class_docstr: SE Block Proposed in https://arxiv.org/pdf/1709.01507.pdf
class_docstr_tok: ["SE","Block","Proposed","in","https",":","\/\/arxiv.org\/pdf\/1709.01507.pdf"]
code: def __init__(self, num_channels, reduction=1):
      super().__init__()
      self.pool = nn.AdaptiveAvgPool2D(1)
      self.conv = nn.Sequential(
          nn.Conv2D(
              num_channels,
              int(num_channels // reduction),
              1,
              bias_attr=False,
          ),
          nn.ReLU(),
          nn.Conv2D(
              int(num_channels // reduction),
              num_channels,
              1,
              bias_attr=False,
          ),
          nn.Sigmoid(),
      )
  
imports: from collections import defaultdict
  import paddle
  import paddle.nn
  import paddle.nn.functional
  import numpy
  import scipy
  import paddleseg
  from paddleseg.models import layers, losses
  from paddleseg import utils
  from paddleseg.cvlibs import manager, param_init
label_desc: Use image node_id 1 to create a new SEBlock object from inherited base classes: nn with example: obj = SEBlock(num_channels, reduction)