support/models.py
def eval(self, w):
        '''
        Evaluate a parameter vector on the test data.
        '''
        # Specify the loss to use here.
        losses = self.l_te(w=w)

        # Specify the loss-based statistics to use here.
        rawres = [losses.mean(), losses.std()]
        
        return rawres

        Evaluate a parameter vector on the test data.
        
Evaluate a parameter vector on the test data.
Evaluate a parameter vector on the test data .
def eval(self, w):
        losses = self.l_te(w=w)
        rawres = [losses.mean(), losses.std()]
        return rawres
def eval ( self , w ) : losses = self . l_te ( w = w ) rawres = [ losses . mean ( ) , losses . std ( ) ] return rawres
Evaluate a parameter vector on the test data.
Evaluate a parameter vector on the test data .
'''
        Evaluate a parameter vector on the test data.
        ''' # Specify the loss to use here. # Specify the loss-based statistics to use here.
self
w