UNIQORN -- The Universal Neural-network Interface for Quantum Observable Readout from N-body wavefunctions
ModelTrainingAndValidation.py File Reference

Namespaces

 ModelTrainingAndValidation
 

Functions

def ModelTrainingAndValidation.make_variable (tuple, initializer)
 
def ModelTrainingAndValidation.shape (tensor)
 
def ModelTrainingAndValidation.plot_interpol (xesnew, ynew)
 
def ModelTrainingAndValidation.ApplyInterpolation (y_data, y_data_interpolation)
 
def ModelTrainingAndValidation.Interpolation_MSE (y_true, y_pred)
 Custom Loss function evaluating the error of an interpolation. More...
 
def ModelTrainingAndValidation.MSE_plus_MAE (y_true, y_pred)
 
def ModelTrainingAndValidation.MSE_plus_LogMSE (y_true, y_pred)
 
def ModelTrainingAndValidation.LogCosh_plus_MAE (y_true, y_pred)
 
def ModelTrainingAndValidation.LogCosh_plus_LogMSE (y_true, y_pred)
 
def ModelTrainingAndValidation.LogCosh_plus_MSE (y_true, y_pred)
 
def ModelTrainingAndValidation.LogCosh_plus_LogMSE_plus_MAE (y_true, y_pred)
 
def ModelTrainingAndValidation.main (*args, **kwargs)
 
def ModelTrainingAndValidation.ModelEvaluation (*args)
 

Variables

 ModelTrainingAndValidation.threshold
 
 ModelTrainingAndValidation.xgrid = np.arange(0.0,1.0*inp.Npoints)
 
 ModelTrainingAndValidation.ygrid = np.arange(0.0,1.0*inp.Npoints)
 
 ModelTrainingAndValidation.test_predictions = ModelEvaluation(model, validation_generator)
 test data:
More...
 
int ModelTrainingAndValidation.size_predictions = 1
 
int ModelTrainingAndValidation.size_labels = 1
 
 ModelTrainingAndValidation.y_val = y_val.reshape(np.shape(test_predictions))