class_docstr: This class defines the convolution layer with batch normalization and PReLU activation
class_docstr_tok: ["This","class","defines","the","convolution","layer","with","batch","normalization","and","PReLU","activation"]
code: def __init__(self, nIn, nOut, kSize, stride=1):
      super().__init__()
      padding = int((kSize - 1) / 2)
  
      self.conv = nn.Sequential(
          nn.Conv2D(
              nIn,
              nIn,
              (kSize, kSize),
              stride=stride,
              padding=(padding, padding),
              groups=nIn,
              bias_attr=False,
          ),
          nn.Conv2D(
              nIn, nOut, kernel_size=1, stride=1, bias_attr=False
          ),
      )
      self.bn = nn.BatchNorm(nOut)
      self.act = nn.PReLU(nOut)
  
imports: import paddle
  import paddle.nn
  import paddle.nn.functional
  from paddleseg.models import layers
  from paddleseg.cvlibs import manager
  from paddleseg.utils import utils
label_desc: Use image node_id 1 to create a new SeparableCBR object from inherited base classes: nn with example: obj = SeparableCBR(nIn, nOut, kSize, stride)