class_docstr: Convolutional Patch embedding layer.
  
  Args:
      opts: Command line arguments.
      patch_size: Patch size for embedding computation.
      stride: Stride for convolutional embedding layer.
      in_channels: Number of channels of input tensor.
      embed_dim: Number of embedding dimensions.
class_docstr_tok: ["Convolutional","Patch","embedding","layer",".","Args",":","opts",":","Command","line","arguments",".","patch_size",":","Patch","size","for","embedding","computation",".","stride",":","Stride","for","convolutional","embedding","layer",".","in_channels",":","Number","of","channels","of","input","tensor",".","embed_dim",":","Number","of","embedding","dimensions","."]
docstr: Forward pass
  
  Args:
      x: Input tensor of shape :math:`(B, C, H, W)`.
  
  Returns:
      torch.Tensor of shape :math:`(B, C, H//s, W//s)`,
      where `s` is the stride provide while instantiating the layer.
docstr_tok: ["Forward","pass","Args",":","x",":","Input","tensor","of","shape",":","math",":","`","(","B",",","C",",","H",",","W",")","`",".","Returns",":","torch.Tensor","of","shape",":","math",":","`","(","B",",","C",",","H\/\/s",",","W\/\/s",")","`",",","where","`","s","`","is","the","stride","provide","while","instantiating","the","layer","."]
code: def forward(self, x: torch.Tensor, *args, **kwargs) -> torch.Tensor:
      """
      Forward pass
  
      Args:
          x: Input tensor of shape :math:`(B, C, H, W)`.
  
      Returns:
          torch.Tensor of shape :math:`(B, C, H//s, W//s)`,
          where `s` is the stride provide while instantiating the layer.
      """
      x = self.proj(x)
      return x
  
imports: import argparse
  from typing import Optional, Tuple, Union
  import torch
  import torch.nn
  from cvnets.layers import ConvLayer2d, MultiHeadAttention, StochasticDepth
  from cvnets.layers.normalization.batch_norm import BatchNorm2d
  from cvnets.modules import BaseModule
  from cvnets.modules.mobileone_block import MobileOneBlock, RepLKBlock
label_desc: Use image node_id 2 for calling the PatchEmbed obj's underlying member method code with example usage: obj.forward(x) and returns: x