From 3b8800f395dee670307a0a9edaf62560379a846d Mon Sep 17 00:00:00 2001 From: Philipp Ross Date: Sun, 17 Sep 2023 13:10:02 +0200 Subject: [PATCH 1/5] Addition of Generative Modeling Modules for QML Co-authored-by: Marvin Erdmann Co-authored-by: Florian Kiwit Co-authored-by: Maroua Marso --- .gitignore | 3 + .settings/module_db.json | 344 +++++++++++++++++- .../BenchmarkManager.BenchmarkManager.rst | 15 +- .../BenchmarkManager.NumpyEncoder.rst | 35 ++ docs/_autosummary/BenchmarkManager.rst | 1 + .../ConfigManager.ConfigManager.rst | 1 - docs/_autosummary/Installer.Installer.rst | 4 +- .../modules.applications.QML.QML.QML.rst | 35 ++ .../modules.applications.QML.QML.rst | 31 ++ ...lications.QML.circuits.Circuit.Circuit.rst | 33 ++ ...ules.applications.QML.circuits.Circuit.rst | 31 ++ ....CircuitCardinality.CircuitCardinality.rst | 33 ++ ...ations.QML.circuits.CircuitCardinality.rst | 31 ++ ...L.circuits.CircuitCopula.CircuitCopula.rst | 33 ++ ...pplications.QML.circuits.CircuitCopula.rst | 31 ++ ...rcuits.CircuitStandard.CircuitStandard.rst | 33 ++ ...lications.QML.circuits.CircuitStandard.rst | 31 ++ .../modules.applications.QML.circuits.rst | 35 ++ .../modules.applications.QML.data.rst | 23 ++ ..._handler.ContinuousData.ContinuousData.rst | 37 ++ ...ations.QML.data_handler.ContinuousData.rst | 31 ++ ...L.data_handler.DataHandler.DataHandler.rst | 36 ++ ...lications.QML.data_handler.DataHandler.rst | 31 ++ ...data_handler.DiscreteData.DiscreteData.rst | 36 ++ ...ications.QML.data_handler.DiscreteData.rst | 31 ++ ...csGeneralization.MetricsGeneralization.rst | 32 ++ ...QML.data_handler.MetricsGeneralization.rst | 31 ++ .../modules.applications.QML.data_handler.rst | 35 ++ ....GenerativeModeling.GenerativeModeling.rst | 36 ++ ...generative_modeling.GenerativeModeling.rst | 31 ++ ...s.applications.QML.generative_modeling.rst | 32 ++ ...ications.QML.libraries.Library.Library.rst | 34 ++ ...les.applications.QML.libraries.Library.rst | 31 ++ ....libraries.LibraryQiskit.LibraryQiskit.rst | 35 ++ ...plications.QML.libraries.LibraryQiskit.rst | 31 ++ .../modules.applications.QML.libraries.rst | 33 ++ .../_autosummary/modules.applications.QML.rst | 39 ++ ...tions.QML.training.Inference.Inference.rst | 36 ++ ...es.applications.QML.training.Inference.rst | 31 ++ ...es.applications.QML.training.QCBM.QCBM.rst | 37 ++ ...modules.applications.QML.training.QCBM.rst | 31 ++ ...cations.QML.training.Training.Training.rst | 36 ++ ...les.applications.QML.training.Training.rst | 31 ++ .../modules.applications.QML.training.rst | 34 ++ ...ions.QML.transformations.MinMax.MinMax.rst | 40 ++ ...pplications.QML.transformations.MinMax.rst | 31 ++ ...plications.QML.transformations.PIT.PIT.rst | 41 +++ ...s.applications.QML.transformations.PIT.rst | 31 ++ ...rmations.Transformation.Transformation.rst | 38 ++ ...ons.QML.transformations.Transformation.rst | 31 ++ ...dules.applications.QML.transformations.rst | 34 ++ docs/_autosummary/modules.applications.rst | 3 +- docs/index.rst | 2 +- src/BenchmarkManager.py | 18 +- src/ConfigManager.py | 2 +- src/Installer.py | 10 +- src/main.py | 13 +- src/modules/applications/QML/QML.py | 36 ++ src/modules/applications/QML/__init__.py | 15 + .../applications/QML/circuits/Circuit.py | 78 ++++ .../QML/circuits/CircuitCardinality.py | 128 +++++++ .../QML/circuits/CircuitCopula.py | 151 ++++++++ .../QML/circuits/CircuitStandard.py | 133 +++++++ .../applications/QML/circuits/__init__.py | 15 + src/modules/applications/QML/data/MG_2D.npy | Bin 0 -> 800128 bytes src/modules/applications/QML/data/O_2D.npy | Bin 0 -> 400128 bytes .../applications/QML/data/Stocks_2D.npy | Bin 0 -> 30160 bytes src/modules/applications/QML/data/X_2D.npy | Bin 0 -> 400128 bytes src/modules/applications/QML/data/__init__.py | 15 + .../QML/data_handler/ContinuousData.py | 162 +++++++++ .../QML/data_handler/DataHandler.py | 214 +++++++++++ .../QML/data_handler/DiscreteData.py | 192 ++++++++++ .../QML/data_handler/MetricsGeneralization.py | 151 ++++++++ .../applications/QML/data_handler/__init__.py | 15 + .../generative_modeling/GenerativeModeling.py | 143 ++++++++ .../QML/generative_modeling/__init__.py | 15 + .../applications/QML/libraries/Library.py | 97 +++++ .../QML/libraries/LibraryQiskit.py | 321 ++++++++++++++++ .../applications/QML/libraries/__init__.py | 15 + .../applications/QML/training/Inference.py | 114 ++++++ src/modules/applications/QML/training/QCBM.py | 303 +++++++++++++++ .../applications/QML/training/Training.py | 148 ++++++++ .../applications/QML/training/__init__.py | 15 + .../QML/transformations/MinMax.py | 197 ++++++++++ .../applications/QML/transformations/PIT.py | 211 +++++++++++ .../QML/transformations/Transformation.py | 231 ++++++++++++ .../QML/transformations/__init__.py | 15 + .../optimization/PVC/mappings/ISING.py | 1 + .../applications/optimization/SAT/SAT.py | 6 +- .../optimization/TSP/createReferenceGraph.py | 1 - src/modules/devices/braket/Braket.py | 1 - src/utils_mpi.py | 89 +++++ 92 files changed, 5111 insertions(+), 32 deletions(-) create mode 100644 docs/_autosummary/BenchmarkManager.NumpyEncoder.rst create mode 100644 docs/_autosummary/modules.applications.QML.QML.QML.rst create mode 100644 docs/_autosummary/modules.applications.QML.QML.rst create mode 100644 docs/_autosummary/modules.applications.QML.circuits.Circuit.Circuit.rst create mode 100644 docs/_autosummary/modules.applications.QML.circuits.Circuit.rst create mode 100644 docs/_autosummary/modules.applications.QML.circuits.CircuitCardinality.CircuitCardinality.rst create mode 100644 docs/_autosummary/modules.applications.QML.circuits.CircuitCardinality.rst create mode 100644 docs/_autosummary/modules.applications.QML.circuits.CircuitCopula.CircuitCopula.rst create mode 100644 docs/_autosummary/modules.applications.QML.circuits.CircuitCopula.rst create mode 100644 docs/_autosummary/modules.applications.QML.circuits.CircuitStandard.CircuitStandard.rst create mode 100644 docs/_autosummary/modules.applications.QML.circuits.CircuitStandard.rst create mode 100644 docs/_autosummary/modules.applications.QML.circuits.rst create mode 100644 docs/_autosummary/modules.applications.QML.data.rst create mode 100644 docs/_autosummary/modules.applications.QML.data_handler.ContinuousData.ContinuousData.rst create mode 100644 docs/_autosummary/modules.applications.QML.data_handler.ContinuousData.rst create mode 100644 docs/_autosummary/modules.applications.QML.data_handler.DataHandler.DataHandler.rst create mode 100644 docs/_autosummary/modules.applications.QML.data_handler.DataHandler.rst create mode 100644 docs/_autosummary/modules.applications.QML.data_handler.DiscreteData.DiscreteData.rst create mode 100644 docs/_autosummary/modules.applications.QML.data_handler.DiscreteData.rst create mode 100644 docs/_autosummary/modules.applications.QML.data_handler.MetricsGeneralization.MetricsGeneralization.rst create mode 100644 docs/_autosummary/modules.applications.QML.data_handler.MetricsGeneralization.rst create mode 100644 docs/_autosummary/modules.applications.QML.data_handler.rst create mode 100644 docs/_autosummary/modules.applications.QML.generative_modeling.GenerativeModeling.GenerativeModeling.rst create mode 100644 docs/_autosummary/modules.applications.QML.generative_modeling.GenerativeModeling.rst create mode 100644 docs/_autosummary/modules.applications.QML.generative_modeling.rst create mode 100644 docs/_autosummary/modules.applications.QML.libraries.Library.Library.rst create mode 100644 docs/_autosummary/modules.applications.QML.libraries.Library.rst create mode 100644 docs/_autosummary/modules.applications.QML.libraries.LibraryQiskit.LibraryQiskit.rst create mode 100644 docs/_autosummary/modules.applications.QML.libraries.LibraryQiskit.rst create mode 100644 docs/_autosummary/modules.applications.QML.libraries.rst create mode 100644 docs/_autosummary/modules.applications.QML.rst create mode 100644 docs/_autosummary/modules.applications.QML.training.Inference.Inference.rst create mode 100644 docs/_autosummary/modules.applications.QML.training.Inference.rst create mode 100644 docs/_autosummary/modules.applications.QML.training.QCBM.QCBM.rst create mode 100644 docs/_autosummary/modules.applications.QML.training.QCBM.rst create mode 100644 docs/_autosummary/modules.applications.QML.training.Training.Training.rst create mode 100644 docs/_autosummary/modules.applications.QML.training.Training.rst create mode 100644 docs/_autosummary/modules.applications.QML.training.rst create mode 100644 docs/_autosummary/modules.applications.QML.transformations.MinMax.MinMax.rst create mode 100644 docs/_autosummary/modules.applications.QML.transformations.MinMax.rst create mode 100644 docs/_autosummary/modules.applications.QML.transformations.PIT.PIT.rst create mode 100644 docs/_autosummary/modules.applications.QML.transformations.PIT.rst create mode 100644 docs/_autosummary/modules.applications.QML.transformations.Transformation.Transformation.rst create mode 100644 docs/_autosummary/modules.applications.QML.transformations.Transformation.rst create mode 100644 docs/_autosummary/modules.applications.QML.transformations.rst create mode 100644 src/modules/applications/QML/QML.py create mode 100644 src/modules/applications/QML/__init__.py create mode 100644 src/modules/applications/QML/circuits/Circuit.py create mode 100644 src/modules/applications/QML/circuits/CircuitCardinality.py create mode 100644 src/modules/applications/QML/circuits/CircuitCopula.py create mode 100644 src/modules/applications/QML/circuits/CircuitStandard.py create mode 100644 src/modules/applications/QML/circuits/__init__.py create mode 100644 src/modules/applications/QML/data/MG_2D.npy create mode 100644 src/modules/applications/QML/data/O_2D.npy create mode 100644 src/modules/applications/QML/data/Stocks_2D.npy create mode 100644 src/modules/applications/QML/data/X_2D.npy create mode 100644 src/modules/applications/QML/data/__init__.py create mode 100644 src/modules/applications/QML/data_handler/ContinuousData.py create mode 100644 src/modules/applications/QML/data_handler/DataHandler.py create mode 100644 src/modules/applications/QML/data_handler/DiscreteData.py create mode 100644 src/modules/applications/QML/data_handler/MetricsGeneralization.py create mode 100644 src/modules/applications/QML/data_handler/__init__.py create mode 100644 src/modules/applications/QML/generative_modeling/GenerativeModeling.py create mode 100644 src/modules/applications/QML/generative_modeling/__init__.py create mode 100644 src/modules/applications/QML/libraries/Library.py create mode 100644 src/modules/applications/QML/libraries/LibraryQiskit.py create mode 100644 src/modules/applications/QML/libraries/__init__.py create mode 100644 src/modules/applications/QML/training/Inference.py create mode 100644 src/modules/applications/QML/training/QCBM.py create mode 100644 src/modules/applications/QML/training/Training.py create mode 100644 src/modules/applications/QML/training/__init__.py create mode 100644 src/modules/applications/QML/transformations/MinMax.py create mode 100644 src/modules/applications/QML/transformations/PIT.py create mode 100644 src/modules/applications/QML/transformations/Transformation.py create mode 100644 src/modules/applications/QML/transformations/__init__.py create mode 100644 src/utils_mpi.py diff --git a/.gitignore b/.gitignore index 89c7a5e5..2c22569e 100644 --- a/.gitignore +++ b/.gitignore @@ -7,6 +7,7 @@ .DS_Store .AppleDouble .LSOverride +.vscode/ # Icon must end with two \r Icon @@ -309,7 +310,9 @@ $RECYCLE.BIN/ # End of https://www.toptal.com/developers/gitignore/api/pycharm,macos,windows,python /benchmark_runs/ +/bash_scripts/ /.idea/ /config.yml /.settings/active_env.json /.settings/envs/ +/configs/ \ No newline at end of file diff --git a/.settings/module_db.json b/.settings/module_db.json index 3492c969..2e894811 100644 --- a/.settings/module_db.json +++ b/.settings/module_db.json @@ -1,7 +1,7 @@ { - "build_number": 1, - "build_date": "11-07-2023 09:25:40", - "git_revision_number": "bc52f5390459f5eb1d09069e403b753884233620", + "build_number": 3, + "build_date": "15-09-2023 13:07:59", + "git_revision_number": "ce28372e0d19413d823d7d6d746052238f52bb23", "modules": [ { "name": "PVC", @@ -1985,6 +1985,344 @@ "version": "1.23.5" } ] + }, + { + "name": "GenerativeModeling", + "class": "GenerativeModeling", + "module": "modules.applications.QML.generative_modeling.GenerativeModeling", + "submodules": [ + { + "name": "Continuous Data", + "class": "ContinuousData", + "args": {}, + "module": "modules.applications.QML.data_handler.ContinuousData", + "requirements": [ + { + "name": "numpy", + "version": "1.23.5" + } + ], + "submodules": [ + { + "name": "PIT", + "class": "PIT", + "args": {}, + "module": "modules.applications.QML.transformations.PIT", + "requirements": [ + { + "name": "numpy", + "version": "1.23.5" + }, + { + "name": "pandas", + "version": "1.5.2" + } + ], + "submodules": [ + { + "name": "CircuitCopula", + "class": "CircuitCopula", + "args": {}, + "module": "modules.applications.QML.circuits.CircuitCopula", + "requirements": [ + { + "name": "scipy", + "version": "1.11.1" + } + ], + "submodules": [ + { + "name": "LibraryQiskit", + "class": "LibraryQiskit", + "args": {}, + "module": "modules.applications.QML.libraries.LibraryQiskit", + "requirements": [ + { + "name": "qiskit", + "version": "0.40.0" + }, + { + "name": "numpy", + "version": "1.23.5" + } + ], + "submodules": [ + { + "name": "QCBM", + "class": "QCBM", + "args": {}, + "module": "modules.applications.QML.training.QCBM", + "requirements": [ + { + "name": "numpy", + "version": "1.23.5" + }, + { + "name": "cma", + "version": "3.3.0" + }, + { + "name": "tensorboard", + "version": "2.13.0" + }, + { + "name": "tensorboardX", + "version": "2.6.2" + } + ], + "submodules": [] + }, + { + "name": "Inference", + "class": "Inference", + "args": {}, + "module": "modules.applications.QML.training.Inference", + "requirements": [ + { + "name": "numpy", + "version": "1.23.5" + } + ], + "submodules": [] + } + ] + } + ] + } + ] + }, + { + "name": "MinMax", + "class": "MinMax", + "args": {}, + "module": "modules.applications.QML.transformations.MinMax", + "requirements": [ + { + "name": "numpy", + "version": "1.23.5" + } + ], + "submodules": [ + { + "name": "CircuitStandard", + "class": "CircuitStandard", + "args": {}, + "module": "modules.applications.QML.circuits.CircuitStandard", + "requirements": [ + { + "name": "scipy", + "version": "1.11.1" + } + ], + "submodules": [ + { + "name": "LibraryQiskit", + "class": "LibraryQiskit", + "args": {}, + "module": "modules.applications.QML.libraries.LibraryQiskit", + "requirements": [ + { + "name": "qiskit", + "version": "0.40.0" + }, + { + "name": "numpy", + "version": "1.23.5" + } + ], + "submodules": [ + { + "name": "QCBM", + "class": "QCBM", + "args": {}, + "module": "modules.applications.QML.training.QCBM", + "requirements": [ + { + "name": "numpy", + "version": "1.23.5" + }, + { + "name": "cma", + "version": "3.3.0" + }, + { + "name": "tensorboard", + "version": "2.13.0" + }, + { + "name": "tensorboardX", + "version": "2.6.2" + } + ], + "submodules": [] + }, + { + "name": "Inference", + "class": "Inference", + "args": {}, + "module": "modules.applications.QML.training.Inference", + "requirements": [ + { + "name": "numpy", + "version": "1.23.5" + } + ], + "submodules": [] + } + ] + } + ] + }, + { + "name": "CircuitCardinality", + "class": "CircuitCardinality", + "args": {}, + "module": "modules.applications.QML.circuits.CircuitCardinality", + "requirements": [], + "submodules": [ + { + "name": "LibraryQiskit", + "class": "LibraryQiskit", + "args": {}, + "module": "modules.applications.QML.libraries.LibraryQiskit", + "requirements": [ + { + "name": "qiskit", + "version": "0.40.0" + }, + { + "name": "numpy", + "version": "1.23.5" + } + ], + "submodules": [ + { + "name": "QCBM", + "class": "QCBM", + "args": {}, + "module": "modules.applications.QML.training.QCBM", + "requirements": [ + { + "name": "numpy", + "version": "1.23.5" + }, + { + "name": "cma", + "version": "3.3.0" + }, + { + "name": "tensorboard", + "version": "2.13.0" + }, + { + "name": "tensorboardX", + "version": "2.6.2" + } + ], + "submodules": [] + }, + { + "name": "Inference", + "class": "Inference", + "args": {}, + "module": "modules.applications.QML.training.Inference", + "requirements": [ + { + "name": "numpy", + "version": "1.23.5" + } + ], + "submodules": [] + } + ] + } + ] + } + ] + } + ] + }, + { + "name": "Discrete Data", + "class": "DiscreteData", + "args": {}, + "module": "modules.applications.QML.data_handler.DiscreteData", + "requirements": [ + { + "name": "numpy", + "version": "1.23.5" + } + ], + "submodules": [ + { + "name": "CircuitCardinality", + "class": "CircuitCardinality", + "args": {}, + "module": "modules.applications.QML.circuits.CircuitCardinality", + "requirements": [], + "submodules": [ + { + "name": "LibraryQiskit", + "class": "LibraryQiskit", + "args": {}, + "module": "modules.applications.QML.libraries.LibraryQiskit", + "requirements": [ + { + "name": "qiskit", + "version": "0.40.0" + }, + { + "name": "numpy", + "version": "1.23.5" + } + ], + "submodules": [ + { + "name": "QCBM", + "class": "QCBM", + "args": {}, + "module": "modules.applications.QML.training.QCBM", + "requirements": [ + { + "name": "numpy", + "version": "1.23.5" + }, + { + "name": "cma", + "version": "3.3.0" + }, + { + "name": "tensorboard", + "version": "2.13.0" + }, + { + "name": "tensorboardX", + "version": "2.6.2" + } + ], + "submodules": [] + }, + { + "name": "Inference", + "class": "Inference", + "args": {}, + "module": "modules.applications.QML.training.Inference", + "requirements": [ + { + "name": "numpy", + "version": "1.23.5" + } + ], + "submodules": [] + } + ] + } + ] + } + ] + } + ], + "requirements": [] } ] } \ No newline at end of file diff --git a/docs/_autosummary/BenchmarkManager.BenchmarkManager.rst b/docs/_autosummary/BenchmarkManager.BenchmarkManager.rst index 1a958dbd..c08148e1 100644 --- a/docs/_autosummary/BenchmarkManager.BenchmarkManager.rst +++ b/docs/_autosummary/BenchmarkManager.BenchmarkManager.rst @@ -8,14 +8,14 @@ BenchmarkManager.BenchmarkManager :show-inheritance: :inherited-members: - + .. automethod:: __init__ - + .. rubric:: Methods .. autosummary:: - + ~BenchmarkManager.__init__ ~BenchmarkManager.load_results ~BenchmarkManager.orchestrate_benchmark @@ -23,8 +23,9 @@ BenchmarkManager.BenchmarkManager ~BenchmarkManager.summarize_results ~BenchmarkManager.traverse_config ~BenchmarkManager.visualize_results + + - - - - + + + \ No newline at end of file diff --git a/docs/_autosummary/BenchmarkManager.NumpyEncoder.rst b/docs/_autosummary/BenchmarkManager.NumpyEncoder.rst new file mode 100644 index 00000000..0e62399e --- /dev/null +++ b/docs/_autosummary/BenchmarkManager.NumpyEncoder.rst @@ -0,0 +1,35 @@ +BenchmarkManager.NumpyEncoder +============================= + +.. currentmodule:: BenchmarkManager + +.. autoclass:: NumpyEncoder + :members: + :show-inheritance: + :inherited-members: + + + .. automethod:: __init__ + + + .. rubric:: Methods + + .. autosummary:: + + ~NumpyEncoder.__init__ + ~NumpyEncoder.default + ~NumpyEncoder.encode + ~NumpyEncoder.iterencode + + + + + + .. rubric:: Attributes + + .. autosummary:: + + ~NumpyEncoder.item_separator + ~NumpyEncoder.key_separator + + \ No newline at end of file diff --git a/docs/_autosummary/BenchmarkManager.rst b/docs/_autosummary/BenchmarkManager.rst index 964ac09d..4c56b859 100644 --- a/docs/_autosummary/BenchmarkManager.rst +++ b/docs/_autosummary/BenchmarkManager.rst @@ -20,6 +20,7 @@ :template: custom-class-template.rst BenchmarkManager + NumpyEncoder diff --git a/docs/_autosummary/ConfigManager.ConfigManager.rst b/docs/_autosummary/ConfigManager.ConfigManager.rst index 7c2ece9f..f460c74c 100644 --- a/docs/_autosummary/ConfigManager.ConfigManager.rst +++ b/docs/_autosummary/ConfigManager.ConfigManager.rst @@ -17,7 +17,6 @@ ConfigManager.ConfigManager .. autosummary:: ~ConfigManager.__init__ - ~ConfigManager.checkbox ~ConfigManager.create_benchmark_backlog ~ConfigManager.create_tree_figure ~ConfigManager.generate_benchmark_configs diff --git a/docs/_autosummary/Installer.Installer.rst b/docs/_autosummary/Installer.Installer.rst index 500a6e4d..65435049 100644 --- a/docs/_autosummary/Installer.Installer.rst +++ b/docs/_autosummary/Installer.Installer.rst @@ -18,8 +18,9 @@ Installer.Installer ~Installer.__init__ ~Installer.check_active_env - ~Installer.check_for_installs + ~Installer.check_for_configs ~Installer.collect_requirements + ~Installer.configure ~Installer.create_conda_file ~Installer.create_module_db ~Installer.create_req_file @@ -27,7 +28,6 @@ Installer.Installer ~Installer.get_env ~Installer.get_module_db ~Installer.get_module_db_build_number - ~Installer.install ~Installer.list_envs ~Installer.query_user ~Installer.save_env diff --git a/docs/_autosummary/modules.applications.QML.QML.QML.rst b/docs/_autosummary/modules.applications.QML.QML.QML.rst new file mode 100644 index 00000000..87920e39 --- /dev/null +++ b/docs/_autosummary/modules.applications.QML.QML.QML.rst @@ -0,0 +1,35 @@ +modules.applications.QML.QML.QML +================================ + +.. currentmodule:: modules.applications.QML.QML + +.. autoclass:: QML + :members: + :show-inheritance: + :inherited-members: + + + .. automethod:: __init__ + + + .. rubric:: Methods + + .. autosummary:: + + ~QML.__init__ + ~QML.generate_problem + ~QML.get_application + ~QML.get_available_submodule_options + ~QML.get_default_submodule + ~QML.get_parameter_options + ~QML.get_requirements + ~QML.get_submodule + ~QML.postprocess + ~QML.preprocess + ~QML.save + + + + + + \ No newline at end of file diff --git a/docs/_autosummary/modules.applications.QML.QML.rst b/docs/_autosummary/modules.applications.QML.QML.rst new file mode 100644 index 00000000..139cb703 --- /dev/null +++ b/docs/_autosummary/modules.applications.QML.QML.rst @@ -0,0 +1,31 @@ +modules.applications.QML.QML +============================ + +.. automodule:: modules.applications.QML.QML + + + + + + + + + + + + .. rubric:: Classes + + .. autosummary:: + :toctree: + :template: custom-class-template.rst + + QML + + + + + + + + + diff --git a/docs/_autosummary/modules.applications.QML.circuits.Circuit.Circuit.rst b/docs/_autosummary/modules.applications.QML.circuits.Circuit.Circuit.rst new file mode 100644 index 00000000..1196bda4 --- /dev/null +++ b/docs/_autosummary/modules.applications.QML.circuits.Circuit.Circuit.rst @@ -0,0 +1,33 @@ +modules.applications.QML.circuits.Circuit.Circuit +================================================= + +.. currentmodule:: modules.applications.QML.circuits.Circuit + +.. autoclass:: Circuit + :members: + :show-inheritance: + :inherited-members: + + + .. automethod:: __init__ + + + .. rubric:: Methods + + .. autosummary:: + + ~Circuit.__init__ + ~Circuit.generate_gate_sequence + ~Circuit.get_available_submodule_options + ~Circuit.get_default_submodule + ~Circuit.get_parameter_options + ~Circuit.get_requirements + ~Circuit.get_submodule + ~Circuit.postprocess + ~Circuit.preprocess + + + + + + \ No newline at end of file diff --git a/docs/_autosummary/modules.applications.QML.circuits.Circuit.rst b/docs/_autosummary/modules.applications.QML.circuits.Circuit.rst new file mode 100644 index 00000000..16ca7183 --- /dev/null +++ b/docs/_autosummary/modules.applications.QML.circuits.Circuit.rst @@ -0,0 +1,31 @@ +modules.applications.QML.circuits.Circuit +========================================= + +.. automodule:: modules.applications.QML.circuits.Circuit + + + + + + + + + + + + .. rubric:: Classes + + .. autosummary:: + :toctree: + :template: custom-class-template.rst + + Circuit + + + + + + + + + diff --git a/docs/_autosummary/modules.applications.QML.circuits.CircuitCardinality.CircuitCardinality.rst b/docs/_autosummary/modules.applications.QML.circuits.CircuitCardinality.CircuitCardinality.rst new file mode 100644 index 00000000..0b194bfc --- /dev/null +++ b/docs/_autosummary/modules.applications.QML.circuits.CircuitCardinality.CircuitCardinality.rst @@ -0,0 +1,33 @@ +modules.applications.QML.circuits.CircuitCardinality.CircuitCardinality +======================================================================= + +.. currentmodule:: modules.applications.QML.circuits.CircuitCardinality + +.. autoclass:: CircuitCardinality + :members: + :show-inheritance: + :inherited-members: + + + .. automethod:: __init__ + + + .. rubric:: Methods + + .. autosummary:: + + ~CircuitCardinality.__init__ + ~CircuitCardinality.generate_gate_sequence + ~CircuitCardinality.get_available_submodule_options + ~CircuitCardinality.get_default_submodule + ~CircuitCardinality.get_parameter_options + ~CircuitCardinality.get_requirements + ~CircuitCardinality.get_submodule + ~CircuitCardinality.postprocess + ~CircuitCardinality.preprocess + + + + + + \ No newline at end of file diff --git a/docs/_autosummary/modules.applications.QML.circuits.CircuitCardinality.rst b/docs/_autosummary/modules.applications.QML.circuits.CircuitCardinality.rst new file mode 100644 index 00000000..9db9c99a --- /dev/null +++ b/docs/_autosummary/modules.applications.QML.circuits.CircuitCardinality.rst @@ -0,0 +1,31 @@ +modules.applications.QML.circuits.CircuitCardinality +==================================================== + +.. automodule:: modules.applications.QML.circuits.CircuitCardinality + + + + + + + + + + + + .. rubric:: Classes + + .. autosummary:: + :toctree: + :template: custom-class-template.rst + + CircuitCardinality + + + + + + + + + diff --git a/docs/_autosummary/modules.applications.QML.circuits.CircuitCopula.CircuitCopula.rst b/docs/_autosummary/modules.applications.QML.circuits.CircuitCopula.CircuitCopula.rst new file mode 100644 index 00000000..3bca6c22 --- /dev/null +++ b/docs/_autosummary/modules.applications.QML.circuits.CircuitCopula.CircuitCopula.rst @@ -0,0 +1,33 @@ +modules.applications.QML.circuits.CircuitCopula.CircuitCopula +============================================================= + +.. currentmodule:: modules.applications.QML.circuits.CircuitCopula + +.. autoclass:: CircuitCopula + :members: + :show-inheritance: + :inherited-members: + + + .. automethod:: __init__ + + + .. rubric:: Methods + + .. autosummary:: + + ~CircuitCopula.__init__ + ~CircuitCopula.generate_gate_sequence + ~CircuitCopula.get_available_submodule_options + ~CircuitCopula.get_default_submodule + ~CircuitCopula.get_parameter_options + ~CircuitCopula.get_requirements + ~CircuitCopula.get_submodule + ~CircuitCopula.postprocess + ~CircuitCopula.preprocess + + + + + + \ No newline at end of file diff --git a/docs/_autosummary/modules.applications.QML.circuits.CircuitCopula.rst b/docs/_autosummary/modules.applications.QML.circuits.CircuitCopula.rst new file mode 100644 index 00000000..812769df --- /dev/null +++ b/docs/_autosummary/modules.applications.QML.circuits.CircuitCopula.rst @@ -0,0 +1,31 @@ +modules.applications.QML.circuits.CircuitCopula +=============================================== + +.. automodule:: modules.applications.QML.circuits.CircuitCopula + + + + + + + + + + + + .. rubric:: Classes + + .. autosummary:: + :toctree: + :template: custom-class-template.rst + + CircuitCopula + + + + + + + + + diff --git a/docs/_autosummary/modules.applications.QML.circuits.CircuitStandard.CircuitStandard.rst b/docs/_autosummary/modules.applications.QML.circuits.CircuitStandard.CircuitStandard.rst new file mode 100644 index 00000000..43e5c4f9 --- /dev/null +++ b/docs/_autosummary/modules.applications.QML.circuits.CircuitStandard.CircuitStandard.rst @@ -0,0 +1,33 @@ +modules.applications.QML.circuits.CircuitStandard.CircuitStandard +================================================================= + +.. currentmodule:: modules.applications.QML.circuits.CircuitStandard + +.. autoclass:: CircuitStandard + :members: + :show-inheritance: + :inherited-members: + + + .. automethod:: __init__ + + + .. rubric:: Methods + + .. autosummary:: + + ~CircuitStandard.__init__ + ~CircuitStandard.generate_gate_sequence + ~CircuitStandard.get_available_submodule_options + ~CircuitStandard.get_default_submodule + ~CircuitStandard.get_parameter_options + ~CircuitStandard.get_requirements + ~CircuitStandard.get_submodule + ~CircuitStandard.postprocess + ~CircuitStandard.preprocess + + + + + + \ No newline at end of file diff --git a/docs/_autosummary/modules.applications.QML.circuits.CircuitStandard.rst b/docs/_autosummary/modules.applications.QML.circuits.CircuitStandard.rst new file mode 100644 index 00000000..0bd08b6d --- /dev/null +++ b/docs/_autosummary/modules.applications.QML.circuits.CircuitStandard.rst @@ -0,0 +1,31 @@ +modules.applications.QML.circuits.CircuitStandard +================================================= + +.. automodule:: modules.applications.QML.circuits.CircuitStandard + + + + + + + + + + + + .. rubric:: Classes + + .. autosummary:: + :toctree: + :template: custom-class-template.rst + + CircuitStandard + + + + + + + + + diff --git a/docs/_autosummary/modules.applications.QML.circuits.rst b/docs/_autosummary/modules.applications.QML.circuits.rst new file mode 100644 index 00000000..a7eea213 --- /dev/null +++ b/docs/_autosummary/modules.applications.QML.circuits.rst @@ -0,0 +1,35 @@ +modules.applications.QML.circuits +================================= + +.. automodule:: modules.applications.QML.circuits + + + + + + + + + + + + + + + + + + + +.. rubric:: Modules + +.. autosummary:: + :toctree: + :template: custom-module-template.rst + :recursive: + + modules.applications.QML.circuits.Circuit + modules.applications.QML.circuits.CircuitCardinality + modules.applications.QML.circuits.CircuitCopula + modules.applications.QML.circuits.CircuitStandard + diff --git a/docs/_autosummary/modules.applications.QML.data.rst b/docs/_autosummary/modules.applications.QML.data.rst new file mode 100644 index 00000000..c9202b9f --- /dev/null +++ b/docs/_autosummary/modules.applications.QML.data.rst @@ -0,0 +1,23 @@ +modules.applications.QML.data +============================= + +.. automodule:: modules.applications.QML.data + + + + + + + + + + + + + + + + + + + diff --git a/docs/_autosummary/modules.applications.QML.data_handler.ContinuousData.ContinuousData.rst b/docs/_autosummary/modules.applications.QML.data_handler.ContinuousData.ContinuousData.rst new file mode 100644 index 00000000..71f084c9 --- /dev/null +++ b/docs/_autosummary/modules.applications.QML.data_handler.ContinuousData.ContinuousData.rst @@ -0,0 +1,37 @@ +modules.applications.QML.data\_handler.ContinuousData.ContinuousData +==================================================================== + +.. currentmodule:: modules.applications.QML.data_handler.ContinuousData + +.. autoclass:: ContinuousData + :members: + :show-inheritance: + :inherited-members: + + + .. automethod:: __init__ + + + .. rubric:: Methods + + .. autosummary:: + + ~ContinuousData.__init__ + ~ContinuousData.data_load + ~ContinuousData.evaluate + ~ContinuousData.generalisation + ~ContinuousData.get_available_submodule_options + ~ContinuousData.get_default_submodule + ~ContinuousData.get_parameter_options + ~ContinuousData.get_requirements + ~ContinuousData.get_submodule + ~ContinuousData.kl_divergence + ~ContinuousData.postprocess + ~ContinuousData.preprocess + ~ContinuousData.tb_to_pd + + + + + + \ No newline at end of file diff --git a/docs/_autosummary/modules.applications.QML.data_handler.ContinuousData.rst b/docs/_autosummary/modules.applications.QML.data_handler.ContinuousData.rst new file mode 100644 index 00000000..6b92d396 --- /dev/null +++ b/docs/_autosummary/modules.applications.QML.data_handler.ContinuousData.rst @@ -0,0 +1,31 @@ +modules.applications.QML.data\_handler.ContinuousData +===================================================== + +.. automodule:: modules.applications.QML.data_handler.ContinuousData + + + + + + + + + + + + .. rubric:: Classes + + .. autosummary:: + :toctree: + :template: custom-class-template.rst + + ContinuousData + + + + + + + + + diff --git a/docs/_autosummary/modules.applications.QML.data_handler.DataHandler.DataHandler.rst b/docs/_autosummary/modules.applications.QML.data_handler.DataHandler.DataHandler.rst new file mode 100644 index 00000000..946631e8 --- /dev/null +++ b/docs/_autosummary/modules.applications.QML.data_handler.DataHandler.DataHandler.rst @@ -0,0 +1,36 @@ +modules.applications.QML.data\_handler.DataHandler.DataHandler +============================================================== + +.. currentmodule:: modules.applications.QML.data_handler.DataHandler + +.. autoclass:: DataHandler + :members: + :show-inheritance: + :inherited-members: + + + .. automethod:: __init__ + + + .. rubric:: Methods + + .. autosummary:: + + ~DataHandler.__init__ + ~DataHandler.data_load + ~DataHandler.evaluate + ~DataHandler.generalisation + ~DataHandler.get_available_submodule_options + ~DataHandler.get_default_submodule + ~DataHandler.get_parameter_options + ~DataHandler.get_requirements + ~DataHandler.get_submodule + ~DataHandler.postprocess + ~DataHandler.preprocess + ~DataHandler.tb_to_pd + + + + + + \ No newline at end of file diff --git a/docs/_autosummary/modules.applications.QML.data_handler.DataHandler.rst b/docs/_autosummary/modules.applications.QML.data_handler.DataHandler.rst new file mode 100644 index 00000000..0d502b9e --- /dev/null +++ b/docs/_autosummary/modules.applications.QML.data_handler.DataHandler.rst @@ -0,0 +1,31 @@ +modules.applications.QML.data\_handler.DataHandler +================================================== + +.. automodule:: modules.applications.QML.data_handler.DataHandler + + + + + + + + + + + + .. rubric:: Classes + + .. autosummary:: + :toctree: + :template: custom-class-template.rst + + DataHandler + + + + + + + + + diff --git a/docs/_autosummary/modules.applications.QML.data_handler.DiscreteData.DiscreteData.rst b/docs/_autosummary/modules.applications.QML.data_handler.DiscreteData.DiscreteData.rst new file mode 100644 index 00000000..98130325 --- /dev/null +++ b/docs/_autosummary/modules.applications.QML.data_handler.DiscreteData.DiscreteData.rst @@ -0,0 +1,36 @@ +modules.applications.QML.data\_handler.DiscreteData.DiscreteData +================================================================ + +.. currentmodule:: modules.applications.QML.data_handler.DiscreteData + +.. autoclass:: DiscreteData + :members: + :show-inheritance: + :inherited-members: + + + .. automethod:: __init__ + + + .. rubric:: Methods + + .. autosummary:: + + ~DiscreteData.__init__ + ~DiscreteData.data_load + ~DiscreteData.evaluate + ~DiscreteData.generalisation + ~DiscreteData.get_available_submodule_options + ~DiscreteData.get_default_submodule + ~DiscreteData.get_parameter_options + ~DiscreteData.get_requirements + ~DiscreteData.get_submodule + ~DiscreteData.postprocess + ~DiscreteData.preprocess + ~DiscreteData.tb_to_pd + + + + + + \ No newline at end of file diff --git a/docs/_autosummary/modules.applications.QML.data_handler.DiscreteData.rst b/docs/_autosummary/modules.applications.QML.data_handler.DiscreteData.rst new file mode 100644 index 00000000..4de3fd93 --- /dev/null +++ b/docs/_autosummary/modules.applications.QML.data_handler.DiscreteData.rst @@ -0,0 +1,31 @@ +modules.applications.QML.data\_handler.DiscreteData +=================================================== + +.. automodule:: modules.applications.QML.data_handler.DiscreteData + + + + + + + + + + + + .. rubric:: Classes + + .. autosummary:: + :toctree: + :template: custom-class-template.rst + + DiscreteData + + + + + + + + + diff --git a/docs/_autosummary/modules.applications.QML.data_handler.MetricsGeneralization.MetricsGeneralization.rst b/docs/_autosummary/modules.applications.QML.data_handler.MetricsGeneralization.MetricsGeneralization.rst new file mode 100644 index 00000000..7b59b380 --- /dev/null +++ b/docs/_autosummary/modules.applications.QML.data_handler.MetricsGeneralization.MetricsGeneralization.rst @@ -0,0 +1,32 @@ +modules.applications.QML.data\_handler.MetricsGeneralization.MetricsGeneralization +================================================================================== + +.. currentmodule:: modules.applications.QML.data_handler.MetricsGeneralization + +.. autoclass:: MetricsGeneralization + :members: + :show-inheritance: + :inherited-members: + + + .. automethod:: __init__ + + + .. rubric:: Methods + + .. autosummary:: + + ~MetricsGeneralization.__init__ + ~MetricsGeneralization.coverage + ~MetricsGeneralization.exploration + ~MetricsGeneralization.fidelity + ~MetricsGeneralization.get_masks + ~MetricsGeneralization.get_metrics + ~MetricsGeneralization.normalized_rate + ~MetricsGeneralization.precision + + + + + + \ No newline at end of file diff --git a/docs/_autosummary/modules.applications.QML.data_handler.MetricsGeneralization.rst b/docs/_autosummary/modules.applications.QML.data_handler.MetricsGeneralization.rst new file mode 100644 index 00000000..d24b4acb --- /dev/null +++ b/docs/_autosummary/modules.applications.QML.data_handler.MetricsGeneralization.rst @@ -0,0 +1,31 @@ +modules.applications.QML.data\_handler.MetricsGeneralization +============================================================ + +.. automodule:: modules.applications.QML.data_handler.MetricsGeneralization + + + + + + + + + + + + .. rubric:: Classes + + .. autosummary:: + :toctree: + :template: custom-class-template.rst + + MetricsGeneralization + + + + + + + + + diff --git a/docs/_autosummary/modules.applications.QML.data_handler.rst b/docs/_autosummary/modules.applications.QML.data_handler.rst new file mode 100644 index 00000000..6fd2b523 --- /dev/null +++ b/docs/_autosummary/modules.applications.QML.data_handler.rst @@ -0,0 +1,35 @@ +modules.applications.QML.data\_handler +====================================== + +.. automodule:: modules.applications.QML.data_handler + + + + + + + + + + + + + + + + + + + +.. rubric:: Modules + +.. autosummary:: + :toctree: + :template: custom-module-template.rst + :recursive: + + modules.applications.QML.data_handler.ContinuousData + modules.applications.QML.data_handler.DataHandler + modules.applications.QML.data_handler.DiscreteData + modules.applications.QML.data_handler.MetricsGeneralization + diff --git a/docs/_autosummary/modules.applications.QML.generative_modeling.GenerativeModeling.GenerativeModeling.rst b/docs/_autosummary/modules.applications.QML.generative_modeling.GenerativeModeling.GenerativeModeling.rst new file mode 100644 index 00000000..fcf9b6b5 --- /dev/null +++ b/docs/_autosummary/modules.applications.QML.generative_modeling.GenerativeModeling.GenerativeModeling.rst @@ -0,0 +1,36 @@ +modules.applications.QML.generative\_modeling.GenerativeModeling.GenerativeModeling +=================================================================================== + +.. currentmodule:: modules.applications.QML.generative_modeling.GenerativeModeling + +.. autoclass:: GenerativeModeling + :members: + :show-inheritance: + :inherited-members: + + + .. automethod:: __init__ + + + .. rubric:: Methods + + .. autosummary:: + + ~GenerativeModeling.__init__ + ~GenerativeModeling.generate_problem + ~GenerativeModeling.get_application + ~GenerativeModeling.get_available_submodule_options + ~GenerativeModeling.get_default_submodule + ~GenerativeModeling.get_parameter_options + ~GenerativeModeling.get_requirements + ~GenerativeModeling.get_solution_quality_unit + ~GenerativeModeling.get_submodule + ~GenerativeModeling.postprocess + ~GenerativeModeling.preprocess + ~GenerativeModeling.save + + + + + + \ No newline at end of file diff --git a/docs/_autosummary/modules.applications.QML.generative_modeling.GenerativeModeling.rst b/docs/_autosummary/modules.applications.QML.generative_modeling.GenerativeModeling.rst new file mode 100644 index 00000000..2b4784bd --- /dev/null +++ b/docs/_autosummary/modules.applications.QML.generative_modeling.GenerativeModeling.rst @@ -0,0 +1,31 @@ +modules.applications.QML.generative\_modeling.GenerativeModeling +================================================================ + +.. automodule:: modules.applications.QML.generative_modeling.GenerativeModeling + + + + + + + + + + + + .. rubric:: Classes + + .. autosummary:: + :toctree: + :template: custom-class-template.rst + + GenerativeModeling + + + + + + + + + diff --git a/docs/_autosummary/modules.applications.QML.generative_modeling.rst b/docs/_autosummary/modules.applications.QML.generative_modeling.rst new file mode 100644 index 00000000..c46b1870 --- /dev/null +++ b/docs/_autosummary/modules.applications.QML.generative_modeling.rst @@ -0,0 +1,32 @@ +modules.applications.QML.generative\_modeling +============================================= + +.. automodule:: modules.applications.QML.generative_modeling + + + + + + + + + + + + + + + + + + + +.. rubric:: Modules + +.. autosummary:: + :toctree: + :template: custom-module-template.rst + :recursive: + + modules.applications.QML.generative_modeling.GenerativeModeling + diff --git a/docs/_autosummary/modules.applications.QML.libraries.Library.Library.rst b/docs/_autosummary/modules.applications.QML.libraries.Library.Library.rst new file mode 100644 index 00000000..23c781a6 --- /dev/null +++ b/docs/_autosummary/modules.applications.QML.libraries.Library.Library.rst @@ -0,0 +1,34 @@ +modules.applications.QML.libraries.Library.Library +================================================== + +.. currentmodule:: modules.applications.QML.libraries.Library + +.. autoclass:: Library + :members: + :show-inheritance: + :inherited-members: + + + .. automethod:: __init__ + + + .. rubric:: Methods + + .. autosummary:: + + ~Library.__init__ + ~Library.get_available_submodule_options + ~Library.get_default_submodule + ~Library.get_execute_circuit + ~Library.get_parameter_options + ~Library.get_requirements + ~Library.get_submodule + ~Library.postprocess + ~Library.preprocess + ~Library.sequence_to_circuit + + + + + + \ No newline at end of file diff --git a/docs/_autosummary/modules.applications.QML.libraries.Library.rst b/docs/_autosummary/modules.applications.QML.libraries.Library.rst new file mode 100644 index 00000000..93ef7023 --- /dev/null +++ b/docs/_autosummary/modules.applications.QML.libraries.Library.rst @@ -0,0 +1,31 @@ +modules.applications.QML.libraries.Library +========================================== + +.. automodule:: modules.applications.QML.libraries.Library + + + + + + + + + + + + .. rubric:: Classes + + .. autosummary:: + :toctree: + :template: custom-class-template.rst + + Library + + + + + + + + + diff --git a/docs/_autosummary/modules.applications.QML.libraries.LibraryQiskit.LibraryQiskit.rst b/docs/_autosummary/modules.applications.QML.libraries.LibraryQiskit.LibraryQiskit.rst new file mode 100644 index 00000000..ea5d644c --- /dev/null +++ b/docs/_autosummary/modules.applications.QML.libraries.LibraryQiskit.LibraryQiskit.rst @@ -0,0 +1,35 @@ +modules.applications.QML.libraries.LibraryQiskit.LibraryQiskit +============================================================== + +.. currentmodule:: modules.applications.QML.libraries.LibraryQiskit + +.. autoclass:: LibraryQiskit + :members: + :show-inheritance: + :inherited-members: + + + .. automethod:: __init__ + + + .. rubric:: Methods + + .. autosummary:: + + ~LibraryQiskit.__init__ + ~LibraryQiskit.get_available_submodule_options + ~LibraryQiskit.get_default_submodule + ~LibraryQiskit.get_execute_circuit + ~LibraryQiskit.get_parameter_options + ~LibraryQiskit.get_requirements + ~LibraryQiskit.get_submodule + ~LibraryQiskit.postprocess + ~LibraryQiskit.preprocess + ~LibraryQiskit.select_backend + ~LibraryQiskit.sequence_to_circuit + + + + + + \ No newline at end of file diff --git a/docs/_autosummary/modules.applications.QML.libraries.LibraryQiskit.rst b/docs/_autosummary/modules.applications.QML.libraries.LibraryQiskit.rst new file mode 100644 index 00000000..600bd0fb --- /dev/null +++ b/docs/_autosummary/modules.applications.QML.libraries.LibraryQiskit.rst @@ -0,0 +1,31 @@ +modules.applications.QML.libraries.LibraryQiskit +================================================ + +.. automodule:: modules.applications.QML.libraries.LibraryQiskit + + + + + + + + + + + + .. rubric:: Classes + + .. autosummary:: + :toctree: + :template: custom-class-template.rst + + LibraryQiskit + + + + + + + + + diff --git a/docs/_autosummary/modules.applications.QML.libraries.rst b/docs/_autosummary/modules.applications.QML.libraries.rst new file mode 100644 index 00000000..8751f8df --- /dev/null +++ b/docs/_autosummary/modules.applications.QML.libraries.rst @@ -0,0 +1,33 @@ +modules.applications.QML.libraries +================================== + +.. automodule:: modules.applications.QML.libraries + + + + + + + + + + + + + + + + + + + +.. rubric:: Modules + +.. autosummary:: + :toctree: + :template: custom-module-template.rst + :recursive: + + modules.applications.QML.libraries.Library + modules.applications.QML.libraries.LibraryQiskit + diff --git a/docs/_autosummary/modules.applications.QML.rst b/docs/_autosummary/modules.applications.QML.rst new file mode 100644 index 00000000..e2311249 --- /dev/null +++ b/docs/_autosummary/modules.applications.QML.rst @@ -0,0 +1,39 @@ +modules.applications.QML +======================== + +.. automodule:: modules.applications.QML + + + + + + + + + + + + + + + + + + + +.. rubric:: Modules + +.. autosummary:: + :toctree: + :template: custom-module-template.rst + :recursive: + + modules.applications.QML.QML + modules.applications.QML.circuits + modules.applications.QML.data + modules.applications.QML.data_handler + modules.applications.QML.generative_modeling + modules.applications.QML.libraries + modules.applications.QML.training + modules.applications.QML.transformations + diff --git a/docs/_autosummary/modules.applications.QML.training.Inference.Inference.rst b/docs/_autosummary/modules.applications.QML.training.Inference.Inference.rst new file mode 100644 index 00000000..3fc9d8df --- /dev/null +++ b/docs/_autosummary/modules.applications.QML.training.Inference.Inference.rst @@ -0,0 +1,36 @@ +modules.applications.QML.training.Inference.Inference +===================================================== + +.. currentmodule:: modules.applications.QML.training.Inference + +.. autoclass:: Inference + :members: + :show-inheritance: + :inherited-members: + + + .. automethod:: __init__ + + + .. rubric:: Methods + + .. autosummary:: + + ~Inference.__init__ + ~Inference.get_available_submodule_options + ~Inference.get_default_submodule + ~Inference.get_parameter_options + ~Inference.get_requirements + ~Inference.get_submodule + ~Inference.kl_divergence + ~Inference.nll + ~Inference.postprocess + ~Inference.preprocess + ~Inference.sample_from_pmf + ~Inference.start_training + + + + + + \ No newline at end of file diff --git a/docs/_autosummary/modules.applications.QML.training.Inference.rst b/docs/_autosummary/modules.applications.QML.training.Inference.rst new file mode 100644 index 00000000..2572ba68 --- /dev/null +++ b/docs/_autosummary/modules.applications.QML.training.Inference.rst @@ -0,0 +1,31 @@ +modules.applications.QML.training.Inference +=========================================== + +.. automodule:: modules.applications.QML.training.Inference + + + + + + + + + + + + .. rubric:: Classes + + .. autosummary:: + :toctree: + :template: custom-class-template.rst + + Inference + + + + + + + + + diff --git a/docs/_autosummary/modules.applications.QML.training.QCBM.QCBM.rst b/docs/_autosummary/modules.applications.QML.training.QCBM.QCBM.rst new file mode 100644 index 00000000..cf0bf023 --- /dev/null +++ b/docs/_autosummary/modules.applications.QML.training.QCBM.QCBM.rst @@ -0,0 +1,37 @@ +modules.applications.QML.training.QCBM.QCBM +=========================================== + +.. currentmodule:: modules.applications.QML.training.QCBM + +.. autoclass:: QCBM + :members: + :show-inheritance: + :inherited-members: + + + .. automethod:: __init__ + + + .. rubric:: Methods + + .. autosummary:: + + ~QCBM.__init__ + ~QCBM.get_available_submodule_options + ~QCBM.get_default_submodule + ~QCBM.get_parameter_options + ~QCBM.get_requirements + ~QCBM.get_submodule + ~QCBM.kl_divergence + ~QCBM.nll + ~QCBM.postprocess + ~QCBM.preprocess + ~QCBM.sample_from_pmf + ~QCBM.setup_training + ~QCBM.start_training + + + + + + \ No newline at end of file diff --git a/docs/_autosummary/modules.applications.QML.training.QCBM.rst b/docs/_autosummary/modules.applications.QML.training.QCBM.rst new file mode 100644 index 00000000..8b4c4187 --- /dev/null +++ b/docs/_autosummary/modules.applications.QML.training.QCBM.rst @@ -0,0 +1,31 @@ +modules.applications.QML.training.QCBM +====================================== + +.. automodule:: modules.applications.QML.training.QCBM + + + + + + + + + + + + .. rubric:: Classes + + .. autosummary:: + :toctree: + :template: custom-class-template.rst + + QCBM + + + + + + + + + diff --git a/docs/_autosummary/modules.applications.QML.training.Training.Training.rst b/docs/_autosummary/modules.applications.QML.training.Training.Training.rst new file mode 100644 index 00000000..9402bbe3 --- /dev/null +++ b/docs/_autosummary/modules.applications.QML.training.Training.Training.rst @@ -0,0 +1,36 @@ +modules.applications.QML.training.Training.Training +=================================================== + +.. currentmodule:: modules.applications.QML.training.Training + +.. autoclass:: Training + :members: + :show-inheritance: + :inherited-members: + + + .. automethod:: __init__ + + + .. rubric:: Methods + + .. autosummary:: + + ~Training.__init__ + ~Training.get_available_submodule_options + ~Training.get_default_submodule + ~Training.get_parameter_options + ~Training.get_requirements + ~Training.get_submodule + ~Training.kl_divergence + ~Training.nll + ~Training.postprocess + ~Training.preprocess + ~Training.sample_from_pmf + ~Training.start_training + + + + + + \ No newline at end of file diff --git a/docs/_autosummary/modules.applications.QML.training.Training.rst b/docs/_autosummary/modules.applications.QML.training.Training.rst new file mode 100644 index 00000000..5ad911a3 --- /dev/null +++ b/docs/_autosummary/modules.applications.QML.training.Training.rst @@ -0,0 +1,31 @@ +modules.applications.QML.training.Training +========================================== + +.. automodule:: modules.applications.QML.training.Training + + + + + + + + + + + + .. rubric:: Classes + + .. autosummary:: + :toctree: + :template: custom-class-template.rst + + Training + + + + + + + + + diff --git a/docs/_autosummary/modules.applications.QML.training.rst b/docs/_autosummary/modules.applications.QML.training.rst new file mode 100644 index 00000000..ca80eea0 --- /dev/null +++ b/docs/_autosummary/modules.applications.QML.training.rst @@ -0,0 +1,34 @@ +modules.applications.QML.training +================================= + +.. automodule:: modules.applications.QML.training + + + + + + + + + + + + + + + + + + + +.. rubric:: Modules + +.. autosummary:: + :toctree: + :template: custom-module-template.rst + :recursive: + + modules.applications.QML.training.Inference + modules.applications.QML.training.QCBM + modules.applications.QML.training.Training + diff --git a/docs/_autosummary/modules.applications.QML.transformations.MinMax.MinMax.rst b/docs/_autosummary/modules.applications.QML.transformations.MinMax.MinMax.rst new file mode 100644 index 00000000..11c557e4 --- /dev/null +++ b/docs/_autosummary/modules.applications.QML.transformations.MinMax.MinMax.rst @@ -0,0 +1,40 @@ +modules.applications.QML.transformations.MinMax.MinMax +====================================================== + +.. currentmodule:: modules.applications.QML.transformations.MinMax + +.. autoclass:: MinMax + :members: + :show-inheritance: + :inherited-members: + + + .. automethod:: __init__ + + + .. rubric:: Methods + + .. autosummary:: + + ~MinMax.__init__ + ~MinMax.compute_discretization + ~MinMax.compute_discretization_efficient + ~MinMax.fit_transform + ~MinMax.generate_samples + ~MinMax.generate_samples_efficient + ~MinMax.get_available_submodule_options + ~MinMax.get_default_submodule + ~MinMax.get_parameter_options + ~MinMax.get_requirements + ~MinMax.get_submodule + ~MinMax.inverse_transform + ~MinMax.postprocess + ~MinMax.preprocess + ~MinMax.reverse_transform + ~MinMax.transform + + + + + + \ No newline at end of file diff --git a/docs/_autosummary/modules.applications.QML.transformations.MinMax.rst b/docs/_autosummary/modules.applications.QML.transformations.MinMax.rst new file mode 100644 index 00000000..b558d243 --- /dev/null +++ b/docs/_autosummary/modules.applications.QML.transformations.MinMax.rst @@ -0,0 +1,31 @@ +modules.applications.QML.transformations.MinMax +=============================================== + +.. automodule:: modules.applications.QML.transformations.MinMax + + + + + + + + + + + + .. rubric:: Classes + + .. autosummary:: + :toctree: + :template: custom-class-template.rst + + MinMax + + + + + + + + + diff --git a/docs/_autosummary/modules.applications.QML.transformations.PIT.PIT.rst b/docs/_autosummary/modules.applications.QML.transformations.PIT.PIT.rst new file mode 100644 index 00000000..1243bcd2 --- /dev/null +++ b/docs/_autosummary/modules.applications.QML.transformations.PIT.PIT.rst @@ -0,0 +1,41 @@ +modules.applications.QML.transformations.PIT.PIT +================================================ + +.. currentmodule:: modules.applications.QML.transformations.PIT + +.. autoclass:: PIT + :members: + :show-inheritance: + :inherited-members: + + + .. automethod:: __init__ + + + .. rubric:: Methods + + .. autosummary:: + + ~PIT.__init__ + ~PIT.compute_discretization + ~PIT.compute_discretization_efficient + ~PIT.emp_integral_trans + ~PIT.fit_transform + ~PIT.generate_samples + ~PIT.generate_samples_efficient + ~PIT.get_available_submodule_options + ~PIT.get_default_submodule + ~PIT.get_parameter_options + ~PIT.get_requirements + ~PIT.get_submodule + ~PIT.inverse_transform + ~PIT.postprocess + ~PIT.preprocess + ~PIT.reverse_transform + ~PIT.transform + + + + + + \ No newline at end of file diff --git a/docs/_autosummary/modules.applications.QML.transformations.PIT.rst b/docs/_autosummary/modules.applications.QML.transformations.PIT.rst new file mode 100644 index 00000000..05c786c9 --- /dev/null +++ b/docs/_autosummary/modules.applications.QML.transformations.PIT.rst @@ -0,0 +1,31 @@ +modules.applications.QML.transformations.PIT +============================================ + +.. automodule:: modules.applications.QML.transformations.PIT + + + + + + + + + + + + .. rubric:: Classes + + .. autosummary:: + :toctree: + :template: custom-class-template.rst + + PIT + + + + + + + + + diff --git a/docs/_autosummary/modules.applications.QML.transformations.Transformation.Transformation.rst b/docs/_autosummary/modules.applications.QML.transformations.Transformation.Transformation.rst new file mode 100644 index 00000000..ad98ce7e --- /dev/null +++ b/docs/_autosummary/modules.applications.QML.transformations.Transformation.Transformation.rst @@ -0,0 +1,38 @@ +modules.applications.QML.transformations.Transformation.Transformation +====================================================================== + +.. currentmodule:: modules.applications.QML.transformations.Transformation + +.. autoclass:: Transformation + :members: + :show-inheritance: + :inherited-members: + + + .. automethod:: __init__ + + + .. rubric:: Methods + + .. autosummary:: + + ~Transformation.__init__ + ~Transformation.compute_discretization + ~Transformation.compute_discretization_efficient + ~Transformation.generate_samples + ~Transformation.generate_samples_efficient + ~Transformation.get_available_submodule_options + ~Transformation.get_default_submodule + ~Transformation.get_parameter_options + ~Transformation.get_requirements + ~Transformation.get_submodule + ~Transformation.postprocess + ~Transformation.preprocess + ~Transformation.reverse_transform + ~Transformation.transform + + + + + + \ No newline at end of file diff --git a/docs/_autosummary/modules.applications.QML.transformations.Transformation.rst b/docs/_autosummary/modules.applications.QML.transformations.Transformation.rst new file mode 100644 index 00000000..f2272fea --- /dev/null +++ b/docs/_autosummary/modules.applications.QML.transformations.Transformation.rst @@ -0,0 +1,31 @@ +modules.applications.QML.transformations.Transformation +======================================================= + +.. automodule:: modules.applications.QML.transformations.Transformation + + + + + + + + + + + + .. rubric:: Classes + + .. autosummary:: + :toctree: + :template: custom-class-template.rst + + Transformation + + + + + + + + + diff --git a/docs/_autosummary/modules.applications.QML.transformations.rst b/docs/_autosummary/modules.applications.QML.transformations.rst new file mode 100644 index 00000000..d9646c58 --- /dev/null +++ b/docs/_autosummary/modules.applications.QML.transformations.rst @@ -0,0 +1,34 @@ +modules.applications.QML.transformations +======================================== + +.. automodule:: modules.applications.QML.transformations + + + + + + + + + + + + + + + + + + + +.. rubric:: Modules + +.. autosummary:: + :toctree: + :template: custom-module-template.rst + :recursive: + + modules.applications.QML.transformations.MinMax + modules.applications.QML.transformations.PIT + modules.applications.QML.transformations.Transformation + diff --git a/docs/_autosummary/modules.applications.rst b/docs/_autosummary/modules.applications.rst index 61995128..d07d06f8 100644 --- a/docs/_autosummary/modules.applications.rst +++ b/docs/_autosummary/modules.applications.rst @@ -1,4 +1,4 @@ -modules.applications +modules.applications ==================== .. automodule:: modules.applications @@ -30,5 +30,6 @@ modules.applications modules.applications.Application modules.applications.Mapping + modules.applications.QML modules.applications.optimization diff --git a/docs/index.rst b/docs/index.rst index f1420461..df84a5c7 100644 --- a/docs/index.rst +++ b/docs/index.rst @@ -22,7 +22,7 @@ to mathematical formulations, solvers, hardware or other custom module definitio :alt: Architecture of the QUARK framework Publications -====== +============ Details about the motivations for the original framework can be found in the [accompanying QUARK paper from Finžgar et al](https://arxiv.org/abs/2202.03028). The data used for the paper can be found in ``results/results.csv``. Even though the architecture changes significantly from QUARK 1.0 to 2.0, the guiding principles still remain. The most recent publication from [Kiwit et al.](https://arxiv.org/abs/2308.04082) provides an updated overview of the functionalities and quantum machine learning features of QUARK 2.0. diff --git a/src/BenchmarkManager.py b/src/BenchmarkManager.py index a2af8c95..1adcfeba 100644 --- a/src/BenchmarkManager.py +++ b/src/BenchmarkManager.py @@ -33,6 +33,10 @@ from modules.Core import Core from utils import get_git_revision +from utils_mpi import get_comm + +comm = get_comm() + matplotlib.rcParams['savefig.dpi'] = 300 @@ -104,8 +108,11 @@ def orchestrate_benchmark(self, benchmark_config_manager: ConfigManager, app_mod self.run_benchmark(benchmark_backlog, benchmark_config_manager.get_reps()) - results = self._collect_all_results() - self._save_as_json(results) + # Wait until all MPI processes have finished and save results on rank 0 + comm.Barrier() + if comm.Get_rank() == 0: + results = self._collect_all_results() + self._save_as_json(results) def run_benchmark(self, benchmark_backlog: list, repetitions: int): """ @@ -157,8 +164,11 @@ def run_benchmark(self, benchmark_backlog: list, repetitions: int): for record in benchmark_records: record.sum_up_times() - with open(f"{path}/results.json", 'w') as filehandler: - json.dump([x.get() for x in benchmark_records], filehandler, indent=2, cls=NumpyEncoder) + # Wait until all MPI processes have finished and save results on rank 0 + comm.Barrier() + if comm.Get_rank() == 0: + with open(f"{path}/results.json", 'w') as filehandler: + json.dump([x.get() for x in benchmark_records], filehandler, indent=2, cls=NumpyEncoder) logging.info("") logging.info(" =============== Run finished =============== ") diff --git a/src/ConfigManager.py b/src/ConfigManager.py index e50a2bac..d5e1d3c2 100644 --- a/src/ConfigManager.py +++ b/src/ConfigManager.py @@ -403,7 +403,7 @@ def _query_for_config(param_opts: dict, prefix: str = "") -> dict: if not config[key_in_cond][0] in config_answer.get("if")["in"]: continue - if len(config_answer['values']) == 1: + if len(config_answer['values']) == 1 and "custom_input" not in config_answer: # When there is only 1 value to choose from skip the user input for now values = config_answer['values'] print(f"{prefix} {config_answer['description']}: {config_answer['values'][0]}") diff --git a/src/Installer.py b/src/Installer.py index ab9ad13d..971a8074 100644 --- a/src/Installer.py +++ b/src/Installer.py @@ -40,9 +40,11 @@ def __init__(self): self.python_version = "3.9.16" self.pip_version = "23.0" self.default_app_modules = [ - {"name": "PVC", "class": "PVC", "module": "modules.applications.optimization.PVC.PVC"}, - {"name": "SAT", "class": "SAT", "module": "modules.applications.optimization.SAT.SAT"}, - {"name": "TSP", "class": "TSP", "module": "modules.applications.optimization.TSP.TSP"} + {"name": "PVC", "class": "PVC", "module": "modules.applications.optimization.PVC.PVC"}, + {"name": "SAT", "class": "SAT", "module": "modules.applications.optimization.SAT.SAT"}, + {"name": "TSP", "class": "TSP", "module": "modules.applications.optimization.TSP.TSP"}, + {"name": "GenerativeModeling", "class": "GenerativeModeling", \ + "module": "modules.applications.QML.generative_modeling.GenerativeModeling"} ] self.core_requirements = [ @@ -259,7 +261,7 @@ def query_user(self, submodules: dict, name: str) -> None: if submodules["submodules"]: answer_submodules = \ checkbox("submodules", f"Which submodule would you like to include for {name}?", - [m["name"] for m in submodules["submodules"]])["submodules"] + [m["name"] for m in submodules["submodules"]])["submodules"] submodules["submodules"] = [x for x in submodules["submodules"] if x["name"] in answer_submodules] for idx, entry in enumerate(submodules["submodules"]): diff --git a/src/main.py b/src/main.py index d229a080..7193d4d5 100644 --- a/src/main.py +++ b/src/main.py @@ -22,6 +22,9 @@ from Installer import Installer from utils import _expand_paths +from utils_mpi import MPIStreamHandler, MPIFileHandler, get_comm + +comm = get_comm() # add the paths install_dir = os.path.dirname(os.path.dirname(os.path.abspath(__file__))) @@ -60,8 +63,8 @@ def setup_logging() -> None: level=logging.INFO, format="%(asctime)s [%(levelname)s] %(message)s", handlers=[ - logging.FileHandler("logging.log"), - logging.StreamHandler() + MPIFileHandler("logging.log"), + MPIStreamHandler() ] ) @@ -189,8 +192,10 @@ def handle_benchmark_run(args: argparse.Namespace) -> None: config_manager.print() else: benchmark_manager.orchestrate_benchmark(config_manager, app_modules) - results = benchmark_manager.load_results() - benchmark_manager.visualize_results(results, benchmark_manager.store_dir) + comm.Barrier() + if comm.Get_rank() == 0: + results = benchmark_manager.load_results() + benchmark_manager.visualize_results(results, benchmark_manager.store_dir) def handler_env_run(args: argparse.Namespace) -> None: diff --git a/src/modules/applications/QML/QML.py b/src/modules/applications/QML/QML.py new file mode 100644 index 00000000..15ab5699 --- /dev/null +++ b/src/modules/applications/QML/QML.py @@ -0,0 +1,36 @@ +# Copyright 2021 The QUARK Authors. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +from modules.applications.Application import * + + +class QML(Application, ABC): + """ + QML Module for QUARK, is used by all QML applications + """ + + @abstractmethod + def generate_problem(self, config) -> any: + """ + Creates a concrete problem and returns it + :param config: + :type config: dict + :return: + :rtype: any + """ + pass + + def save(self, path: str, iter_count: int) -> None: + # Transform tensorboard output file to pandas dataframe + pass diff --git a/src/modules/applications/QML/__init__.py b/src/modules/applications/QML/__init__.py new file mode 100644 index 00000000..d8c95d20 --- /dev/null +++ b/src/modules/applications/QML/__init__.py @@ -0,0 +1,15 @@ +# Copyright 2022 The QUARK Authors. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +""" Module containing all QML applications""" diff --git a/src/modules/applications/QML/circuits/Circuit.py b/src/modules/applications/QML/circuits/Circuit.py new file mode 100644 index 00000000..2a6c6fef --- /dev/null +++ b/src/modules/applications/QML/circuits/Circuit.py @@ -0,0 +1,78 @@ +# Copyright 2021 The QUARK Authors. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +from typing import TypedDict +from abc import ABC, abstractmethod +from modules.Core import Core +from utils import start_time_measurement, end_time_measurement + + +class Circuit(Core, ABC): + """ + This module is abstract base class for the libarary-agnostic gate sequence, that define a quantum circuit. + """ + + def __init__(self, name): + """ + Constructor method + """ + super().__init__() + self.architecture_name = name + + @abstractmethod + def generate_gate_sequence(self, input_data: dict, config: dict) -> dict: + """ + Generates the library agnostic gate sequence, a well-defined definition of the quantum circuit. + + """ + pass + + def preprocess(self, input_data: dict, config: dict, **kwargs) -> (dict, float): + """ + Library-agnostic implementation of the gate sequence, that will be mapped to backend such as Qiskit in the + subsequent module. + + :param input_data: Collection of information from the previous modules + :type input_data: dict + :param config: Config specifying the number of qubits of the circuit + :type config: Config + :param kwargs: optional keyword arguments + :type kwargs: dict + :return: Dictionary including the dataset and gate sequence needed for circuit construction. The time it took + generate the gate sequence. + :rtype: (dict, float) + """ + start = start_time_measurement() + circuit_constr = self.generate_gate_sequence(input_data, config) + + if "generalization_metrics" in list(input_data.keys()): + circuit_constr["generalization_metrics"] = input_data["generalization_metrics"] + return circuit_constr, end_time_measurement(start) + + def postprocess(self, input_data: dict, config: dict, **kwargs) -> (dict, float): + """ + Method that passes back information of the subsequent modules to the preceding modules. + + :param input_data: Collected information of the benchmarking process + :type input_data: dict + :param config: Config specifying the number of qubits of the circuit + :type config: Config + :param kwargs: optional keyword arguments + :type kwargs: dict + :return: Same dictionary like input_data with architecture_name + :rtype: (dict, float) + """ + start = start_time_measurement() + input_data["architecture_name"] = self.architecture_name + return input_data, end_time_measurement(start) diff --git a/src/modules/applications/QML/circuits/CircuitCardinality.py b/src/modules/applications/QML/circuits/CircuitCardinality.py new file mode 100644 index 00000000..de648edb --- /dev/null +++ b/src/modules/applications/QML/circuits/CircuitCardinality.py @@ -0,0 +1,128 @@ +# Copyright 2021 The QUARK Authors. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +from typing import TypedDict + +from modules.applications.QML.circuits.Circuit import Circuit +from modules.applications.QML.libraries.LibraryQiskit import LibraryQiskit + + +class CircuitCardinality(Circuit): + """ + This class generates a library-agnostic gate sequence, i.e. a list containing information + about the gates and the wires they act on. + The circuit follows the implementation by Gili et al. https://arxiv.org/abs/2207.13645 + """ + + def __init__(self): + """ + Constructor method + """ + super().__init__("CircuitCardinality") + self.submodule_options = ["LibraryQiskit"] + + def get_parameter_options(self) -> dict: + """ + Returns the configurable settings for this Copula Circuit. + + :return: + .. code-block:: python + + return { + "depth": { + "values": [2, 4, 8, 16], + "description": "What depth do you want?" + } + } + + """ + return { + + "depth": { + "values": [2, 4, 8, 16], + "description": "What depth do you want?" + }, + } + + def get_default_submodule(self, library_option: str) -> LibraryQiskit: + if library_option == "LibraryQiskit": + return LibraryQiskit() + else: + raise NotImplementedError(f"Library Option {library_option} not implemented") + + class Config(TypedDict): + """ + Attributes of a valid config + + .. code-block:: python + + depth: int + + """ + depth: int + + def generate_gate_sequence(self, input_data: dict, config: Config) -> dict: + """ + Returns gate sequence of copula architecture + + :param input_data: Collection of information from the previous modules + :type input_data: dict + :param config: Config specifying the number of qubits of the circuit + :type config: Config + :return: Dictionary including the gate sequence of the Cardinality Circuit + :rtype: dict + """ + n_qubits = input_data["n_qubits"] + depth = config["depth"] // 2 + + gate_sequence = [] + + for k in range(n_qubits): + gate_sequence.append(["RX", [k]]) + gate_sequence.append(["RZ", [k]]) + + for d in range(depth): + gate_sequence.append(["Barrier", None]) + for k in range(n_qubits - 1): + gate_sequence.append(["RXX", [k, k + 1]]) + gate_sequence.append(["Barrier", None]) + + if d == depth - 2: + for k in range(n_qubits): + gate_sequence.append(["RX", [k]]) + gate_sequence.append(["RZ", [k]]) + gate_sequence.append(["RX", [k]]) + + elif d < depth - 2: + for k in range(n_qubits): + gate_sequence.append(["RX", [k]]) + gate_sequence.append(["RZ", [k]]) + + gate_sequence.append(["Barrier", None]) + + for k in range(n_qubits): + gate_sequence.append(["Measure", [k, k]]) + + output_dict = { + "gate_sequence": gate_sequence, + "circuit_name": "Cardinality", + "n_qubits": n_qubits, + "n_registers": None, + "depth": depth, + "histogram_train": input_data["histogram_train"], + "store_dir_iter": input_data["store_dir_iter"], + "dataset_name": input_data["dataset_name"] + } + + return output_dict diff --git a/src/modules/applications/QML/circuits/CircuitCopula.py b/src/modules/applications/QML/circuits/CircuitCopula.py new file mode 100644 index 00000000..45962fa9 --- /dev/null +++ b/src/modules/applications/QML/circuits/CircuitCopula.py @@ -0,0 +1,151 @@ +# Copyright 2021 The QUARK Authors. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +from typing import TypedDict +from itertools import combinations + +from scipy.special import binom + +from modules.applications.QML.circuits.Circuit import Circuit +from modules.applications.QML.libraries.LibraryQiskit import LibraryQiskit + + +class CircuitCopula(Circuit): + """ + This class generates a library-agnostic gate sequence, i.e. a list containing information + about the gates and the wires they act on. The marginal ditribtions generated by the copula + are uniformaly distributed. + """ + + def __init__(self): + """ + Constructor method + """ + super().__init__("DiscreteCopula") + self.submodule_options = ["LibraryQiskit"] + + @staticmethod + def get_requirements() -> list[dict]: + """ + Returns requirements of this module + + :return: list of dict with requirements of this module + :rtype: list[dict] + """ + return [ + { + "name": "scipy", + "version": "1.11.1" + } + ] + + def get_parameter_options(self) -> dict: + """ + Returns the configurable settings for this Copula Circuit. + + :return: + + .. code-block:: python + + return { + "depth": { + "values": [1, 2, 3, 4, 5], + "description": "What depth do you want?" + }, + } + + """ + return { + "depth": { + "values": [1, 2, 3, 4, 5], + "description": "What depth do you want?" + }, + } + + def get_default_submodule(self, library_option: str) -> LibraryQiskit: + if library_option == "LibraryQiskit": + return LibraryQiskit() + else: + raise NotImplementedError(f"Library Option {library_option} not implemented") + + class Config(TypedDict): + """ + Attributes of a valid config + + .. code-block:: python + + depth: int + + """ + depth: int + + def generate_gate_sequence(self, input_data: dict, config: Config) -> dict: + """ + Returns gate sequence of copula architecture + + :param input_data: Collection of information from the previous modules + :type input_data: dict + :param config: Config specifying the number of qubits of the circuit + :type config: Config + :return: Dictionary including the gate sequence of the Copula Circuit + :rtype: dict + """ + n_registers = input_data["n_registers"] + n_qubits = input_data["n_qubits"] + depth = config["depth"] + n = n_qubits // n_registers + + gate_sequence = [] + for k in range(n): + gate_sequence.append(["Hadamard", [k]]) + + for j in range(n_registers - 1): + for k in range(n): + gate_sequence.append(["CNOT", [k, k + n * (j + 1)]]) + + gate_sequence.append(["Barrier", None]) + + shift = 0 + for _ in range(depth): + for k in range(n): + for j in range(n_registers): + gate_sequence.append(["RZ", [j * n + k]]) + gate_sequence.append(["RX", [j * n + k]]) + gate_sequence.append(["RZ", [j * n + k]]) + + k = 3 * n + shift + for i, j in combinations(range(n), 2): + for l in range(n_registers): + gate_sequence.append(["RXX", [l * n + i, l * n + j]]) + + k += 1 + shift += 3 * n + int(binom(n, 2)) + + gate_sequence.append(["Barrier", None]) + + for k in range(n_qubits): + gate_sequence.append(["Measure", [k, k]]) + + output_dict = { + "gate_sequence": gate_sequence, + "circuit_name": "Copula", + "n_qubits": n_qubits, + "n_registers": n_registers, + "depth": depth, + "histogram_train": input_data["histogram_train"], + "store_dir_iter": input_data["store_dir_iter"], + "dataset_name": input_data["dataset_name"] + } + + return output_dict diff --git a/src/modules/applications/QML/circuits/CircuitStandard.py b/src/modules/applications/QML/circuits/CircuitStandard.py new file mode 100644 index 00000000..3db2680c --- /dev/null +++ b/src/modules/applications/QML/circuits/CircuitStandard.py @@ -0,0 +1,133 @@ +# Copyright 2021 The QUARK Authors. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +from typing import TypedDict + +from modules.applications.QML.circuits.Circuit import Circuit +from modules.applications.QML.libraries.LibraryQiskit import LibraryQiskit + + +class CircuitStandard(Circuit): + """ + This class generates a library-agnostic gate sequence, i.e. a list containing information + about the gates and the wires they act on. + """ + + def __init__(self): + """ + Constructor method + """ + super().__init__("DiscreteStandard") + self.submodule_options = ["LibraryQiskit"] + + @staticmethod + def get_requirements() -> list[dict]: + """ + Returns requirements of this module + + :return: list of dict with requirements of this module + :rtype: list[dict] + """ + return [ + { + "name": "scipy", + "version": "1.11.1" + } + ] + + def get_parameter_options(self) -> dict: + """ + Returns the configurable settings for this standard circuit. + + :return: + .. code-block:: python + + return { + "depth": { + "values": [1, 2, 3, 4, 5], + "description": "What depth do you want?" + } + } + + """ + return { + + "depth": { + "values": [1, 2, 3], + "description": "What depth do you want?" + } + } + + def get_default_submodule(self, library_option: str) -> LibraryQiskit: + if library_option == "LibraryQiskit": + return LibraryQiskit() + else: + raise NotImplementedError(f"Library Option {library_option} not implemented") + + class Config(TypedDict): + """ + Attributes of a valid config + + .. code-block:: python + + depth: int + + """ + depth: int + + def generate_gate_sequence(self, input_data: dict, config: Config) -> dict: + """ + Returns gate sequence of standard architecture + + :param input_data: Collection of information from the previous modules + :type input_data: dict + :param config: Config specifying the number of qubits of the circuit + :type config: Config + :return: Dictionary including the gate sequence of the Standard Circuit + :rtype: dict + """ + n_registers = input_data["n_registers"] + n_qubits = input_data["n_qubits"] + depth = config["depth"] + n = n_qubits // n_registers + + gate_sequence = [] + + for _ in range(depth): + for k in range(n_qubits): + gate_sequence.append(["RY", [k]]) + + for k in range(n_qubits - 1): + gate_sequence.append(["RYY", [k, k + 1]]) + + for k in range(n_qubits - 1): + gate_sequence.append(["CRY", [k, k + 1]]) + + gate_sequence.append(["Barrier", None]) + + for k in range(n_qubits): + gate_sequence.append(["Measure", [k, k]]) + + output_dict = { + "gate_sequence": gate_sequence, + "circuit_name": "Standard", + "n_qubits": n_qubits, + "n_registers": n_registers, + "depth": depth, + "histogram_train": input_data["histogram_train"], + "store_dir_iter": input_data["store_dir_iter"], + "dataset_name": input_data["dataset_name"] + } + + return output_dict diff --git a/src/modules/applications/QML/circuits/__init__.py b/src/modules/applications/QML/circuits/__init__.py new file mode 100644 index 00000000..0ded5981 --- /dev/null +++ b/src/modules/applications/QML/circuits/__init__.py @@ -0,0 +1,15 @@ +# Copyright 2022 The QUARK Authors. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +"""Package containing all circuits""" diff --git a/src/modules/applications/QML/data/MG_2D.npy b/src/modules/applications/QML/data/MG_2D.npy new file mode 100644 index 0000000000000000000000000000000000000000..01d0add2f7d8aec45527c2f5f65bff08f0df76a1 GIT binary patch literal 800128 zcmbT7_dnI||Ho~|K6}|CNtB9=#_KAQgrq@|85IpAMMzO7B1zIxS;;7bP_HLZ>MhwT zNkS@nZ{OGFU-+Ki9Jd>e*L6Lw$GBg&Ee@Dl9^&Qk<+-@>sOwo5@0A7$D>u98t<+Fh 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zkVq5B>hz>hxR-j8DV^W`WlFD3KmOfNfhy8Vv?@W5>0{=Cwac30el=`Z`8?=#iF52LVknm?n@SHaE&l1VC;J&sEs{2yCL-t+(f literal 0 HcmV?d00001 diff --git a/src/modules/applications/QML/data/__init__.py b/src/modules/applications/QML/data/__init__.py new file mode 100644 index 00000000..2c76fe0a --- /dev/null +++ b/src/modules/applications/QML/data/__init__.py @@ -0,0 +1,15 @@ +# Copyright 2022 The QUARK Authors. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +"""Module containing all datasets""" diff --git a/src/modules/applications/QML/data_handler/ContinuousData.py b/src/modules/applications/QML/data_handler/ContinuousData.py new file mode 100644 index 00000000..23a848ea --- /dev/null +++ b/src/modules/applications/QML/data_handler/ContinuousData.py @@ -0,0 +1,162 @@ +# Copyright 2021 The QUARK Authors. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +from utils import start_time_measurement, end_time_measurement +from typing import TypedDict, Union + +import numpy as np + +import pkg_resources +import logging + +from modules.applications.QML.data_handler.DataHandler import * +from modules.applications.QML.transformations.MinMax import MinMax +from modules.applications.QML.transformations.PIT import PIT + + +class ContinuousData(DataHandler): + """ + A data handler for continuous datasets. This class loads a dataset from a specified path and provides + methods for data transformation and evaluation. + + """ + + def __init__(self): + """ + The continuous data class loads a dataset from the path + src/modules/applications/QML/data + """ + super().__init__("") + self.submodule_options = ["PIT", "MinMax"] + self.transformation = None + self.dataset = None + self.n_registers = None + self.gc = None + + @staticmethod + def get_requirements() -> list[dict]: + """ + Returns requirements of this module + + :return: list of dict with requirements of this module + :rtype: list[dict] + """ + return [ + { + "name": "numpy", + "version": "1.23.5" + } + ] + + def get_default_submodule(self, transform_option: str) -> Union[PIT, MinMax]: + if transform_option == "MinMax": + self.transformation = MinMax() + elif transform_option == "PIT": + self.transformation = PIT() + else: + raise NotImplementedError(f"Transformation Option {transform_option} not implemented") + return self.transformation + + def get_parameter_options(self) -> dict: + """ + Returns the configurable settings for this application + + :return: + + .. code-block:: python + + return { + "data_set": { + "values": ["X_2D", "O_2D", "MG_2D", "Stocks_2D"], + "description": "Which dataset do you want to use?" + } + } + + """ + return { + "data_set": { + "values": ["X_2D", "O_2D", "MG_2D", "Stocks_2D"], + "description": "Which dataset do you want to use?" + } + } + + class Config(TypedDict): + """ + Attributes of a valid config + + .. code-block:: python + + data_set: str + + """ + + data_set: int + + def data_load(self, gen_mod: dict, config: Config) -> dict: + + """ + The chosen dataset is loaded and split into a training set. + + :param gen_mod: Dictionary with collected information of the previous modules + :type gen_mod: dict + :param config: Config specifying the paramters of the data handler + :type config: dict + :return: Must always return the mapped problem and the time it took to create the mapping + :rtype: tuple(any, float) + """ + self.dataset_name = config["data_set"] + self.n_qubits = gen_mod["n_qubits"] + + filename = pkg_resources.resource_filename('modules.applications.QML.data', f"{self.dataset_name}.npy") + self.dataset = np.load(filename) + + application_config = { + "dataset_name": self.dataset_name, + "n_qubits": self.n_qubits, + "dataset": self.dataset, + "store_dir_iter": gen_mod["store_dir_iter"]} + + return application_config + + def evaluate(self, solution: list, **kwargs) -> (float, float): + """ + Calculate KL in original space. + + :param solution: A dictionary-like object containing the solution data, including histogram_generated_original and histogram_train_original. + :type solution: list + + :return: KL for the generated samples and the time it took to calculate it. + :rtype: tuple(float, float) + """ + start = start_time_measurement() + + generated = solution["histogram_generated_original"] + generated[generated == 0] = 1e-8 + + histogram_train_original = solution["histogram_train_original"] + histogram_train_original[histogram_train_original == 0] = 1e-8 + + # Flatten the arrays for efficient computation + target = histogram_train_original.ravel() + generated = generated.ravel() + + # Compute KL divergence using NumPy vectorized operations + kl_divergence = self.kl_divergence(target, generated) + + logging.info(f"KL original space: {kl_divergence}") + + return kl_divergence, end_time_measurement(start) + + def kl_divergence(self, target, q): + return np.sum(target * np.log(target / q)) diff --git a/src/modules/applications/QML/data_handler/DataHandler.py b/src/modules/applications/QML/data_handler/DataHandler.py new file mode 100644 index 00000000..931c3e54 --- /dev/null +++ b/src/modules/applications/QML/data_handler/DataHandler.py @@ -0,0 +1,214 @@ +# Copyright 2021 The QUARK Authors. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +import pickle +import os + +import numpy as np +import pandas as pd +from tensorboard.backend.event_processing.event_accumulator import EventAccumulator + +from modules.Core import * +from utils import start_time_measurement, end_time_measurement + + +class DataHandler(Core, ABC): + """ + The task of the DataHandler module is to translate the application’s data and problem specification into preproccesed format. + """ + + def __init__(self, name): + """ + Constructor method + """ + super().__init__() + self.dataset_name = name + self.generalization_mark = None + + @staticmethod + def get_requirements() -> list[dict]: + """ + Returns requirements of this module + + :return: list of dict with requirements of this module + :rtype: list[dict] + """ + return [ + { + "name": "numpy", + "version": "1.23.5" + }, + { + "name": "pandas", + "version": "1.5.2" + }, + { + "name": "tensorboard", + "version": "2.13.0" + } + ] + + def preprocess(self, input_data: dict, config: dict, **kwargs): + """ + In this module, the preprocessing step is transforming the data to the correct target format. + + :param input_data: collected information of the benchmarking process + :type input_data: dict + :param config: config specifying the parameters of the training + :type config: dict + :param kwargs: optional additional settings + :type kwargs: dict + :return: tuple with transformed problem and the time it took to map it + :rtype: (dict, float) + """ + start = start_time_measurement() + output = self.data_load(input_data, config) + + if "generalization_metrics" in list(output.keys()): + self.generalization_mark = True + + return output, end_time_measurement(start) + + def postprocess(self, input_data: dict, config: dict, **kwargs): + """ + In this module, the postprocessing step is transforming the data to the correct target format. + + :param input_data: any + :type input_data: dict + :param config: config specifying the parameters of the training + :type config: dict + :param kwargs: optional additional settings + :type kwargs: dict + :return: tuple with an output_dictionary and the time it took + :rtype: (dict, float) + """ + start = start_time_measurement() + store_dir_iter = input_data["store_dir_iter"] + current_directory = os.getcwd() + + if "samples_complete" in list(input_data.keys()): + with open(f"{store_dir_iter}/samples_complete_{kwargs['rep_count']}.pkl", 'wb') as f: + pickle.dump(input_data.pop("samples_complete"), f) + + evaluation, _ = self.evaluate(input_data) + + if self.generalization_mark is not None: + self.metrics.add_metric_batch({"KL_best": evaluation["KL_best"]}) + metrics, _ = self.generalisation(input_data) + + # Save generalisation metrics + with open(f"{store_dir_iter}/record_gen_metrics_{kwargs['rep_count']}.pkl", 'wb') as f: + pickle.dump(metrics, f) + + self.metrics.add_metric_batch({"generalisation_metrics": metrics}) + + else: + self.metrics.add_metric_batch({"KL_best": evaluation}) + + # Save metrics per iteration + if "inference" not in input_data.keys(): + DataHandler.tb_to_pd(logdir=store_dir_iter, rep=kwargs['rep_count']) + self.metrics.add_metric_batch( + {"metrics_pandas": os.path.relpath(f"{store_dir_iter}/data.pkl", current_directory)}) + if self.generalization_mark is not None: + np.save(f"{store_dir_iter}/histogram_generated.npy", evaluation["histogram_generated"]) + else: + np.save(f"{store_dir_iter}/histogram_generated.npy", input_data.pop("histogram_generated")) + self.metrics.add_metric_batch({"histogram_generated": os.path.relpath( + f"{store_dir_iter}/histogram_generated.npy_{kwargs['rep_count']}.npy", current_directory)}) + + # Save histogram generated dataset + np.save(f"{store_dir_iter}/histogram_train.npy", input_data.pop("histogram_train")) + self.metrics.add_metric_batch({"histogram_train": os.path.relpath( + f"{store_dir_iter}/histogram_train.npy_{kwargs['rep_count']}.npy", current_directory)}) + + # Save best parameters + np.save(f"{store_dir_iter}/best_parameters_{kwargs['rep_count']}.npy", input_data.pop("best_parameter")) + self.metrics.add_metric_batch({"best_parameter": os.path.relpath( + f"{store_dir_iter}/best_parameters_{kwargs['rep_count']}.npy", current_directory)}) + + # Save training results + with open(f"{store_dir_iter}/training_results-{kwargs['rep_count']}.pkl", 'wb') as f: + pickle.dump(input_data, f) + + # Save variables transformed space + if "Transformation" in list(input_data.keys()): + self.metrics.add_metric_batch({"KL_best": input_data["KL_best_transformed"]}) + np.save(f"{store_dir_iter}/histogram_train_original.npy", input_data.pop("histogram_train_original")) + np.save(f"{store_dir_iter}/histogram_generated_original.npy", + input_data.pop("histogram_generated_original")) + with open(f"{store_dir_iter}/best_samples_transformed_{kwargs['rep_count']}.pkl", 'wb') as f: + pickle.dump(input_data["transformed_samples"], f) + + return input_data, end_time_measurement(start) + + @abstractmethod + def data_load(self, gen_mod: dict, config: dict) -> dict: + """ + Helps to ensure that the model can effectively learn the underlying + patterns and structure of the data, and produce high-quality outputs. + + :param gen_mod: dictionary with collected information of the previous modules + :type gen_mod: dict + :param config: config specifying the parameters of the data handler + :type config: dict + :return: mapped problem and the time it took to create the mapping + :rtype: tuple(any, float) + """ + pass + + def generalisation(self, solution: list) -> (dict, float): + """ + Compute generalisation metrics + + :param solution: + :type solution: any + :return: Evaluation and the time it took to create it + :rtype: tuple(any, float) + + """ + pass + + @abstractmethod + def evaluate(self, solution: any) -> (dict, float): + """ + Compute best loss values. + + :param solution: + :type solution: any + :return: bool and the time it took to create it + :rtype: tuple(bool, float) + + """ + pass + + @staticmethod + def tb_to_pd(logdir: str, rep: str) -> None: + """ + Converts TensorBoard event files in the specified log directory into a pandas DataFrame and saves it as a pickle file. + + :param logdir: path to the log directory containing TensorBoard event files + :type logdir: str + + """ + event_acc = EventAccumulator(logdir) + event_acc.Reload() + tags = event_acc.Tags() + tag_data = {} + for tag in tags['scalars']: + data = event_acc.Scalars(tag) + tag_values = [d.value for d in data] + tag_data[tag] = tag_values + data = pd.DataFrame(tag_data, index=[d.step for d in data]) + data.to_pickle(f"{logdir}/data_{rep}.pkl") diff --git a/src/modules/applications/QML/data_handler/DiscreteData.py b/src/modules/applications/QML/data_handler/DiscreteData.py new file mode 100644 index 00000000..0cc1135f --- /dev/null +++ b/src/modules/applications/QML/data_handler/DiscreteData.py @@ -0,0 +1,192 @@ +# Copyright 2021 The QUARK Authors. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +from typing import TypedDict, Union +import itertools +import logging +from pprint import pformat + +import numpy as np + +from modules.applications.QML.data_handler.DataHandler import * +from modules.applications.QML.circuits.CircuitCardinality import CircuitCardinality +from modules.applications.QML.data_handler.MetricsGeneralization import MetricsGeneralization + + +class DiscreteData(DataHandler): + """ + A data handler for discrete datasets with cardinality constraints. This class creates a dataset with a cardinality constraint and provides + methods for generalisation metrics computing and evaluation. + """ + + def __init__(self): + super().__init__("") + self.submodule_options = ["CircuitCardinality"] + self.dataset_name = None + self.n_registers = None + + @staticmethod + def get_requirements() -> list[dict]: + """ + Returns requirements of this module + + :return: list of dict with requirements of this module + :rtype: list[dict] + """ + return [ + { + "name": "numpy", + "version": "1.23.5" + } + ] + + def get_default_submodule(self, circuit_option: str) -> CircuitCardinality: + + if circuit_option == "CircuitCardinality": + return CircuitCardinality() + else: + raise NotImplementedError( + f"Circuit Option {circuit_option} not implemented") + + def get_parameter_options(self) -> dict: + """ + Returns the configurable settings for this application + + :return: + .. code-block:: python + + return { + "train_size": { + "values": [0.1, 0.3, 0.5, 0.7, 0.9, 1.0], + "description": "What percentage of the dataset do you want to use for training?" + } + } + + """ + return { + "train_size": { + "values": [0.1, 0.3, 0.5, 0.7, 0.9, 1.0], + "description": "What percentage of the dataset do you want to use for training?" + }, + } + + class Config(TypedDict): + """ + Attributes of a valid config + + .. code-block:: python + + n_qubits: int + train_size: int + + """ + + n_qubits: int + train_size: int + + def data_load(self, gen_mod: dict, config: Config) -> dict: + """ + The cardinality constrained dataset is created and split into a training set. + + :param gen_mod: Dictionary with collected information of the previous modules + :type gen_mod: dict + :param config: Config specifying the paramters of the data handler + :type config: dict + :return: Must always return the mapped problem and the time it took to create the mapping + :rtype: tuple(any, float) + """ + self.dataset_name = "Cardinality_Constraint" + self.n_qubits = gen_mod["n_qubits"] + self.train_size = config["train_size"] + self.num_ones = self.n_qubits // 2 + + # Generate all possible binary permutations of length n_qubits using NumPy arrays + search_space = np.array(list(itertools.product([0, 1], repeat=self.n_qubits))) + search_space = np.apply_along_axis(lambda x: ''.join(str(bit) for bit in x), 1, search_space) + + # Filter the binary permutations based on the cardinality constraint using np.char.count + cardinality_constraint = np.char.count(search_space, '1') == self.num_ones + solution_set = search_space[cardinality_constraint] + + # Use np.random.choice to select the desired number of rows randomly + size_train = int(self.train_size * len(solution_set)) + train_set_indices = np.random.choice(len(solution_set), size_train, replace=False) + train_set = solution_set[train_set_indices] + + # Create the histogram solution data + self.histogram_solution = np.zeros(2 ** self.n_qubits) + self.solution_set = np.array([int(i, 2) for i in solution_set]) + self.histogram_solution[self.solution_set] = 1 / len(self.solution_set) + + # Create the histogram training data + self.histogram_train = np.zeros(2 ** self.n_qubits) + self.train_set = np.array([int(i, 2) for i in train_set]) + self.histogram_train[self.train_set] = 1 / len(self.train_set) + + self.generalization_metrics = MetricsGeneralization( + train_set=self.train_set, + train_size=self.train_size, + solution_set=self.solution_set, + n_qubits=self.n_qubits, + ) + + application_config = { + "dataset_name": self.dataset_name, + "n_qubits": self.n_qubits, + "histogram_solution": self.histogram_solution, + "histogram_train": self.histogram_train, + "generalization_metrics": self.generalization_metrics, + "store_dir_iter": gen_mod["store_dir_iter"]} + + return application_config + + def generalisation(self, solution: list) -> (dict, float): + """ + Calculate generalization metrics for the generated. + + :param solution: A list representing the solution to be evaluated. + :type solution: list + :return: A tuple containing a dictionary of generalization metrics and the execution time in seconds. + :rtype: tuple + """ + start = start_time_measurement() + results = self.generalization_metrics.get_metrics(self.samples) + + logging.info(pformat(results)) + + return results, end_time_measurement(start) + + def evaluate(self, solution: list) -> (dict, float): + """ + Evaluates a given solution and calculates the histogram of generated samples and the minimum KL divergence value. + + :param solution: A dictionary-like object containing the solution data, including generated samples and KL divergence values. + :type solution: list + :return: A tuple containing a dictionary with the histogram of generated samples and the minimum KL divergence value, + and the time it took to evaluate the solution in milliseconds. + :rtype: (dict, float) + """ + start = start_time_measurement() + self.samples = solution["best_sample"] + self.n_shots = np.sum(self.samples) + + histogram_generated = np.asarray(self.samples) / self.n_shots + histogram_generated[histogram_generated == 0] = 1e-8 + + KL_list = solution["KL"] + KL_best = min(KL_list) + + evaluate_dict = {"histogram_generated": histogram_generated, "KL_best": KL_best} + + return evaluate_dict, end_time_measurement(start) diff --git a/src/modules/applications/QML/data_handler/MetricsGeneralization.py b/src/modules/applications/QML/data_handler/MetricsGeneralization.py new file mode 100644 index 00000000..7890d1e5 --- /dev/null +++ b/src/modules/applications/QML/data_handler/MetricsGeneralization.py @@ -0,0 +1,151 @@ +# Copyright 2021 The QUARK Authors. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +import math + +import numpy as np +from typing import Tuple, Dict + + +class MetricsGeneralization: + """ + A class to compute generalization metrics for generated samples based on train and solution sets. + + :param train_set: Set of queries in the training set. + :type train_set: np.array + :param train_size: The fraction of queries used for training. + :type train_size: float + :param solution_set: Set of queries in the solution set. + :type solution_set: np.array + :param n_qubits: The number of qubits. + :type n_qubits: int + """ + + def __init__( + + self, + train_set, + train_size, + solution_set, + n_qubits, + + ) -> None: + self.train_set = train_set + self.train_size = train_size + self.solution_set = solution_set + self.n_states = 2 ** n_qubits + self.n_shots = 10000 + + self.mask_new, self.mask_sol = self.get_masks() + + def get_masks(self) -> Tuple[np.array, np.array]: + """ + Method to determine the masks, on which the generalization metrics are based on + + :return: The masks needed to determine the generalization metrics for a given train and solution set + :rtype: tuple(np.array, np.array) + """ + + mask_new = np.ones(self.n_states, dtype=bool) + mask_new[self.train_set] = 0 + + mask_sol = np.zeros(self.n_states, dtype=bool) + mask_sol[self.solution_set] = 1 + mask_sol[self.train_set] = 0 + + return mask_new, mask_sol + + def get_metrics(self, generated: np.array) -> Dict[str, float]: + """ + Method that determines all generalization metrics a given multiset of generated samples + + :param generated: Generated samples + :type generated: np.array + :return: Dictionary with generalization metrics + :rtype: dict + """ + g_new = np.sum(generated[self.mask_new]) + g_sol = np.sum(generated[self.mask_sol]) + g_sol_unique = generated[self.mask_sol & self.mask_new] + g_sol_unique = g_sol_unique[g_sol_unique != 0].size + g_train = generated[self.train_set] + + results = { + "fidelity": self.fidelity(g_new, g_sol), + "exploration": self.exploration(g_new), + "coverage": self.coverage(g_sol_unique), + "normalized_rate": self.normalized_rate(g_sol), + "precision": self.precision(g_sol, g_train) + + } + return results + + def fidelity(self, g_new: float, g_sol: float) -> float: + """ + Method to determine the fidelity + + :param g_new: Multi-subset of unseen queries (noisy or valid) + :type g_new: float + :param g_sol: Multi-subset of unseen and valid queries + :type g_sol: float + :return: fidelity + :rtype: float + """ + return g_sol / g_new + + def coverage(self, g_sol_unique: float) -> float: + """ + Method to determine the coverage + + :param g_sol_unique: Subset of unique unseen and valid queries + :type g_sol_unique: float + :return: coverage + :rtype: float + """ + return g_sol_unique / (math.ceil(1 - self.train_size) * len(self.solution_set)) + + def normalized_rate(self, g_sol: float) -> float: + """ + Method to determine the normalized_rate + + :param g_sol: Multi-subset of unseen and valid queries + :type g_sol: float + :return: normalized_rate + :rtype: float + """ + return g_sol / ((1 - self.train_size) * self.n_shots) + + def exploration(self, g_new: float) -> float: + """ + Method to determine the exploration + + :param g_new: Multi-subset of unseen queries (noisy or valid) + :type g_new: float + :return: exploration + :rtype: float + """ + return g_new / self.n_shots + + def precision(self, g_sol: float, g_train: float) -> float: + """ + Method to determine the precision + + :param g_sol: Multi-subset of unseen and valid queries + :type g_sol: float + :param g_train: Number of queries that were memorized from the training set + :type g_train: float + :return: precision + :rtype: float + """ + return (np.sum(g_sol) + np.sum(g_train)) / self.n_shots diff --git a/src/modules/applications/QML/data_handler/__init__.py b/src/modules/applications/QML/data_handler/__init__.py new file mode 100644 index 00000000..e0539e5e --- /dev/null +++ b/src/modules/applications/QML/data_handler/__init__.py @@ -0,0 +1,15 @@ +# Copyright 2022 The QUARK Authors. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +"""Package containing the dataset modules""" diff --git a/src/modules/applications/QML/generative_modeling/GenerativeModeling.py b/src/modules/applications/QML/generative_modeling/GenerativeModeling.py new file mode 100644 index 00000000..97d97d73 --- /dev/null +++ b/src/modules/applications/QML/generative_modeling/GenerativeModeling.py @@ -0,0 +1,143 @@ +# Copyright 2021 The QUARK Authors. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +from utils import start_time_measurement, end_time_measurement +from typing import Union + +from modules.applications.Application import * +from modules.applications.QML.QML import QML +from modules.applications.QML.data_handler.DiscreteData import DiscreteData +from modules.applications.QML.data_handler.ContinuousData import ContinuousData + + +class GenerativeModeling(QML): + """ + Generative models enable the creation of new data by learning the underlying probability distribution of the + training data set of interest. More specifically, a generative model attempts to learn an unknown probability + distribution Q by modeling an approximated probability distribution P(θ) which is parameterized by a set of + variables θ. Data sampled from Q is used to train a model by tuning θ such that P(θ) more closely approximates Q. + """ + + def __init__(self): + """ + Constructor method + """ + super().__init__("GenerativeModeling") + self.submodule_options = ["Continuous Data", "Discrete Data"] + self.data = None + self.dataset_name = None + self.n_registers = None + self.true_probability = None + self.cc = None + self.gc = None + self.bitstrings = None + self.bitstrings_train = None + self.constrained_bitstring = None + self.processed_solution = None + + @staticmethod + def get_requirements() -> list[dict]: + """ + Returns requirements of this module + + :return: list of dict with requirements of this module + :rtype: list[dict] + """ + return [] + + def get_solution_quality_unit(self) -> str: + return "minimum KL" + + def get_default_submodule(self, data_option: str) -> Union[ContinuousData, DiscreteData]: + if data_option == "Continuous Data": + self.data = ContinuousData() + elif data_option == "Discrete Data": + self.data = DiscreteData() + else: + raise NotImplementedError(f"Transformation Option {data_option} not implemented") + return self.data + + def get_parameter_options(self) -> dict: + """ + Returns the configurable settings for this application + + :return: + .. code-block:: python + + return { + "n_qubits": { + "values": [4, 6, 8, 10, 12], + "description": "How many qubits do you want to use?" + } + } + + """ + return { + "n_qubits": { + "values": [6, 8, 10, 12], + "description": "How many qubits do you want to use?" + } + } + + def generate_problem(self, config) -> dict: + + """ + The number of qubits is chosen for this problem. + + :param config: + :type config: Config + :return: n_qubits + :rtype: dict + """ + + application_config = {"n_qubits": config["n_qubits"]} + return application_config + + def preprocess(self, input_data: dict, config: dict, **kwargs): + """ + Generate the actual problem instance in the preprocess function. + :param input_data: Usually not used for this method. + :type input_data: dict + + :param config: config for the problem creation. + :param config: + + :param kwargs: Optional additional arguments + :type kwargs: dict + + :param kwargs: optional additional arguments. + + :return: + """ + start = start_time_measurement() + output = self.generate_problem(config) + output["store_dir_iter"] = f"{kwargs['store_dir']}/rep_{kwargs['rep_count']}" + return output, end_time_measurement(start) + + def postprocess(self, input_data: dict, config: dict, **kwargs): + """ + Process the solution here, then validate and evluate it. + + :param input_data: A representation of the quntum machine learning model that will be trained + :type input_data: dict + :param config: Config specifying the parameters of the training + :type config: dict + :param kwargs: optional keyword arguments + :type kwargs: dict + :return: tuple with same dictionary like input_data and the time it + :rtype: (dict, float) + """ + + start = start_time_measurement() + return input_data, end_time_measurement(start) diff --git a/src/modules/applications/QML/generative_modeling/__init__.py b/src/modules/applications/QML/generative_modeling/__init__.py new file mode 100644 index 00000000..270cd77a --- /dev/null +++ b/src/modules/applications/QML/generative_modeling/__init__.py @@ -0,0 +1,15 @@ +# Copyright 2022 The QUARK Authors. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +"""Package containing all generative model applications""" diff --git a/src/modules/applications/QML/libraries/Library.py b/src/modules/applications/QML/libraries/Library.py new file mode 100644 index 00000000..699d007d --- /dev/null +++ b/src/modules/applications/QML/libraries/Library.py @@ -0,0 +1,97 @@ +# Copyright 2021 The QUARK Authors. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +from abc import ABC, abstractmethod +from typing import TypedDict +import logging +from utils import start_time_measurement, end_time_measurement + +from modules.Core import Core + + +class Library(Core, ABC): + """ + This class is an abstract base class for mapping a library-agnostic gate sequence to a library such as Qiskit + """ + + def __init__(self): + """ + Constructor method + """ + super().__init__() + + class Config(TypedDict): + """ + Attributes of a valid config + + .. code-block:: python + + backend: str + n_shots: int + + """ + backend: str + n_shots: int + + def preprocess(self, input_data: dict, config: Config, **kwargs): + """ + Base class for mapping the gate sequence to a library such as Qiskit. + + :param input_data: Collection of information from the previous modules + :type input_data: dict + :param config: Config specifying the number of qubits of the circuit + :type config: Config + :param kwargs: optional keyword arguments + :type kwargs: dict + :return: Dictionary including the function to execute the quantum cicrcuit on a simulator or on quantum hardware + :rtype: (dict, float) + """ + + start = start_time_measurement() + + output = self.sequence_to_circuit(input_data) + backend = self.select_backend(config["backend"]) + output["execute_circuit"] = self.get_execute_circuit(output["circuit"], backend, config["backend"], + config["n_shots"]) + output["backend"] = config["backend"] + output["n_shots"] = config["n_shots"] + logging.info("Library created") + output["store_dir"] = kwargs["store_dir"] + + return output, end_time_measurement(start) + + def postprocess(self, input_data: dict, config: dict, **kwargs): + """ + This method corresponds to the identity and passes the information of the subsequent module + back to the preceding module in the benchmarking process. + + :param input_data: Collected information of the benchmarking process + :type input_data: dict + :param config: Config specifying the number of qubits of the circuit + :type config: Config + :param kwargs: optional keyword arguments + :type kwargs: dict + :return: Same dictionary like input_data with architecture_name + :rtype: (dict, float) + """ + start = start_time_measurement() + return input_data, end_time_measurement(start) + + @abstractmethod + def sequence_to_circuit(self, input_data): + pass + + @abstractmethod + def get_execute_circuit(self): + pass diff --git a/src/modules/applications/QML/libraries/LibraryQiskit.py b/src/modules/applications/QML/libraries/LibraryQiskit.py new file mode 100644 index 00000000..7fd4f9d4 --- /dev/null +++ b/src/modules/applications/QML/libraries/LibraryQiskit.py @@ -0,0 +1,321 @@ +# Copyright 2021 The QUARK Authors. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +from typing import Union +import logging + +from qiskit import QuantumCircuit +from qiskit.circuit import Parameter +from qiskit.compiler import transpile, assemble +from qiskit.providers import Backend +import numpy as np + +from modules.applications.QML.training.QCBM import QCBM +from modules.applications.QML.training.Inference import Inference +from modules.applications.QML.libraries.Library import Library + +logging.getLogger("qiskit").setLevel(logging.WARNING) + + +class LibraryQiskit(Library): + """ + This module maps a library-agnostic gate sequence to a qiskit circuit + """ + + def __init__(self): + """ + Constructor method + """ + super().__init__() + self.submodule_options = ["QCBM", "Inference"] + + @staticmethod + def get_requirements() -> list[dict]: + """ + Returns requirements of this module + + :return: list of dict with requirements of this module + :rtype: list[dict] + """ + return [ + { + "name": "qiskit", + "version": "0.40.0" + }, + { + "name": "numpy", + "version": "1.23.5" + }, + ] + + def get_parameter_options(self) -> dict: + """ + Returns the configurable settings for the Qiskit Library. + + :return: + .. code-block:: python + + return { + "backend": { + "values": ["aer_statevector_simulator_gpu", "aer_statevector_simulator_cpu", + "cusvaer_simulator (only available in cuQuantum applicance)", "aer_simulator_gpu", + "aer_simulator_cpu", "ionQ_Harmony", "Amazon_SV1"], + "description": "Which backend do you want to use? (aer_statevector_simulator uses the measurement probability vector, the others are shot based)" + }, + + "n_shots": { + "values": [100, 1000, 10000, 1000000], + "description": "How many shots do you want use for estimating the PMF of the model? (If the aer_statevector_simulator selected, only relevant for studying generalization)" + } + } + + """ + return { + "backend": { + "values": ["aer_statevector_simulator_gpu", "aer_statevector_simulator_cpu", + "cusvaer_simulator (only available in cuQuantum applicance)", "aer_simulator_gpu", + "aer_simulator_cpu", "ionQ_Harmony", "Amazon_SV1"], + "description": "Which backend do you want to use? (aer_statevector_simulator uses the measurement probability vector, the others are shot based)" + }, + + "n_shots": { + "values": [100, 1000, 10000, 1000000], + "description": "How many shots do you want use for estimating the PMF of the model? (If the aer_statevector_simulator selected, only relevant for studying generalization)" + } + } + + def get_default_submodule(self, training_option: str) -> Union[QCBM, Inference]: + + if training_option == "QCBM": + return QCBM() + elif training_option == "Inference": + return Inference() + else: + raise NotImplementedError(f"Training option {training_option} not implemented") + + def sequence_to_circuit(self, input_data: dict) -> dict: + """ + Maps the gate sequence, that specifies the architecture of a quantum circuit + to its Qiskit implementation. + + :param input_data: Collected information of the benchmarking process + :type input_data: dict + :return: Same dictionary but the gate sequence is replaced by it Qiskit implementation + :rtype: dict + """ + n_qubits = input_data["n_qubits"] + gate_sequence = input_data["gate_sequence"] + + circuit = QuantumCircuit(n_qubits, n_qubits) + param_counter = 0 + for gate, wires in gate_sequence: + + if gate == "Hadamard": + circuit.h(wires[0]) + + elif gate == "CNOT": + circuit.cnot(wires[0], wires[1]) + + elif gate == "RZ": + circuit.rz(Parameter(f"x_{param_counter:03d}"), wires[0]) + param_counter += 1 + + elif gate == "RX": + circuit.rx(Parameter(f"x_{param_counter:03d}"), wires[0]) + param_counter += 1 + + elif gate == "RY": + circuit.ry(Parameter(f"x_{param_counter:03d}"), wires[0]) + param_counter += 1 + + elif gate == "RXX": + circuit.rxx(Parameter(f"x_{param_counter:03d}"), wires[0], wires[1]) + param_counter += 1 + + elif gate == "RYY": + circuit.ryy(Parameter(f"x_{param_counter:03d}"), wires[0], wires[1]) + param_counter += 1 + + elif gate == "RZZ": + circuit.rzz(Parameter(f"x_{param_counter:03d}"), wires[0], wires[1]) + param_counter += 1 + + elif gate == "CRY": + circuit.cry(Parameter(f"x_{param_counter:03d}"), wires[0], wires[1]) + param_counter += 1 + + elif gate == "Barrier": + circuit.barrier() + + elif gate == "Measure": + circuit.measure(wires[0], wires[0]) + + else: + raise NotImplementedError(f"Gate {gate} not implemented") + + input_data["circuit"] = circuit + input_data.pop("gate_sequence") + return input_data + + @staticmethod + def select_backend(backend_config: str) -> dict: + """ + This method configures the backend + + :param backend_config: Name of a backend + :type backend_config: str + :return: Configured qiskit backend + :rtype: qiskit.providers.Backend + """ + if backend_config == "cusvaer_simulator (only available in cuQuantum applicance)": + import cusvaer + from qiskit.providers.aer import AerSimulator + backend = AerSimulator( + method="statevector", + device="GPU", + cusvaer_enable=True, + noise_model=None, + cusvaer_p2p_device_bits=3, + cusvaer_comm_plugin_type=cusvaer.CommPluginType.MPI_AUTO, + cusvaer_comm_plugin_soname="libmpi.so" + ) + + elif backend_config == "aer_simulator_gpu": + from qiskit import Aer + backend = Aer.get_backend("aer_simulator") + backend.set_options(device="GPU") + + elif backend_config == "aer_simulator_cpu": + from qiskit import Aer + backend = Aer.get_backend("aer_simulator") + backend.set_options(device="CPU") + + elif backend_config == "aer_statevector_simulator_gpu": + from qiskit import Aer + backend = Aer.get_backend('statevector_simulator') + backend.set_options(device="GPU") + + elif backend_config == "aer_statevector_simulator_cpu": + from qiskit import Aer + backend = Aer.get_backend('statevector_simulator') + backend.set_options(device="CPU") + + elif backend_config == "ionQ_Harmony": + from modules.devices.braket.Ionq import Ionq + from qiskit_braket_provider import AWSBraketBackend, AWSBraketProvider + device_wrapper = Ionq("ionQ", "arn:aws:braket:::device/qpu/ionq/ionQdevice") + backend = AWSBraketBackend( + device=device_wrapper.device, + provider=AWSBraketProvider(), + name=device_wrapper.device.name, + description=f"AWS Device: {device_wrapper.device.provider_name} {device_wrapper.device.name}.", + online_date=device_wrapper.device.properties.service.updatedAt, + backend_version="2", + ) + + elif backend_config == "Amazon_SV1": + from modules.devices.braket.SV1 import SV1 + from qiskit_braket_provider import AWSBraketBackend, AWSBraketProvider + device_wrapper = SV1("SV1", "arn:aws:braket:::device/quantum-simulator/amazon/sv1") + backend = AWSBraketBackend( + device=device_wrapper.device, + provider=AWSBraketProvider(), + name=device_wrapper.device.name, + description=f"AWS Device: {device_wrapper.device.provider_name} {device_wrapper.device.name}.", + online_date=device_wrapper.device.properties.service.updatedAt, + backend_version="2", + ) + + else: + raise NotImplementedError(f"Device Configuration {backend_config} not implemented") + + return backend + + @staticmethod + def get_execute_circuit(circuit: QuantumCircuit, backend: Backend, backend_config: str, n_shots: int) -> callable: + """ + This method combnines the qiskit circuit implemenation and the selected backend and returns a function, + that will be called during training. + + :param circuit: Qiskit implementation of the quantum circuit + :type circuit: qiskit.circuit.QuantumCircuit + :param backend: Configured qiskit backend + :type backend: qiskit.providers.Backend + :param backend_config: Name of a backend + :type backend_config: str + :param n_shots: The number of times the circuit is run + :type n_shots: int + :return: Method that executes the quantum circuit for a given set of parameters + :rtype: callable + """ + n_qubits = circuit.num_qubits + circuit_transpiled = transpile(circuit, backend=backend) + + if backend_config in ["aer_statevector_simulator_gpu", "aer_statevector_simulator_cpu"]: + circuit_transpiled.remove_final_measurements() + + def execute_circuit(solutions): + all_circuits = [circuit_transpiled.bind_parameters(solution) for solution in solutions] + qobj = assemble(all_circuits, backend=backend) + jobs = backend.run(qobj) + pmfs = [jobs.result().get_statevector(circuit).probabilities() for circuit in all_circuits] + return pmfs, None + + elif backend_config in ["ionQ_Harmony", "Amazon_SV1"]: + import time as timetest + def execute_circuit(solutions): + all_circuits = [circuit_transpiled.bind_parameters(solution) for solution in solutions] + jobs = backend.run(all_circuits, shots=n_shots) + while not jobs.in_final_state(): + logging.info("Waiting 10 seconds for task to finish") + timetest.sleep(10) + + samples_dictionary = [jobs.result().get_counts(circuit).int_outcomes() for circuit in all_circuits] + + samples = [] + for result in samples_dictionary: + target_iter = np.zeros(2 ** n_qubits) + result_keys = list(result.keys()) + result_vals = list(result.values()) + target_iter[result_keys] = result_vals + target_iter = np.asarray(target_iter) + samples.append(target_iter) + + samples = np.asarray(samples) + pmfs = samples / n_shots + + return pmfs, samples + + elif backend_config in ["cusvaer_simulator (only available in cuQuantum applicance)", "aer_simulator_cpu", + "aer_simulator_gpu"]: + def execute_circuit(solutions): + all_circuits = [circuit_transpiled.bind_parameters(solution) for solution in solutions] + qobjs = assemble(all_circuits, backend=backend) + jobs = backend.run(qobjs, shots=n_shots) + samples_dictionary = [jobs.result().get_counts(circuit).int_outcomes() for circuit in all_circuits] + + samples = [] + for result in samples_dictionary: + target_iter = np.zeros(2 ** n_qubits) + result_keys = list(result.keys()) + result_vals = list(result.values()) + target_iter[result_keys] = result_vals + target_iter = np.asarray(target_iter) + samples.append(target_iter) + + samples = np.asarray(samples) + pmfs = samples / n_shots + return pmfs, samples + + return execute_circuit diff --git a/src/modules/applications/QML/libraries/__init__.py b/src/modules/applications/QML/libraries/__init__.py new file mode 100644 index 00000000..d88744ab --- /dev/null +++ b/src/modules/applications/QML/libraries/__init__.py @@ -0,0 +1,15 @@ +# Copyright 2022 The QUARK Authors. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +"""Package containing all libraries""" diff --git a/src/modules/applications/QML/training/Inference.py b/src/modules/applications/QML/training/Inference.py new file mode 100644 index 00000000..ea8548aa --- /dev/null +++ b/src/modules/applications/QML/training/Inference.py @@ -0,0 +1,114 @@ +# Copyright 2021 The QUARK Authors. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +from typing import TypedDict +from modules.applications.QML.training.Training import * + + +class Inference(Training): + """ + This module executes a quantum circuit with parameters of a pretrained model. + """ + + def __init__(self): + """ + Constructor method + """ + super().__init__("Inference") + + @staticmethod + def get_requirements() -> list[dict]: + """ + Returns requirements of this module + + :return: list of dict with requirements of this module + :rtype: list[dict] + """ + return [ + { + "name": "numpy", + "version": "1.23.5" + } + ] + + def get_parameter_options(self) -> dict: + """ + Returns the configurable settings for this circuit + + :return: + .. code-block:: python + + return { + "pretrained": { + "values": [False], + "custom_input": True, + "postproc": str, + "description": "Please provide the parameters of a pretrained model?" + }, + } + """ + return { + "pretrained": { + "values": [], + "custom_input": True, + "postproc": str, + "description": "Please provide the parameters of a pretrained model?" + }, + } + + class Config(TypedDict): + """ + Attributes of a valid config. + + .. code-block:: python + + pretrained: str + + """ + pretrained: str + + def get_default_submodule(self, option: str) -> Core: + raise ValueError("This module has no submodules.") + + def start_training(self, input_data: dict, config: Config, **kwargs: dict) -> dict: + """ + Method that uses a pretrained model for inference + + :param input_data: Dictionary with information needed for inference + :type input_data: dict + :param config: Inference settings + :type config: Config + :param kwargs: Optional additional arguments + :type kwargs: dict + :return: Dictionary including the information of previous modules as well as of this module + :rtype: dict + """ + self.n_states_range = range(2 ** input_data['n_qubits']) + self.target = np.asarray(input_data["histogram_train"]) + execute_circuit = input_data["execute_circuit"] + + parameters = np.load(config["pretrained"]) + + pmfs, samples = execute_circuit([parameters.get() if gpu else parameters]) + pmfs = np.asarray(pmfs) + samples = self.sample_from_pmf(pmf=pmfs[0], n_shots=input_data["n_shots"]) if samples is None else samples[0] + + loss = self.kl_divergence(pmfs.reshape([-1, 1])) + + input_data["best_parameter"] = parameters + input_data["inference"] = True + input_data["KL"] = [loss.get() if gpu else loss] + input_data["best_sample"] = samples.astype(int) + + return input_data diff --git a/src/modules/applications/QML/training/QCBM.py b/src/modules/applications/QML/training/QCBM.py new file mode 100644 index 00000000..3214fb90 --- /dev/null +++ b/src/modules/applications/QML/training/QCBM.py @@ -0,0 +1,303 @@ +# Copyright 2021 The QUARK Authors. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +from typing import TypedDict +import logging +from cma import CMAEvolutionStrategy +from tensorboardX import SummaryWriter +import matplotlib.pyplot as plt + +from modules.applications.QML.training.Training import * +from utils_mpi import is_running_mpi, get_comm + +MPI = is_running_mpi() +comm = get_comm() + + +class QCBM(Training): + """ + This module optmizes the paramters of quantum circuit using CMA-ES. + This training method is referred to as quantum circuit born machine (QCBM). + """ + + def __init__(self): + """ + Constructor method + """ + super().__init__("QCBM") + + @staticmethod + def get_requirements() -> list[dict]: + """ + Returns requirements of this module + + :return: list of dict with requirements of this module + :rtype: list[dict] + """ + return [ + { + "name": "numpy", + "version": "1.23.5" + }, + { + "name": "cma", + "version": "3.3.0" + }, + { + "name": "tensorboard", + "version": "2.13.0" + }, + { + "name": "tensorboardX", + "version": "2.6.2" + } + ] + + def get_parameter_options(self) -> dict: + """ + Returns the configurable settings for the quantum circuit born machine + + :return: + .. code-block:: python + + return { + + "population_size": { + "values": [5, 10, 100, 200, 10000], + "description": "What population size do you want?" + }, + + "max_evaluations": { + "values": [100, 1000, 20000, 100000], + "description": "What should be the maximum number of evaluations?" + }, + + "sigma": { + "values": [0.01, 0.5, 1, 2], + "description": "Which sigma would you like to use?" + }, + + "pretrained": { + "values": [False], + "custom_input": True, + "postproc": str, + "description": "Please provide the parameters of a pretrained model?" + }, + + "loss": { + "values": ["KL", "NLL"], + "description": "Which loss function do you want to use?" + } + } + """ + return { + "population_size": { + "values": [5, 10, 100, 200, 10000], + "description": "What population size do you want?" + }, + + "max_evaluations": { + "values": [100, 1000, 20000, 100000], + "description": "What should be the maximum number of evaluations?" + }, + + "sigma": { + "values": [0.01, 0.5, 1, 2], + "description": "Which sigma would you like to use?" + }, + + "pretrained": { + "values": [False], + "custom_input": True, + "postproc": str, + "description": "Please provide the parameters of a pretrained model?" + }, + + "loss": { + "values": ["KL", "NLL"], + "description": "Which loss function do you want to use?" + } + } + + class Config(TypedDict): + """ + Attributes of a valid config + + .. code-block:: python + + population_size: int + max_evaluations: int + sigma: float + pretrained: str + loss: str + + """ + population_size: int + max_evaluations: int + sigma: float + pretrained: str + loss: str + + def get_default_submodule(self, option: str) -> Core: + raise ValueError("This module has no submodules.") + + def setup_training(self, input_data, config) -> dict: + """ + Method to configure the training setup including CMA-ES and tensorboard. + + :param input_data: A representation of the quntum machine learning model that will be trained + :type input_data: dict + :param config: Config specifying the parameters of the training + :type config: dict + :return: Updated input_data + :rtype: dict + """ + size = None + input_data['MPI_size'] = size + input_data["store_dir_iter"] += f"_{input_data['dataset_name']}_qubits{input_data['n_qubits']}" + logging.info( + f"Running config: [backend={input_data['backend']}] [n_qubits={input_data['n_qubits']}] [n_shots={input_data['n_shots']}] [population_size={config['population_size']}]") + + if comm.Get_rank() == 0: + self.target = np.asarray(input_data["histogram_train"]) + self.target[self.target == 0] = 1e-8 + self.n_states_range = range(2 ** input_data['n_qubits']) + self.n_shots = input_data["n_shots"] + self.execute_circuit = input_data["execute_circuit"] + self.timing = self.Timing(gpu=gpu) + + self.study_generalization = "generalization_metrics" in list(input_data.keys()) + if self.study_generalization: + self.generalization_metrics = input_data["generalization_metrics"] + self.generalization_metrics.n_shots = input_data["n_shots"] + input_data["store_dir_iter"] += f"_alpha{self.generalization_metrics.train_size}_depth{input_data['depth']}" + + self.writer = SummaryWriter(input_data["store_dir_iter"]) + epochs = int(config['max_evaluations'] / config['population_size']) + self.image_epochs = range(0, epochs, 1) if int(epochs / 100) < 1 else range(0, epochs, int(epochs / 100)) + self.tb_images = "2D" in input_data["dataset_name"] + + if config['loss'] == "KL": + self.loss_func = self.kl_divergence + elif config['loss'] == "NLL": + self.loss_func = self.nll + else: + raise NotImplementedError("Loss function not implemented") + + self.n_params = len(input_data["circuit"].parameters) + self.x0 = (np.random.rand(self.n_params) - 0.5) * np.pi + + if config["pretrained"] != "False": + parameters = np.load(config["pretrained"]) + self.x0[:len(parameters)] = parameters + logging.info(f'Training starting from parameters in path {config["pretrained"]}') + + self.options = { + 'bounds': [self.n_params * [-np.pi], self.n_params * [np.pi]], + 'maxfevals': config['max_evaluations'], + 'popsize': config['population_size'], + 'verbose': -3, + 'tolfun': 1e-12 + } + + return input_data + + def start_training(self, input_data: dict, config: Config, **kwargs: dict) -> (dict, float): + """ + This function finds the best parameters of the circuit on a transformed problem instance and returns a solution. + + :param input_data: A representation of the quntum machine learning model that will be trained + :type input_data: dict + :param config: Config specifying the paramters of the training + :type config: dict + :param kwargs: optional additional settings + :type kwargs: dict + :return: Dictionary including the information of previous modules as well as of the training + :rtype: dict + """ + input_data = self.setup_training(input_data, config) + + es = CMAEvolutionStrategy(self.x0.get() if gpu else self.x0, config['sigma'], self.options) + for parameter in ["best_parameters", "time_circuit", "time_loss", "KL", "best_sample"]: + input_data[parameter] = [] + + best_loss = float("inf") + fig, ax = plt.subplots() + while not es.stop(): + solutions = es.ask() + epoch = es.result[4] + sigma = es.sigma + + self.timing.start_recording() + pmfs_model, samples = self.execute_circuit(solutions) + pmfs_model = np.asarray(pmfs_model) + time_circ = self.timing.stop_recording() + + self.timing.start_recording() + if comm.Get_rank() == 0: + loss_epoch = self.loss_func(pmfs_model.reshape([config['population_size'], -1])) + else: + loss_epoch = np.empty(config["population_size"]) + comm.Bcast(loss_epoch, root=0) + comm.Barrier() + + time_loss = self.timing.stop_recording() + + es.tell(solutions, loss_epoch.get() if gpu else loss_epoch) + + if es.result[1] < best_loss: + best_loss = es.result[1] + index = loss_epoch.argmin() + best_pmf = pmfs_model[index] / pmfs_model[index].sum() + if self.study_generalization: + counts = self.sample_from_pmf(pmf=best_pmf.get() if gpu else best_pmf, + n_shots=self.generalization_metrics.n_shots) if samples is None else \ + samples[int(index)] + metrics = self.generalization_metrics.get_metrics(counts) + for (key, value) in metrics.items(): + self.writer.add_scalar(f"metrics/{key}", value, epoch) + + self.writer.add_scalar("metrics/NLL", self.nll(best_pmf.reshape([1, -1])).get() if gpu else self.nll( + best_pmf.reshape([1, -1])), epoch) + self.writer.add_scalar("metrics/KL", self.kl_divergence( + best_pmf.reshape([1, -1])).get() if gpu else self.kl_divergence(best_pmf.reshape([1, -1])), epoch) + self.writer.add_scalar("time/circuit", time_circ, epoch) + self.writer.add_scalar("time/loss", time_loss, epoch) + input_data["best_parameters"].append(es.result[0]) + + input_data["KL"].append(float(es.result[1])) + + if self.tb_images and epoch in self.image_epochs: + ax.clear() + ax.imshow( + best_pmf.reshape(int(np.sqrt(best_pmf.size)), int(np.sqrt(best_pmf.size))).get() if gpu + else best_pmf.reshape(int(np.sqrt(best_pmf.size)), + int(np.sqrt(best_pmf.size))), + cmap='binary', + interpolation='none') + ax.set_title(f'Iteration {epoch}') + self.writer.add_figure('grid_figure', fig, global_step=epoch) + + logging.info( + f"[Iteration {es.result[4]}] [{config['loss']}: {es.result[1]:.5f}] [Circuit processing: {(time_circ):.3f} ms] [{config['loss']} processing: {(time_loss):.3f} ms] [sigma: {sigma:.5f}] ") + + plt.close() + self.writer.flush() + self.writer.close() + + input_data["best_parameter"] = es.result[0] + input_data["best_sample"] = self.sample_from_pmf(best_pmf.get() if gpu else best_pmf, + n_shots=input_data["n_shots"]) + + return input_data diff --git a/src/modules/applications/QML/training/Training.py b/src/modules/applications/QML/training/Training.py new file mode 100644 index 00000000..964dc049 --- /dev/null +++ b/src/modules/applications/QML/training/Training.py @@ -0,0 +1,148 @@ +# Copyright 2021 The QUARK Authors. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +import logging +from abc import ABC, abstractmethod + +import numpy as np_cpu + +try: + import cupy as np + + gpu = True + logging.info("Using CuPy, dataprocessing on GPU") +except ModuleNotFoundError: + import numpy as np + + gpu = False + logging.info("CuPy not available, using vanilla numpy, dataprocessing on CPU") + +from modules.Core import Core +from utils import start_time_measurement, end_time_measurement + + +class Training(Core, ABC): + """ + The Training module is the base class fot both finding (QCBM) and excuting trained models (Inference) + """ + + def __init__(self, name): + """ + Constructor method + """ + self.name = name + super().__init__() + + @staticmethod + def get_requirements() -> list[dict]: + """ + Returns requirements of this module + + :return: list of dict with requirements of this module + :rtype: list[dict] + """ + return [ + { + "name": "numpy", + "version": "1.23.5" + } + ] + + def postprocess(self, input_data: dict, config: dict, **kwargs): + """ + Here, the actual training of the machine learnning model is done + + :param input_data: Collected information of the benchmarking process + :type input_data: dict + :param config: Training settings + :type config: dict + :param kwargs: Optional additional arguments + :type kwargs: dict + :return: + :rtype: + """ + start = start_time_measurement() + logging.info("Start training") + training_results = self.start_training( + self.preprocessed_input, + config, + **kwargs + ) + for dict_key in ["backend", "circuit", "execute_circuit"]: + training_results.pop(dict_key) + postprocessing_time = end_time_measurement(start) + logging.info(f"Training finished in {postprocessing_time / 1000} s.") + return training_results, postprocessing_time + + @abstractmethod + def start_training(self, input_data, config, **kwargs) -> dict: + """ + This function starts the training of QML model or deploys a pretrained model. + + :param input_data: A representation of the quntum machine learning model that will be trained + :type input_data: dict + :param config: Config specifying the paramters of the training + :type config: dict + :param kwargs: optional additional settings + :type kwargs: dict + :return: Solution, the time it took to compute it and some optional additional information + :rtype: dict + """ + pass + + def sample_from_pmf(self, pmf, n_shots): + samples = np_cpu.random.choice(self.n_states_range, size=n_shots, p=pmf) + counts = np_cpu.bincount(samples, minlength=len(self.n_states_range)) + return counts + + def kl_divergence(self, pmf_model): + pmf_model[pmf_model == 0] = 1e-8 + return np.sum(self.target * np.log(self.target / pmf_model), axis=1) + + def nll(self, pmf_model): + pmf_model[pmf_model == 0] = 1e-8 + return -np.sum(self.target * np.log(pmf_model), axis=1) + + class Timing: + """ + This module is an abstraction of time measurement for for both CPU and GPU precesses + """ + + def __init__(self, gpu: bool): + """ + Constructor method + """ + self.gpu = gpu + if gpu: + self.start_recording = self.start_recording_gpu + self.stop_recording = self.stop_recording_gpu + else: + self.start_recording = self.start_recording_cpu + self.stop_recording = self.stop_recording_cpu + + def start_recording_cpu(self): + self.start_cpu = start_time_measurement() + + def stop_recording_cpu(self): + return end_time_measurement(self.start_cpu) + + def start_recording_gpu(self): + self.start_gpu = np.cuda.Event() + self.end_gpu = np.cuda.Event() + self.start_gpu.record() + + def stop_recording_gpu(self): + self.end_gpu.record() + self.end_gpu.synchronize() + return np.cuda.get_elapsed_time(self.start_gpu, self.end_gpu) diff --git a/src/modules/applications/QML/training/__init__.py b/src/modules/applications/QML/training/__init__.py new file mode 100644 index 00000000..44ac89bf --- /dev/null +++ b/src/modules/applications/QML/training/__init__.py @@ -0,0 +1,15 @@ +# Copyright 2022 The QUARK Authors. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +"""Package containing all training and inference modules""" diff --git a/src/modules/applications/QML/transformations/MinMax.py b/src/modules/applications/QML/transformations/MinMax.py new file mode 100644 index 00000000..f67329a8 --- /dev/null +++ b/src/modules/applications/QML/transformations/MinMax.py @@ -0,0 +1,197 @@ +# Copyright 2021 The QUARK Authors. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +from typing import Union + +import numpy as np + +from modules.applications.QML.transformations.Transformation import * +from modules.applications.QML.circuits.CircuitStandard import CircuitStandard +from modules.applications.QML.circuits.CircuitCardinality import CircuitCardinality + + +class MinMax(Transformation): + """ + In min-max normalization each data point is shifted + such that it lies between 0 and 1 + """ + + def __init__(self): + super().__init__("MinMax") + self.submodule_options = ["CircuitStandard", "CircuitCardinality"] + self.key_mapping = None + self.transform_config = None + self.max = None + self.min = None + + @staticmethod + def get_requirements() -> list[dict]: + """ + Returns requirements of this module + + :return: list of dict with requirements of this module + :rtype: list[dict] + """ + return [ + { + "name": "numpy", + "version": "1.23.5" + } + ] + + def get_default_submodule(self, circuit_option: str) -> Union[CircuitStandard, CircuitCardinality]: + + if circuit_option == "CircuitStandard": + return CircuitStandard() + elif circuit_option == "CircuitCardinality": + return CircuitCardinality() + else: + raise NotImplementedError(f"Circuit Option {circuit_option} not implemented") + + def get_parameter_options(self) -> dict: + """ + Returns empty dict as this transformation has no configurable settings + + :return: empty dict + :rtype: dict + """ + return { + + } + + def transform(self, application_config: dict, config: dict) -> (dict, float): + """ + Transforms the input dataset using MinMax transformation and computes histograms of the training dataset in the transformed space. + + :param application_config: A dictionary containing information about the dataset and application configuration. + :type application_config: dict + :param config: A dictionary with parameters specified in the Config class. + :type config: dict + :return: A tuple containing a dictionary with MinMax-transformed data. + :rtype: tuple(dict, float) + """ + self.dataset_name = application_config["dataset_name"] + self.dataset = application_config["dataset"] + self.n_qubits = application_config["n_qubits"] + self.grid_shape = int(2 ** (self.n_qubits // 2)) + n_registers = self.dataset.shape[-1] + + # Calculate ranges for the original dataset and the transformed dataset + ranges_original = np.column_stack((np.min(self.dataset, axis=0), np.max(self.dataset, axis=0))) + transformed_dataset = self.fit_transform(self.dataset) + ranges_transformed = np.column_stack((np.min(transformed_dataset, axis=0), np.max(transformed_dataset, axis=0))) + + # Compute histogram for the original dataset + learned_histogram = np.histogramdd(self.dataset, bins=self.grid_shape, range=ranges_original) + self.histogram_train_original = learned_histogram[0] / np.sum(learned_histogram[0]) + + # Compute histogram for the transformed dataset + learned_histogram = np.histogramdd(transformed_dataset, bins=self.grid_shape, range=ranges_transformed) + histogram_train = learned_histogram[0] / np.sum(learned_histogram[0]) + self.histogram_train = histogram_train.flatten() + + self.transform_config = { + "histogram_train": self.histogram_train, + "dataset_name": self.dataset_name, + "n_registers": n_registers, + "n_qubits": self.n_qubits, + "store_dir_iter": application_config["store_dir_iter"] + } + + return self.transform_config + + def reverse_transform(self, solution: dict) -> (any, float): + """ + Transforms the solution back to the representation needed for validation/evaluation. + + :param solution: dictionary containing the solution + :type solution: dict + :return: solution transformed accordingly, time it took to map it + :rtype: tuple(dict, float) + """ + best_results = solution["best_sample"] + depth = solution["depth"] + architecture_name = solution["architecture_name"] + n_qubits = solution["n_qubits"] + n_registers = self.transform_config["n_registers"] + KL_best_transformed = min(solution["KL"]) + + array_bins = Transformation.compute_discretization_efficient(n_qubits, n_registers) + transformed_samples = Transformation.generate_samples_efficient(best_results, array_bins, n_registers, + noisy=True) + + # Calculate ranges for the transformed samples + ranges_transformed = np.column_stack((np.min(transformed_samples, axis=0), np.max(transformed_samples, axis=0))) + + # Compute histogram for the transformed samples + learned_histogram = np.histogramdd(transformed_samples, bins=self.grid_shape, range=ranges_transformed) + histogram_generated_transformed = learned_histogram[0] / np.sum(learned_histogram[0]) + histogram_generated_transformed = histogram_generated_transformed.flatten() + + original_samples = self.inverse_transform(transformed_samples) + + # Calculate ranges for the original samples + ranges_original = np.column_stack((np.min(original_samples, axis=0), np.max(original_samples, axis=0))) + + # Compute histogram for the original samples + learned_histogram = np.histogramdd(original_samples, bins=self.grid_shape, range=ranges_original) + histogram_generated_original = learned_histogram[0] / np.sum(learned_histogram[0]) + histogram_generated_original = histogram_generated_original.flatten() + + best_parameter = solution["best_parameter"] + + reverse_config_trans = { + "generated_samples": best_results, + "transformed_samples": transformed_samples, + "depth": depth, + "architecture_name": architecture_name, + "dataset_name": self.dataset_name, + "n_qubits": n_qubits, + "best_parameter": best_parameter, + "histogram_train": self.histogram_train, + "histogram_train_original": self.histogram_train_original, + "histogram_generated_original": histogram_generated_original, + "histogram_generated": histogram_generated_transformed, + "KL_best_transformed": KL_best_transformed, + "store_dir_iter": solution["store_dir_iter"] + } + + return reverse_config_trans + + def fit_transform(self, data: np.ndarray) -> np.ndarray: + """ + Method that performs the min max normalization + + :param data: Data to be fitted + :type data: np.ndarray + :return: fitted data + :rtype: np.ndarray + """ + self.min = data.min() + self.max = data.max() - data.min() + data = (data - self.min) / self.max + return data + + def inverse_transform(self, data: np.ndarray) -> np.ndarray: + """ + Method that performs the inverse min max normalization + + :param data: Data to be fitted + :type data: np.ndarray + :return: data in original space + :rtype: np.ndarray + """ + self.min = data.min() + self.max = data.max() - data.min() + return data * self.max + self.min diff --git a/src/modules/applications/QML/transformations/PIT.py b/src/modules/applications/QML/transformations/PIT.py new file mode 100644 index 00000000..d1b50a7d --- /dev/null +++ b/src/modules/applications/QML/transformations/PIT.py @@ -0,0 +1,211 @@ +# Copyright 2021 The QUARK Authors. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +from typing import List + +import numpy as np +import pandas as pd + +from modules.applications.QML.transformations.Transformation import * +from modules.applications.QML.circuits.CircuitCopula import CircuitCopula + + +class PIT(Transformation): + """ + The transformation of the original probability distribution to + the distribution of its uniformly distributed cumulative marginals is known as the copula. + """ + + def __init__(self): + super().__init__("PIT") + self.submodule_options = ["CircuitCopula"] + self.reverse_epit_lookup = None + self.key_mapping = None + self.transform_config = None + + @staticmethod + def get_requirements() -> list[dict]: + """ + Returns requirements of this module + + :return: list of dict with requirements of this module + :rtype: list[dict] + """ + return [ + { + "name": "numpy", + "version": "1.23.5" + }, + { + "name": "pandas", + "version": "1.5.2" + } + ] + + def get_parameter_options(self) -> dict: + """ + Returns empty dict as this transformation has no configurable settings + + :return: empty dict + :rtype: dict + """ + return {} + + def get_default_submodule(self, circuit_option: str) -> CircuitCopula: + + if circuit_option == "CircuitCopula": + return CircuitCopula() + else: + raise NotImplementedError(f"Circuit Option {circuit_option} not implemented") + + def transform(self, application_config: dict, config: dict) -> (dict, float): + """ + Transforms the input dataset using PIT transformation and computes histograms of the training dataset in the transformed space. + + :param data_set: dataset + :type graph: npdarray + :param config: config with the parameters specified in Config class + :type config: Config + :return: dict with MinMax transformation, time it took to map it + :rtype: tuple(dict, float) + """ + self.dataset_name = application_config["dataset_name"] + self.dataset = application_config["dataset"] + self.n_qubits = application_config["n_qubits"] + self.grid_shape = int(2 ** (self.n_qubits // 2)) + n_registers = self.dataset.shape[-1] + + # Calculate ranges for the original dataset and the transformed dataset + ranges_original = np.column_stack((np.min(self.dataset, axis=0), np.max(self.dataset, axis=0))) + transformed_dataset = self.fit_transform(self.dataset) + ranges_transformed = np.column_stack((np.min(transformed_dataset, axis=0), np.max(transformed_dataset, axis=0))) + + # Compute histogram for the original dataset + learned_histogram = np.histogramdd(self.dataset, bins=self.grid_shape, range=ranges_original) + self.histogram_train_original = learned_histogram[0] / np.sum(learned_histogram[0]) + + # Compute histogram for the transformed dataset + train_histogram = np.histogramdd(transformed_dataset, bins=self.grid_shape, range=ranges_transformed) + histogram_train = train_histogram[0] / np.sum(train_histogram[0]) + self.histogram_train = histogram_train.flatten() + + self.transform_config = { + "histogram_train": self.histogram_train, + "dataset_name": self.dataset_name, + "n_registers": n_registers, + "n_qubits": self.n_qubits, + "store_dir_iter": application_config["store_dir_iter"], + "transformed_dataset": transformed_dataset + } + + return self.transform_config + + def reverse_transform(self, solution: dict) -> (any, float): + """ + Transforms the solution back to the representation needed for validation/evaluation. + + :param solution: dictionary containing the solution + :type solution: dict + :return: solution transformed accordingly, time it took to map it + :rtype: tuple(dict, float) + """ + depth = solution["depth"] + architecture_name = solution["architecture_name"] + n_qubits = solution["n_qubits"] + n_registers = self.transform_config["n_registers"] + KL_best_transformed = min(solution["KL"]) + best_results = solution["best_sample"] + + array_bins = self.compute_discretization_efficient(n_qubits, n_registers) + transformed_samples = self.generate_samples_efficient(best_results, array_bins, n_registers, noisy=True) + + # Calculate ranges for the transformed samples + ranges_transformed = np.column_stack((np.min(transformed_samples, axis=0), np.max(transformed_samples, axis=0))) + + # Compute histogram for the transformed samples + learned_histogram = np.histogramdd(transformed_samples, bins=self.grid_shape, range=ranges_transformed) + histogram_generated_transformed = learned_histogram[0] / np.sum(learned_histogram[0]) + histogram_generated_transformed = histogram_generated_transformed.flatten() + + original_samples = self.inverse_transform(transformed_samples) + + # Calculate ranges for the original samples + ranges_original = np.column_stack((np.min(original_samples, axis=0), np.max(original_samples, axis=0))) + + # Compute histogram for the original samples + learned_histogram = np.histogramdd(original_samples, bins=self.grid_shape, range=ranges_original) + histogram_generated_original = learned_histogram[0] / np.sum(learned_histogram[0]) + histogram_generated_original = histogram_generated_original.flatten() + + best_parameter = solution["best_parameter"] + + reverse_config_trans = { + "generated_samples": best_results, + "transformed_samples": transformed_samples, + "depth": depth, + "architecture_name": architecture_name, + "dataset_name": self.dataset_name, + "n_qubits": n_qubits, + "best_parameter": best_parameter, + "histogram_train_original": self.histogram_train_original, + "histogram_train": self.histogram_train, + "histogram_generated_original": histogram_generated_original, + "histogram_generated": histogram_generated_transformed, + "KL_best_transformed": KL_best_transformed, + "store_dir_iter": solution["store_dir_iter"] + } + + return reverse_config_trans + + def fit_transform(self, data: np.ndarray) -> np.ndarray: + df = pd.DataFrame(data) + epit = df.copy(deep=True).transpose() + self.reverse_epit_lookup = epit.copy(deep=True) + + epit.values[::] = [PIT.emp_integral_trans(row) for row in epit.values] + epit = epit.transpose() + self.reverse_epit_lookup.values[::] = [np.sort(row) for row in self.reverse_epit_lookup.values] + + df = epit.copy() + self.reverse_epit_lookup = self.reverse_epit_lookup.values + return df.values + + def _reverse_emp_integral_trans_single(self, values: np.ndarray) -> List[float]: + # assumes non ragged array + values = values * (np.shape(self.reverse_epit_lookup)[1] - 1) + rows = np.shape(self.reverse_epit_lookup)[0] + # if we are an integer do not use linear interpolation + valuesL = np.floor(values).astype(int) + valuesH = np.ceil(values).astype(int) + # if we are an integer then floor and ceiling are the same + isIntMask = 1 - (valuesH - valuesL) + rowIndexer = np.arange(rows) + resultL = self.reverse_epit_lookup[ + ([rowIndexer], [valuesL])] # doing 2d lookup as [[index1.row, index2.row],[index1.column, index2.column]] + resultH = self.reverse_epit_lookup[ + ([rowIndexer], [valuesH])] # where 2d index tuple would be (index1.row, index1.column) + # lookup int or do linear interpolation + return resultL * (isIntMask + values - valuesL) + resultH * (valuesH - values) + + def inverse_transform(self, data: np.ndarray) -> np.ndarray: + res = [self._reverse_emp_integral_trans_single(row) for row in data] + return np.array(res)[:, 0, :] + + def emp_integral_trans(data: np.ndarray): + # calling arggsort on the result of argsort creates a bijective mapping mask + rank = data.argsort().argsort() + len = data.size + ecdf = np.linspace(0, 1, len, dtype=np.float64) + ecdf_biject = ecdf[rank] + return ecdf_biject diff --git a/src/modules/applications/QML/transformations/Transformation.py b/src/modules/applications/QML/transformations/Transformation.py new file mode 100644 index 00000000..f15cffcc --- /dev/null +++ b/src/modules/applications/QML/transformations/Transformation.py @@ -0,0 +1,231 @@ +# Copyright 2021 The QUARK Authors. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +from itertools import product + +import numpy as np + +from modules.Core import * +from utils import start_time_measurement, end_time_measurement + + +class Transformation(Core, ABC): + """ + The task of the transformation module is to translate the application’s data and problem specification into + preprocessed format. + """ + + def __init__(self, name): + """ + Constructor method + """ + super().__init__() + self.transformation_name = name + + @staticmethod + def get_requirements() -> list[dict]: + """ + Returns requirements of this module + + :return: list of dict with requirements of this module + :rtype: list[dict] + """ + return [ + { + "name": "numpy", + "version": "1.23.5" + } + ] + + def preprocess(self, input_data: dict, config: dict, **kwargs): + """ + In this module, the preprocessing step is tansforming the data to the correct target format. + + :param input_data: Collected information of the benchmarking process + :type input_data: dict + :param config: Config specifying the parameters of the transormation + :type config: dict + :param kwargs: + :type kwargs: dict + :return: tuple with transformed problem and the time it took to map it + :rtype: (dict, float) + """ + + start = start_time_measurement() + output = self.transform(input_data, config) + + return output, end_time_measurement(start) + + def postprocess(self, input_data: dict, config: dict, **kwargs): + """ + Does the reverse transformation + + :param input_data: + :type input_data: dict + :param config: + :type config: dict + :param kwargs: + :type kwargs: dict + :return: + """ + start = start_time_measurement() + + output = self.reverse_transform(input_data) + output["Transformation"] = True + if "inference" in input_data: + output["inference"] = input_data["inference"] + return output, end_time_measurement(start) + + @abstractmethod + def transform(self, problem) -> (dict): + """ + Helps to ensure that the model can effectively learn the underlying + patterns and structure of the data, and produce high-quality outputs. + + + :param config: instance of class Config specifying the mapping settings + :param problem: problem instance which should be mapped to the target representation + :return: Must always return the mapped problem and the time it took to create the mapping + :rtype: dict + """ + pass + + def reverse_transform(self, solution) -> (any, float): + """ + Transforms the solution back to the original problem. This might not be necessary in all cases, so the default is + to return the original solution. This might be needed to convert the solution to a representation needed + for validation and evaluation. + + :param solution: + :type solution: any + :return: Mapped solution and the time it took to create it + :rtype: tuple(any, float) + + """ + return + + @staticmethod + def compute_discretization(n_qubits: int, n_registered: int) -> np.ndarray: + """ + Compute discretization for the grid. + + :param n_qubits: Total number of qubits. + :type n_qubits: int + :param n_registered: Number of qubits to be registered. + :type n_registered: int + :return: Discretization data. + :rtype: np.ndarray + """ + n = 2 ** (n_qubits // n_registered) + n_bins = n ** n_registered + bin_data = np.empty((n_bins, n_registered + 1), dtype=float) + + for k, coords in enumerate(product(range(n), repeat=n_registered)): + normalized_coords = np.array(coords) / n + 0.5 / n + bin_data[k] = np.concatenate(([k], normalized_coords)) + + return bin_data + + @staticmethod + def compute_discretization_efficient(n_qubits: int, n_registers: int) -> np.ndarray: + """ + Compute grid discretization. + + :param n_qubits: Total number of qubits. + :type n_qubits: int + :param n_registers: Number of qubits to be registered. + :type n_registers: int + :return: Discretization data. + :rtype: np.ndarray + """ + n = 2 ** (n_qubits // n_registers) + n_bins = n ** n_registers + + # Create an array of all possible coordinate combinations + coords = np.array(list(product(range(n), repeat=n_registers))) + + # Calculate normalized_coords for all combinations + normalized_coords = (coords.astype(float) + 0.5) / n + + # Create bin_data by concatenating normalized_coords with row indices + bin_data = np.hstack((np.arange(n_bins).reshape(-1, 1), normalized_coords)) + + return bin_data + + @staticmethod + def generate_samples(results: np.ndarray, bin_data: np.ndarray, n_registers: int, noisy: bool = True) -> np.ndarray: + """ + Generate samples based on measurement results and the grid bins. + + :param results: Results of measurements. + :type results: np.ndarray + :param bin_data: Binned data. + :type bin_data: np.ndarray + :param n_registers: Number of registers. + :type n_registers: int + :param noisy: Flag indicating whether to add noise. + :type noisy: bool, optional + :return: Generated samples. + :rtype: np.ndarray + """ + n_shots = np.sum(results) + width = 1 / len(bin_data) ** (1 / n_registers) + points = ( + 0.5 * width * np.random.uniform(low=-1, high=1, size=(n_shots, n_registers)) + if noisy + else np.zeros((n_shots, n_registers)) + ) + + position = 0 + for idx, value in enumerate(results): + bin_coords = bin_data[idx, 1:] + points[position: position + value, :] += np.tile(bin_coords, (value, 1)) + position += value + + return points.astype(np.float32) + + @staticmethod + def generate_samples_efficient(results, bin_data, n_registers, noisy=True): + """ + Generate samples efficiently using numpy arrays based on measurement results and the grid bins + + :param results: Results of measurements. + :type results: np.ndarray + :param bin_data: Binned data. + :type bin_data: np.ndarray + :param n_registers: Number of registers. + :type n_registers: int + :param noisy: Flag indicating whether to add noise. + :type noisy: bool, optional + :return: Generated samples. + :rtype: np.ndarray + """ + n_shots = np.sum(results) + width = 1 / len(bin_data) ** (1 / n_registers) + + # Generate random noise or zeros + noise = 0.5 * width * np.random.uniform(low=-1, high=1, size=(n_shots, n_registers)) if noisy else np.zeros( + (n_shots, n_registers)) + + # Create an array of bin_coords for each result, then stack them vertically + bin_coords = bin_data[:, 1:] + expanded_bin_coords = np.repeat(bin_coords, results, axis=0) + + # Reshape expanded_bin_coords to match the shape of noise + expanded_bin_coords = expanded_bin_coords.reshape(n_shots, n_registers) + + # Add noise to the expanded_bin_coords + points = expanded_bin_coords + noise + + return points.astype(np.float32) diff --git a/src/modules/applications/QML/transformations/__init__.py b/src/modules/applications/QML/transformations/__init__.py new file mode 100644 index 00000000..b12ba606 --- /dev/null +++ b/src/modules/applications/QML/transformations/__init__.py @@ -0,0 +1,15 @@ +# Copyright 2022 The QUARK Authors. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +""" Module containing all transformations""" diff --git a/src/modules/applications/optimization/PVC/mappings/ISING.py b/src/modules/applications/optimization/PVC/mappings/ISING.py index 9a2ccc7e..50ced28a 100644 --- a/src/modules/applications/optimization/PVC/mappings/ISING.py +++ b/src/modules/applications/optimization/PVC/mappings/ISING.py @@ -28,6 +28,7 @@ class Ising(Mapping): Ising formulation for the PVC """ + def __init__(self): """ Constructor method diff --git a/src/modules/applications/optimization/SAT/SAT.py b/src/modules/applications/optimization/SAT/SAT.py index f52c9192..5912f889 100644 --- a/src/modules/applications/optimization/SAT/SAT.py +++ b/src/modules/applications/optimization/SAT/SAT.py @@ -69,7 +69,8 @@ def get_solution_quality_unit(self) -> str: def get_default_submodule(self, option: str) -> Core: if option == "QubovertQUBO": - from modules.applications.optimization.SAT.mappings.QubovertQUBO import QubovertQUBO # pylint: disable=C0415 + from modules.applications.optimization.SAT.mappings.QubovertQUBO import \ + QubovertQUBO # pylint: disable=C0415 return QubovertQUBO() elif option == "Direct": from modules.applications.optimization.SAT.mappings.Direct import Direct # pylint: disable=C0415 @@ -84,7 +85,8 @@ def get_default_submodule(self, option: str) -> Core: from modules.applications.optimization.SAT.mappings.DinneenQUBO import DinneenQUBO # pylint: disable=C0415 return DinneenQUBO() elif option == "DinneenIsing": - from modules.applications.optimization.SAT.mappings.DinneenISING import DinneenIsing # pylint: disable=C0415 + from modules.applications.optimization.SAT.mappings.DinneenISING import \ + DinneenIsing # pylint: disable=C0415 return DinneenIsing() else: raise NotImplementedError(f"Mapping Option {option} not implemented") diff --git a/src/modules/applications/optimization/TSP/createReferenceGraph.py b/src/modules/applications/optimization/TSP/createReferenceGraph.py index 64a27cdd..4b8537ac 100644 --- a/src/modules/applications/optimization/TSP/createReferenceGraph.py +++ b/src/modules/applications/optimization/TSP/createReferenceGraph.py @@ -15,7 +15,6 @@ import networkx as nx import tsplib95 - # Source http://comopt.ifi.uni-heidelberg.de/software/TSPLIB95/tsp/ filename = "dsj1000.tsp" print(f"Loading {filename}") diff --git a/src/modules/devices/braket/Braket.py b/src/modules/devices/braket/Braket.py index 4ca5c418..c49ae08c 100644 --- a/src/modules/devices/braket/Braket.py +++ b/src/modules/devices/braket/Braket.py @@ -23,7 +23,6 @@ from botocore.exceptions import ProfileNotFound from braket.aws import AwsSession - from modules.devices.Device import Device diff --git a/src/utils_mpi.py b/src/utils_mpi.py new file mode 100644 index 00000000..7fd6c2a2 --- /dev/null +++ b/src/utils_mpi.py @@ -0,0 +1,89 @@ +# Copyright 2021 The QUARK Authors. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +import os +import logging + + +def is_running_mpiexec(): + # This is not 100% robust but should cover MPICH & Open MPI + for key in os.environ: + if key.startswith("PMI_") or key.startswith("OMPI_COMM_WORLD_"): + return True + return False + + +def is_running_mpi(): + if is_running_mpiexec(): + try: + from mpi4py import MPI # pylint: disable=C0415 + except ImportError as e: + raise RuntimeError( + 'it seems you are running mpiexec/mpirun but mpi4py cannot be ' + 'imported, maybe you forgot to install it?') from e + else: + MPI = None + return MPI + + +class MPIStreamHandler(logging.StreamHandler): + + def __init__(self, *args, **kwargs): + super().__init__(*args, **kwargs) + MPI = is_running_mpi() + if MPI: + self.rank = MPI.COMM_WORLD.Get_rank() + else: + self.rank = 0 + + def emit(self, record): + # don't log unless I am the root process + if self.rank == 0: + super().emit(record) + + +class MPIFileHandler(logging.FileHandler): + + def __init__(self, *args, **kwargs): + super().__init__(*args, **kwargs) + MPI = is_running_mpi() + if MPI: + self.rank = MPI.COMM_WORLD.Get_rank() + else: + self.rank = 0 + + def emit(self, record): + # don't log unless I am the root process + if self.rank == 0: + super().emit(record) + + +def get_comm(): + MPI = is_running_mpi() + if MPI: + comm = MPI.COMM_WORLD + else: + class comm(): + @staticmethod + def Get_rank(): + return 0 + + @staticmethod + def Bcast(loss, root): + pass + + @staticmethod + def Barrier(): + pass + return comm From 7b001a6e1d1a127d23c94cf912031f781132ae98 Mon Sep 17 00:00:00 2001 From: "Florian Kiwit (Q615005)" Date: Sun, 17 Sep 2023 22:51:02 -0700 Subject: [PATCH 2/5] Fix various problems with QML Co-authored-by: Florian Kiwit Co-authored-by: Maroua Marso --- .../QML/circuits/CircuitCardinality.py | 6 +- .../QML/circuits/CircuitCopula.py | 6 +- .../QML/circuits/CircuitStandard.py | 7 +- .../QML/data_handler/ContinuousData.py | 18 +++-- .../QML/data_handler/DataHandler.py | 6 +- .../QML/data_handler/DiscreteData.py | 55 ++++++++----- .../QML/data_handler/MetricsGeneralization.py | 2 +- .../generative_modeling/GenerativeModeling.py | 11 +-- .../applications/QML/libraries/Library.py | 20 ++++- .../QML/libraries/LibraryQiskit.py | 80 ++++++++++--------- .../applications/QML/training/Inference.py | 14 +++- src/modules/applications/QML/training/QCBM.py | 63 +++++++++++---- .../applications/QML/training/Training.py | 43 +++++----- .../QML/transformations/MinMax.py | 44 +++++----- .../applications/QML/transformations/PIT.py | 54 +++++++------ .../QML/transformations/Transformation.py | 30 +++---- 16 files changed, 264 insertions(+), 195 deletions(-) diff --git a/src/modules/applications/QML/circuits/CircuitCardinality.py b/src/modules/applications/QML/circuits/CircuitCardinality.py index de648edb..62911a6a 100644 --- a/src/modules/applications/QML/circuits/CircuitCardinality.py +++ b/src/modules/applications/QML/circuits/CircuitCardinality.py @@ -55,11 +55,11 @@ def get_parameter_options(self) -> dict: }, } - def get_default_submodule(self, library_option: str) -> LibraryQiskit: - if library_option == "LibraryQiskit": + def get_default_submodule(self, option: str) -> LibraryQiskit: + if option == "LibraryQiskit": return LibraryQiskit() else: - raise NotImplementedError(f"Library Option {library_option} not implemented") + raise NotImplementedError(f"Option {option} not implemented") class Config(TypedDict): """ diff --git a/src/modules/applications/QML/circuits/CircuitCopula.py b/src/modules/applications/QML/circuits/CircuitCopula.py index 45962fa9..9d4b35dd 100644 --- a/src/modules/applications/QML/circuits/CircuitCopula.py +++ b/src/modules/applications/QML/circuits/CircuitCopula.py @@ -73,11 +73,11 @@ def get_parameter_options(self) -> dict: }, } - def get_default_submodule(self, library_option: str) -> LibraryQiskit: - if library_option == "LibraryQiskit": + def get_default_submodule(self, option: str) -> LibraryQiskit: + if option == "LibraryQiskit": return LibraryQiskit() else: - raise NotImplementedError(f"Library Option {library_option} not implemented") + raise NotImplementedError(f"Option {option} not implemented") class Config(TypedDict): """ diff --git a/src/modules/applications/QML/circuits/CircuitStandard.py b/src/modules/applications/QML/circuits/CircuitStandard.py index 3db2680c..a823d956 100644 --- a/src/modules/applications/QML/circuits/CircuitStandard.py +++ b/src/modules/applications/QML/circuits/CircuitStandard.py @@ -69,11 +69,11 @@ def get_parameter_options(self) -> dict: } } - def get_default_submodule(self, library_option: str) -> LibraryQiskit: - if library_option == "LibraryQiskit": + def get_default_submodule(self, option: str) -> LibraryQiskit: + if option == "LibraryQiskit": return LibraryQiskit() else: - raise NotImplementedError(f"Library Option {library_option} not implemented") + raise NotImplementedError(f"Option {option} not implemented") class Config(TypedDict): """ @@ -100,7 +100,6 @@ def generate_gate_sequence(self, input_data: dict, config: Config) -> dict: n_registers = input_data["n_registers"] n_qubits = input_data["n_qubits"] depth = config["depth"] - n = n_qubits // n_registers gate_sequence = [] diff --git a/src/modules/applications/QML/data_handler/ContinuousData.py b/src/modules/applications/QML/data_handler/ContinuousData.py index 23a848ea..5b10162d 100644 --- a/src/modules/applications/QML/data_handler/ContinuousData.py +++ b/src/modules/applications/QML/data_handler/ContinuousData.py @@ -12,13 +12,13 @@ # See the License for the specific language governing permissions and # limitations under the License. -from utils import start_time_measurement, end_time_measurement from typing import TypedDict, Union +import logging import numpy as np - import pkg_resources -import logging + +from utils import start_time_measurement, end_time_measurement from modules.applications.QML.data_handler.DataHandler import * from modules.applications.QML.transformations.MinMax import MinMax @@ -43,6 +43,7 @@ def __init__(self): self.dataset = None self.n_registers = None self.gc = None + self.n_qubits = None @staticmethod def get_requirements() -> list[dict]: @@ -59,13 +60,13 @@ def get_requirements() -> list[dict]: } ] - def get_default_submodule(self, transform_option: str) -> Union[PIT, MinMax]: - if transform_option == "MinMax": + def get_default_submodule(self, option: str) -> Union[PIT, MinMax]: + if option == "MinMax": self.transformation = MinMax() - elif transform_option == "PIT": + elif option == "PIT": self.transformation = PIT() else: - raise NotImplementedError(f"Transformation Option {transform_option} not implemented") + raise NotImplementedError(f"Transformation Option {option} not implemented") return self.transformation def get_parameter_options(self) -> dict: @@ -133,7 +134,8 @@ def evaluate(self, solution: list, **kwargs) -> (float, float): """ Calculate KL in original space. - :param solution: A dictionary-like object containing the solution data, including histogram_generated_original and histogram_train_original. + :param solution: A dictionary-like object containing the solution data, + including histogram_generated_original and histogram_train_original. :type solution: list :return: KL for the generated samples and the time it took to calculate it. diff --git a/src/modules/applications/QML/data_handler/DataHandler.py b/src/modules/applications/QML/data_handler/DataHandler.py index 931c3e54..527e61d8 100644 --- a/src/modules/applications/QML/data_handler/DataHandler.py +++ b/src/modules/applications/QML/data_handler/DataHandler.py @@ -25,7 +25,8 @@ class DataHandler(Core, ABC): """ - The task of the DataHandler module is to translate the application’s data and problem specification into preproccesed format. + The task of the DataHandler module is to translate the application’s data + and problem specification into preproccesed format. """ def __init__(self, name): @@ -196,7 +197,8 @@ def evaluate(self, solution: any) -> (dict, float): @staticmethod def tb_to_pd(logdir: str, rep: str) -> None: """ - Converts TensorBoard event files in the specified log directory into a pandas DataFrame and saves it as a pickle file. + Converts TensorBoard event files in the specified log directory + into a pandas DataFrame and saves it as a pickle file. :param logdir: path to the log directory containing TensorBoard event files :type logdir: str diff --git a/src/modules/applications/QML/data_handler/DiscreteData.py b/src/modules/applications/QML/data_handler/DiscreteData.py index 0cc1135f..1dae2a92 100644 --- a/src/modules/applications/QML/data_handler/DiscreteData.py +++ b/src/modules/applications/QML/data_handler/DiscreteData.py @@ -26,15 +26,22 @@ class DiscreteData(DataHandler): """ - A data handler for discrete datasets with cardinality constraints. This class creates a dataset with a cardinality constraint and provides + A data handler for discrete datasets with cardinality constraints. + This class creates a dataset with a cardinality constraint and provides methods for generalisation metrics computing and evaluation. """ def __init__(self): super().__init__("") self.submodule_options = ["CircuitCardinality"] - self.dataset_name = None self.n_registers = None + self.n_qubits = None + self.train_size = None + self.histogram_train = None + self.histogram_solution = None + self.generalization_metrics = None + self.samples = None + @staticmethod def get_requirements() -> list[dict]: @@ -51,13 +58,13 @@ def get_requirements() -> list[dict]: } ] - def get_default_submodule(self, circuit_option: str) -> CircuitCardinality: + def get_default_submodule(self, option: str) -> CircuitCardinality: - if circuit_option == "CircuitCardinality": + if option == "CircuitCardinality": return CircuitCardinality() else: raise NotImplementedError( - f"Circuit Option {circuit_option} not implemented") + f"Circuit Option {option} not implemented") def get_parameter_options(self) -> dict: """ @@ -106,17 +113,17 @@ def data_load(self, gen_mod: dict, config: Config) -> dict: :return: Must always return the mapped problem and the time it took to create the mapping :rtype: tuple(any, float) """ - self.dataset_name = "Cardinality_Constraint" + dataset_name = "Cardinality_Constraint" self.n_qubits = gen_mod["n_qubits"] self.train_size = config["train_size"] - self.num_ones = self.n_qubits // 2 + num_ones = self.n_qubits // 2 # Generate all possible binary permutations of length n_qubits using NumPy arrays search_space = np.array(list(itertools.product([0, 1], repeat=self.n_qubits))) search_space = np.apply_along_axis(lambda x: ''.join(str(bit) for bit in x), 1, search_space) # Filter the binary permutations based on the cardinality constraint using np.char.count - cardinality_constraint = np.char.count(search_space, '1') == self.num_ones + cardinality_constraint = np.char.count(search_space, '1') == num_ones solution_set = search_space[cardinality_constraint] # Use np.random.choice to select the desired number of rows randomly @@ -126,23 +133,23 @@ def data_load(self, gen_mod: dict, config: Config) -> dict: # Create the histogram solution data self.histogram_solution = np.zeros(2 ** self.n_qubits) - self.solution_set = np.array([int(i, 2) for i in solution_set]) - self.histogram_solution[self.solution_set] = 1 / len(self.solution_set) + solution_set = np.array([int(i, 2) for i in solution_set]) + self.histogram_solution[solution_set] = 1 / len(solution_set) # Create the histogram training data self.histogram_train = np.zeros(2 ** self.n_qubits) - self.train_set = np.array([int(i, 2) for i in train_set]) - self.histogram_train[self.train_set] = 1 / len(self.train_set) + train_set = np.array([int(i, 2) for i in train_set]) + self.histogram_train[train_set] = 1 / len(train_set) self.generalization_metrics = MetricsGeneralization( - train_set=self.train_set, + train_set=train_set, train_size=self.train_size, - solution_set=self.solution_set, + solution_set=solution_set, n_qubits=self.n_qubits, ) application_config = { - "dataset_name": self.dataset_name, + "dataset_name": dataset_name, "n_qubits": self.n_qubits, "histogram_solution": self.histogram_solution, "histogram_train": self.histogram_train, @@ -157,7 +164,8 @@ def generalisation(self, solution: list) -> (dict, float): :param solution: A list representing the solution to be evaluated. :type solution: list - :return: A tuple containing a dictionary of generalization metrics and the execution time in seconds. + :return: A tuple containing a dictionary of generalization metrics + and the execution time in seconds. :rtype: tuple """ start = start_time_measurement() @@ -169,19 +177,22 @@ def generalisation(self, solution: list) -> (dict, float): def evaluate(self, solution: list) -> (dict, float): """ - Evaluates a given solution and calculates the histogram of generated samples and the minimum KL divergence value. + Evaluates a given solution and calculates the histogram of generated samples + and the minimum KL divergence value. - :param solution: A dictionary-like object containing the solution data, including generated samples and KL divergence values. + :param solution: A dictionary-like object containing the solution data, + including generated samples and KL divergence values. :type solution: list - :return: A tuple containing a dictionary with the histogram of generated samples and the minimum KL divergence value, - and the time it took to evaluate the solution in milliseconds. + :return: A tuple containing a dictionary with the histogram of generated samples + and the minimum KL divergence value, and the time it took to evaluate + the solution in milliseconds. :rtype: (dict, float) """ start = start_time_measurement() self.samples = solution["best_sample"] - self.n_shots = np.sum(self.samples) + n_shots = np.sum(self.samples) - histogram_generated = np.asarray(self.samples) / self.n_shots + histogram_generated = np.asarray(self.samples) / n_shots histogram_generated[histogram_generated == 0] = 1e-8 KL_list = solution["KL"] diff --git a/src/modules/applications/QML/data_handler/MetricsGeneralization.py b/src/modules/applications/QML/data_handler/MetricsGeneralization.py index 7890d1e5..004e7ca5 100644 --- a/src/modules/applications/QML/data_handler/MetricsGeneralization.py +++ b/src/modules/applications/QML/data_handler/MetricsGeneralization.py @@ -14,8 +14,8 @@ import math -import numpy as np from typing import Tuple, Dict +import numpy as np class MetricsGeneralization: diff --git a/src/modules/applications/QML/generative_modeling/GenerativeModeling.py b/src/modules/applications/QML/generative_modeling/GenerativeModeling.py index 97d97d73..ff5561d1 100644 --- a/src/modules/applications/QML/generative_modeling/GenerativeModeling.py +++ b/src/modules/applications/QML/generative_modeling/GenerativeModeling.py @@ -12,8 +12,8 @@ # See the License for the specific language governing permissions and # limitations under the License. -from utils import start_time_measurement, end_time_measurement from typing import Union +from utils import start_time_measurement, end_time_measurement from modules.applications.Application import * from modules.applications.QML.QML import QML @@ -36,15 +36,6 @@ def __init__(self): super().__init__("GenerativeModeling") self.submodule_options = ["Continuous Data", "Discrete Data"] self.data = None - self.dataset_name = None - self.n_registers = None - self.true_probability = None - self.cc = None - self.gc = None - self.bitstrings = None - self.bitstrings_train = None - self.constrained_bitstring = None - self.processed_solution = None @staticmethod def get_requirements() -> list[dict]: diff --git a/src/modules/applications/QML/libraries/Library.py b/src/modules/applications/QML/libraries/Library.py index 699d007d..da84a2b7 100644 --- a/src/modules/applications/QML/libraries/Library.py +++ b/src/modules/applications/QML/libraries/Library.py @@ -13,8 +13,11 @@ # limitations under the License. from abc import ABC, abstractmethod -from typing import TypedDict import logging +from typing import TypedDict +from qiskit import QuantumCircuit +from qiskit.providers import Backend + from utils import start_time_measurement, end_time_measurement from modules.Core import Core @@ -62,8 +65,11 @@ def preprocess(self, input_data: dict, config: Config, **kwargs): output = self.sequence_to_circuit(input_data) backend = self.select_backend(config["backend"]) - output["execute_circuit"] = self.get_execute_circuit(output["circuit"], backend, config["backend"], - config["n_shots"]) + output["execute_circuit"] = self.get_execute_circuit( + output["circuit"], + backend, + config["backend"], + config["n_shots"]) output["backend"] = config["backend"] output["n_shots"] = config["n_shots"] logging.info("Library created") @@ -92,6 +98,12 @@ def postprocess(self, input_data: dict, config: dict, **kwargs): def sequence_to_circuit(self, input_data): pass + @staticmethod + @abstractmethod + def get_execute_circuit(circuit: QuantumCircuit, backend: Backend, config: str, n_shots: int): + pass + + @staticmethod @abstractmethod - def get_execute_circuit(self): + def select_backend(config: str): pass diff --git a/src/modules/applications/QML/libraries/LibraryQiskit.py b/src/modules/applications/QML/libraries/LibraryQiskit.py index 7fd4f9d4..b4c7ce86 100644 --- a/src/modules/applications/QML/libraries/LibraryQiskit.py +++ b/src/modules/applications/QML/libraries/LibraryQiskit.py @@ -69,14 +69,18 @@ def get_parameter_options(self) -> dict: return { "backend": { "values": ["aer_statevector_simulator_gpu", "aer_statevector_simulator_cpu", - "cusvaer_simulator (only available in cuQuantum applicance)", "aer_simulator_gpu", + "cusvaer_simulator (only available in cuQuantum applicance)", + "aer_simulator_gpu", "aer_simulator_cpu", "ionQ_Harmony", "Amazon_SV1"], - "description": "Which backend do you want to use? (aer_statevector_simulator uses the measurement probability vector, the others are shot based)" + "description": "Which backend do you want to use? (aer_statevector_simulator + uses the measurement probability vector, the others are shot based)" }, "n_shots": { "values": [100, 1000, 10000, 1000000], - "description": "How many shots do you want use for estimating the PMF of the model? (If the aer_statevector_simulator selected, only relevant for studying generalization)" + "description": "How many shots do you want use for estimating the PMF of the model? + (If the aer_statevector_simulator selected, + only relevant for studying generalization)" } } @@ -86,23 +90,25 @@ def get_parameter_options(self) -> dict: "values": ["aer_statevector_simulator_gpu", "aer_statevector_simulator_cpu", "cusvaer_simulator (only available in cuQuantum applicance)", "aer_simulator_gpu", "aer_simulator_cpu", "ionQ_Harmony", "Amazon_SV1"], - "description": "Which backend do you want to use? (aer_statevector_simulator uses the measurement probability vector, the others are shot based)" + "description": "Which backend do you want to use? (aer_statevector_simulator\ + uses the measurement probability vector, the others are shot based)" }, "n_shots": { "values": [100, 1000, 10000, 1000000], - "description": "How many shots do you want use for estimating the PMF of the model? (If the aer_statevector_simulator selected, only relevant for studying generalization)" + "description": "How many shots do you want use for estimating the PMF of the model?\ + (If the aer_statevector_simulator selected, only relevant for studying generalization)" } } - def get_default_submodule(self, training_option: str) -> Union[QCBM, Inference]: + def get_default_submodule(self, option: str) -> Union[QCBM, Inference]: - if training_option == "QCBM": + if option == "QCBM": return QCBM() - elif training_option == "Inference": + elif option == "Inference": return Inference() else: - raise NotImplementedError(f"Training option {training_option} not implemented") + raise NotImplementedError(f"Option {option} not implemented") def sequence_to_circuit(self, input_data: dict) -> dict: """ @@ -169,18 +175,18 @@ def sequence_to_circuit(self, input_data: dict) -> dict: return input_data @staticmethod - def select_backend(backend_config: str) -> dict: + def select_backend(config: str) -> dict: """ This method configures the backend - :param backend_config: Name of a backend - :type backend_config: str + :param config: Name of a backend + :type config: str :return: Configured qiskit backend :rtype: qiskit.providers.Backend """ - if backend_config == "cusvaer_simulator (only available in cuQuantum applicance)": - import cusvaer - from qiskit.providers.aer import AerSimulator + if config == "cusvaer_simulator (only available in cuQuantum applicance)": + import cusvaer # pylint: disable=C0415 + from qiskit.providers.aer import AerSimulator # pylint: disable=C0415 backend = AerSimulator( method="statevector", device="GPU", @@ -191,29 +197,29 @@ def select_backend(backend_config: str) -> dict: cusvaer_comm_plugin_soname="libmpi.so" ) - elif backend_config == "aer_simulator_gpu": - from qiskit import Aer + elif config == "aer_simulator_gpu": + from qiskit import Aer # pylint: disable=C0415 backend = Aer.get_backend("aer_simulator") backend.set_options(device="GPU") - elif backend_config == "aer_simulator_cpu": - from qiskit import Aer + elif config == "aer_simulator_cpu": + from qiskit import Aer # pylint: disable=C0415 backend = Aer.get_backend("aer_simulator") backend.set_options(device="CPU") - elif backend_config == "aer_statevector_simulator_gpu": - from qiskit import Aer + elif config == "aer_statevector_simulator_gpu": + from qiskit import Aer # pylint: disable=C0415 backend = Aer.get_backend('statevector_simulator') backend.set_options(device="GPU") - elif backend_config == "aer_statevector_simulator_cpu": - from qiskit import Aer + elif config == "aer_statevector_simulator_cpu": + from qiskit import Aer # pylint: disable=C0415 backend = Aer.get_backend('statevector_simulator') backend.set_options(device="CPU") - elif backend_config == "ionQ_Harmony": - from modules.devices.braket.Ionq import Ionq - from qiskit_braket_provider import AWSBraketBackend, AWSBraketProvider + elif config == "ionQ_Harmony": + from modules.devices.braket.Ionq import Ionq # pylint: disable=C0415 + from qiskit_braket_provider import AWSBraketBackend, AWSBraketProvider # pylint: disable=C0415 device_wrapper = Ionq("ionQ", "arn:aws:braket:::device/qpu/ionq/ionQdevice") backend = AWSBraketBackend( device=device_wrapper.device, @@ -224,9 +230,9 @@ def select_backend(backend_config: str) -> dict: backend_version="2", ) - elif backend_config == "Amazon_SV1": - from modules.devices.braket.SV1 import SV1 - from qiskit_braket_provider import AWSBraketBackend, AWSBraketProvider + elif config == "Amazon_SV1": + from modules.devices.braket.SV1 import SV1 # pylint: disable=C0415 + from qiskit_braket_provider import AWSBraketBackend, AWSBraketProvider # pylint: disable=C0415 device_wrapper = SV1("SV1", "arn:aws:braket:::device/quantum-simulator/amazon/sv1") backend = AWSBraketBackend( device=device_wrapper.device, @@ -238,12 +244,12 @@ def select_backend(backend_config: str) -> dict: ) else: - raise NotImplementedError(f"Device Configuration {backend_config} not implemented") + raise NotImplementedError(f"Device Configuration {config} not implemented") return backend @staticmethod - def get_execute_circuit(circuit: QuantumCircuit, backend: Backend, backend_config: str, n_shots: int) -> callable: + def get_execute_circuit(circuit: QuantumCircuit, backend: Backend, config: str, n_shots: int) -> callable: """ This method combnines the qiskit circuit implemenation and the selected backend and returns a function, that will be called during training. @@ -252,8 +258,8 @@ def get_execute_circuit(circuit: QuantumCircuit, backend: Backend, backend_confi :type circuit: qiskit.circuit.QuantumCircuit :param backend: Configured qiskit backend :type backend: qiskit.providers.Backend - :param backend_config: Name of a backend - :type backend_config: str + :param config: Name of a backend + :type config: str :param n_shots: The number of times the circuit is run :type n_shots: int :return: Method that executes the quantum circuit for a given set of parameters @@ -262,7 +268,7 @@ def get_execute_circuit(circuit: QuantumCircuit, backend: Backend, backend_confi n_qubits = circuit.num_qubits circuit_transpiled = transpile(circuit, backend=backend) - if backend_config in ["aer_statevector_simulator_gpu", "aer_statevector_simulator_cpu"]: + if config in ["aer_statevector_simulator_gpu", "aer_statevector_simulator_cpu"]: circuit_transpiled.remove_final_measurements() def execute_circuit(solutions): @@ -272,8 +278,8 @@ def execute_circuit(solutions): pmfs = [jobs.result().get_statevector(circuit).probabilities() for circuit in all_circuits] return pmfs, None - elif backend_config in ["ionQ_Harmony", "Amazon_SV1"]: - import time as timetest + elif config in ["ionQ_Harmony", "Amazon_SV1"]: + import time as timetest # pylint: disable=C0415 def execute_circuit(solutions): all_circuits = [circuit_transpiled.bind_parameters(solution) for solution in solutions] jobs = backend.run(all_circuits, shots=n_shots) @@ -297,7 +303,7 @@ def execute_circuit(solutions): return pmfs, samples - elif backend_config in ["cusvaer_simulator (only available in cuQuantum applicance)", "aer_simulator_cpu", + elif config in ["cusvaer_simulator (only available in cuQuantum applicance)", "aer_simulator_cpu", "aer_simulator_gpu"]: def execute_circuit(solutions): all_circuits = [circuit_transpiled.bind_parameters(solution) for solution in solutions] diff --git a/src/modules/applications/QML/training/Inference.py b/src/modules/applications/QML/training/Inference.py index ea8548aa..5ed14e3c 100644 --- a/src/modules/applications/QML/training/Inference.py +++ b/src/modules/applications/QML/training/Inference.py @@ -27,6 +27,9 @@ def __init__(self): """ super().__init__("Inference") + self.target: np.array + self.n_states_range: list + @staticmethod def get_requirements() -> list[dict]: """ @@ -100,15 +103,18 @@ def start_training(self, input_data: dict, config: Config, **kwargs: dict) -> di parameters = np.load(config["pretrained"]) - pmfs, samples = execute_circuit([parameters.get() if gpu else parameters]) + pmfs, samples = execute_circuit([parameters.get() if GPU else parameters]) pmfs = np.asarray(pmfs) - samples = self.sample_from_pmf(pmf=pmfs[0], n_shots=input_data["n_shots"]) if samples is None else samples[0] + samples = self.sample_from_pmf( + n_states_range=self.n_states_range, + pmf=pmfs[0], + n_shots=input_data["n_shots"]) if samples is None else samples[0] - loss = self.kl_divergence(pmfs.reshape([-1, 1])) + loss = self.kl_divergence(pmfs.reshape([-1, 1]), self.target) input_data["best_parameter"] = parameters input_data["inference"] = True - input_data["KL"] = [loss.get() if gpu else loss] + input_data["KL"] = [loss.get() if GPU else loss] input_data["best_sample"] = samples.astype(int) return input_data diff --git a/src/modules/applications/QML/training/QCBM.py b/src/modules/applications/QML/training/QCBM.py index 3214fb90..a398f31d 100644 --- a/src/modules/applications/QML/training/QCBM.py +++ b/src/modules/applications/QML/training/QCBM.py @@ -37,6 +37,21 @@ def __init__(self): """ super().__init__("QCBM") + self.n_states_range: list + self.target: np.array + self.n_shots: int + self.execute_circuit: callable + self.timing: object + self.study_generalization: bool + self.generalization_metrics: dict + self.writer: SummaryWriter + self.image_epochs: list + self.tb_images: bool + self.loss_func: callable + self.n_params: int + self.x0: np.array + self.options: dict + @staticmethod def get_requirements() -> list[dict]: """ @@ -167,7 +182,8 @@ def setup_training(self, input_data, config) -> dict: input_data['MPI_size'] = size input_data["store_dir_iter"] += f"_{input_data['dataset_name']}_qubits{input_data['n_qubits']}" logging.info( - f"Running config: [backend={input_data['backend']}] [n_qubits={input_data['n_qubits']}] [n_shots={input_data['n_shots']}] [population_size={config['population_size']}]") + f"Running config: [backend={input_data['backend']}] [n_qubits={input_data['n_qubits']}] "\ + f"[n_shots={input_data['n_shots']}] [population_size={config['population_size']}]") if comm.Get_rank() == 0: self.target = np.asarray(input_data["histogram_train"]) @@ -175,7 +191,7 @@ def setup_training(self, input_data, config) -> dict: self.n_states_range = range(2 ** input_data['n_qubits']) self.n_shots = input_data["n_shots"] self.execute_circuit = input_data["execute_circuit"] - self.timing = self.Timing(gpu=gpu) + self.timing = self.Timing() self.study_generalization = "generalization_metrics" in list(input_data.keys()) if self.study_generalization: @@ -228,7 +244,7 @@ def start_training(self, input_data: dict, config: Config, **kwargs: dict) -> (d """ input_data = self.setup_training(input_data, config) - es = CMAEvolutionStrategy(self.x0.get() if gpu else self.x0, config['sigma'], self.options) + es = CMAEvolutionStrategy(self.x0.get() if GPU else self.x0, config['sigma'], self.options) for parameter in ["best_parameters", "time_circuit", "time_loss", "KL", "best_sample"]: input_data[parameter] = [] @@ -246,7 +262,7 @@ def start_training(self, input_data: dict, config: Config, **kwargs: dict) -> (d self.timing.start_recording() if comm.Get_rank() == 0: - loss_epoch = self.loss_func(pmfs_model.reshape([config['population_size'], -1])) + loss_epoch = self.loss_func(pmfs_model.reshape([config['population_size'], -1]), self.target) else: loss_epoch = np.empty(config["population_size"]) comm.Bcast(loss_epoch, root=0) @@ -254,24 +270,31 @@ def start_training(self, input_data: dict, config: Config, **kwargs: dict) -> (d time_loss = self.timing.stop_recording() - es.tell(solutions, loss_epoch.get() if gpu else loss_epoch) + es.tell(solutions, loss_epoch.get() if GPU else loss_epoch) if es.result[1] < best_loss: best_loss = es.result[1] index = loss_epoch.argmin() best_pmf = pmfs_model[index] / pmfs_model[index].sum() if self.study_generalization: - counts = self.sample_from_pmf(pmf=best_pmf.get() if gpu else best_pmf, - n_shots=self.generalization_metrics.n_shots) if samples is None else \ - samples[int(index)] - metrics = self.generalization_metrics.get_metrics(counts) + + if samples is None: + counts = self.sample_from_pmf( + n_states_range=self.n_states_range, + pmf=best_pmf.get() if GPU else best_pmf, + n_shots=self.generalization_metrics.n_shots) + else: + counts = samples[int(index)] + + metrics = self.generalization_metrics.get_metrics(counts.get() if GPU else counts) for (key, value) in metrics.items(): self.writer.add_scalar(f"metrics/{key}", value, epoch) - self.writer.add_scalar("metrics/NLL", self.nll(best_pmf.reshape([1, -1])).get() if gpu else self.nll( - best_pmf.reshape([1, -1])), epoch) - self.writer.add_scalar("metrics/KL", self.kl_divergence( - best_pmf.reshape([1, -1])).get() if gpu else self.kl_divergence(best_pmf.reshape([1, -1])), epoch) + nll = self.nll(best_pmf.reshape([1, -1]), self.target) + kl = self.kl_divergence(best_pmf.reshape([1, -1]), self.target) + # best_pmf_cpu = best_pmf.reshape([1, -1]) if GPU else best_pmf.reshape([1, -1]) + self.writer.add_scalar("metrics/NLL", nll.get() if GPU else nll, epoch) + self.writer.add_scalar("metrics/KL", kl.get() if GPU else kl, epoch) self.writer.add_scalar("time/circuit", time_circ, epoch) self.writer.add_scalar("time/loss", time_loss, epoch) input_data["best_parameters"].append(es.result[0]) @@ -281,7 +304,7 @@ def start_training(self, input_data: dict, config: Config, **kwargs: dict) -> (d if self.tb_images and epoch in self.image_epochs: ax.clear() ax.imshow( - best_pmf.reshape(int(np.sqrt(best_pmf.size)), int(np.sqrt(best_pmf.size))).get() if gpu + best_pmf.reshape(int(np.sqrt(best_pmf.size)), int(np.sqrt(best_pmf.size))).get() if GPU else best_pmf.reshape(int(np.sqrt(best_pmf.size)), int(np.sqrt(best_pmf.size))), cmap='binary', @@ -290,14 +313,20 @@ def start_training(self, input_data: dict, config: Config, **kwargs: dict) -> (d self.writer.add_figure('grid_figure', fig, global_step=epoch) logging.info( - f"[Iteration {es.result[4]}] [{config['loss']}: {es.result[1]:.5f}] [Circuit processing: {(time_circ):.3f} ms] [{config['loss']} processing: {(time_loss):.3f} ms] [sigma: {sigma:.5f}] ") + f"[Iteration {es.result[4]}] " + f"[{config['loss']}: {es.result[1]:.5f}] "\ + f"[Circuit processing: {(time_circ):.3f} ms] "\ + f"[{config['loss']} processing: {(time_loss):.3f} ms] "\ + f"[sigma: {sigma:.5f}]") plt.close() self.writer.flush() self.writer.close() input_data["best_parameter"] = es.result[0] - input_data["best_sample"] = self.sample_from_pmf(best_pmf.get() if gpu else best_pmf, - n_shots=input_data["n_shots"]) + best_sample = self.sample_from_pmf(self.n_states_range, + best_pmf.get() if GPU else best_pmf, + n_shots=input_data["n_shots"]) + input_data["best_sample"] = best_sample.get() if GPU else best_sample return input_data diff --git a/src/modules/applications/QML/training/Training.py b/src/modules/applications/QML/training/Training.py index 964dc049..fbe61a96 100644 --- a/src/modules/applications/QML/training/Training.py +++ b/src/modules/applications/QML/training/Training.py @@ -14,24 +14,20 @@ import logging from abc import ABC, abstractmethod - -import numpy as np_cpu +import time try: import cupy as np - - gpu = True + GPU = True logging.info("Using CuPy, dataprocessing on GPU") except ModuleNotFoundError: import numpy as np - - gpu = False + GPU = False logging.info("CuPy not available, using vanilla numpy, dataprocessing on CPU") from modules.Core import Core from utils import start_time_measurement, end_time_measurement - class Training(Core, ABC): """ The Training module is the base class fot both finding (QCBM) and excuting trained models (Inference) @@ -101,35 +97,38 @@ def start_training(self, input_data, config, **kwargs) -> dict: """ pass - def sample_from_pmf(self, pmf, n_shots): - samples = np_cpu.random.choice(self.n_states_range, size=n_shots, p=pmf) - counts = np_cpu.bincount(samples, minlength=len(self.n_states_range)) + @staticmethod + def sample_from_pmf(n_states_range, pmf, n_shots): + samples = np.random.choice(n_states_range, size=n_shots, p=pmf) + counts = np.bincount(samples, minlength=len(n_states_range)) return counts - def kl_divergence(self, pmf_model): + def kl_divergence(self, pmf_model, pmf_target): pmf_model[pmf_model == 0] = 1e-8 - return np.sum(self.target * np.log(self.target / pmf_model), axis=1) + return np.sum(pmf_target * np.log(pmf_target / pmf_model), axis=1) - def nll(self, pmf_model): + def nll(self, pmf_model, pmf_target): pmf_model[pmf_model == 0] = 1e-8 - return -np.sum(self.target * np.log(pmf_model), axis=1) + return -np.sum(pmf_target * np.log(pmf_model), axis=1) class Timing: """ - This module is an abstraction of time measurement for for both CPU and GPU precesses + This module is an abstraction of time measurement for for both CPU and GPU processes """ - def __init__(self, gpu: bool): + def __init__(self): """ Constructor method """ - self.gpu = gpu - if gpu: - self.start_recording = self.start_recording_gpu - self.stop_recording = self.stop_recording_gpu + + if GPU: + self.start_cpu: time.perf_counter else: - self.start_recording = self.start_recording_cpu - self.stop_recording = self.stop_recording_cpu + self.start_gpu: np.cuda.Event + self.end_gpu: self.start_cpu + + self.start_recording = self.start_recording_gpu if GPU else self.start_recording_cpu + self.stop_recording = self.stop_recording_gpu if GPU else self.stop_recording_cpu def start_recording_cpu(self): self.start_cpu = start_time_measurement() diff --git a/src/modules/applications/QML/transformations/MinMax.py b/src/modules/applications/QML/transformations/MinMax.py index f67329a8..1d58aa73 100644 --- a/src/modules/applications/QML/transformations/MinMax.py +++ b/src/modules/applications/QML/transformations/MinMax.py @@ -30,10 +30,15 @@ class MinMax(Transformation): def __init__(self): super().__init__("MinMax") self.submodule_options = ["CircuitStandard", "CircuitCardinality"] - self.key_mapping = None self.transform_config = None self.max = None self.min = None + self.n_qubits = None + self.dataset = None + self.dataset_name = None + self.grid_shape = None + self.histogram_train = None + self.histogram_train_original = None @staticmethod def get_requirements() -> list[dict]: @@ -50,14 +55,14 @@ def get_requirements() -> list[dict]: } ] - def get_default_submodule(self, circuit_option: str) -> Union[CircuitStandard, CircuitCardinality]: + def get_default_submodule(self, option: str) -> Union[CircuitStandard, CircuitCardinality]: - if circuit_option == "CircuitStandard": + if option == "CircuitStandard": return CircuitStandard() - elif circuit_option == "CircuitCardinality": + elif option == "CircuitCardinality": return CircuitCardinality() else: - raise NotImplementedError(f"Circuit Option {circuit_option} not implemented") + raise NotImplementedError(f"Circuit Option {option} not implemented") def get_parameter_options(self) -> dict: """ @@ -70,9 +75,10 @@ def get_parameter_options(self) -> dict: } - def transform(self, application_config: dict, config: dict) -> (dict, float): + def transform(self, input_data: dict, config: dict) -> (dict, float): """ - Transforms the input dataset using MinMax transformation and computes histograms of the training dataset in the transformed space. + Transforms the input dataset using MinMax transformation and computes histograms + of the training dataset in the transformed space. :param application_config: A dictionary containing information about the dataset and application configuration. :type application_config: dict @@ -81,9 +87,9 @@ def transform(self, application_config: dict, config: dict) -> (dict, float): :return: A tuple containing a dictionary with MinMax-transformed data. :rtype: tuple(dict, float) """ - self.dataset_name = application_config["dataset_name"] - self.dataset = application_config["dataset"] - self.n_qubits = application_config["n_qubits"] + self.dataset_name = input_data["dataset_name"] + self.dataset = input_data["dataset"] + self.n_qubits = input_data["n_qubits"] self.grid_shape = int(2 ** (self.n_qubits // 2)) n_registers = self.dataset.shape[-1] @@ -106,12 +112,12 @@ def transform(self, application_config: dict, config: dict) -> (dict, float): "dataset_name": self.dataset_name, "n_registers": n_registers, "n_qubits": self.n_qubits, - "store_dir_iter": application_config["store_dir_iter"] + "store_dir_iter": input_data["store_dir_iter"] } return self.transform_config - def reverse_transform(self, solution: dict) -> (any, float): + def reverse_transform(self, input_data: dict) -> (any, float): """ Transforms the solution back to the representation needed for validation/evaluation. @@ -120,12 +126,12 @@ def reverse_transform(self, solution: dict) -> (any, float): :return: solution transformed accordingly, time it took to map it :rtype: tuple(dict, float) """ - best_results = solution["best_sample"] - depth = solution["depth"] - architecture_name = solution["architecture_name"] - n_qubits = solution["n_qubits"] + best_results = input_data["best_sample"] + depth = input_data["depth"] + architecture_name = input_data["architecture_name"] + n_qubits = input_data["n_qubits"] n_registers = self.transform_config["n_registers"] - KL_best_transformed = min(solution["KL"]) + KL_best_transformed = min(input_data["KL"]) array_bins = Transformation.compute_discretization_efficient(n_qubits, n_registers) transformed_samples = Transformation.generate_samples_efficient(best_results, array_bins, n_registers, @@ -149,7 +155,7 @@ def reverse_transform(self, solution: dict) -> (any, float): histogram_generated_original = learned_histogram[0] / np.sum(learned_histogram[0]) histogram_generated_original = histogram_generated_original.flatten() - best_parameter = solution["best_parameter"] + best_parameter = input_data["best_parameter"] reverse_config_trans = { "generated_samples": best_results, @@ -164,7 +170,7 @@ def reverse_transform(self, solution: dict) -> (any, float): "histogram_generated_original": histogram_generated_original, "histogram_generated": histogram_generated_transformed, "KL_best_transformed": KL_best_transformed, - "store_dir_iter": solution["store_dir_iter"] + "store_dir_iter": input_data["store_dir_iter"] } return reverse_config_trans diff --git a/src/modules/applications/QML/transformations/PIT.py b/src/modules/applications/QML/transformations/PIT.py index d1b50a7d..e3d0da6a 100644 --- a/src/modules/applications/QML/transformations/PIT.py +++ b/src/modules/applications/QML/transformations/PIT.py @@ -31,8 +31,13 @@ def __init__(self): super().__init__("PIT") self.submodule_options = ["CircuitCopula"] self.reverse_epit_lookup = None - self.key_mapping = None self.transform_config = None + self.n_qubits = None + self.dataset = None + self.dataset_name = None + self.grid_shape = None + self.histogram_train = None + self.histogram_train_original = None @staticmethod def get_requirements() -> list[dict]: @@ -62,16 +67,17 @@ def get_parameter_options(self) -> dict: """ return {} - def get_default_submodule(self, circuit_option: str) -> CircuitCopula: + def get_default_submodule(self, option: str) -> CircuitCopula: - if circuit_option == "CircuitCopula": + if option == "CircuitCopula": return CircuitCopula() else: - raise NotImplementedError(f"Circuit Option {circuit_option} not implemented") + raise NotImplementedError(f"Circuit Option {option} not implemented") - def transform(self, application_config: dict, config: dict) -> (dict, float): + def transform(self, input_data: dict, config: dict) -> (dict, float): """ - Transforms the input dataset using PIT transformation and computes histograms of the training dataset in the transformed space. + Transforms the input dataset using PIT transformation and computes histograms + of the training dataset in the transformed space. :param data_set: dataset :type graph: npdarray @@ -80,9 +86,9 @@ def transform(self, application_config: dict, config: dict) -> (dict, float): :return: dict with MinMax transformation, time it took to map it :rtype: tuple(dict, float) """ - self.dataset_name = application_config["dataset_name"] - self.dataset = application_config["dataset"] - self.n_qubits = application_config["n_qubits"] + self.dataset_name = input_data["dataset_name"] + self.dataset = input_data["dataset"] + self.n_qubits = input_data["n_qubits"] self.grid_shape = int(2 ** (self.n_qubits // 2)) n_registers = self.dataset.shape[-1] @@ -105,13 +111,13 @@ def transform(self, application_config: dict, config: dict) -> (dict, float): "dataset_name": self.dataset_name, "n_registers": n_registers, "n_qubits": self.n_qubits, - "store_dir_iter": application_config["store_dir_iter"], + "store_dir_iter": input_data["store_dir_iter"], "transformed_dataset": transformed_dataset } return self.transform_config - def reverse_transform(self, solution: dict) -> (any, float): + def reverse_transform(self, input_data: dict) -> (any, float): """ Transforms the solution back to the representation needed for validation/evaluation. @@ -120,12 +126,12 @@ def reverse_transform(self, solution: dict) -> (any, float): :return: solution transformed accordingly, time it took to map it :rtype: tuple(dict, float) """ - depth = solution["depth"] - architecture_name = solution["architecture_name"] - n_qubits = solution["n_qubits"] + depth = input_data["depth"] + architecture_name = input_data["architecture_name"] + n_qubits = input_data["n_qubits"] n_registers = self.transform_config["n_registers"] - KL_best_transformed = min(solution["KL"]) - best_results = solution["best_sample"] + KL_best_transformed = min(input_data["KL"]) + best_results = input_data["best_sample"] array_bins = self.compute_discretization_efficient(n_qubits, n_registers) transformed_samples = self.generate_samples_efficient(best_results, array_bins, n_registers, noisy=True) @@ -148,7 +154,7 @@ def reverse_transform(self, solution: dict) -> (any, float): histogram_generated_original = learned_histogram[0] / np.sum(learned_histogram[0]) histogram_generated_original = histogram_generated_original.flatten() - best_parameter = solution["best_parameter"] + best_parameter = input_data["best_parameter"] reverse_config_trans = { "generated_samples": best_results, @@ -163,7 +169,7 @@ def reverse_transform(self, solution: dict) -> (any, float): "histogram_generated_original": histogram_generated_original, "histogram_generated": histogram_generated_transformed, "KL_best_transformed": KL_best_transformed, - "store_dir_iter": solution["store_dir_iter"] + "store_dir_iter": input_data["store_dir_iter"] } return reverse_config_trans @@ -173,7 +179,7 @@ def fit_transform(self, data: np.ndarray) -> np.ndarray: epit = df.copy(deep=True).transpose() self.reverse_epit_lookup = epit.copy(deep=True) - epit.values[::] = [PIT.emp_integral_trans(row) for row in epit.values] + epit.values[::] = [self.emp_integral_trans(row) for row in epit.values] epit = epit.transpose() self.reverse_epit_lookup.values[::] = [np.sort(row) for row in self.reverse_epit_lookup.values] @@ -202,10 +208,10 @@ def inverse_transform(self, data: np.ndarray) -> np.ndarray: res = [self._reverse_emp_integral_trans_single(row) for row in data] return np.array(res)[:, 0, :] - def emp_integral_trans(data: np.ndarray): - # calling arggsort on the result of argsort creates a bijective mapping mask - rank = data.argsort().argsort() - len = data.size - ecdf = np.linspace(0, 1, len, dtype=np.float64) + def emp_integral_trans(self, data: np.ndarray): + # calling argsort on the result of argsort creates a bijective mapping mask + rank = np.argsort(data).argsort() # Use np.argsort here + length = data.size # Rename 'len' to 'length' to avoid conflict with built-in len() + ecdf = np.linspace(0, 1, length, dtype=np.float64) ecdf_biject = ecdf[rank] return ecdf_biject diff --git a/src/modules/applications/QML/transformations/Transformation.py b/src/modules/applications/QML/transformations/Transformation.py index f15cffcc..85124ec3 100644 --- a/src/modules/applications/QML/transformations/Transformation.py +++ b/src/modules/applications/QML/transformations/Transformation.py @@ -88,32 +88,32 @@ def postprocess(self, input_data: dict, config: dict, **kwargs): return output, end_time_measurement(start) @abstractmethod - def transform(self, problem) -> (dict): + def transform(self, input_data: dict, config: dict) -> dict: """ Helps to ensure that the model can effectively learn the underlying patterns and structure of the data, and produce high-quality outputs. - - :param config: instance of class Config specifying the mapping settings - :param problem: problem instance which should be mapped to the target representation - :return: Must always return the mapped problem and the time it took to create the mapping + :param input_data: Input data for transformation. + :type input_data: dict + :param config: Configuration parameters for the transformation. + :type config: dict + :return: Transformed data. :rtype: dict """ pass - def reverse_transform(self, solution) -> (any, float): + def reverse_transform(self, input_data: dict) -> dict: """ - Transforms the solution back to the original problem. This might not be necessary in all cases, so the default is - to return the original solution. This might be needed to convert the solution to a representation needed - for validation and evaluation. - - :param solution: - :type solution: any - :return: Mapped solution and the time it took to create it - :rtype: tuple(any, float) + Transforms the solution back to the original problem. + This might not be necessary in all cases, so the default is to return the original solution. + This might be needed to convert the solution to a representation needed for validation and evaluation. + :param input_data: The input data to be transformed. + :type input_data: dict + :return: Transformed data. + :rtype: dict """ - return + return input_data @staticmethod def compute_discretization(n_qubits: int, n_registered: int) -> np.ndarray: From ef04a70a6ef4356256fd3d57a25db00668d58c01 Mon Sep 17 00:00:00 2001 From: "Florian Kiwit (Q615005)" Date: Thu, 21 Sep 2023 22:41:52 -0700 Subject: [PATCH 3/5] Fix minor problems with QML Co-authored-by: Florian Kiwit Co-authored-by: Maroua Marso --- .../QML/data_handler/DataHandler.py | 9 +- .../QML/data_handler/DiscreteData.py | 2 +- .../generative_modeling/GenerativeModeling.py | 8 +- .../applications/QML/libraries/Library.py | 3 +- .../QML/libraries/LibraryQiskit.py | 2 +- .../applications/QML/training/Inference.py | 4 +- src/modules/applications/QML/training/QCBM.py | 144 +++++++++--------- 7 files changed, 85 insertions(+), 87 deletions(-) diff --git a/src/modules/applications/QML/data_handler/DataHandler.py b/src/modules/applications/QML/data_handler/DataHandler.py index 527e61d8..0089bcf7 100644 --- a/src/modules/applications/QML/data_handler/DataHandler.py +++ b/src/modules/applications/QML/data_handler/DataHandler.py @@ -106,7 +106,7 @@ def postprocess(self, input_data: dict, config: dict, **kwargs): if self.generalization_mark is not None: self.metrics.add_metric_batch({"KL_best": evaluation["KL_best"]}) - metrics, _ = self.generalisation(input_data) + metrics, _ = self.generalisation() # Save generalisation metrics with open(f"{store_dir_iter}/record_gen_metrics_{kwargs['rep_count']}.pkl", 'wb') as f: @@ -169,7 +169,7 @@ def data_load(self, gen_mod: dict, config: dict) -> dict: """ pass - def generalisation(self, solution: list) -> (dict, float): + def generalisation(self) -> (dict, float): """ Compute generalisation metrics @@ -179,7 +179,10 @@ def generalisation(self, solution: list) -> (dict, float): :rtype: tuple(any, float) """ - pass + # Compute your metrics here + metrics = {} # Replace with actual metric calculations + time_taken = 0.0 # Replace with actual time calculation + return metrics, time_taken @abstractmethod def evaluate(self, solution: any) -> (dict, float): diff --git a/src/modules/applications/QML/data_handler/DiscreteData.py b/src/modules/applications/QML/data_handler/DiscreteData.py index 1dae2a92..4c8dc18a 100644 --- a/src/modules/applications/QML/data_handler/DiscreteData.py +++ b/src/modules/applications/QML/data_handler/DiscreteData.py @@ -158,7 +158,7 @@ def data_load(self, gen_mod: dict, config: Config) -> dict: return application_config - def generalisation(self, solution: list) -> (dict, float): + def generalisation(self) -> (dict, float): """ Calculate generalization metrics for the generated. diff --git a/src/modules/applications/QML/generative_modeling/GenerativeModeling.py b/src/modules/applications/QML/generative_modeling/GenerativeModeling.py index ff5561d1..2624ec03 100644 --- a/src/modules/applications/QML/generative_modeling/GenerativeModeling.py +++ b/src/modules/applications/QML/generative_modeling/GenerativeModeling.py @@ -50,13 +50,13 @@ def get_requirements() -> list[dict]: def get_solution_quality_unit(self) -> str: return "minimum KL" - def get_default_submodule(self, data_option: str) -> Union[ContinuousData, DiscreteData]: - if data_option == "Continuous Data": + def get_default_submodule(self, option: str) -> Union[ContinuousData, DiscreteData]: + if option == "Continuous Data": self.data = ContinuousData() - elif data_option == "Discrete Data": + elif option == "Discrete Data": self.data = DiscreteData() else: - raise NotImplementedError(f"Transformation Option {data_option} not implemented") + raise NotImplementedError(f"Transformation Option {option} not implemented") return self.data def get_parameter_options(self) -> dict: diff --git a/src/modules/applications/QML/libraries/Library.py b/src/modules/applications/QML/libraries/Library.py index da84a2b7..35b23e9a 100644 --- a/src/modules/applications/QML/libraries/Library.py +++ b/src/modules/applications/QML/libraries/Library.py @@ -28,10 +28,11 @@ class Library(Core, ABC): This class is an abstract base class for mapping a library-agnostic gate sequence to a library such as Qiskit """ - def __init__(self): + def __init__(self, name): """ Constructor method """ + self.name = name super().__init__() class Config(TypedDict): diff --git a/src/modules/applications/QML/libraries/LibraryQiskit.py b/src/modules/applications/QML/libraries/LibraryQiskit.py index b4c7ce86..0224db6e 100644 --- a/src/modules/applications/QML/libraries/LibraryQiskit.py +++ b/src/modules/applications/QML/libraries/LibraryQiskit.py @@ -37,7 +37,7 @@ def __init__(self): """ Constructor method """ - super().__init__() + super().__init__("LibraryQiskit") self.submodule_options = ["QCBM", "Inference"] @staticmethod diff --git a/src/modules/applications/QML/training/Inference.py b/src/modules/applications/QML/training/Inference.py index 5ed14e3c..d9fc2a08 100644 --- a/src/modules/applications/QML/training/Inference.py +++ b/src/modules/applications/QML/training/Inference.py @@ -112,9 +112,9 @@ def start_training(self, input_data: dict, config: Config, **kwargs: dict) -> di loss = self.kl_divergence(pmfs.reshape([-1, 1]), self.target) - input_data["best_parameter"] = parameters + input_data["best_parameter"] = parameters.get() if GPU else parameters input_data["inference"] = True input_data["KL"] = [loss.get() if GPU else loss] - input_data["best_sample"] = samples.astype(int) + input_data["best_sample"] = samples.astype(int).get() if GPU else samples.astype(int) return input_data diff --git a/src/modules/applications/QML/training/QCBM.py b/src/modules/applications/QML/training/QCBM.py index a398f31d..d8c9aab7 100644 --- a/src/modules/applications/QML/training/QCBM.py +++ b/src/modules/applications/QML/training/QCBM.py @@ -16,6 +16,7 @@ import logging from cma import CMAEvolutionStrategy from tensorboardX import SummaryWriter +from matplotlib import figure, axes import matplotlib.pyplot as plt from modules.applications.QML.training.Training import * @@ -39,18 +40,12 @@ def __init__(self): self.n_states_range: list self.target: np.array - self.n_shots: int - self.execute_circuit: callable - self.timing: object self.study_generalization: bool self.generalization_metrics: dict self.writer: SummaryWriter - self.image_epochs: list - self.tb_images: bool self.loss_func: callable - self.n_params: int - self.x0: np.array - self.options: dict + self.fig: figure + self.ax: axes.Axes @staticmethod def get_requirements() -> list[dict]: @@ -167,7 +162,7 @@ class Config(TypedDict): def get_default_submodule(self, option: str) -> Core: raise ValueError("This module has no submodules.") - def setup_training(self, input_data, config) -> dict: + def setup_training(self, input_data, config) -> tuple: """ Method to configure the training setup including CMA-ES and tensorboard. @@ -178,20 +173,10 @@ def setup_training(self, input_data, config) -> dict: :return: Updated input_data :rtype: dict """ - size = None - input_data['MPI_size'] = size - input_data["store_dir_iter"] += f"_{input_data['dataset_name']}_qubits{input_data['n_qubits']}" + logging.info( f"Running config: [backend={input_data['backend']}] [n_qubits={input_data['n_qubits']}] "\ - f"[n_shots={input_data['n_shots']}] [population_size={config['population_size']}]") - - if comm.Get_rank() == 0: - self.target = np.asarray(input_data["histogram_train"]) - self.target[self.target == 0] = 1e-8 - self.n_states_range = range(2 ** input_data['n_qubits']) - self.n_shots = input_data["n_shots"] - self.execute_circuit = input_data["execute_circuit"] - self.timing = self.Timing() + f"[population_size={config['population_size']}]") self.study_generalization = "generalization_metrics" in list(input_data.keys()) if self.study_generalization: @@ -200,9 +185,6 @@ def setup_training(self, input_data, config) -> dict: input_data["store_dir_iter"] += f"_alpha{self.generalization_metrics.train_size}_depth{input_data['depth']}" self.writer = SummaryWriter(input_data["store_dir_iter"]) - epochs = int(config['max_evaluations'] / config['population_size']) - self.image_epochs = range(0, epochs, 1) if int(epochs / 100) < 1 else range(0, epochs, int(epochs / 100)) - self.tb_images = "2D" in input_data["dataset_name"] if config['loss'] == "KL": self.loss_func = self.kl_divergence @@ -211,23 +193,22 @@ def setup_training(self, input_data, config) -> dict: else: raise NotImplementedError("Loss function not implemented") - self.n_params = len(input_data["circuit"].parameters) - self.x0 = (np.random.rand(self.n_params) - 0.5) * np.pi - + n_params = len(input_data["circuit"].parameters) + x0 = (np.random.rand(n_params) - 0.5) * np.pi if config["pretrained"] != "False": parameters = np.load(config["pretrained"]) - self.x0[:len(parameters)] = parameters + x0[:len(parameters)] = parameters logging.info(f'Training starting from parameters in path {config["pretrained"]}') - self.options = { - 'bounds': [self.n_params * [-np.pi], self.n_params * [np.pi]], + options = { + 'bounds': [n_params * [-np.pi], n_params * [np.pi]], 'maxfevals': config['max_evaluations'], 'popsize': config['population_size'], 'verbose': -3, 'tolfun': 1e-12 } - return input_data + return x0, options def start_training(self, input_data: dict, config: Config, **kwargs: dict) -> (dict, float): """ @@ -242,25 +223,36 @@ def start_training(self, input_data: dict, config: Config, **kwargs: dict) -> (d :return: Dictionary including the information of previous modules as well as of the training :rtype: dict """ - input_data = self.setup_training(input_data, config) - es = CMAEvolutionStrategy(self.x0.get() if GPU else self.x0, config['sigma'], self.options) + size = None # TODO: define correct mpi size + input_data['MPI_size'] = size + input_data["store_dir_iter"] += f"_{input_data['dataset_name']}_qubits{input_data['n_qubits']}" + x0, options = self.setup_training(input_data, config) + + if comm.Get_rank() == 0: + self.target = np.asarray(input_data["histogram_train"]) + self.target[self.target == 0] = 1e-8 + self.n_states_range = range(2 ** input_data['n_qubits']) + execute_circuit = input_data["execute_circuit"] + timing = self.Timing() + + es = CMAEvolutionStrategy(x0.get() if GPU else x0, config['sigma'], options) for parameter in ["best_parameters", "time_circuit", "time_loss", "KL", "best_sample"]: input_data[parameter] = [] best_loss = float("inf") - fig, ax = plt.subplots() + self.fig, self.ax = plt.subplots() while not es.stop(): solutions = es.ask() epoch = es.result[4] sigma = es.sigma - self.timing.start_recording() - pmfs_model, samples = self.execute_circuit(solutions) + timing.start_recording() + pmfs_model, samples = execute_circuit(solutions) pmfs_model = np.asarray(pmfs_model) - time_circ = self.timing.stop_recording() + time_circ = timing.stop_recording() - self.timing.start_recording() + timing.start_recording() if comm.Get_rank() == 0: loss_epoch = self.loss_func(pmfs_model.reshape([config['population_size'], -1]), self.target) else: @@ -268,50 +260,17 @@ def start_training(self, input_data: dict, config: Config, **kwargs: dict) -> (d comm.Bcast(loss_epoch, root=0) comm.Barrier() - time_loss = self.timing.stop_recording() + time_loss = timing.stop_recording() es.tell(solutions, loss_epoch.get() if GPU else loss_epoch) if es.result[1] < best_loss: best_loss = es.result[1] - index = loss_epoch.argmin() - best_pmf = pmfs_model[index] / pmfs_model[index].sum() - if self.study_generalization: - - if samples is None: - counts = self.sample_from_pmf( - n_states_range=self.n_states_range, - pmf=best_pmf.get() if GPU else best_pmf, - n_shots=self.generalization_metrics.n_shots) - else: - counts = samples[int(index)] - - metrics = self.generalization_metrics.get_metrics(counts.get() if GPU else counts) - for (key, value) in metrics.items(): - self.writer.add_scalar(f"metrics/{key}", value, epoch) - - nll = self.nll(best_pmf.reshape([1, -1]), self.target) - kl = self.kl_divergence(best_pmf.reshape([1, -1]), self.target) - # best_pmf_cpu = best_pmf.reshape([1, -1]) if GPU else best_pmf.reshape([1, -1]) - self.writer.add_scalar("metrics/NLL", nll.get() if GPU else nll, epoch) - self.writer.add_scalar("metrics/KL", kl.get() if GPU else kl, epoch) - self.writer.add_scalar("time/circuit", time_circ, epoch) - self.writer.add_scalar("time/loss", time_loss, epoch) - input_data["best_parameters"].append(es.result[0]) + best_pmf = self.data_visualization(loss_epoch, pmfs_model, samples, epoch) + input_data["best_parameters"].append(es.result[0]) input_data["KL"].append(float(es.result[1])) - if self.tb_images and epoch in self.image_epochs: - ax.clear() - ax.imshow( - best_pmf.reshape(int(np.sqrt(best_pmf.size)), int(np.sqrt(best_pmf.size))).get() if GPU - else best_pmf.reshape(int(np.sqrt(best_pmf.size)), - int(np.sqrt(best_pmf.size))), - cmap='binary', - interpolation='none') - ax.set_title(f'Iteration {epoch}') - self.writer.add_figure('grid_figure', fig, global_step=epoch) - logging.info( f"[Iteration {es.result[4]}] " f"[{config['loss']}: {es.result[1]:.5f}] "\ @@ -327,6 +286,41 @@ def start_training(self, input_data: dict, config: Config, **kwargs: dict) -> (d best_sample = self.sample_from_pmf(self.n_states_range, best_pmf.get() if GPU else best_pmf, n_shots=input_data["n_shots"]) - input_data["best_sample"] = best_sample.get() if GPU else best_sample + input_data["best_sample"] = best_sample.get() if GPU else best_sample # pylint: disable=E1101 return input_data + + + def data_visualization(self, loss_epoch, pmfs_model, samples, epoch): + index = loss_epoch.argmin() + best_pmf = pmfs_model[index] / pmfs_model[index].sum() + if self.study_generalization: + + if samples is None: + counts = self.sample_from_pmf( + n_states_range=self.n_states_range, + pmf=best_pmf.get() if GPU else best_pmf, + n_shots=self.generalization_metrics.n_shots) + else: + counts = samples[int(index)] + + metrics = self.generalization_metrics.get_metrics(counts.get() if GPU else counts) + for (key, value) in metrics.items(): + self.writer.add_scalar(f"metrics/{key}", value, epoch) + + nll = self.nll(best_pmf.reshape([1, -1]), self.target) + kl = self.kl_divergence(best_pmf.reshape([1, -1]), self.target) + self.writer.add_scalar("metrics/NLL", nll.get() if GPU else nll, epoch) + self.writer.add_scalar("metrics/KL", kl.get() if GPU else kl, epoch) + + self.ax.clear() + self.ax.imshow( + best_pmf.reshape(int(np.sqrt(best_pmf.size)), int(np.sqrt(best_pmf.size))).get() if GPU + else best_pmf.reshape(int(np.sqrt(best_pmf.size)), + int(np.sqrt(best_pmf.size))), + cmap='binary', + interpolation='none') + self.ax.set_title(f'Iteration {epoch}') + self.writer.add_figure('grid_figure', self.fig, global_step=epoch) + + return best_pmf From aa2f578cbc65cda03fd6a743505a14049bd260d6 Mon Sep 17 00:00:00 2001 From: "Marvin Erdmann (FG-231)" Date: Sun, 5 Nov 2023 14:10:12 +0100 Subject: [PATCH 4/5] Architecture update to make directory structure more consistent --- .settings/module_db.json | 46 +++++++++--------- .../generative_modeling/GenerativeModeling.py | 4 +- .../{ => generative_modeling}/data/MG_2D.npy | Bin .../{ => generative_modeling}/data/O_2D.npy | Bin .../data/Stocks_2D.npy | Bin .../{ => generative_modeling}/data/X_2D.npy | Bin .../data/__init__.py | 0 .../data}/data_handler/ContinuousData.py | 11 +++-- .../data}/data_handler/DataHandler.py | 6 ++- .../data}/data_handler/DiscreteData.py | 23 ++++----- .../data_handler/MetricsGeneralization.py | 0 .../data}/data_handler/__init__.py | 0 .../mappings}/Library.py | 0 .../mappings}/LibraryQiskit.py | 6 +-- .../mappings}/__init__.py | 0 .../transformations/MinMax.py | 6 +-- .../transformations/PIT.py | 4 +- .../transformations/Transformation.py | 2 +- .../transformations/__init__.py | 0 .../PVC/{ => data}/createReferenceGraph.py | 0 .../PVC/{ => data}/reference_data.txt | 0 .../PVC/{ => data}/reference_graph.gpickle | Bin .../TSP/{ => data}/createReferenceGraph.py | 0 .../optimization/TSP/{ => data}/dsj1000.tsp | 0 .../TSP/{ => data}/reference_graph.gpickle | Bin .../QML => }/circuits/Circuit.py | 0 .../QML => }/circuits/CircuitCardinality.py | 4 +- .../QML => }/circuits/CircuitCopula.py | 4 +- .../QML => }/circuits/CircuitStandard.py | 4 +- .../QML => }/circuits/__init__.py | 0 .../QML => }/training/Inference.py | 2 +- .../{applications/QML => }/training/QCBM.py | 2 +- .../QML => }/training/Training.py | 0 .../QML => }/training/__init__.py | 0 34 files changed, 65 insertions(+), 59 deletions(-) rename src/modules/applications/QML/{ => generative_modeling}/data/MG_2D.npy (100%) rename src/modules/applications/QML/{ => generative_modeling}/data/O_2D.npy (100%) rename src/modules/applications/QML/{ => generative_modeling}/data/Stocks_2D.npy (100%) rename src/modules/applications/QML/{ => generative_modeling}/data/X_2D.npy (100%) rename src/modules/applications/QML/{ => generative_modeling}/data/__init__.py (100%) rename src/modules/applications/QML/{ => generative_modeling/data}/data_handler/ContinuousData.py (92%) rename src/modules/applications/QML/{ => generative_modeling/data}/data_handler/DataHandler.py (97%) rename src/modules/applications/QML/{ => generative_modeling/data}/data_handler/DiscreteData.py (91%) rename src/modules/applications/QML/{ => generative_modeling/data}/data_handler/MetricsGeneralization.py (100%) rename src/modules/applications/QML/{ => generative_modeling/data}/data_handler/__init__.py (100%) rename src/modules/applications/QML/{libraries => generative_modeling/mappings}/Library.py (100%) rename src/modules/applications/QML/{libraries => generative_modeling/mappings}/LibraryQiskit.py (98%) rename src/modules/applications/QML/{libraries => generative_modeling/mappings}/__init__.py (100%) rename src/modules/applications/QML/{ => generative_modeling}/transformations/MinMax.py (97%) rename src/modules/applications/QML/{ => generative_modeling}/transformations/PIT.py (98%) rename src/modules/applications/QML/{ => generative_modeling}/transformations/Transformation.py (98%) rename src/modules/applications/QML/{ => generative_modeling}/transformations/__init__.py (100%) rename src/modules/applications/optimization/PVC/{ => data}/createReferenceGraph.py (100%) rename src/modules/applications/optimization/PVC/{ => data}/reference_data.txt (100%) rename src/modules/applications/optimization/PVC/{ => data}/reference_graph.gpickle (100%) rename src/modules/applications/optimization/TSP/{ => data}/createReferenceGraph.py (100%) rename src/modules/applications/optimization/TSP/{ => data}/dsj1000.tsp (100%) rename src/modules/applications/optimization/TSP/{ => data}/reference_graph.gpickle (100%) rename src/modules/{applications/QML => }/circuits/Circuit.py (100%) rename src/modules/{applications/QML => }/circuits/CircuitCardinality.py (96%) rename src/modules/{applications/QML => }/circuits/CircuitCopula.py (97%) rename src/modules/{applications/QML => }/circuits/CircuitStandard.py (96%) rename src/modules/{applications/QML => }/circuits/__init__.py (100%) rename src/modules/{applications/QML => }/training/Inference.py (98%) rename src/modules/{applications/QML => }/training/QCBM.py (99%) rename src/modules/{applications/QML => }/training/Training.py (100%) rename src/modules/{applications/QML => }/training/__init__.py (100%) diff --git a/.settings/module_db.json b/.settings/module_db.json index 2e894811..a57799d4 100644 --- a/.settings/module_db.json +++ b/.settings/module_db.json @@ -1,7 +1,7 @@ { - "build_number": 3, - "build_date": "15-09-2023 13:07:59", - "git_revision_number": "ce28372e0d19413d823d7d6d746052238f52bb23", + "build_number": 4, + "build_date": "17-11-2023 08:32:15", + "git_revision_number": "909e072a1c55494dd5b9628acac0fafa978cf65a", "modules": [ { "name": "PVC", @@ -1995,7 +1995,7 @@ "name": "Continuous Data", "class": "ContinuousData", "args": {}, - "module": "modules.applications.QML.data_handler.ContinuousData", + "module": "modules.applications.QML.generative_modeling.data.data_handler.ContinuousData", "requirements": [ { "name": "numpy", @@ -2007,7 +2007,7 @@ "name": "PIT", "class": "PIT", "args": {}, - "module": "modules.applications.QML.transformations.PIT", + "module": "modules.applications.QML.generative_modeling.transformations.PIT", "requirements": [ { "name": "numpy", @@ -2023,7 +2023,7 @@ "name": "CircuitCopula", "class": "CircuitCopula", "args": {}, - "module": "modules.applications.QML.circuits.CircuitCopula", + "module": "modules.circuits.CircuitCopula", "requirements": [ { "name": "scipy", @@ -2035,7 +2035,7 @@ "name": "LibraryQiskit", "class": "LibraryQiskit", "args": {}, - "module": "modules.applications.QML.libraries.LibraryQiskit", + "module": "modules.applications.QML.generative_modeling.mappings.LibraryQiskit", "requirements": [ { "name": "qiskit", @@ -2051,7 +2051,7 @@ "name": "QCBM", "class": "QCBM", "args": {}, - "module": "modules.applications.QML.training.QCBM", + "module": "modules.training.QCBM", "requirements": [ { "name": "numpy", @@ -2076,7 +2076,7 @@ "name": "Inference", "class": "Inference", "args": {}, - "module": "modules.applications.QML.training.Inference", + "module": "modules.training.Inference", "requirements": [ { "name": "numpy", @@ -2095,7 +2095,7 @@ "name": "MinMax", "class": "MinMax", "args": {}, - "module": "modules.applications.QML.transformations.MinMax", + "module": "modules.applications.QML.generative_modeling.transformations.MinMax", "requirements": [ { "name": "numpy", @@ -2107,7 +2107,7 @@ "name": "CircuitStandard", "class": "CircuitStandard", "args": {}, - "module": "modules.applications.QML.circuits.CircuitStandard", + "module": "modules.circuits.CircuitStandard", "requirements": [ { "name": "scipy", @@ -2119,7 +2119,7 @@ "name": "LibraryQiskit", "class": "LibraryQiskit", "args": {}, - "module": "modules.applications.QML.libraries.LibraryQiskit", + "module": "modules.applications.QML.generative_modeling.mappings.LibraryQiskit", "requirements": [ { "name": "qiskit", @@ -2135,7 +2135,7 @@ "name": "QCBM", "class": "QCBM", "args": {}, - "module": "modules.applications.QML.training.QCBM", + "module": "modules.training.QCBM", "requirements": [ { "name": "numpy", @@ -2160,7 +2160,7 @@ "name": "Inference", "class": "Inference", "args": {}, - "module": "modules.applications.QML.training.Inference", + "module": "modules.training.Inference", "requirements": [ { "name": "numpy", @@ -2177,14 +2177,14 @@ "name": "CircuitCardinality", "class": "CircuitCardinality", "args": {}, - "module": "modules.applications.QML.circuits.CircuitCardinality", + "module": "modules.circuits.CircuitCardinality", "requirements": [], "submodules": [ { "name": "LibraryQiskit", "class": "LibraryQiskit", "args": {}, - "module": "modules.applications.QML.libraries.LibraryQiskit", + "module": "modules.applications.QML.generative_modeling.mappings.LibraryQiskit", "requirements": [ { "name": "qiskit", @@ -2200,7 +2200,7 @@ "name": "QCBM", "class": "QCBM", "args": {}, - "module": "modules.applications.QML.training.QCBM", + "module": "modules.training.QCBM", "requirements": [ { "name": "numpy", @@ -2225,7 +2225,7 @@ "name": "Inference", "class": "Inference", "args": {}, - "module": "modules.applications.QML.training.Inference", + "module": "modules.training.Inference", "requirements": [ { "name": "numpy", @@ -2246,7 +2246,7 @@ "name": "Discrete Data", "class": "DiscreteData", "args": {}, - "module": "modules.applications.QML.data_handler.DiscreteData", + "module": "modules.applications.QML.generative_modeling.data.data_handler.DiscreteData", "requirements": [ { "name": "numpy", @@ -2258,14 +2258,14 @@ "name": "CircuitCardinality", "class": "CircuitCardinality", "args": {}, - "module": "modules.applications.QML.circuits.CircuitCardinality", + "module": "modules.circuits.CircuitCardinality", "requirements": [], "submodules": [ { "name": "LibraryQiskit", "class": "LibraryQiskit", "args": {}, - "module": "modules.applications.QML.libraries.LibraryQiskit", + "module": "modules.applications.QML.generative_modeling.mappings.LibraryQiskit", "requirements": [ { "name": "qiskit", @@ -2281,7 +2281,7 @@ "name": "QCBM", "class": "QCBM", "args": {}, - "module": "modules.applications.QML.training.QCBM", + "module": "modules.training.QCBM", "requirements": [ { "name": "numpy", @@ -2306,7 +2306,7 @@ "name": "Inference", "class": "Inference", "args": {}, - "module": "modules.applications.QML.training.Inference", + "module": "modules.training.Inference", "requirements": [ { "name": "numpy", diff --git a/src/modules/applications/QML/generative_modeling/GenerativeModeling.py b/src/modules/applications/QML/generative_modeling/GenerativeModeling.py index 2624ec03..95a1ae15 100644 --- a/src/modules/applications/QML/generative_modeling/GenerativeModeling.py +++ b/src/modules/applications/QML/generative_modeling/GenerativeModeling.py @@ -17,8 +17,8 @@ from modules.applications.Application import * from modules.applications.QML.QML import QML -from modules.applications.QML.data_handler.DiscreteData import DiscreteData -from modules.applications.QML.data_handler.ContinuousData import ContinuousData +from modules.applications.QML.generative_modeling.data.data_handler.DiscreteData import DiscreteData +from modules.applications.QML.generative_modeling.data.data_handler.ContinuousData import ContinuousData class GenerativeModeling(QML): diff --git a/src/modules/applications/QML/data/MG_2D.npy b/src/modules/applications/QML/generative_modeling/data/MG_2D.npy similarity index 100% rename from src/modules/applications/QML/data/MG_2D.npy rename to src/modules/applications/QML/generative_modeling/data/MG_2D.npy diff --git a/src/modules/applications/QML/data/O_2D.npy b/src/modules/applications/QML/generative_modeling/data/O_2D.npy similarity index 100% rename from src/modules/applications/QML/data/O_2D.npy rename to src/modules/applications/QML/generative_modeling/data/O_2D.npy diff --git a/src/modules/applications/QML/data/Stocks_2D.npy b/src/modules/applications/QML/generative_modeling/data/Stocks_2D.npy similarity index 100% rename from src/modules/applications/QML/data/Stocks_2D.npy rename to src/modules/applications/QML/generative_modeling/data/Stocks_2D.npy diff --git a/src/modules/applications/QML/data/X_2D.npy b/src/modules/applications/QML/generative_modeling/data/X_2D.npy similarity index 100% rename from src/modules/applications/QML/data/X_2D.npy rename to src/modules/applications/QML/generative_modeling/data/X_2D.npy diff --git a/src/modules/applications/QML/data/__init__.py b/src/modules/applications/QML/generative_modeling/data/__init__.py similarity index 100% rename from src/modules/applications/QML/data/__init__.py rename to src/modules/applications/QML/generative_modeling/data/__init__.py diff --git a/src/modules/applications/QML/data_handler/ContinuousData.py b/src/modules/applications/QML/generative_modeling/data/data_handler/ContinuousData.py similarity index 92% rename from src/modules/applications/QML/data_handler/ContinuousData.py rename to src/modules/applications/QML/generative_modeling/data/data_handler/ContinuousData.py index 5b10162d..2ff1131a 100644 --- a/src/modules/applications/QML/data_handler/ContinuousData.py +++ b/src/modules/applications/QML/generative_modeling/data/data_handler/ContinuousData.py @@ -20,9 +20,9 @@ from utils import start_time_measurement, end_time_measurement -from modules.applications.QML.data_handler.DataHandler import * -from modules.applications.QML.transformations.MinMax import MinMax -from modules.applications.QML.transformations.PIT import PIT +from modules.applications.QML.generative_modeling.transformations.MinMax import MinMax +from modules.applications.QML.generative_modeling.transformations.PIT import PIT +from modules.applications.QML.generative_modeling.data.data_handler.DataHandler import * class ContinuousData(DataHandler): @@ -35,7 +35,7 @@ class ContinuousData(DataHandler): def __init__(self): """ The continuous data class loads a dataset from the path - src/modules/applications/QML/data + src/modules/applications/QML/generative_modeling/data """ super().__init__("") self.submodule_options = ["PIT", "MinMax"] @@ -119,7 +119,8 @@ def data_load(self, gen_mod: dict, config: Config) -> dict: self.dataset_name = config["data_set"] self.n_qubits = gen_mod["n_qubits"] - filename = pkg_resources.resource_filename('modules.applications.QML.data', f"{self.dataset_name}.npy") + filename = pkg_resources.resource_filename('modules.applications.QML.generative_modeling.data', + f"{self.dataset_name}.npy") self.dataset = np.load(filename) application_config = { diff --git a/src/modules/applications/QML/data_handler/DataHandler.py b/src/modules/applications/QML/generative_modeling/data/data_handler/DataHandler.py similarity index 97% rename from src/modules/applications/QML/data_handler/DataHandler.py rename to src/modules/applications/QML/generative_modeling/data/data_handler/DataHandler.py index 0089bcf7..cf864e0b 100644 --- a/src/modules/applications/QML/data_handler/DataHandler.py +++ b/src/modules/applications/QML/generative_modeling/data/data_handler/DataHandler.py @@ -125,7 +125,11 @@ def postprocess(self, input_data: dict, config: dict, **kwargs): if self.generalization_mark is not None: np.save(f"{store_dir_iter}/histogram_generated.npy", evaluation["histogram_generated"]) else: - np.save(f"{store_dir_iter}/histogram_generated.npy", input_data.pop("histogram_generated")) + samples = input_data["best_sample"] + n_shots = np.sum(samples) + histogram_generated = np.asarray(samples) / n_shots + histogram_generated[histogram_generated == 0] = 1e-8 + np.save(f"{store_dir_iter}/histogram_generated.npy", histogram_generated) self.metrics.add_metric_batch({"histogram_generated": os.path.relpath( f"{store_dir_iter}/histogram_generated.npy_{kwargs['rep_count']}.npy", current_directory)}) diff --git a/src/modules/applications/QML/data_handler/DiscreteData.py b/src/modules/applications/QML/generative_modeling/data/data_handler/DiscreteData.py similarity index 91% rename from src/modules/applications/QML/data_handler/DiscreteData.py rename to src/modules/applications/QML/generative_modeling/data/data_handler/DiscreteData.py index 4c8dc18a..0ff03a5e 100644 --- a/src/modules/applications/QML/data_handler/DiscreteData.py +++ b/src/modules/applications/QML/generative_modeling/data/data_handler/DiscreteData.py @@ -19,9 +19,9 @@ import numpy as np -from modules.applications.QML.data_handler.DataHandler import * -from modules.applications.QML.circuits.CircuitCardinality import CircuitCardinality -from modules.applications.QML.data_handler.MetricsGeneralization import MetricsGeneralization +from modules.circuits.CircuitCardinality import CircuitCardinality +from modules.applications.QML.generative_modeling.data.data_handler.DataHandler import * +from modules.applications.QML.generative_modeling.data.data_handler.MetricsGeneralization import MetricsGeneralization class DiscreteData(DataHandler): @@ -141,21 +141,22 @@ def data_load(self, gen_mod: dict, config: Config) -> dict: train_set = np.array([int(i, 2) for i in train_set]) self.histogram_train[train_set] = 1 / len(train_set) - self.generalization_metrics = MetricsGeneralization( - train_set=train_set, - train_size=self.train_size, - solution_set=solution_set, - n_qubits=self.n_qubits, - ) - application_config = { "dataset_name": dataset_name, "n_qubits": self.n_qubits, "histogram_solution": self.histogram_solution, "histogram_train": self.histogram_train, - "generalization_metrics": self.generalization_metrics, "store_dir_iter": gen_mod["store_dir_iter"]} + if self.train_size != 1: + self.generalization_metrics = MetricsGeneralization( + train_set=train_set, + train_size=self.train_size, + solution_set=solution_set, + n_qubits=self.n_qubits, + ) + application_config["generalization_metrics"] = self.generalization_metrics + return application_config def generalisation(self) -> (dict, float): diff --git a/src/modules/applications/QML/data_handler/MetricsGeneralization.py b/src/modules/applications/QML/generative_modeling/data/data_handler/MetricsGeneralization.py similarity index 100% rename from src/modules/applications/QML/data_handler/MetricsGeneralization.py rename to src/modules/applications/QML/generative_modeling/data/data_handler/MetricsGeneralization.py diff --git a/src/modules/applications/QML/data_handler/__init__.py b/src/modules/applications/QML/generative_modeling/data/data_handler/__init__.py similarity index 100% rename from src/modules/applications/QML/data_handler/__init__.py rename to src/modules/applications/QML/generative_modeling/data/data_handler/__init__.py diff --git a/src/modules/applications/QML/libraries/Library.py b/src/modules/applications/QML/generative_modeling/mappings/Library.py similarity index 100% rename from src/modules/applications/QML/libraries/Library.py rename to src/modules/applications/QML/generative_modeling/mappings/Library.py diff --git a/src/modules/applications/QML/libraries/LibraryQiskit.py b/src/modules/applications/QML/generative_modeling/mappings/LibraryQiskit.py similarity index 98% rename from src/modules/applications/QML/libraries/LibraryQiskit.py rename to src/modules/applications/QML/generative_modeling/mappings/LibraryQiskit.py index 0224db6e..c10fea18 100644 --- a/src/modules/applications/QML/libraries/LibraryQiskit.py +++ b/src/modules/applications/QML/generative_modeling/mappings/LibraryQiskit.py @@ -21,9 +21,9 @@ from qiskit.providers import Backend import numpy as np -from modules.applications.QML.training.QCBM import QCBM -from modules.applications.QML.training.Inference import Inference -from modules.applications.QML.libraries.Library import Library +from modules.training.QCBM import QCBM +from modules.training.Inference import Inference +from modules.applications.QML.generative_modeling.mappings.Library import Library logging.getLogger("qiskit").setLevel(logging.WARNING) diff --git a/src/modules/applications/QML/libraries/__init__.py b/src/modules/applications/QML/generative_modeling/mappings/__init__.py similarity index 100% rename from src/modules/applications/QML/libraries/__init__.py rename to src/modules/applications/QML/generative_modeling/mappings/__init__.py diff --git a/src/modules/applications/QML/transformations/MinMax.py b/src/modules/applications/QML/generative_modeling/transformations/MinMax.py similarity index 97% rename from src/modules/applications/QML/transformations/MinMax.py rename to src/modules/applications/QML/generative_modeling/transformations/MinMax.py index 1d58aa73..34e3cd84 100644 --- a/src/modules/applications/QML/transformations/MinMax.py +++ b/src/modules/applications/QML/generative_modeling/transformations/MinMax.py @@ -16,9 +16,9 @@ import numpy as np -from modules.applications.QML.transformations.Transformation import * -from modules.applications.QML.circuits.CircuitStandard import CircuitStandard -from modules.applications.QML.circuits.CircuitCardinality import CircuitCardinality +from modules.applications.QML.generative_modeling.transformations.Transformation import * +from modules.circuits.CircuitStandard import CircuitStandard +from modules.circuits.CircuitCardinality import CircuitCardinality class MinMax(Transformation): diff --git a/src/modules/applications/QML/transformations/PIT.py b/src/modules/applications/QML/generative_modeling/transformations/PIT.py similarity index 98% rename from src/modules/applications/QML/transformations/PIT.py rename to src/modules/applications/QML/generative_modeling/transformations/PIT.py index e3d0da6a..4e8490d2 100644 --- a/src/modules/applications/QML/transformations/PIT.py +++ b/src/modules/applications/QML/generative_modeling/transformations/PIT.py @@ -17,8 +17,8 @@ import numpy as np import pandas as pd -from modules.applications.QML.transformations.Transformation import * -from modules.applications.QML.circuits.CircuitCopula import CircuitCopula +from modules.applications.QML.generative_modeling.transformations.Transformation import * +from modules.circuits.CircuitCopula import CircuitCopula class PIT(Transformation): diff --git a/src/modules/applications/QML/transformations/Transformation.py b/src/modules/applications/QML/generative_modeling/transformations/Transformation.py similarity index 98% rename from src/modules/applications/QML/transformations/Transformation.py rename to src/modules/applications/QML/generative_modeling/transformations/Transformation.py index 85124ec3..5b80caa8 100644 --- a/src/modules/applications/QML/transformations/Transformation.py +++ b/src/modules/applications/QML/generative_modeling/transformations/Transformation.py @@ -22,7 +22,7 @@ class Transformation(Core, ABC): """ - The task of the transformation module is to translate the application’s data and problem specification into + The task of the transformation module is to translate data and problem specification of the application into preprocessed format. """ diff --git a/src/modules/applications/QML/transformations/__init__.py b/src/modules/applications/QML/generative_modeling/transformations/__init__.py similarity index 100% rename from src/modules/applications/QML/transformations/__init__.py rename to src/modules/applications/QML/generative_modeling/transformations/__init__.py diff --git a/src/modules/applications/optimization/PVC/createReferenceGraph.py b/src/modules/applications/optimization/PVC/data/createReferenceGraph.py similarity index 100% rename from src/modules/applications/optimization/PVC/createReferenceGraph.py rename to src/modules/applications/optimization/PVC/data/createReferenceGraph.py diff --git a/src/modules/applications/optimization/PVC/reference_data.txt b/src/modules/applications/optimization/PVC/data/reference_data.txt similarity index 100% rename from src/modules/applications/optimization/PVC/reference_data.txt rename to src/modules/applications/optimization/PVC/data/reference_data.txt diff --git a/src/modules/applications/optimization/PVC/reference_graph.gpickle b/src/modules/applications/optimization/PVC/data/reference_graph.gpickle similarity index 100% rename from src/modules/applications/optimization/PVC/reference_graph.gpickle rename to src/modules/applications/optimization/PVC/data/reference_graph.gpickle diff --git a/src/modules/applications/optimization/TSP/createReferenceGraph.py b/src/modules/applications/optimization/TSP/data/createReferenceGraph.py similarity index 100% rename from src/modules/applications/optimization/TSP/createReferenceGraph.py rename to src/modules/applications/optimization/TSP/data/createReferenceGraph.py diff --git a/src/modules/applications/optimization/TSP/dsj1000.tsp b/src/modules/applications/optimization/TSP/data/dsj1000.tsp similarity index 100% rename from src/modules/applications/optimization/TSP/dsj1000.tsp rename to src/modules/applications/optimization/TSP/data/dsj1000.tsp diff --git a/src/modules/applications/optimization/TSP/reference_graph.gpickle b/src/modules/applications/optimization/TSP/data/reference_graph.gpickle similarity index 100% rename from src/modules/applications/optimization/TSP/reference_graph.gpickle rename to src/modules/applications/optimization/TSP/data/reference_graph.gpickle diff --git a/src/modules/applications/QML/circuits/Circuit.py b/src/modules/circuits/Circuit.py similarity index 100% rename from src/modules/applications/QML/circuits/Circuit.py rename to src/modules/circuits/Circuit.py diff --git a/src/modules/applications/QML/circuits/CircuitCardinality.py b/src/modules/circuits/CircuitCardinality.py similarity index 96% rename from src/modules/applications/QML/circuits/CircuitCardinality.py rename to src/modules/circuits/CircuitCardinality.py index 62911a6a..a533adcf 100644 --- a/src/modules/applications/QML/circuits/CircuitCardinality.py +++ b/src/modules/circuits/CircuitCardinality.py @@ -14,8 +14,8 @@ from typing import TypedDict -from modules.applications.QML.circuits.Circuit import Circuit -from modules.applications.QML.libraries.LibraryQiskit import LibraryQiskit +from modules.circuits.Circuit import Circuit +from modules.applications.QML.generative_modeling.mappings.LibraryQiskit import LibraryQiskit class CircuitCardinality(Circuit): diff --git a/src/modules/applications/QML/circuits/CircuitCopula.py b/src/modules/circuits/CircuitCopula.py similarity index 97% rename from src/modules/applications/QML/circuits/CircuitCopula.py rename to src/modules/circuits/CircuitCopula.py index 9d4b35dd..c1f97225 100644 --- a/src/modules/applications/QML/circuits/CircuitCopula.py +++ b/src/modules/circuits/CircuitCopula.py @@ -17,8 +17,8 @@ from scipy.special import binom -from modules.applications.QML.circuits.Circuit import Circuit -from modules.applications.QML.libraries.LibraryQiskit import LibraryQiskit +from modules.circuits.Circuit import Circuit +from modules.applications.QML.generative_modeling.mappings.LibraryQiskit import LibraryQiskit class CircuitCopula(Circuit): diff --git a/src/modules/applications/QML/circuits/CircuitStandard.py b/src/modules/circuits/CircuitStandard.py similarity index 96% rename from src/modules/applications/QML/circuits/CircuitStandard.py rename to src/modules/circuits/CircuitStandard.py index a823d956..86903fe1 100644 --- a/src/modules/applications/QML/circuits/CircuitStandard.py +++ b/src/modules/circuits/CircuitStandard.py @@ -14,8 +14,8 @@ from typing import TypedDict -from modules.applications.QML.circuits.Circuit import Circuit -from modules.applications.QML.libraries.LibraryQiskit import LibraryQiskit +from modules.circuits.Circuit import Circuit +from modules.applications.QML.generative_modeling.mappings.LibraryQiskit import LibraryQiskit class CircuitStandard(Circuit): diff --git a/src/modules/applications/QML/circuits/__init__.py b/src/modules/circuits/__init__.py similarity index 100% rename from src/modules/applications/QML/circuits/__init__.py rename to src/modules/circuits/__init__.py diff --git a/src/modules/applications/QML/training/Inference.py b/src/modules/training/Inference.py similarity index 98% rename from src/modules/applications/QML/training/Inference.py rename to src/modules/training/Inference.py index d9fc2a08..f61b6319 100644 --- a/src/modules/applications/QML/training/Inference.py +++ b/src/modules/training/Inference.py @@ -13,7 +13,7 @@ # limitations under the License. from typing import TypedDict -from modules.applications.QML.training.Training import * +from modules.training.Training import * class Inference(Training): diff --git a/src/modules/applications/QML/training/QCBM.py b/src/modules/training/QCBM.py similarity index 99% rename from src/modules/applications/QML/training/QCBM.py rename to src/modules/training/QCBM.py index d8c9aab7..770613b3 100644 --- a/src/modules/applications/QML/training/QCBM.py +++ b/src/modules/training/QCBM.py @@ -19,7 +19,7 @@ from matplotlib import figure, axes import matplotlib.pyplot as plt -from modules.applications.QML.training.Training import * +from modules.training.Training import * from utils_mpi import is_running_mpi, get_comm MPI = is_running_mpi() diff --git a/src/modules/applications/QML/training/Training.py b/src/modules/training/Training.py similarity index 100% rename from src/modules/applications/QML/training/Training.py rename to src/modules/training/Training.py diff --git a/src/modules/applications/QML/training/__init__.py b/src/modules/training/__init__.py similarity index 100% rename from src/modules/applications/QML/training/__init__.py rename to src/modules/training/__init__.py From 99fe0be194d37a335a30518847945f44fe23e4ae Mon Sep 17 00:00:00 2001 From: Philipp Ross Date: Wed, 22 Nov 2023 10:58:21 +0100 Subject: [PATCH 5/5] Update module database --- .settings/module_db.json | 6 +++--- .settings/requirements_full.txt | 6 +++++- 2 files changed, 8 insertions(+), 4 deletions(-) diff --git a/.settings/module_db.json b/.settings/module_db.json index a57799d4..7b025d2e 100644 --- a/.settings/module_db.json +++ b/.settings/module_db.json @@ -1,7 +1,7 @@ { - "build_number": 4, - "build_date": "17-11-2023 08:32:15", - "git_revision_number": "909e072a1c55494dd5b9628acac0fafa978cf65a", + "build_number": 5, + "build_date": "22-11-2023 09:57:53", + "git_revision_number": "aa2f578cbc65cda03fd6a743505a14049bd260d6", "modules": [ { "name": "PVC", diff --git a/.settings/requirements_full.txt b/.settings/requirements_full.txt index 560752e9..04f0ee7d 100644 --- a/.settings/requirements_full.txt +++ b/.settings/requirements_full.txt @@ -9,7 +9,7 @@ sphinx-rtd-theme==1.2.0 numpy==1.23.5 dimod==0.12.5 amazon-braket-sdk==1.35.1 -scipy==1.10.1 +scipy==1.11.1 botocore==1.25.7 boto3==1.22.7 pennylane==0.28.0 @@ -24,3 +24,7 @@ qiskit-optimization==0.5.0 pyqubo==1.4.0 dwave_networkx==0.8.13 qiskit==0.40.0 +pandas==1.5.2 +cma==3.3.0 +tensorboard==2.13.0 +tensorboardX==2.6.2

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