class_docstr: Image to Patch Embedding
code: def __init__(self, patch_size=7, stride=4, in_chans=3, embed_dim=768):
      super().__init__()
  
      self.embed_dim = embed_dim
      self.patch_size = patch_size
      self.proj = nn.Conv2d(
          in_chans,
          embed_dim,
          kernel_size=patch_size,
          stride=stride,
          padding=patch_size // 2,
      )
      self.norm = nn.LayerNorm(embed_dim)
      self.stride = stride
      self.apply(self._init_weights)
  
imports: import math
  from functools import partial
  from typing import Optional
  import torch
  import torch.nn
  from pytorch_toolbelt.modules.interfaces import AbstractEncoder, FeatureMapsSpecification
  from pytorch_toolbelt.modules.activations import instantiate_activation_block, ACT_GELU
  from pytorch_toolbelt.modules.drop_path import DropPath
label_desc: Use image node_id 1 to create a new OverlapPatchEmbed object from inherited base classes: nn with example: obj = OverlapPatchEmbed(patch_size, stride, in_chans, embed_dim)