Index

A

account_status() (in module dynex)

AllStumpsClassifier (class in dynex_qboost.qboost)

B

biases_hidden (HybridQRBM.optimizers.Parameters attribute) biases_visible (HybridQRBM.optimizers.Parameters attribute)

binary() (in module HybridQRBM.utils) binary_three_bits() (in module HybridQRBM.utils) BQM (class in dynex)

C

calculate_update() (HybridQRBM.optimizers.RBMOptimizer method) Callbacks (class in HybridQRBM.rbm) compute_and_log_metric() (MAQRBM.marbm.MARBM method) compute_free_energy() (MAQRBM.marbm.MARBM method) compute_kl_divergence() (MAQRBM.marbm.MARBM method) compute_mae() (MAQRBM.marbm.MARBM method) compute_mse() (MAQRBM.marbm.MARBM method)

compute_ssim() (MAQRBM.marbm.MARBM method) contrastive_divergence() (MAQRBM.marbm.MARBM method) ContrastiveDivergenceSampler (class in HybridQRBM.samplers) corrcoef() (in module dynex_scikit_plugin.utilities) cov() (in module dynex_scikit_plugin.utilities) CQM (class in dynex) CXRDataset_pca (class in HybridQRBM.utils)

D

DecisionStumpClassifier (class in dynex_qboost.qboost) delta() (DynexQSVM.QSVM_Layer.QSVM_Layer method) dnx (class in HybridQRBM.pytorchdnx) dnx_experimental (class in HybridQRBM.pytorchdnx) dot_2d() (in module dynex_scikit_plugin.utilities) DWaveInferenceSampler (class in HybridQRBM.samplers) DWaveSampler (class in HybridQRBM.samplers) dynex module dynex_qboost module dynex_qboost.qboost module DYNEX_QRBM (class in DynexQRBM.QRBM)

dynex_scikit_plugin module dynex_scikit_plugin.utilities module DynexQRBM module DynexQRBM.QRBM module DynexQSVM module DynexQSVM.QSVM_Layer module DynexSampler (class in dynex) (class in HybridQRBM.samplers)

E

encode() (in module HybridQRBM.utils) energy() (HybridQRBM.rbm.RBM method) EnsembleClassifier (class in dynex_qboost.qboost)

estimate_costs() (in module dynex) extract_data_only_from_batch() (MAQRBM.marbm.MARBM method) extract_features() (MAQRBM.marbm.MARBM method)

F

fit() (HybridQRBM.rbm.RBM method) fit_offset() (dynex_qboost.qboost.EnsembleClassifier method) fit_range() (HybridQRBM.rbm.RBM method)

forward() (DynexQSVM.QSVM_Layer.QSVM_Layer method) (HybridQRBM.pytorchdnx.dnx method) (HybridQRBM.pytorchdnx.dnx_experimental method) (MAQRBM.marbm.MARBM method)

G

generate() (DynexQRBM.QRBM.DYNEX_QRBM method) (HybridQRBM.samplers.Sampler method) generate_visible_layer() (DynexQRBM.QRBM.DYNEX_QRBM method) get_auc_calculator() (in module HybridQRBM.callbacks)

get_selected_features() (dynex_qboost.qboost.EnsembleClassifier method) get_visualization_data() (MAQRBM.marbm.MARBM method) get_weights() (DynexQRBM.QRBM.DYNEX_QRBM method) gibbs_updates() (HybridQRBM.samplers.Sampler method)

H

hidden (HybridQRBM.callbacks.Sample attribute) hidden_prob (HybridQRBM.callbacks.Sample attribute) HybridQRBM module HybridQRBM.callbacks module HybridQRBM.optimizers module

HybridQRBM.pytorchdnx module HybridQRBM.rbm module HybridQRBM.samplers module HybridQRBM.utils module

I

infer() (DynexQRBM.QRBM.DYNEX_QRBM method) (HybridQRBM.samplers.Sampler method)

K

kernel() (DynexQSVM.QSVM_Layer.QSVM_Layer method)

kl_divergence() (MAQRBM.marbm.MARBM method)

L

l2_regularizer() (in module HybridQRBM.utils) load() (DynexQRBM.QRBM.DYNEX_QRBM method) load_data() (in module HybridQRBM.utils)

load_model() (DynexQSVM.QSVM_Layer.QSVM_Layer method) (MAQRBM.marbm.MARBM method) lock_weights() (MAQRBM.marbm.MARBM method)

M

MAQRBM module MAQRBM.marbm module MARBM (class in MAQRBM.marbm) module dynex dynex_qboost dynex_qboost.qboost dynex_scikit_plugin dynex_scikit_plugin.utilities DynexQRBM DynexQRBM.QRBM DynexQSVM DynexQSVM.QSVM_Layer HybridQRBM HybridQRBM.callbacks HybridQRBM.optimizers HybridQRBM.pytorchdnx HybridQRBM.rbm HybridQRBM.samplers HybridQRBM.utils MAQRBM MAQRBM.marbm

N

NaiveSampler (class in HybridQRBM.samplers)

O

on_batch_end (HybridQRBM.rbm.Callbacks attribute) on_batch_start (HybridQRBM.rbm.Callbacks attribute) on_epoch_end (HybridQRBM.rbm.Callbacks attribute)

on_epoch_start (HybridQRBM.rbm.Callbacks attribute) on_fit_end (HybridQRBM.rbm.Callbacks attribute) on_fit_start (HybridQRBM.rbm.Callbacks attribute)

P

Parameters (class in HybridQRBM.optimizers) PersistentContrastiveDivergenceSampler (class in HybridQRBM.samplers) predict() (dynex_qboost.qboost.DecisionStumpClassifier method) (dynex_qboost.qboost.EnsembleClassifier method) (DynexQRBM.QRBM.DYNEX_QRBM method) (HybridQRBM.rbm.RBM method) (HybridQRBM.samplers.DWaveInferenceSampler method) (HybridQRBM.samplers.Sampler method)

predict_class() (dynex_qboost.qboost.EnsembleClassifier method) preprocess_to_binary() (MAQRBM.marbm.MARBM method) produce_logger() (in module HybridQRBM.callbacks)

Q

qboost_lambda_sweep() (in module dynex_qboost.qboost)

QBoostClassifier (class in dynex_qboost.qboost) QSVM_Layer (class in DynexQSVM.QSVM_Layer)

R

RBM (class in HybridQRBM.rbm) rbm2qubo() (MAQRBM.marbm.MARBM method)

RBMOptimizer (class in HybridQRBM.optimizers) reconstruct() (MAQRBM.marbm.MARBM method) report_baseline() (dynex_qboost.qboost.QBoostClassifier method)

S

Sample (class in HybridQRBM.callbacks) sample() (dynex.DynexSampler method) (HybridQRBM.samplers.ContrastiveDivergenceSampler method) (HybridQRBM.samplers.DWaveSampler method) (HybridQRBM.samplers.DynexSampler method) (HybridQRBM.samplers.NaiveSampler method) (HybridQRBM.samplers.PersistentContrastiveDivergenceSampler method) (HybridQRBM.samplers.Sampler method) (in module dynex) sample_hidden() (MAQRBM.marbm.MARBM method) sample_ising() (in module dynex) sample_opposite_layer_pyqubo() (DynexQRBM.QRBM.DYNEX_QRBM method) (HybridQRBM.pytorchdnx.dnx_experimental method)

sample_opposite_layer_pyqubo_batch() (DynexQRBM.QRBM.DYNEX_QRBM method) sample_qubo() (in module dynex) sample_visible() (MAQRBM.marbm.MARBM method) Sampler (class in HybridQRBM.samplers) SAT (class in dynex) save() (DynexQRBM.QRBM.DYNEX_QRBM method) save_model() (DynexQSVM.QSVM_Layer.QSVM_Layer method) (MAQRBM.marbm.MARBM method) save_particles() (in module HybridQRBM.callbacks) score() (dynex_qboost.qboost.EnsembleClassifier method) set_sampler_parameters() (MAQRBM.marbm.MARBM method) set_weights() (DynexQRBM.QRBM.DYNEX_QRBM method) sigmoid() (in module DynexQRBM.QRBM) squared_error() (dynex_qboost.qboost.EnsembleClassifier method)

T

test() (in module dynex) to_qubo_matrix() (HybridQRBM.pytorchdnx.dnx method) (HybridQRBM.rbm.RBM method) train() (DynexQRBM.QRBM.DYNEX_QRBM method) (DynexQSVM.QSVM_Layer.QSVM_Layer method) (MAQRBM.marbm.MARBM method)

training (DynexQSVM.QSVM_Layer.QSVM_Layer attribute) (HybridQRBM.pytorchdnx.dnx attribute) (HybridQRBM.pytorchdnx.dnx_experimental attribute) (MAQRBM.marbm.MARBM attribute)

U

unlock_weights() (MAQRBM.marbm.MARBM method)

V

visible (HybridQRBM.callbacks.Sample attribute)

visible_prob (HybridQRBM.callbacks.Sample attribute)

W

weights (HybridQRBM.optimizers.Parameters attribute)