP, mv, samples, counter): # pylint: disable=unused-argument - return np.array([dct[mv.measurements[0]] for dct in samples]) - - -@gather_mcm.register -def _(measurement: VarianceMP, mv, samples, counter): # pylint: disable=unused-argument - return qml.math.var(np.array([dct[mv.measurements[0]] for dct in samples])) + mv = measurement.mv + if isinstance(measurement, (CountsMP, ProbabilityMP, SampleMP)) and isinstance(mv, Sequence): + wires = qml.wires.Wires(range(len(mv))) + mcm_samples = list( + np.array([m.concretize(dct) for dct in samples]).reshape((-1, 1)) for m in mv + ) + mcm_samples = np.concatenate(mcm_samples, axis=1) + meas_tmp = measurement.__class__(wires=wires) + return meas_tmp.process_samples(mcm_samples, wire_order=wires) + mcm_samples = np.array([mv.concretize(dct) for dct in samples]).reshape((-1, 1)) + use_as_is = len(mv.measurements) == 1 + if use_as_is: + wires, meas_tmp = mv.wires, measurement + else: + # For composite measurements, `mcm_samples` has one column but + # `mv.wires` usually includes several wires. We therefore need to create a + # single-wire measurement for `process_samples` to handle the conversion + # correctly. + if isinstance(measurement, (ExpectationMP, VarianceMP)): + mcm_samples = mcm_samples.ravel() + wires = qml.wires.Wires(0) + meas_tmp = measurement.__class__(wires=wires) + new_measurement = meas_tmp.process_samples(mcm_samples, wire_order=wires) + if isinstance(measurement, CountsMP) and not use_as_is: + new_measurement = dict(sorted((int(x, 2), y) for x, y in new_measurement.items())) + return new_measurement diff --git a/pennylane/measurements/mid_measure.py b/pennylane/measurements/mid_measure.py index ea2ff4a4e8a..589335c48bc 100644 --- a/pennylane/measurements/mid_measure.py +++ b/pennylane/measurements/mid_measure.py @@ -400,6 +400,11 @@ def _apply(self, fn): """Apply a post computation to this measurement""" return MeasurementValue(self.measurements, lambda *x: fn(self.processing_fn(*x))) + def concretize(self, measurements: dict): + """Returns a concrete value from a dictionary of hashes with concrete values.""" + values = tuple(measurements[meas] for meas in self.measurements) + return self.processing_fn(*values) + def _merge(self, other: "MeasurementValue"): """Merge two measurement values""" diff --git a/pennylane/typing.py b/pennylane/typing.py index 3b10f00de60..979034bba2d 100644 --- a/pennylane/typing.py +++ b/pennylane/typing.py @@ -86,7 +86,7 @@ def _is_jax(other, subclass=False): jax.Array # TODO: keep this after jax>=0.4 is required if hasattr(jax, "Array") else Union[jaxlib.xla_extension.DeviceArray, jax.core.Tracer] - ), + ), # pylint: disable=c-extension-no-member ] check = issubclass if subclass else isinstance diff --git a/tests/devices/default_qubit/test_default_qubit.py b/tests/devices/default_qubit/test_default_qubit.py index 06925409e85..6288f149583 100644 --- a/tests/devices/default_qubit/test_default_qubit.py +++ b/tests/devices/default_qubit/test_default_qubit.py @@ -15,6 +15,7 @@ # pylint: disable=import-outside-toplevel, no-member, too-many-arguments from unittest import mock +from flaky import flaky import pytest import numpy as np @@ -1706,6 +1707,7 @@ def circ_expected(): assert qml.math.allclose(res, expected) assert qml.math.get_interface(res) == qml.math.get_interface(expected) + @flaky(max_runs=5) @pytest.mark.parametrize( "mp", [ diff --git a/tests/devices/default_qubit/test_default_qubit_native_mcm.py b/tests/devices/default_qubit/test_default_qubit_native_mcm.py index 3da8f71bc86..5d953167520 100644 --- a/tests/devices/default_qubit/test_default_qubit_native_mcm.py +++ b/tests/devices/default_qubit/test_default_qubit_native_mcm.py @@ -12,6 +12,8 @@ # See the License for the specific language governing permissions and # limitations under the License. """Tests for default qubit preprocessing.""" +from functools import reduce +from typing import Sequence from flaky import flaky import numpy as np @@ -19,41 +21,80 @@ import pennylane as qml from pennylane.devices.qubit.apply_operation import apply_mid_measure, MidMeasureMP -from pennylane.devices.qubit.simulate import gather_mcm +from pennylane.devices.qubit.simulate import ( + accumulate_native_mcm, + parse_native_mid_circuit_measurements, +) def validate_counts(shots, results1, results2): - if isinstance(results1, (list, tuple)): + """Compares two counts. + + If the results are ``Sequence``s, loop over entries. + + Fails if a key of ``results1`` is not found in ``results2``. + Passes if counts are too low, chosen as ``100``. + Otherwise, fails if counts differ by more than ``20`` plus 20 percent. + """ + if isinstance(results1, Sequence): + assert isinstance(results2, Sequence) assert len(results1) == len(results2) for r1, r2 in zip(results1, results2): validate_counts(shots, r1, r2) return - ncounts = 0.5 * (sum(results1.values()) + sum(results2.values())) - for r1, r2 in zip(sorted(results1.items()), sorted(results2.items())): - assert abs(sum(r1) - sum(r2)) < (ncounts // 10) + for key1, val1 in results1.items(): + val2 = results2[key1] + if abs(val1 + val2) > 100: + assert np.allclose(val1, val2, rtol=20, atol=0.2) def validate_samples(shots, results1, results2): - for res in [results1, results2]: - if isinstance(shots, (list, tuple)): - assert len(res) == len(shots) - assert all(r.shape == (s,) for r, s in zip(res, shots)) - assert all( - abs(sum(r1) - sum(r2)) < (s // 10) for r1, r2, s in zip(results1, results2, shots) - ) - else: - assert res.shape == (shots,) - assert abs(sum(results1) - sum(results2)) < (shots // 10) + """Compares two samples. + + If the results are ``Sequence``s, loop over entries. + + Fails if the results do not have the same shape, within ``20`` entries plus 20 percent. + This is to handle cases when post-selection yields variable shapes. + Otherwise, fails if the sums of samples differ by more than ``20`` plus 20 percent. + """ + if isinstance(shots, Sequence): + assert isinstance(results1, Sequence) + assert isinstance(results2, Sequence) + assert len(results1) == len(results2) + for s, r1, r2 in zip(shots, results1, results2): + validate_samples(s, r1, r2) + else: + sh1, sh2 = results1.shape[0], results2.shape[0] + assert np.allclose(sh1, sh2, rtol=20, atol=0.2) + assert results1.ndim == results2.ndim + if results2.ndim > 1: + assert results1.shape[1] == results2.shape[1] + np.allclose(np.sum(results1), np.sum(results2), rtol=20, atol=0.2) def validate_expval(shots, results1, results2): + """Compares two expval, probs or var. + + If the results are ``Sequence``s, validate the average of items. + + If ``shots is None``, validate using ``np.allclose``'s default parameters. + Otherwise, fails if the results do not match within ``0.01`` plus 20 percent. + """ + if isinstance(results1, Sequence): + assert isinstance(results2, Sequence) + assert len(results1) == len(results2) + results1 = reduce(lambda x, y: x + y, results1) / len(results1) + results2 = reduce(lambda x, y: x + y, results2) / len(results2) + validate_expval(shots, results1, results2) + return if shots is None: assert np.allclose(results1, results2) return - assert np.allclose(results1, results2, atol=0, rtol=0.3) + assert np.allclose(results1, results2, atol=0.01, rtol=0.2) def validate_measurements(func, shots, results1, results2): + """Calls the correct validation function based on measurement type.""" if func is qml.counts: validate_counts(shots, results1, results2) return @@ -70,8 +111,58 @@ def test_apply_mid_measure(): _ = apply_mid_measure( MidMeasureMP(0), np.zeros((2, 2)), is_state_batched=True, mid_measurements={} ) - with pytest.raises(ValueError, match="Cannot normalize projected state."): - _ = apply_mid_measure(MidMeasureMP(0), np.zeros(2), mid_measurements={}) + m0 = MidMeasureMP(0, postselect=1) + mid_measurements = {} + state = apply_mid_measure(m0, np.zeros(2), mid_measurements=mid_measurements) + assert mid_measurements[m0] == 0 + assert np.allclose(state, 0.0) + state = apply_mid_measure(m0, np.array([1, 0]), mid_measurements=mid_measurements) + assert mid_measurements[m0] == 0 + assert np.allclose(state, 0.0) + + +def test_accumulate_native_mcm_unsupported_error(): + with pytest.raises( + TypeError, match=f"Unsupported measurement of {type(qml.var(qml.PauliZ(0))).__name__}" + ): + accumulate_native_mcm(qml.tape.QuantumScript([], [qml.var(qml.PauliZ(0))]), [None], [None]) + + +def test_all_invalid_shots_circuit(): + + dev = qml.device("default.qubit") + + @qml.qnode(dev) + def circuit_op(): + m = qml.measure(0, postselect=1) + qml.cond(m, qml.PauliX)(1) + return ( + qml.expval(op=qml.PauliZ(1)), + qml.probs(op=qml.PauliY(0) @ qml.PauliZ(1)), + qml.var(op=qml.PauliZ(1)), + ) + + res1 = circuit_op() + res2 = circuit_op(shots=10) + for r1, r2 in zip(res1, res2): + if isinstance(r1, Sequence): + assert len(r1) == len(r2) + assert np.all(np.isnan(r1)) + assert np.all(np.isnan(r2)) + + @qml.qnode(dev) + def circuit_mcm(): + m = qml.measure(0, postselect=1) + qml.cond(m, qml.PauliX)(1) + return qml.expval(op=m), qml.probs(op=m), qml.var(op=m) + + res1 = circuit_mcm() + res2 = circuit_mcm(shots=10) + for r1, r2 in zip(res1, res2): + if isinstance(r1, Sequence): + assert len(r1) == len(r2) + assert np.all(np.isnan(r1)) + assert np.all(np.isnan(r2)) @pytest.mark.parametrize( @@ -83,12 +174,12 @@ def test_apply_mid_measure(): qml.mutual_info(0, 1), qml.purity(0), qml.classical_shadow(0), - qml.shadow_expval(0), ], ) -def test_gather_mcm(measurement): +def test_parse_native_mid_circuit_measurements_unsupported_meas(measurement): + circuit = qml.tape.QuantumScript([qml.RX(1, 0)], [measurement]) with pytest.raises(ValueError, match="Native mid-circuit measurement mode does not support"): - gather_mcm(measurement, None, None, None) + parse_native_mid_circuit_measurements(circuit, None, None) def test_unsupported_measurement(): @@ -103,27 +194,29 @@ def func(x, y): return qml.classical_shadow(wires=0) with pytest.raises( - ValueError, - match="Native mid-circuit measurement mode does not support ClassicalShadowMP measurements.", + TypeError, + match=f"Unsupported measurement of {type(qml.classical_shadow(wires=0)).__name__}", ): func(*params) @flaky(max_runs=5) @pytest.mark.parametrize("shots", [None, 1000, [1000, 1001]]) +@pytest.mark.parametrize("postselect", [None, 0, 1]) @pytest.mark.parametrize("reset", [False, True]) -@pytest.mark.parametrize("measure_f", [qml.expval, qml.probs, qml.sample, qml.counts, qml.var]) -def test_single_mcm_single_measure_mcm(shots, reset, measure_f): +@pytest.mark.parametrize("measure_f", [qml.counts, qml.expval, qml.probs, qml.sample, qml.var]) +def test_single_mcm_single_measure_mcm(shots, postselect, reset, measure_f): """Tests that DefaultQubit handles a circuit with a single mid-circuit measurement and a conditional gate. A single measurement of the mid-circuit measurement value is performed at the end.""" + dev = qml.device("default.qubit", shots=shots) params = np.pi / 4 * np.ones(2) @qml.qnode(dev) def func1(x, y): qml.RX(x, wires=0) - m0 = qml.measure(0, reset=reset) + m0 = qml.measure(0, reset=reset, postselect=postselect) qml.cond(m0, qml.RY)(y, wires=1) return measure_f(op=m0) @@ -135,26 +228,78 @@ def func1(x, y): results1 = func1(*params) results2 = func2(*params) - validate_measurements(measure_f, shots, results1, results2) + if postselect is None or measure_f in (qml.expval, qml.probs, qml.var): + validate_measurements(measure_f, shots, results1, results2) + + +# pylint: disable=unused-argument +def obs_tape(x, y, z, reset=False, postselect=None): + qml.RX(x, 0) + qml.RZ(np.pi / 4, 0) + m0 = qml.measure(0, reset=reset) + qml.cond(m0 == 0, qml.RX)(np.pi / 4, 0) + qml.cond(m0 == 0, qml.RZ)(np.pi / 4, 0) + qml.cond(m0 == 1, qml.RX)(-np.pi / 4, 0) + qml.cond(m0 == 1, qml.RZ)(-np.pi / 4, 0) + qml.RX(y, 1) + qml.RZ(np.pi / 4, 1) + m1 = qml.measure(1, postselect=postselect) + qml.cond(m1 == 0, qml.RX)(np.pi / 4, 1) + qml.cond(m1 == 0, qml.RZ)(np.pi / 4, 1) + qml.cond(m1 == 1, qml.RX)(-np.pi / 4, 1) + qml.cond(m1 == 1, qml.RZ)(-np.pi / 4, 1) + return m0, m1 @flaky(max_runs=5) -@pytest.mark.parametrize("shots", [None, 1000, [1000, 1001]]) +@pytest.mark.parametrize("shots", [None, 5000, [5000, 5001]]) +@pytest.mark.parametrize("postselect", [None, 0, 1]) +@pytest.mark.parametrize("reset", [False, True]) +@pytest.mark.parametrize("measure_f", [qml.counts, qml.expval, qml.probs, qml.sample, qml.var]) +@pytest.mark.parametrize("obs", [qml.PauliZ(0), qml.PauliY(1), qml.PauliZ(0) @ qml.PauliY(1)]) +def test_single_mcm_single_measure_obs(shots, postselect, reset, measure_f, obs): + """Tests that DefaultQubit handles a circuit with a single mid-circuit measurement and a + conditional gate. A single measurement of a common observable is performed at the end.""" + + dev = qml.device("default.qubit", shots=shots) + params = [np.pi / 7, np.pi / 6, -np.pi / 5] + + @qml.qnode(dev) + def func1(x, y, z): + obs_tape(x, y, z, reset=reset, postselect=postselect) + return measure_f(op=obs) + + func2 = qml.defer_measurements(func1) + + if shots is None and measure_f in (qml.counts, qml.sample): + return + + results1 = func1(*params) + results2 = func2(*params) + + if postselect is None or measure_f in (qml.expval, qml.probs, qml.var): + validate_measurements(measure_f, shots, results1, results2) + + +@flaky(max_runs=5) +@pytest.mark.parametrize("shots", [None, 3000, [3000, 3001]]) +@pytest.mark.parametrize("postselect", [None, 0, 1]) @pytest.mark.parametrize("reset", [False, True]) -@pytest.mark.parametrize("measure_f", [qml.expval, qml.probs, qml.sample, qml.counts, qml.var]) -def test_single_mcm_single_measure_obs(shots, reset, measure_f): +@pytest.mark.parametrize("measure_f", [qml.counts, qml.probs, qml.sample]) +@pytest.mark.parametrize("wires", [[0], [0, 1]]) +def test_single_mcm_single_measure_wires(shots, postselect, reset, measure_f, wires): """Tests that DefaultQubit handles a circuit with a single mid-circuit measurement and a - conditional gate. A single measurement of a common observable is is performed at the end.""" + conditional gate. A single measurement of one or several wires is performed at the end.""" + dev = qml.device("default.qubit", shots=shots) params = np.pi / 4 * np.ones(2) - obs = qml.PauliZ(0) @qml.qnode(dev) def func1(x, y): qml.RX(x, wires=0) - m0 = qml.measure(0, reset=reset) + m0 = qml.measure(0, reset=reset, postselect=postselect) qml.cond(m0, qml.RY)(y, wires=1) - return measure_f(op=obs) + return measure_f(wires=wires) func2 = qml.defer_measurements(func1) @@ -164,32 +309,169 @@ def func1(x, y): results1 = func1(*params) results2 = func2(*params) - validate_measurements(measure_f, shots, results1, results2) + if postselect is None or measure_f in (qml.expval, qml.probs, qml.var): + validate_measurements(measure_f, shots, results1, results2) @flaky(max_runs=5) -@pytest.mark.parametrize("shots", [1000]) +@pytest.mark.parametrize("shots", [5000]) +@pytest.mark.parametrize("postselect", [None, 0, 1]) @pytest.mark.parametrize("reset", [False, True]) -@pytest.mark.parametrize("measure_f", [qml.expval, qml.probs, qml.sample, qml.counts, qml.var]) -def test_single_mcm_multiple_measurements(shots, reset, measure_f): +@pytest.mark.parametrize("measure_f", [qml.counts, qml.expval, qml.probs, qml.sample, qml.var]) +def test_single_mcm_multiple_measurements(shots, postselect, reset, measure_f): """Tests that DefaultQubit handles a circuit with a single mid-circuit measurement with reset and a conditional gate. Multiple measurements of the mid-circuit measurement value are performed.""" + dev = qml.device("default.qubit", shots=shots) - params = np.pi / 4 * np.ones(2) - obs = qml.PauliZ(0) + params = [np.pi / 7, np.pi / 6, -np.pi / 5] + obs = qml.PauliY(1) @qml.qnode(dev) - def func1(x, y): - qml.RX(x, wires=0) - m0 = qml.measure(0, reset=reset) - qml.cond(m0, qml.RY)(y, wires=1) - return measure_f(op=obs), measure_f(op=m0) + def func1(x, y, z): + mcms = obs_tape(x, y, z, reset=reset, postselect=postselect) + return measure_f(op=obs), measure_f(op=mcms[0]) + + func2 = qml.defer_measurements(func1) + + results1 = func1(*params) + results2 = func2(*params) + + if postselect is None or measure_f in (qml.expval, qml.probs, qml.var): + for r1, r2 in zip(results1, results2): + validate_measurements(measure_f, shots, r1, r2) + + +@flaky(max_runs=5) +@pytest.mark.parametrize("shots", [None, 5000, [5000, 5001]]) +@pytest.mark.parametrize("postselect", [None, 0, 1]) +@pytest.mark.parametrize("reset", [False, True]) +@pytest.mark.parametrize("measure_f", [qml.counts, qml.expval, qml.sample, qml.var]) +def test_composite_mcm_measure_composite_mcm(shots, postselect, reset, measure_f): + """Tests that DefaultQubit handles a circuit with a composite mid-circuit measurement and a + conditional gate. A single measurement of a composite mid-circuit measurement is performed + at the end.""" + + dev = qml.device("default.qubit", shots=shots) + param = np.pi / 3 + + @qml.qnode(dev) + def func1(x): + qml.RX(x, 0) + m0 = qml.measure(0) + qml.RX(0.5 * x, 1) + m1 = qml.measure(1, reset=reset, postselect=postselect) + qml.cond((m0 + m1) == 2, qml.RY)(2.0 * x, 0) + m2 = qml.measure(0) + return measure_f(op=(m0 - 2 * m1) * m2 + 7) + + func2 = qml.defer_measurements(func1) + + if shots is None and measure_f in (qml.counts, qml.sample): + return + + results1 = func1(param) + results2 = func2(param) + + if postselect is None or measure_f in (qml.expval, qml.probs, qml.var): + validate_measurements(measure_f, shots, results1, results2) + + +@flaky(max_runs=5) +@pytest.mark.parametrize("shots", [None, 5000, [5000, 5001]]) +@pytest.mark.parametrize("postselect", [None, 0, 1]) +@pytest.mark.parametrize("reset", [False, True]) +@pytest.mark.parametrize("measure_f", [qml.counts, qml.expval, qml.probs, qml.sample, qml.var]) +def test_composite_mcm_single_measure_obs(shots, postselect, reset, measure_f): + """Tests that DefaultQubit handles a circuit with a composite mid-circuit measurement and a + conditional gate. A single measurement of a common observable is performed at the end.""" + + dev = qml.device("default.qubit", shots=shots) + params = [np.pi / 7, np.pi / 6, -np.pi / 5] + obs = qml.PauliZ(0) @ qml.PauliY(1) + + @qml.qnode(dev) + def func1(x, y, z): + mcms = obs_tape(x, y, z, reset=reset, postselect=postselect) + qml.cond(mcms[0] != mcms[1], qml.RY)(z, wires=0) + qml.cond(mcms[0] == mcms[1], qml.RY)(z, wires=1) + return measure_f(op=obs) func2 = qml.defer_measurements(func1) + if shots is None and measure_f in (qml.counts, qml.sample): + return + results1 = func1(*params) results2 = func2(*params) - for r1, r2 in zip(results1, results2): - validate_measurements(measure_f, shots, r1, r2) + if postselect is None or measure_f in (qml.expval, qml.probs, qml.var): + validate_measurements(measure_f, shots, results1, results2) + + +@flaky(max_runs=5) +@pytest.mark.parametrize("shots", [5000, [5000, 5001]]) +@pytest.mark.parametrize("postselect", [None, 0, 1]) +@pytest.mark.parametrize("reset", [False, True]) +@pytest.mark.parametrize("measure_f", [qml.counts, qml.probs, qml.sample]) +def test_composite_mcm_measure_value_list(shots, postselect, reset, measure_f): + """Tests that DefaultQubit handles a circuit with a composite mid-circuit measurement and a + conditional gate. A single measurement of a composite mid-circuit measurement is performed + at the end.""" + + dev = qml.device("default.qubit", shots=shots) + param = np.pi / 3 + + @qml.qnode(dev) + def func1(x): + qml.RX(x, 0) + m0 = qml.measure(0) + qml.RX(0.5 * x, 1) + m1 = qml.measure(1, reset=reset, postselect=postselect) + qml.cond((m0 + m1) == 2, qml.RY)(2.0 * x, 0) + m2 = qml.measure(0) + return measure_f(op=[m0, m1, m2]) + + func2 = qml.defer_measurements(func1) + + results1 = func1(param) + results2 = func2(param) + + validate_measurements(measure_f, shots, results1, results2) + + +@flaky(max_runs=5) +@pytest.mark.parametrize("shots", [5000]) +@pytest.mark.parametrize("postselect", [None, 0, 1]) +@pytest.mark.parametrize("reset", [False, True]) +@pytest.mark.parametrize("measure_f", [qml.expval]) +def composite_mcm_gradient_measure_obs(shots, postselect, reset, measure_f): + """Tests that DefaultQubit can differentiate a circuit with a composite mid-circuit + measurement and a conditional gate. A single measurement of a common observable is + performed at the end.""" + + dev = qml.device("default.qubit", shots=shots) + param = qml.numpy.array([np.pi / 3, np.pi / 6]) + obs = qml.PauliZ(0) @ qml.PauliZ(1) + + @qml.qnode(dev, diff_method="parameter-shift") + def func1(x, y): + qml.RX(x, 0) + m0 = qml.measure(0) + qml.RX(y, 1) + m1 = qml.measure(1, reset=reset, postselect=postselect) + qml.cond((m0 + m1) == 2, qml.RY)(2 * np.pi / 3, 0) + qml.cond((m0 + m1) > 0, qml.RY)(2 * np.pi / 3, 1) + return measure_f(op=obs) + + func2 = qml.defer_measurements(func1) + + results1 = func1(*param) + results2 = func2(*param) + + validate_measurements(measure_f, shots, results1, results2) + + grad1 = qml.grad(func1)(*param) + grad2 = qml.grad(func2)(*param) + + assert np.allclose(grad1, grad2, atol=0.01, rtol=0.3) diff --git a/tests/measurements/test_expval.py b/tests/measurements/test_expval.py index f25c51a39b5..21c36428de9 100644 --- a/tests/measurements/test_expval.py +++ b/tests/measurements/test_expval.py @@ -113,10 +113,10 @@ def circuit(phi): m0 = qml.measure(0) return qml.expval(m0) - res = circuit(phi) - atol = tol if shots is None else tol_stochastic - assert np.allclose(np.array(res), np.sin(phi / 2) ** 2, atol=atol, rtol=0) + for func in [circuit, qml.defer_measurements(circuit)]: + res = func(phi) + assert np.allclose(np.array(res), np.sin(phi / 2) ** 2, atol=atol, rtol=0) @pytest.mark.parametrize("shots", [None, 10000, [10000, 10000]]) @pytest.mark.parametrize("phi", np.arange(0, 2 * np.pi, np.pi / 3)) @@ -127,7 +127,6 @@ def test_observable_is_composite_measurement_value( are correct for a composite measurement value.""" dev = qml.device("default.qubit") - @qml.defer_measurements @qml.qnode(dev) def circuit(phi): qml.RX(phi, 0) @@ -138,8 +137,6 @@ def circuit(phi): m2 = qml.measure(2) return qml.expval(m0 * m1 + m2) - res = circuit(phi, shots=shots) - @qml.qnode(dev) def expected_circuit(phi): qml.RX(phi, 0) @@ -155,7 +152,9 @@ def expected_circuit(phi): expected = evals[0] * evals[1] + evals[2] atol = tol if shots is None else tol_stochastic - assert np.allclose(np.array(res), expected, atol=atol, rtol=0) + for func in [circuit, qml.defer_measurements(circuit)]: + res = func(phi, shots=shots) + assert np.allclose(np.array(res), expected, atol=atol, rtol=0) def test_measurement_value_list_not_allowed(self): """Test that measuring a list of measurement values raises an error.""" diff --git a/tests/measurements/test_probs.py b/tests/measurements/test_probs.py index 48c1aa1ab0c..1b4c1cb1bca 100644 --- a/tests/measurements/test_probs.py +++ b/tests/measurements/test_probs.py @@ -262,19 +262,19 @@ def circuit(phi): m0 = qml.measure(0) return qml.probs(op=m0) - res = circuit(phi) - atol = tol if shots is None else tol_stochastic expected = np.array([np.cos(phi / 2) ** 2, np.sin(phi / 2) ** 2]) - if not isinstance(shots, list): - assert np.allclose(np.array(res), expected, atol=atol, rtol=0) - else: - for r in res: # pylint: disable=not-an-iterable - assert np.allclose(r, expected, atol=atol, rtol=0) + for func in [circuit, qml.defer_measurements(circuit)]: + res = func(phi) + if not isinstance(shots, list): + assert np.allclose(np.array(res), expected, atol=atol, rtol=0) + else: + for r in res: # pylint: disable=not-an-iterable + assert np.allclose(r, expected, atol=atol, rtol=0) @pytest.mark.parametrize("shots", [None, 10000, [10000, 10000]]) - @pytest.mark.parametrize("phi", np.arange(0, 2 * np.pi, np.pi / 3)) + @pytest.mark.parametrize("phi", [0.0, np.pi / 3, np.pi]) def test_observable_is_measurement_value_list( self, shots, phi, tol, tol_stochastic ): # pylint: disable=too-many-arguments @@ -282,7 +282,6 @@ def test_observable_is_measurement_value_list( are correct for a measurement value list.""" dev = qml.device("default.qubit") - @qml.defer_measurements @qml.qnode(dev) def circuit(phi): qml.RX(phi, 0) diff --git a/tests/measurements/test_sample.py b/tests/measurements/test_sample.py index c6df2fc2fa7..527cc5863c9 100644 --- a/tests/measurements/test_sample.py +++ b/tests/measurements/test_sample.py @@ -165,13 +165,13 @@ def circuit(phi): m0 = qml.measure(0) return qml.sample(m0) - res = circuit(phi) - - if isinstance(shots, list): - assert len(res) == len(shots) - assert all(r.shape == (s,) for r, s in zip(res, shots)) - else: - assert res.shape == (shots,) + for func in [circuit, qml.defer_measurements(circuit)]: + res = func(phi) + if isinstance(shots, list): + assert len(res) == len(shots) + assert all(r.shape == (s,) for r, s in zip(res, shots)) + else: + assert res.shape == (shots,) @pytest.mark.parametrize("shots", [5, [5, 5]]) @pytest.mark.parametrize("phi", np.arange(0, 2 * np.pi, np.pi / 2)) @@ -180,7 +180,6 @@ def test_observable_is_composite_measurement_value(self, shots, phi): are correct for a composite measurement value.""" dev = qml.device("default.qubit", shots=shots) - @qml.defer_measurements @qml.qnode(dev) def circuit(phi): qml.RX(phi, 0) @@ -189,13 +188,13 @@ def circuit(phi): m1 = qml.measure(1) return qml.sample(op=m0 + m1) - res = circuit(phi) - - if isinstance(shots, list): - assert len(res) == len(shots) - assert all(r.shape == (s,) for r, s in zip(res, shots)) - else: - assert res.shape == (shots,) + for func in [circuit, qml.defer_measurements(circuit)]: + res = func(phi) + if isinstance(shots, list): + assert len(res) == len(shots) + assert all(r.shape == (s,) for r, s in zip(res, shots)) + else: + assert res.shape == (shots,) @pytest.mark.parametrize("shots", [5, [5, 5]]) @pytest.mark.parametrize("phi", np.arange(0, 2 * np.pi, np.pi / 2)) @@ -212,13 +211,13 @@ def circuit(phi): m1 = qml.measure(1) return qml.sample(op=[m0, m1]) - res = circuit(phi) - - if isinstance(shots, list): - assert len(res) == len(shots) - assert all(r.shape == (s, 2) for r, s in zip(res, shots)) - else: - assert res.shape == (shots, 2) + for func in [circuit, qml.defer_measurements(circuit)]: + res = func(phi) + if isinstance(shots, list): + assert len(res) == len(shots) + assert all(r.shape == (s, 2) for r, s in zip(res, shots)) + else: + assert res.shape == (shots, 2) def test_mixed_lists_as_op_not_allowed(self): """Test that passing a list not containing only measurement values raises an error.""" diff --git a/tests/measurements/test_var.py b/tests/measurements/test_var.py index 19b802c4acf..4ec1c4391a4 100644 --- a/tests/measurements/test_var.py +++ b/tests/measurements/test_var.py @@ -12,6 +12,7 @@ # See the License for the specific language governing permissions and # limitations under the License. """Unit tests for the var module""" +from flaky import flaky import numpy as np import pytest @@ -86,12 +87,13 @@ def circuit(phi): m0 = qml.measure(0) return qml.var(m0) - res = circuit(phi) - atol = tol if shots is None else tol_stochastic expected = np.sin(phi / 2) ** 2 - np.sin(phi / 2) ** 4 - assert np.allclose(np.array(res), expected, atol=atol, rtol=0) + for func in [circuit, qml.defer_measurements(circuit)]: + res = func(phi) + assert np.allclose(np.array(res), expected, atol=atol, rtol=0) + @flaky(max_runs=5) @pytest.mark.parametrize("shots", [None, 10000, [10000, 10000]]) @pytest.mark.parametrize("phi", np.arange(0, 2 * np.pi, np.pi / 3)) def test_observable_is_composite_measurement_value( @@ -101,7 +103,6 @@ def test_observable_is_composite_measurement_value( are correct for a composite measurement value.""" dev = qml.device("default.qubit") - @qml.defer_measurements @qml.qnode(dev) def circuit(phi): qml.RX(phi, 0) @@ -112,8 +113,6 @@ def circuit(phi): m2 = qml.measure(2) return qml.var(m0 - 2 * m1 + m2) - res = circuit(phi, shots=shots) - @qml.qnode(dev) def expected_circuit(phi): qml.RX(phi, 0) @@ -130,7 +129,9 @@ def expected_circuit(phi): ) atol = tol if shots is None else tol_stochastic - assert np.allclose(np.array(res), expected, atol=atol, rtol=0) + for func in [circuit, qml.defer_measurements(circuit)]: + res = func(phi, shots=shots) + assert np.allclose(np.array(res), expected, atol=atol, rtol=0) def test_measurement_value_list_not_allowed(self): """Test that measuring a list of measurement values raises an error."""