class_docstr: ## 2D Convolution Layer
  
  This extends the standard 2D Convolution layer and standardize the weights before the convolution step.
code: def forward(self, x: torch.Tensor):
      return F.conv2d(
          x,
          weight_standardization(self.weight, self.eps),
          self.bias,
          self.stride,
          self.padding,
          self.dilation,
          self.groups,
      )
  
file_path: annotated_deep_learning_paper_implementations/labml_nn/normalization/weight_standardization/conv2d.py
imports: import torch
  import torch.nn
  from torch.nn import functional
  from labml_nn.normalization.weight_standardization import weight_standardization
label_desc: Use image node_id 2 for calling the Conv2d obj's underlying member method code with example usage: obj.forward(x) and returns: F