qml/__init__.py,sha256=9ifTJuaR23uJGXaAky9AZSNzBQvNh29EqQ-4dSm5qeA,1311
qml/__main__.py,sha256=O8QoHmwN838d4YdBoutT3TiadLTfchzMHd3f_cGrLWA,22928
qml/ansatz.py,sha256=FzzZ8ryDkllxD5svnwHdlsyA3zJfDeANRVPt6Dgzt2I,2197
qml/benchmarks.py,sha256=cOz7ZiuFKZ0ZClN0TWg_Msowx7Ifqg1ALsd0mn20tV4,12946
qml/classical_baselines.py,sha256=kN3JqUdO9X24Yxh7z65L4i4HPWQVSIXdkKCca-bt0xM,14549
qml/classifiers.py,sha256=XjdGnodX3OB1ja8UzsPt-t4R3oFQOf5ZJaxzYr6Smcs,9021
qml/data.py,sha256=vtiNUN8h-Vq2R6NQPAqABygvYftHM7XQMJ1ZDInj8wE,9984
qml/embeddings.py,sha256=pY5IPNJa6Y7_Tc57YbYj-U33byKjzELgiz-2DKykgXI,3593
qml/io_utils.py,sha256=58uf2wPoEjF4WMn2VuZH8YxLoATXNlheWAmtao-RcFA,2703
qml/kernel_methods.py,sha256=DqlNK04oCnVQmpqo69WSZ36Aa48CxBa1YcomxiFmvbQ,5955
qml/losses.py,sha256=k8iYsCeZJEgbYmKuEE7VQf-U3DjBOP1h1ReTKOjM0yY,382
qml/metric_learning.py,sha256=Q4uC2YxV2G3Ljnxclyj6mREh6gG6UrrVLUo9Iyl3fuM,11653
qml/metrics.py,sha256=felJohlsZ0qZkilKCgXeMaFBlCeV51qeA6mgAq635vc,1131
qml/optimizers.py,sha256=UGD0SRUWrk9K62-3YlfX-px09gGlWrHYpTXSXILzsLo,1338
qml/regression.py,sha256=1f4WMNgrEeqg3B7xEHjLXwbhP2R1-LGnYt9tmD0EuZ8,6650
qml/trainable_kernels.py,sha256=BTFm-Sd1rIGq8i7SBCFsJE6IIVk5hUheNCfGhvsR_rw,14441
qml/training.py,sha256=CPGRkqsAURdQTq-1fh0beb5xSocO_35GEw1rWkXxHWw,1060
qml/utils.py,sha256=P2a2MdDViX8ip8aGwRn1zeRSvcYAQmWKUWbEjtgteZs,521
qml/visualize.py,sha256=6iqFH5Y7P0kjnu8nOBLorZNxFOEXlTrFTtV4oEa5YPc,7402
qml_pennylane-0.1.8.dist-info/licenses/LICENSE,sha256=8yjLrHRw7qIlfoogu8raXR4DVceIzWyMgJJ9veAAoKo,1069
qml_pennylane-0.1.8.dist-info/METADATA,sha256=oS7k3nFv22MMBA1sA-iZ0DSepntG3fKHNkb8aQ_TlMY,10592
qml_pennylane-0.1.8.dist-info/WHEEL,sha256=aeYiig01lYGDzBgS8HxWXOg3uV61G9ijOsup-k9o1sk,91
qml_pennylane-0.1.8.dist-info/top_level.txt,sha256=NPT3piXWWmFbwUfI_iKxDMnDCKNtTYRrd7PRmwR0nRI,4
qml_pennylane-0.1.8.dist-info/RECORD,,
