densenet_efficient.py 文件源码

def __init__(self, num_layers, num_input_features, bn_size, growth_rate, drop_rate, storage_size=1024):
        input_storage_1 = torch.Storage(storage_size)
        input_storage_2 = torch.Storage(storage_size)
        self.final_num_features = num_input_features + (growth_rate * num_layers)
        self.shared_allocation_1 = _SharedAllocation(input_storage_1)
        self.shared_allocation_2 = _SharedAllocation(input_storage_2)

        super(_DenseBlock, self).__init__()
        for i in range(num_layers):
            layer = _DenseLayer(self.shared_allocation_1, self.shared_allocation_2, num_input_features + i * growth_rate,
                                growth_rate, bn_size, drop_rate)
            self.add_module('denselayer%d' % (i + 1), layer)