UNIQORN -- The Universal Neural-network Interface for Quantum Observable Readout from N-body wavefunctions
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Regression_Loop_NShots.py File Reference
Namespaces
Regression_Loop_NShots
Variables
list
Regression_Loop_NShots.histories
= []
Regression_Loop_NShots.NSPS
= np.arange(10, 30 , 10, dtype=int)
list
Regression_Loop_NShots.scores
= []
int
Regression_Loop_NShots.count
= 0
Regression_Loop_NShots.Learn
Regression_Loop_NShots.momLabels
Regression_Loop_NShots.momData
Regression_Loop_NShots.DataString
= SpaceString(inp.momData)
Regression_Loop_NShots.LabelString
= SpaceString(inp.momLabels)
string
Regression_Loop_NShots.fname
= 'Errors_'+inp.Learn+'_in_'+LabelString+'_from_SSS_in_'+DataString
Regression_Loop_NShots.NShotsPerSample
Regression_Loop_NShots.NShots
Regression_Loop_NShots.Loss
Regression_Loop_NShots.training_generator
Regression_Loop_NShots.validation_generator
Regression_Loop_NShots.y_val
= np.array(y_val)
Regression_Loop_NShots.X_train
Regression_Loop_NShots.y_train
Regression_Loop_NShots.X_val
Regression_Loop_NShots.test_predictions
Regression_Loop_NShots.best_val_loss_index
= np.argmin(np.array(history.history['val_loss']))
Regression_Loop_NShots.score
= np.reshape(model.evaluate(validation_generator, verbose=0),(1,-1))
list
Regression_Loop_NShots.legend
= []
Regression_Loop_NShots.fig
Regression_Loop_NShots.ax
Regression_Loop_NShots.loc
Regression_Loop_NShots.xlabel
Regression_Loop_NShots.ylabel
Regression_Loop_NShots.py
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