def __init__(self, num_input_features, num_output_features):
    super(_Transition, self).__init__()
    self.add_module('norm', nn.BatchNorm2d(num_input_features))
    self.add_module('relu', nn.ReLU(inplace=True))
    self.add_module('conv', nn.Conv2d(num_input_features, num_output_features, kernel_size=1, stride=1, bias=False))
    self.add_module('pool', nn.AvgPool2d(kernel_size=2, stride=2))
def __init__(self, num_input_features, num_output_features):
    super(_Transition, self).__init__()
    self.add_module('norm', nn.BatchNorm2d(num_input_features))
    self.add_module('relu', nn.ReLU(inplace=True))
    self.add_module('conv', nn.Conv2d(num_input_features, num_output_features, kernel_size=1, stride=1, bias=False))
    self.add_module('pool', nn.AvgPool2d(kernel_size=2, stride=2))