from?torch.nn?import?Module?Sequential?
from?torch.nn?import?Conv3d?ConvTranspose3d?BatchNorm3d?MaxPool3d?AvgPool1d
from?torch.nn?import?ReLU?Sigmoid
import?torch

class?UNet3D（Module）:
????#?__????????????????????????????__
????#??1|__???________________???__|1
????#?????2|__??____________??__|2
????#????????3|__??______??__|3
????#???????????4|__?__?__|4?
????#?The?convolution?operations?on?either?side?are?residual?subject?to?1*1?Convolution?for?channel?homogeneity?

????def?__init__（self?num_channels=32?feat_channels=[64?128?256?512?1024]?residual=‘conv‘）:
????????
????????#?residual:?conv?for?residual?input?x?through?1*1?conv?across?every?layer?for?downsampling?None?for?removal?of?residuals

????????super（UNet3D?self）.__init__（）
????????
????????#?Encoder?downsamplers
????????self.pool1?=?MaxPool3d（（122））
????????self.pool2?=?MaxPool3d（（122））
????????self.pool3?=?MaxPool3d（（122））
????????self.pool4?=?MaxPool3d（（122））
????????
????????#?Encoder?convolutions
??