[WIP] initial version of classifier and regressor #13
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beichensinn
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manoelmarques,
pbark,
stefan-woerner and
woodsp-ibm
as code owners
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stefan-woerner
changed the title
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Please make sure all files here have the required copyright header in them - this includes the init files too. |
woodsp-ibm
reviewed
Mar 18, 2021
| from ...exceptions import QiskitMachineLearningError | ||
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| class Loss(ABC): |
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Do we need a whole package for one file. If these were all in separate files I could see it. But with everything in one file I would have a thought a loss_functions.py file directly in utils would have sufficed. Unless there is some view to future expansion that would see more coming to this loss_functions folder.
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Yes. it is our plan to add more loss in this folder.
…rning into batches � Conflicts: � qiskit_machine_learning/neural_networks/circuit_qnn.py � qiskit_machine_learning/neural_networks/opflow_qnn.py � test/neural_networks/test_opflow_qnn.py � test/neural_networks/test_two_layer_qnn.py
2) add VQR
2. fit, predict and score functions were removed from VQR
# Conflicts: # docs/tutorials/02_neural_network_classifier_and_regressor.ipynb
stefan-woerner
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Mar 30, 2021
gentinettagian
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Dec 14, 2021
* initial version of classifier and regressor * update structure * fix l1 and l2 losses * clean imports * add `dense` to QNNs and update NNClassifier/Regressor * shelved changes * batching * more on batching * more on batching * more on batching * consistent batching * some spelling * add copyright * some docstrings. * fix some lint errors * add unit tests and fix output shape * fix circuit qnn tests * fix typing * fix typing * more batching * more batching * Update circuit_qnn.py * Update opflow_qnn.py * use sparse probability gradients in case of sample based evaluation * update neural network classifier * fix style/spelling/mypy * fix tests * Update neural_network_classifier.py * more batching * removed duplicate code * gradients reshaping and more tests. * fix circuit QNN tests * fix typing * add batching logic to `sample()`, `probabilities()`, and `probability_gradients()` * fix lint * add gradients for circuit QNN classification + tests * add initial draft for VQC * gradient tests. * add tests with cross entropy * fix lint, style, mypy * cross_entropy gradient added * add cross entropy test with gradients * fix style, spell * removed _sample double definition * make a clean git mv instead of just renaming (1) * make a clean git mv instead of just renaming (2) * add vqc + test * update vqc and tests * update tutorials * cross_entropy sigmod, softmax, softmax_stable added * cross_entropy sigmod, softmax, softmax_stable added * cross_entropy sigmod added to NN classifier * cross_entropy and sigmod_cross_entropy has been changed to "CrossEntryLoss" and "CrossEntropySigmodLoss" in both classifier and regression; initial version of NN regressor * fix loss + minor changes * revert changes in raw_feature_vector as non-required. * minor fixes * Update 02_neural_network_classifier_and_regressor.ipynb * Update 02_neural_network_classifier_and_regressor.ipynb * use given gradient in circuit qnn * remove double output_shape handling * style, lint * update tutorial to use regressor * fix mypy * merged with new RawFeatureVector, some tests fail * fix test randomness, disable some of test_raw_feature_vector * One hot encoding has been removed from NNregression * randomness, tests * fix tutorial * fix tutorial * fix vqc test with bfgs and qasm simulator * fix raw feature vector tests * import fix * Update 02_neural_network_classifier_and_regressor.ipynb * test neural network regressor * 1) 1 bug in NNregressor has been fixed 2) add VQR * revert notebook to python 3 * 1. VQR updated with TwoLayerQNN 2. fit, predict and score functions were removed from VQR * new readme test, fix style, lint * updated vqc notebook, refactored readme test * update circuit QNN to remove final circuit measurements for gradient * remove old tutorials * update TwoLayerQNN and VQR to use default feature map and var form * update init files * update NNC/NNR tutorial (02) * update vqc and vqr * Update 02_neural_network_classifier_and_regressor.ipynb * fix lint, mypy * Update 02_neural_network_classifier_and_regressor.ipynb * added test_vqr.py * updated readme Co-authored-by: Stefan Woerner <WOR@zurich.ibm.com> Co-authored-by: Anton Dekusar <adekusar@ie.ibm.com> Co-authored-by: Manoel Marques <Manoel.Marques@ibm.com>
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