python/methylnet/datasets.py
def generate(self):
        """Generate function for transform.

        Returns
        -------
        function

        """
        data_aug = []
        if self.convolutional and self.l != None:
            data_aug.append(_reshape(self.cpgs_per_row, self.l))
        data_aug.append(convert_to_tensor())
        return Compose(data_aug)
Generate function for transform.

        Returns
        -------
        function

        
Generate function for transform.
Returns

function
Generate function for transform . Returns function
def generate(self):
        data_aug = []
        if self.convolutional and self.l != None:
            data_aug.append(_reshape(self.cpgs_per_row, self.l))
        data_aug.append(convert_to_tensor())
        return Compose(data_aug)
def generate ( self ) : data_aug = [ ] if self . convolutional and self . l != None : data_aug . append ( _reshape ( self . cpgs_per_row , self . l ) ) data_aug . append ( convert_to_tensor ( ) ) return Compose ( data_aug )
Generate function for transform.
Generate function for transform .
"""Generate function for transform.

        Returns
        -------
        function

        """
self