class_docstr: Depthwise seperable convolution with batchnorm and activation.
class_docstr_tok: ["Depthwise","seperable","convolution","with","batchnorm","and","activation","."]
code: def forward(self, x: Tensor) -> Tensor:
      x = self.depthwise(x)
      x = self.bn(x)
      return self.act(x)
  
file_path: pytorch-toolbelt/pytorch_toolbelt/modules/dsconv.py
imports: from torch import nn, Tensor
  from pytorch_toolbelt.modules.normalization import instantiate_normalization_block, NORM_BATCH
  from pytorch_toolbelt.modules.activations import instantiate_activation_block
label_desc: Use image node_id 2 for calling the DepthwiseSeparableConv2dBlock obj's underlying member method code with example usage: obj.forward(x) and returns: self