code: def __init__(
      self,
      in_channels: int,
      embed_dim: int,
      activation: type[Module] = nn.GELU,
  ) -> None:
      super().__init__()
      self.seq = nn.Sequential(
          ConvBN(in_channels, embed_dim // 2, 3, 2, 1),
          activation(),
          ConvBN(embed_dim // 2, embed_dim, 3, 2, 1),
      )
  
imports: from __future__ import annotations
  import itertools
  import warnings
  from typing import Any, Optional
  import torch
  import torch.nn.functional
  from torch import nn
  from torch.utils import checkpoint
  from kornia.contrib.models.common import DropPath, LayerNorm2d, window_partition, window_unpartition
  from kornia.core import Module, Tensor
  from kornia.core.check import KORNIA_CHECK
label_desc: Use image node_id 1 to create a new PatchEmbed object from inherited base classes: nn with example: obj = PatchEmbed(in_channels, embed_dim, activation)