waller-lab / multiwienernet Goto Github PK

class ConvBlock():
    def __init__(self, in_channels, out_channels, dropout=False, norm='batch',
                 residual=True, activation='leakyrelu', transpose=False):
        self.dropout = dropout
        self.residual = residual
        self.activation = activation
        self.transpose = transpose
        self.norm = norm
    
    def printme(self):
        print('Dropout: ', self.dropout)
        print('Residual: ', self.residual)
        print('Activation: ', self.activation)
        print('Transpose: ', self.transpose)
        print('Norm: ', self.norm)

residual = True
activation = 'relu'
c = ConvBlock(32, 64, residual, activation)
c.printme()
"""Dropout:  True
Residual:  True
Activation:  leakyrelu
Transpose:  False
Norm:  relu
"""

c2 = ConvBlock(32, 64, residual=residual, activation=activation)
c2.printme()
"""
Dropout:  False
Residual:  True
Activation:  relu
Transpose:  False
Norm:  batch
"""