





"""simple docstring"""





import argparse
import json

import requests
import timm
import torch
from huggingface_hub import hf_hub_download
from PIL import Image

from transformers import AutoImageProcessor, SwinConfig, SwinForImageClassification


def 			UpperCAmelCase__							(  SCREAMING_SNAKE_CASE     :						Optional[Any]			):







      '''simple docstring'''




      lowerCAmelCase  						=       SwinConfig()
      lowerCAmelCase  						=       swin_name.split("""_"""			)

      lowerCAmelCase  						=       name_split[1]
      lowerCAmelCase  						=       int(name_split[4]			)
      lowerCAmelCase  						=       int(name_split[3][-1]			)

      if model_size == "tiny":
            lowerCAmelCase  						=       96
            lowerCAmelCase  						=       (2, 2, 6, 2)
            lowerCAmelCase  						=       (3, 6, 12, 24)
      elif model_size == "small":
            lowerCAmelCase  						=       96
            lowerCAmelCase  						=       (2, 2, 18, 2)
            lowerCAmelCase  						=       (3, 6, 12, 24)
      elif model_size == "base":
            lowerCAmelCase  						=       1_28
            lowerCAmelCase  						=       (2, 2, 18, 2)
            lowerCAmelCase  						=       (4, 8, 16, 32)
      else:
            lowerCAmelCase  						=       1_92
            lowerCAmelCase  						=       (2, 2, 18, 2)
            lowerCAmelCase  						=       (6, 12, 24, 48)

      if "in22k" in swin_name:
            lowerCAmelCase  						=       2_18_41
      else:
            lowerCAmelCase  						=       10_00
            lowerCAmelCase  						=       """huggingface/label-files"""
            lowerCAmelCase  						=       """imagenet-1k-id2label.json"""
            lowerCAmelCase  						=       json.load(open(hf_hub_download(SCREAMING_SNAKE_CASE							,						SCREAMING_SNAKE_CASE							,						repo_type="""dataset"""			)							,						"""r"""			)			)
            lowerCAmelCase  						=       {int(SCREAMING_SNAKE_CASE			): v for k, v in idalabel.items()}
            lowerCAmelCase  						=       idalabel
            lowerCAmelCase  						=       {v: k for k, v in idalabel.items()}

      lowerCAmelCase  						=       img_size
      lowerCAmelCase  						=       num_classes
      lowerCAmelCase  						=       embed_dim
      lowerCAmelCase  						=       depths
      lowerCAmelCase  						=       num_heads
      lowerCAmelCase  						=       window_size

      return config


def 			UpperCAmelCase__							(  SCREAMING_SNAKE_CASE     :						Union[str, Any]			):







      '''simple docstring'''




      if "patch_embed.proj" in name:
            lowerCAmelCase  						=       name.replace("""patch_embed.proj"""							,						"""embeddings.patch_embeddings.projection"""			)
      if "patch_embed.norm" in name:
            lowerCAmelCase  						=       name.replace("""patch_embed.norm"""							,						"""embeddings.norm"""			)
      if "layers" in name:
            lowerCAmelCase  						=       """encoder.""" + name
      if "attn.proj" in name:
            lowerCAmelCase  						=       name.replace("""attn.proj"""							,						"""attention.output.dense"""			)
      if "attn" in name:
            lowerCAmelCase  						=       name.replace("""attn"""							,						"""attention.self"""			)
      if "norm1" in name:
            lowerCAmelCase  						=       name.replace("""norm1"""							,						"""layernorm_before"""			)
      if "norm2" in name:
            lowerCAmelCase  						=       name.replace("""norm2"""							,						"""layernorm_after"""			)
      if "mlp.fc1" in name:
            lowerCAmelCase  						=       name.replace("""mlp.fc1"""							,						"""intermediate.dense"""			)
      if "mlp.fc2" in name:
            lowerCAmelCase  						=       name.replace("""mlp.fc2"""							,						"""output.dense"""			)

      if name == "norm.weight":
            lowerCAmelCase  						=       """layernorm.weight"""
      if name == "norm.bias":
            lowerCAmelCase  						=       """layernorm.bias"""

      if "head" in name:
            lowerCAmelCase  						=       name.replace("""head"""							,						"""classifier"""			)
      else:
            lowerCAmelCase  						=       """swin.""" + name

      return name


def 			UpperCAmelCase__							(  SCREAMING_SNAKE_CASE     :						Dict							,						SCREAMING_SNAKE_CASE     :						str			):







      '''simple docstring'''




      for key in orig_state_dict.copy().keys():
            lowerCAmelCase  						=       orig_state_dict.pop(SCREAMING_SNAKE_CASE			)

            if "mask" in key:
                  continue
            elif "qkv" in key:
                  lowerCAmelCase  						=       key.split("""."""			)
                  lowerCAmelCase  						=       int(key_split[1]			)
                  lowerCAmelCase  						=       int(key_split[3]			)
                  lowerCAmelCase  						=       model.swin.encoder.layers[layer_num].blocks[block_num].attention.self.all_head_size

                  if "weight" in key:
                        lowerCAmelCase  						=       val[:dim, :]
                        lowerCAmelCase  						=       val[
                            dim : dim * 2, :
                        ]
                        lowerCAmelCase  						=       val[-dim:, :]
                  else:
                        lowerCAmelCase  						=       val[
                            :dim
                        ]
                        lowerCAmelCase  						=       val[
                            dim : dim * 2
                        ]
                        lowerCAmelCase  						=       val[
                            -dim:
                        ]
            else:
                  lowerCAmelCase  						=       val

      return orig_state_dict


def 			UpperCAmelCase__							(  SCREAMING_SNAKE_CASE     :						List[str]							,						SCREAMING_SNAKE_CASE     :						Tuple			):







      '''simple docstring'''




      lowerCAmelCase  						=       timm.create_model(SCREAMING_SNAKE_CASE							,						pretrained=SCREAMING_SNAKE_CASE			)
      timm_model.eval()

      lowerCAmelCase  						=       get_swin_config(SCREAMING_SNAKE_CASE			)
      lowerCAmelCase  						=       SwinForImageClassification(SCREAMING_SNAKE_CASE			)
      model.eval()

      lowerCAmelCase  						=       convert_state_dict(timm_model.state_dict()							,						SCREAMING_SNAKE_CASE			)
      model.load_state_dict(SCREAMING_SNAKE_CASE			)

      lowerCAmelCase  						=       """http://images.cocodataset.org/val2017/000000039769.jpg"""

      lowerCAmelCase  						=       AutoImageProcessor.from_pretrained("""microsoft/{}""".format(swin_name.replace("""_"""							,						"""-"""			)			)			)
      lowerCAmelCase  						=       Image.open(requests.get(SCREAMING_SNAKE_CASE							,						stream=SCREAMING_SNAKE_CASE			).raw			)
      lowerCAmelCase  						=       image_processor(images=SCREAMING_SNAKE_CASE							,						return_tensors="""pt"""			)

      lowerCAmelCase  						=       timm_model(inputs["""pixel_values"""]			)
      lowerCAmelCase  						=       model(**SCREAMING_SNAKE_CASE			).logits

      assert torch.allclose(SCREAMING_SNAKE_CASE							,						SCREAMING_SNAKE_CASE							,						atol=1e-3			)

      print(F'Saving model {swin_name} to {pytorch_dump_folder_path}'			)
      model.save_pretrained(SCREAMING_SNAKE_CASE			)

      print(F'Saving image processor to {pytorch_dump_folder_path}'			)
      image_processor.save_pretrained(SCREAMING_SNAKE_CASE			)


if __name__ == "__main__":
       SCREAMING_SNAKE_CASE__					=   argparse.ArgumentParser()
       # Required parameters
       parser.add_argument(
           "--swin_name",
           default="swin_tiny_patch4_window7_224",
           type=str,
           help="Name of the Swin timm model you'd like to convert.",
       )
       parser.add_argument(
           "--pytorch_dump_folder_path", default=None, type=str, help="Path to the output PyTorch model directory."
       )

       SCREAMING_SNAKE_CASE__					=   parser.parse_args()
       convert_swin_checkpoint(args.swin_name, args.pytorch_dump_folder_path)













"""simple docstring"""





from __future__ import annotations


def 			UpperCAmelCase__							(  SCREAMING_SNAKE_CASE     :						str			):







      '''simple docstring'''




      return [ord(SCREAMING_SNAKE_CASE			) - 96 for elem in plain]


def 			UpperCAmelCase__							(  SCREAMING_SNAKE_CASE     :						list[int]			):







      '''simple docstring'''




      return "".join(chr(elem + 96			) for elem in encoded			)


def 			UpperCAmelCase__							(  ):







      '''simple docstring'''




      lowerCAmelCase  						=       encode(input("""-> """			).strip().lower()			)
      print("""Encoded: """							,						SCREAMING_SNAKE_CASE			)
      print("""Decoded:"""							,						decode(SCREAMING_SNAKE_CASE			)			)


if __name__ == "__main__":
       main()






