Added getter/setter, exception handling for OpflowQNN, CircuitQNN #79

stephenmurray2 · 2021-04-30T03:27:20Z

Summary

This PR closes #75:

Added getter and setter to OpflowQNN
In CircuitQNN, raises errors in methods for which a quantum_instance is required

Details and comments

My first PR in this repo, still figuring things out :)

CLAassistant · 2021-04-30T03:27:24Z

All committers have signed the CLA.

woodsp-ibm

Welcome and thanks for looking at this. I made some comments in regards of the aspects I know about this code.

qiskit_machine_learning/neural_networks/circuit_qnn.py

woodsp-ibm · 2021-04-30T20:10:37Z

qiskit_machine_learning/neural_networks/opflow_qnn.py

@@ -80,6 +80,16 @@ def __init__(self, operator: OperatorBase,
        super().__init__(len(self._input_params), len(self._weight_params),
                         sparse=False, output_shape=output_shape)

+    @property


I think the comments here are similar. The setter should allow Backend... and wrap it like in the constructor. Also I think it again needs to take care of CircuitSampler, that is setup in the constructor if the quantum instance is updated we need to redo that I think off the new quantum instance

qiskit_machine_learning/neural_networks/circuit_qnn.py

woodsp-ibm · 2021-04-30T20:12:53Z

qiskit_machine_learning/neural_networks/circuit_qnn.py

@@ -112,6 +115,8 @@ def _compute_output_shape(self, interpret, output_shape, sampling) -> Tuple[int,
        # this definition is required by mypy
        output_shape_: Tuple[int, ...] = (-1,)
        if sampling:
+            if not self._quantum_instance:


if self._quantum_instance is not None:

adekusar-drl

Thanks a lot for taking care of this, really appreciated!

qiskit_machine_learning/neural_networks/circuit_qnn.py

stephenmurray2 · 2021-05-01T17:10:20Z

@woodsp-ibm @adekusar-drl Thanks so much for the feedback, will address these comments shortly

into quantum-instance-checks � Conflicts: � qiskit_machine_learning/neural_networks/circuit_qnn.py

adekusar-drl

Please also make sure you reformat the code with black: make black. This is a new addition to the CI checks.

test/neural_networks/test_circuit_qnn.py

qiskit_machine_learning/neural_networks/circuit_qnn.py

…iskit-machine-learning into quantum-instance-checks

adekusar-drl · 2021-05-28T13:28:20Z

Looks good to me, thanks.

stefan-woerner

lgtm

into quantum-instance-checks � Conflicts: � test/neural_networks/test_circuit_qnn.py

qiskit_machine_learning/neural_networks/opflow_qnn.py

adekusar-drl · 2021-06-10T08:51:36Z

@stephenmurray2 Would you be able to finish the PR? There's just one open comment left.

into quantum-instance-checks

adekusar-drl · 2021-07-30T13:31:33Z

@woodsp-ibm please take a look, the code is heavily revised, you may consider it as a brand new version.

qiskit_machine_learning/neural_networks/circuit_qnn.py

qiskit_machine_learning/neural_networks/opflow_qnn.py

Co-authored-by: Steve Wood <40241007+woodsp-ibm@users.noreply.github.com>

into quantum-instance-checks

adekusar-drl · 2021-08-05T15:14:23Z

@woodsp-ibm could please take a look?

… into quantum-instance-checks

qiskit_machine_learning/neural_networks/circuit_qnn.py

dlasecki · 2021-08-10T13:54:59Z

qiskit_machine_learning/neural_networks/circuit_qnn.py

+        Returns:
+            None.


Not necessary because of the typehint. Please check other places.

Removed the return statements.

dlasecki · 2021-08-10T13:57:58Z

qiskit_machine_learning/neural_networks/opflow_qnn.py

        # this "if" statement is on purpose, to prevent sub-classes.
        # pylint:disable=unidiomatic-typecheck
        if type(op) == ListOp:
            shapes = []
            for op_ in op.oplist:
-                shape_ = self._get_output_shape_from_op(op_)
+                shape_ = self._compute_output_shape(op_)


Suggested change

shape_ = self._compute_output_shape(op_)

shapes = [self._compute_output_shape(op_) for op_ in op.oplist]

Updated. Let's focus on the changes introduced in the PR.

dlasecki · 2021-08-10T14:00:00Z

test/neural_networks/test_circuit_qnn.py

+        # sparse, sampling, quantum_instance_type, interpret (0=no, 1=1d, 2=2d), batch_size
+        (True, True, STATEVECTOR, 0, 1),
+        (True, True, STATEVECTOR, 0, 2),
+        (True, True, STATEVECTOR, 1, 1),
+        (True, True, STATEVECTOR, 1, 2),
+        (True, True, STATEVECTOR, 2, 1),
+        (True, True, STATEVECTOR, 2, 2),
+        (True, True, QASM, 0, 1),
+        (True, True, QASM, 0, 2),
+        (True, True, QASM, 1, 1),
+        (True, True, QASM, 1, 2),
+        (True, True, QASM, 2, 1),
+        (True, False, STATEVECTOR, 0, 1),
+        (True, False, STATEVECTOR, 0, 2),
+        (True, False, STATEVECTOR, 1, 1),
+        (True, False, STATEVECTOR, 1, 2),
+        (True, False, STATEVECTOR, 2, 1),
+        (True, False, STATEVECTOR, 2, 2),
+        (True, False, QASM, 0, 1),
+        (True, False, QASM, 0, 2),
+        (True, False, QASM, 1, 1),
+        (True, False, QASM, 1, 2),
+        (True, False, QASM, 2, 1),
+        (True, False, QASM, 2, 2),
+        (False, True, STATEVECTOR, 0, 1),
+        (False, True, STATEVECTOR, 0, 2),
+        (False, True, STATEVECTOR, 1, 1),
+        (False, True, STATEVECTOR, 1, 2),
+        (False, True, STATEVECTOR, 2, 1),
+        (False, True, STATEVECTOR, 2, 2),
+        (False, True, QASM, 0, 1),
+        (False, True, QASM, 0, 2),
+        (False, True, QASM, 1, 1),
+        (False, True, QASM, 1, 2),
+        (False, True, QASM, 2, 1),
+        (False, True, QASM, 2, 2),
+        (False, False, STATEVECTOR, 0, 1),
+        (False, False, STATEVECTOR, 0, 2),
+        (False, False, STATEVECTOR, 1, 1),
+        (False, False, STATEVECTOR, 1, 2),
+        (False, False, STATEVECTOR, 2, 1),
+        (False, False, STATEVECTOR, 2, 2),
+        (False, False, QASM, 0, 1),
+        (False, False, QASM, 0, 2),
+        (False, False, QASM, 1, 1),
+        (False, False, QASM, 1, 2),
+        (False, False, QASM, 2, 1),
+        (False, False, QASM, 2, 2),


So many lines of data could be extracted to a separate file.

Agree, but left as it is now. There should a consolidated change across all tests. And I'm not sure moving out such things to a separate file will solve the issue. Test parameters will be hidden, so I'm not convinced. Could be a dedicated function with a lot of nested loops better. But to be discussed, I think.

Since it looks like the whole data set there for the test is easily computed, just combinations of the parameters, it seems like some sort of simplification should be easily doable in the future at some point if desired.

Co-authored-by: dlasecki <dal@zurich.ibm.com>

… into quantum-instance-checks

adekusar-drl · 2021-08-11T12:47:15Z

@dlasecki thanks a lot!
@stephenmurray2 thanks for looking into it. I'm sorry for the "goodfirstissue" label, apparently it was misleading. This issue was not a very good first issue. Appreciated!

…skit-community#79) * added getter and setter, raises exception if no qi * set sampler in qi setter, added tests * added logic to setters, fixed tests * fix black * calling setter with instantiation * setters no longer accept optional qi * undid changes to docstrings * reset output shape within qi setter * revised implementation * fix spell * fix mypy * Update qiskit_machine_learning/neural_networks/circuit_qnn.py Co-authored-by: Steve Wood <40241007+woodsp-ibm@users.noreply.github.com> * Update qiskit_machine_learning/neural_networks/circuit_qnn.py Co-authored-by: Steve Wood <40241007+woodsp-ibm@users.noreply.github.com> * Update qiskit_machine_learning/neural_networks/opflow_qnn.py Co-authored-by: Steve Wood <40241007+woodsp-ibm@users.noreply.github.com> * code review * updated docstrings * Update qiskit_machine_learning/neural_networks/circuit_qnn.py Co-authored-by: dlasecki <dal@zurich.ibm.com> * Update qiskit_machine_learning/neural_networks/circuit_qnn.py Co-authored-by: dlasecki <dal@zurich.ibm.com> * code review * docstrings Co-authored-by: Anton Dekusar <adekusar@ie.ibm.com> Co-authored-by: Anton Dekusar <62334182+adekusar-drl@users.noreply.github.com> Co-authored-by: Manoel Marques <Manoel.Marques@ibm.com> Co-authored-by: Steve Wood <40241007+woodsp-ibm@users.noreply.github.com> Co-authored-by: dlasecki <dal@zurich.ibm.com>

* Update default batch_size in quantum_kernel (#150) The max circuits per job for most/all backend devices is 900. Setting batch_size=900 fixes an inefficient jobs being created. Co-authored-by: Anton Dekusar <adekusar@ie.ibm.com> Co-authored-by: Anton Dekusar <62334182+adekusar-drl@users.noreply.github.com> * This adds the callback feature for NN Classifier and Regressor (#112) (#151) * Added a wrapper `get_objective` method in `TrainableModel`, and `callback` argument to NN classifier `get_objective` returns a callable which is passed as objective function to NN classifier. It checks for a callable `callback` argument, which if not `None` can access the intermediate data during the optimization. * style changes * Updated callback tests for `NeuralNetworkClassifier` * Added callback for `NeuralNetworkRegressor` * Added tests for callback * Refactored `get_objective` * Added release note * Updated `callback` argument docstring * Shifted `callback` parameter to parent class `TrainableModel` * Added assertions for number of weights in `TestNeuralNetworkClassifier` `TestNeuralNetworkRegressor` * Rephrased release note and debugged tests for callback Co-authored-by: Anton Dekusar <62334182+adekusar-drl@users.noreply.github.com> Co-authored-by: Steve Wood <40241007+woodsp-ibm@users.noreply.github.com> Co-authored-by: Manoel Marques <Manoel.Marques@ibm.com> * Added ability to automatically handle categorical labels (#62) (#143) Added categorical label encoding * Added documentation * Update qiskit_machine_learning/algorithms/classifiers/neural_network_classifier.py * Update releasenotes/notes/cateforical-output-049e682adc9d1e28.yaml * Update releasenotes/notes/cateforical-output-049e682adc9d1e28.yaml * Update releasenotes/notes/cateforical-output-049e682adc9d1e28.yaml * Cleaned and organized code * Update qiskit_machine_learning/algorithms/classifiers/neural_network_classifier.py * Update qiskit_machine_learning/algorithms/classifiers/neural_network_classifier.py * Update qiskit_machine_learning/algorithms/classifiers/neural_network_classifier.py * Split categorical encoding into two functions for classifier's fit and score methods * Set sparse=False in one-hot encoder * removed unnecessary copy of arrays * Renamed methods and fixed label reshape * Added explanatory comments Co-authored-by: Steve Wood <40241007+woodsp-ibm@users.noreply.github.com> Co-authored-by: Manoel Marques <Manoel.Marques@ibm.com> Co-authored-by: Anton Dekusar <adekusar@ie.ibm.com> Co-authored-by: Anton Dekusar <62334182+adekusar-drl@users.noreply.github.com> * Add hybrid qnn unit tests for TorchConnector (#156) * Add hybrid qnn unit tests * Fix spelling * Add docstrings * Retry * Fix style * Register weight name * Update test * Separate hybrid tests * Fix spelling * Fix lint * Add comments * Remove unused functions * Add register weight param. reno * Clarify procedure * Remove unused import Co-authored-by: Anton Dekusar <62334182+adekusar-drl@users.noreply.github.com> Co-authored-by: Manoel Marques <Manoel.Marques@ibm.com> * Fixed variable name in file 03_quantum_kernel.ipynb . (#179) Co-authored-by: Steve Wood <40241007+woodsp-ibm@users.noreply.github.com> * Added getter/setter, exception handling for OpflowQNN, CircuitQNN (#79) * added getter and setter, raises exception if no qi * set sampler in qi setter, added tests * added logic to setters, fixed tests * fix black * calling setter with instantiation * setters no longer accept optional qi * undid changes to docstrings * reset output shape within qi setter * revised implementation * fix spell * fix mypy * Update qiskit_machine_learning/neural_networks/circuit_qnn.py Co-authored-by: Steve Wood <40241007+woodsp-ibm@users.noreply.github.com> * Update qiskit_machine_learning/neural_networks/circuit_qnn.py Co-authored-by: Steve Wood <40241007+woodsp-ibm@users.noreply.github.com> * Update qiskit_machine_learning/neural_networks/opflow_qnn.py Co-authored-by: Steve Wood <40241007+woodsp-ibm@users.noreply.github.com> * code review * updated docstrings * Update qiskit_machine_learning/neural_networks/circuit_qnn.py Co-authored-by: dlasecki <dal@zurich.ibm.com> * Update qiskit_machine_learning/neural_networks/circuit_qnn.py Co-authored-by: dlasecki <dal@zurich.ibm.com> * code review * docstrings Co-authored-by: Anton Dekusar <adekusar@ie.ibm.com> Co-authored-by: Anton Dekusar <62334182+adekusar-drl@users.noreply.github.com> Co-authored-by: Manoel Marques <Manoel.Marques@ibm.com> Co-authored-by: Steve Wood <40241007+woodsp-ibm@users.noreply.github.com> Co-authored-by: dlasecki <dal@zurich.ibm.com> * Global random seed (#178) * Made TrainableModel use global seed (issue #158) Made TrainableModel use RandomState object seeded by algorithm_globals.random_seed to choose an initial point for the optimizer outside of warm start. * Global random seed for QSVC constructor (issue #158) The value of algorithm_globals.random_seed is being used as random_state parameter for SVC constructor during construction of QSVC object. * Added Qiskit into requirements.txt (issu #158) Added Qiskit~=0.26.0 into requirements.txt, as qiskit.utils contain algorithm_globals object. * Added Qiskit into requirements.txt & improved code formatting (issue #158) Added Qiskit~=0.26.0 into requirements.txt, as qiskit.utils contain algorithm_globals object. * Removed unnecessary explicit requirement of Qiskit package (issue #158). * Simplified random number generation using global seed (issue #158). * random_state is now being randomly initialized only if not passed as parameter (issue #158). * Parameter 'random_state' now initialized by 'random_seed' in kwargs (issue #158). * Update qiskit_machine_learning/algorithms/trainable_model.py * Reverted incorrect changes to requirements.txt (issue #158). Co-authored-by: Anton Dekusar <62334182+adekusar-drl@users.noreply.github.com> Co-authored-by: Steve Wood <40241007+woodsp-ibm@users.noreply.github.com> * Fix `RawFeatureVector` copy (#182) * Fix num_qubits * Remove _num_qubits * Fix style * Add tests for copy, bind_parameters * Add Fix RawFeatVec reno * Fix typing * Fix test * Add reset registers * Fix num_qubits>0 * Fix mypy conflict * Fix black * Update if check Co-authored-by: Steve Wood <40241007+woodsp-ibm@users.noreply.github.com> * Add if check * Add comment * Modify reno * code review * code review * updated docstrings * code review Co-authored-by: Anton Dekusar <62334182+adekusar-drl@users.noreply.github.com> Co-authored-by: Steve Wood <40241007+woodsp-ibm@users.noreply.github.com> Co-authored-by: Anton Dekusar <adekusar@ie.ibm.com> * Prepare 0.2.1 release Co-authored-by: Anna Phan <9410731+attp@users.noreply.github.com> Co-authored-by: Anton Dekusar <adekusar@ie.ibm.com> Co-authored-by: Anton Dekusar <62334182+adekusar-drl@users.noreply.github.com> Co-authored-by: Darsh Kaushik <70013230+darshkaushik@users.noreply.github.com> Co-authored-by: Steve Wood <40241007+woodsp-ibm@users.noreply.github.com> Co-authored-by: Matt Wright <44040188+mattwright99@users.noreply.github.com> Co-authored-by: ElePT <57907331+ElePT@users.noreply.github.com> Co-authored-by: Martin Beseda <martinbeseda@seznam.cz> Co-authored-by: Stephen Murray <stephenandrewmurray@gmail.com> Co-authored-by: dlasecki <dal@zurich.ibm.com> Co-authored-by: Martin Beseda <martin.beseda@vsb.cz>

…skit-community#79) * added getter and setter, raises exception if no qi * set sampler in qi setter, added tests * added logic to setters, fixed tests * fix black * calling setter with instantiation * setters no longer accept optional qi * undid changes to docstrings * reset output shape within qi setter * revised implementation * fix spell * fix mypy * Update qiskit_machine_learning/neural_networks/circuit_qnn.py Co-authored-by: Steve Wood <40241007+woodsp-ibm@users.noreply.github.com> * Update qiskit_machine_learning/neural_networks/circuit_qnn.py Co-authored-by: Steve Wood <40241007+woodsp-ibm@users.noreply.github.com> * Update qiskit_machine_learning/neural_networks/opflow_qnn.py Co-authored-by: Steve Wood <40241007+woodsp-ibm@users.noreply.github.com> * code review * updated docstrings * Update qiskit_machine_learning/neural_networks/circuit_qnn.py Co-authored-by: dlasecki <dal@zurich.ibm.com> * Update qiskit_machine_learning/neural_networks/circuit_qnn.py Co-authored-by: dlasecki <dal@zurich.ibm.com> * code review * docstrings Co-authored-by: Anton Dekusar <adekusar@ie.ibm.com> Co-authored-by: Anton Dekusar <62334182+adekusar-drl@users.noreply.github.com> Co-authored-by: Manoel Marques <Manoel.Marques@ibm.com> Co-authored-by: Steve Wood <40241007+woodsp-ibm@users.noreply.github.com> Co-authored-by: dlasecki <dal@zurich.ibm.com>

added getter and setter, raises exception if no qi

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Merge branch 'main' of https://github.com/Qiskit/qiskit-machine-learning

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Merge branch 'main' into quantum-instance-checks

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set sampler in qi setter, added tests

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added logic to setters, fixed tests

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Merge branch 'quantum-instance-checks' of github.com:stephenmurray2/q…

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Merge branch 'main' into quantum-instance-checks

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Merge branch 'main' of https://github.com/Qiskit/qiskit-machine-learning

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revised implementation

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fix spell

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fix mypy

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Update qiskit_machine_learning/neural_networks/circuit_qnn.py

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Update qiskit_machine_learning/neural_networks/circuit_qnn.py

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Merge branch 'main' of https://github.com/Qiskit/qiskit-machine-learning

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updated docstrings

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Added getter/setter, exception handling for OpflowQNN, CircuitQNN #79

Added getter/setter, exception handling for OpflowQNN, CircuitQNN #79

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	shape_ = self._compute_output_shape(op_)
	shapes = [self._compute_output_shape(op_) for op_ in op.oplist]

Added getter/setter, exception handling for OpflowQNN, CircuitQNN #79

Added getter/setter, exception handling for OpflowQNN, CircuitQNN #79

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