class_docstr: 2D Image to Patch Embedding
      
class_docstr_tok: ["2D","Image","to","Patch","Embedding"]
code: def __init__(
      self,
      img_size: Optional[int] = 224,
      patch_size: int = 16,
      in_chans: int = 3,
      embed_dim: int = 768,
      norm_layer: Optional[Callable] = None,
      flatten: bool = True,
      output_fmt: Optional[str] = None,
      bias: bool = True,
  ):
      super().__init__(
          img_size=img_size,
          patch_size=patch_size,
          in_chans=in_chans,
          embed_dim=embed_dim,
          norm_layer=norm_layer,
          flatten=flatten,
          output_fmt=output_fmt,
          bias=bias,
      )
  
file_path: pytorch-image-models/timm/layers/patch_embed.py
imports: import logging
  from typing import Callable, List, Optional, Tuple, Union
  import torch
  from torch import nn
  import torch.nn.functional
  from .format import Format, nchw_to
  from .helpers import to_2tuple
  from .trace_utils import _assert
label_desc: Use image node_id 1 to create a new PatchEmbedWithSize object from inherited base classes: PatchEmbed with example: obj = PatchEmbedWithSize(img_size, patch_size, in_chans, embed_dim, norm_layer, flatten, output_fmt, bias)