输出以上图像转换网络的结构

这个图像转换网络的结构如下：

ImageTransformerModel(
  (_initial): Sequential(
    (0): Conv2d(3, 32, kernel_size=(9, 9), stride=(1, 1), padding=(4, 4), padding_mode=reflect)
    (1): InstanceNorm2d(32, eps=1e-05, momentum=0.1, affine=True, track_running_stats=False)
    (2): ReLU(inplace=True)
  )
  (_down_blocks): Sequential(
    (0): DownBlock(
      (_conv1): Conv2d(32, 64, kernel_size=(3, 3), stride=(2, 2), padding=(1, 1), padding_mode=reflect)
      (_conv2): Conv2d(64, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), padding_mode=reflect)
      (_norm1): InstanceNorm2d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=False)
      (_norm2): InstanceNorm2d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=False)
      (_act): ReLU(inplace=True)
    )
    (1): DownBlock(
      (_conv1): Conv2d(64, 128, kernel_size=(3, 3), stride=(2, 2), padding=(1, 1), padding_mode=reflect)
      (_conv2): Conv2d(128, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), padding_mode=reflect)
      (_norm1): InstanceNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=False)
      (_norm2): InstanceNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=False)
      (_act): ReLU(inplace=True)
    )
  )
  (_residual_blocks): Sequential(
    (0): ResidualBlock(
      (_conv1): Conv2d(128, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), padding_mode=reflect)
      (_conv2): Conv2d(128, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), padding_mode=reflect)
      (_norm1): InstanceNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=False)
      (_norm2): InstanceNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=False)
      (_act): ReLU(inplace=True)
    )
    (1): ResidualBlock(
      (_conv1): Conv2d(128, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), padding_mode=reflect)
      (_conv2): Conv2d(128, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), padding_mode=reflect)
      (_norm1): InstanceNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=False)
      (_norm2): InstanceNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=False)
      (_act): ReLU(inplace=True)
    )
    (2): ResidualBlock(
      (_conv1): Conv2d(128, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), padding_mode=reflect)
      (_conv2): Conv2d(128, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), padding_mode=reflect)
      (_norm1): InstanceNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=False)
      (_norm2): InstanceNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=False)
      (_act): ReLU(inplace=True)
    )
    (3): ResidualBlock(
      (_conv1): Conv2d(128, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), padding_mode=reflect)
      (_conv2): Conv2d(128, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), padding_mode=reflect)
      (_norm1): InstanceNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=False)
      (_norm2): InstanceNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=False)
      (_act): ReLU(inplace=True)
    )
    (4): ResidualBlock(
      (_conv1): Conv2d(128, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), padding_mode=reflect)
      (_conv2): Conv2d(128, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), padding_mode=reflect)
      (_norm1): InstanceNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=False)
      (_norm2): InstanceNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=False)
      (_act): ReLU(inplace=True)
    )
  )
  (_up_blocks): Sequential(
    (0): UpBlock(
      (_conv1): ConvTranspose2d(128, 64, kernel_size=(3, 3), stride=(2, 2), padding=(1, 1), output_padding=(1, 1))
      (_conv2): Conv2d(64, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), padding_mode=reflect)
      (_norm1): InstanceNorm2d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=False)
      (_norm2): InstanceNorm2d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=False)
      (_act): ReLU(inplace=True)
    )
    (1): UpBlock(
      (_conv1): ConvTranspose2d(64, 32, kernel_size=(3, 3), stride=(2, 2), padding=(1, 1), output_padding=(1, 1))
      (_conv2): Conv2d(32, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), padding_mode=reflect)
      (_norm1): InstanceNorm2d(32, eps=1e-05, momentum=0.1, affine=True, track_running_stats=False)
      (_norm2): InstanceNorm2d(32, eps=1e-05, momentum=0.1, affine=True, track_running_stats=False)
      (_act): ReLU(inplace=True)
    )
  )
  (_final): Conv2d(32, 3, kernel_size=(9, 9), stride=(1, 1), padding=(4, 4), padding_mode=reflect)
)