import bza
import gzip
import lzma
import os
import shutil
import struct
import tarfile
import warnings
import zipfile
from abc import ABC, abstractmethod
from pathlib import Path
from typing import Dict, List, Optional, Type, Union

from .. import config
from .filelock import FileLock
from .logging import get_logger


UpperCamelCase__    							= get_logger(__name__)





class 					A							:


   def __init__(self					:						List[str]	,  __UpperCAmelCase					:						Optional[str] = None		)						->    Union[str, Any]:
         """simple docstring"""



         UpperCAmelCase__								=  (
             os.path.join(__UpperCAmelCase	,  config.EXTRACTED_DATASETS_DIR		) if cache_dir else config.EXTRACTED_DATASETS_PATH
         )
         UpperCAmelCase__								=  Extractor


   def       lowercase_				(self					:						str	,  __UpperCAmelCase					:						str		)						->    str:
         """simple docstring"""



         from .file_utils import hash_url_to_filename

         # Path where we extract compressed archives
         # We extract in the cache dir, and get the extracted path name by hashing the original path"
         UpperCAmelCase__								=  os.path.abspath(__UpperCAmelCase		)
         return os.path.join(self.extract_dir	,  hash_url_to_filename(__UpperCAmelCase		)		)


   def       lowercase_				(self					:						int	,  __UpperCAmelCase					:						str	,  __UpperCAmelCase					:						bool		)						->    bool:
         """simple docstring"""



         return force_extract or (
             not os.path.isfile(__UpperCAmelCase		) and not (os.path.isdir(__UpperCAmelCase		) and os.listdir(__UpperCAmelCase		))
         )





   def       lowercase_				(self					:						Union[str, Any]	,  __UpperCAmelCase					:						str	,  __UpperCAmelCase					:						bool = False		)						->    str:
         """simple docstring"""



         UpperCAmelCase__								=  self.extractor.infer_extractor_format(__UpperCAmelCase		)
         if not extractor_format:
               return input_path
         UpperCAmelCase__								=  self._get_output_path(__UpperCAmelCase		)
         if self._do_extract(__UpperCAmelCase	,  __UpperCAmelCase		):
               self.extractor.extract(__UpperCAmelCase	,  __UpperCAmelCase	,  __UpperCAmelCase		)
         return output_path





class 					A							(    UpperCAmelCase_					):


   @classmethod
   @abstractmethod
   def       lowercase_				(cls					:						Dict	,  __UpperCAmelCase					:						Union[Path, str]	,  **__UpperCAmelCase					:						Dict		)						->    bool:
         """simple docstring"""



         ...





   @staticmethod
   @abstractmethod
   def       lowercase_				(__UpperCAmelCase					:						Union[Path, str]	,  __UpperCAmelCase					:						Union[Path, str]		)						->    None:
         """simple docstring"""



         ...





class 					A							(    UpperCAmelCase_		,    UpperCAmelCase_					):
   __UpperCAmelCase			:			List[bytes]              =      []


   @staticmethod
   def       lowercase_				(__UpperCAmelCase					:						Union[Path, str]	,  __UpperCAmelCase					:						int		)						->    Dict:
         """simple docstring"""



         with open(__UpperCAmelCase	,  "rb"		) as f:
               return f.read(__UpperCAmelCase		)





   @classmethod
   def       lowercase_				(cls					:						Any	,  __UpperCAmelCase					:						Union[Path, str]	,  __UpperCAmelCase					:						bytes = b""		)						->    bool:
         """simple docstring"""



         if not magic_number:
               UpperCAmelCase__								=  max(len(__UpperCAmelCase		) for cls_magic_number in cls.magic_numbers		)
               try:
                     UpperCAmelCase__								=  cls.read_magic_number(__UpperCAmelCase	,  __UpperCAmelCase		)
               except OSError:
                     return False
         return any(magic_number.startswith(__UpperCAmelCase		) for cls_magic_number in cls.magic_numbers		)





class 					A							(    UpperCAmelCase_					):


   @classmethod
   def       lowercase_				(cls					:						Optional[int]	,  __UpperCAmelCase					:						Union[Path, str]	,  **__UpperCAmelCase					:						Tuple		)						->    bool:
         """simple docstring"""



         return tarfile.is_tarfile(__UpperCAmelCase		)


   @staticmethod
   def       lowercase_				(__UpperCAmelCase					:						Union[str, Any]	,  __UpperCAmelCase					:						List[Any]		)						->    int:
         """simple docstring"""



         def resolved(__UpperCAmelCase					:						str		) -> str:
               return os.path.realpath(os.path.abspath(__UpperCAmelCase		)		)

         def badpath(__UpperCAmelCase					:						str	,  __UpperCAmelCase					:						str		) -> bool:
               # joinpath will ignore base if path is absolute
               return not resolved(os.path.join(__UpperCAmelCase	,  __UpperCAmelCase		)		).startswith(__UpperCAmelCase		)

         def badlink(__UpperCAmelCase					:						List[str]	,  __UpperCAmelCase					:						str		) -> bool:
               # Links are interpreted relative to the directory containing the link
               UpperCAmelCase__								=  resolved(os.path.join(__UpperCAmelCase	,  os.path.dirname(info.name		)		)		)
               return badpath(info.linkname	,  base=__UpperCAmelCase		)

         UpperCAmelCase__								=  resolved(__UpperCAmelCase		)

         for finfo in members:
               if badpath(finfo.name	,  __UpperCAmelCase		):
                     logger.error(f"""Extraction of {finfo.name} is blocked (illegal path)"""		)
               elif finfo.issym() and badlink(__UpperCAmelCase	,  __UpperCAmelCase		):
                     logger.error(f"""Extraction of {finfo.name} is blocked: Symlink to {finfo.linkname}"""		)
               elif finfo.islnk() and badlink(__UpperCAmelCase	,  __UpperCAmelCase		):
                     logger.error(f"""Extraction of {finfo.name} is blocked: Hard link to {finfo.linkname}"""		)
               else:
                     yield finfo





   @staticmethod
   def       lowercase_				(__UpperCAmelCase					:						Union[Path, str]	,  __UpperCAmelCase					:						Union[Path, str]		)						->    None:
         """simple docstring"""



         os.makedirs(__UpperCAmelCase	,  exist_ok=__UpperCAmelCase		)
         UpperCAmelCase__								=  tarfile.open(__UpperCAmelCase		)
         tar_file.extractall(__UpperCAmelCase	,  members=TarExtractor.safemembers(__UpperCAmelCase	,  __UpperCAmelCase		)		)
         tar_file.close()





class 					A							(    UpperCAmelCase_					):
   __UpperCAmelCase			:			Optional[int]              =      [b'\x1F\x8B']


   @staticmethod
   def       lowercase_				(__UpperCAmelCase					:						Union[Path, str]	,  __UpperCAmelCase					:						Union[Path, str]		)						->    None:
         """simple docstring"""



         with gzip.open(__UpperCAmelCase	,  "rb"		) as gzip_file:
               with open(__UpperCAmelCase	,  "wb"		) as extracted_file:
                     shutil.copyfileobj(__UpperCAmelCase	,  __UpperCAmelCase		)





class 					A							(    UpperCAmelCase_					):
   __UpperCAmelCase			:			Tuple              =      [
       b'PK\x03\x04',
       b'PK\x05\x06',  # empty archive
       b'PK\x07\x08',  # spanned archive
   ]


   @classmethod
   def       lowercase_				(cls					:						Optional[Any]	,  __UpperCAmelCase					:						Union[Path, str]	,  __UpperCAmelCase					:						bytes = b""		)						->    bool:
         """simple docstring"""



         if super().is_extractable(__UpperCAmelCase	,  magic_number=__UpperCAmelCase		):
               return True
         try:
               # Alternative version of zipfile.is_zipfile that has less false positives, but misses executable zip archives.
               # From: https://github.com/python/cpython/pull/5053
               from zipfile import (
                   _CD_SIGNATURE,
                   _ECD_DISK_NUMBER,
                   _ECD_DISK_START,
                   _ECD_ENTRIES_TOTAL,
                   _ECD_OFFSET,
                   _ECD_SIZE,
                   _EndRecData,
                   sizeCentralDir,
                   stringCentralDir,
                   structCentralDir,
               )

               with open(__UpperCAmelCase	,  "rb"		) as fp:
                     UpperCAmelCase__								=  _EndRecData(__UpperCAmelCase		)
                     if endrec:
                           if endrec[_ECD_ENTRIES_TOTAL] == 0 and endrec[_ECD_SIZE] == 0 and endrec[_ECD_OFFSET] == 0:
                                 return True  # Empty zipfiles are still zipfiles
                           elif endrec[_ECD_DISK_NUMBER] == endrec[_ECD_DISK_START]:
                                 fp.seek(endrec[_ECD_OFFSET]		)  # Central directory is on the same disk
                                 if fp.tell() == endrec[_ECD_OFFSET] and endrec[_ECD_SIZE] >= sizeCentralDir:
                                       UpperCAmelCase__								=  fp.read(__UpperCAmelCase		)  # CD is where we expect it to be
                                       if len(__UpperCAmelCase		) == sizeCentralDir:
                                             UpperCAmelCase__								=  struct.unpack(__UpperCAmelCase	,  __UpperCAmelCase		)  # CD is the right size
                                             if centdir[_CD_SIGNATURE] == stringCentralDir:
                                                   return True  # First central directory entry  has correct magic number
               return False
         except Exception:  # catch all errors in case future python versions change the zipfile internals
               return False





   @staticmethod
   def       lowercase_				(__UpperCAmelCase					:						Union[Path, str]	,  __UpperCAmelCase					:						Union[Path, str]		)						->    None:
         """simple docstring"""



         os.makedirs(__UpperCAmelCase	,  exist_ok=__UpperCAmelCase		)
         with zipfile.ZipFile(__UpperCAmelCase	,  "r"		) as zip_file:
               zip_file.extractall(__UpperCAmelCase		)
               zip_file.close()





class 					A							(    UpperCAmelCase_					):
   __UpperCAmelCase			:			str              =      [b'\xFD\x37\x7A\x58\x5A\x00']


   @staticmethod
   def       lowercase_				(__UpperCAmelCase					:						Union[Path, str]	,  __UpperCAmelCase					:						Union[Path, str]		)						->    None:
         """simple docstring"""



         with lzma.open(__UpperCAmelCase		) as compressed_file:
               with open(__UpperCAmelCase	,  "wb"		) as extracted_file:
                     shutil.copyfileobj(__UpperCAmelCase	,  __UpperCAmelCase		)





class 					A							(    UpperCAmelCase_					):
   __UpperCAmelCase			:			Union[str, Any]              =      [b'Rar!\x1a\x07\x00', b'Rar!\x1a\x07\x01\x00']  # RAR_ID  # RAR5_ID


   @staticmethod
   def       lowercase_				(__UpperCAmelCase					:						Union[Path, str]	,  __UpperCAmelCase					:						Union[Path, str]		)						->    None:
         """simple docstring"""



         if not config.RARFILE_AVAILABLE:
               raise ImportError("Please pip install rarfile"		)
         import rarfile

         os.makedirs(__UpperCAmelCase	,  exist_ok=__UpperCAmelCase		)
         UpperCAmelCase__								=  rarfile.RarFile(__UpperCAmelCase		)
         rf.extractall(__UpperCAmelCase		)
         rf.close()





class 					A							(    UpperCAmelCase_					):
   __UpperCAmelCase			:			str              =      [b'\x28\xb5\x2F\xFD']


   @staticmethod
   def       lowercase_				(__UpperCAmelCase					:						Union[Path, str]	,  __UpperCAmelCase					:						Union[Path, str]		)						->    None:
         """simple docstring"""



         if not config.ZSTANDARD_AVAILABLE:
               raise ImportError("Please pip install zstandard"		)
         import zstandard as zstd

         UpperCAmelCase__								=  zstd.ZstdDecompressor()
         with open(__UpperCAmelCase	,  "rb"		) as ifh, open(__UpperCAmelCase	,  "wb"		) as ofh:
               dctx.copy_stream(__UpperCAmelCase	,  __UpperCAmelCase		)





class 					A							(    UpperCAmelCase_					):
   __UpperCAmelCase			:			Tuple              =      [b'\x42\x5A\x68']


   @staticmethod
   def       lowercase_				(__UpperCAmelCase					:						Union[Path, str]	,  __UpperCAmelCase					:						Union[Path, str]		)						->    None:
         """simple docstring"""



         with bza.open(__UpperCAmelCase	,  "rb"		) as compressed_file:
               with open(__UpperCAmelCase	,  "wb"		) as extracted_file:
                     shutil.copyfileobj(__UpperCAmelCase	,  __UpperCAmelCase		)





class 					A							(    UpperCAmelCase_					):
   __UpperCAmelCase			:			Any              =      [b'\x37\x7A\xBC\xAF\x27\x1C']


   @staticmethod
   def       lowercase_				(__UpperCAmelCase					:						Union[Path, str]	,  __UpperCAmelCase					:						Union[Path, str]		)						->    None:
         """simple docstring"""



         if not config.PY7ZR_AVAILABLE:
               raise ImportError("Please pip install py7zr"		)
         import pyazr

         os.makedirs(__UpperCAmelCase	,  exist_ok=__UpperCAmelCase		)
         with pyazr.SevenZipFile(__UpperCAmelCase	,  "r"		) as archive:
               archive.extractall(__UpperCAmelCase		)





class 					A							(    UpperCAmelCase_					):
   __UpperCAmelCase			:			Optional[Any]              =      [b'\x04\x22\x4D\x18']


   @staticmethod
   def       lowercase_				(__UpperCAmelCase					:						Union[Path, str]	,  __UpperCAmelCase					:						Union[Path, str]		)						->    None:
         """simple docstring"""



         if not config.LZ4_AVAILABLE:
               raise ImportError("Please pip install lz4"		)
         import lza.frame

         with lza.frame.open(__UpperCAmelCase	,  "rb"		) as compressed_file:
               with open(__UpperCAmelCase	,  "wb"		) as extracted_file:
                     shutil.copyfileobj(__UpperCAmelCase	,  __UpperCAmelCase		)





class 					A							:
   #  Put zip file to the last, b/c it is possible wrongly detected as zip (I guess it means: as tar or gzip)
   __UpperCAmelCase			:			Dict[str, Type[BaseExtractor]]              =      {
       "tar": TarExtractor,
       "gzip": GzipExtractor,
       "zip": ZipExtractor,
       "xz": XzExtractor,
       "rar": RarExtractor,
       "zstd": ZstdExtractor,
       "bz2": BzipaExtractor,
       "7z": SevenZipExtractor,  # <Added version="2.4.0"/>
       "lz4": LzaExtractor,  # <Added version="2.4.0"/>
   }


   @classmethod
   def       lowercase_				(cls					:						Optional[int]		)						->    Optional[int]:
         """simple docstring"""



         return max(
             len(__UpperCAmelCase		)
             for extractor in cls.extractors.values()
             if issubclass(__UpperCAmelCase	,  __UpperCAmelCase		)
             for extractor_magic_number in extractor.magic_numbers		)


   @staticmethod
   def       lowercase_				(__UpperCAmelCase					:						Union[Path, str]	,  __UpperCAmelCase					:						int		)						->    int:
         """simple docstring"""



         try:
               return MagicNumberBaseExtractor.read_magic_number(__UpperCAmelCase	,  magic_number_length=__UpperCAmelCase		)
         except OSError:
               return b""


   @classmethod
   def       lowercase_				(cls					:						Union[str, Any]	,  __UpperCAmelCase					:						Union[Path, str]	,  __UpperCAmelCase					:						bool = False		)						->    bool:
         """simple docstring"""



         warnings.warn(
             "Method 'is_extractable' was deprecated in version 2.4.0 and will be removed in 3.0.0. "
             "Use 'infer_extractor_format' instead."	,  category=__UpperCAmelCase	,  )
         UpperCAmelCase__								=  cls.infer_extractor_format(__UpperCAmelCase		)
         if extractor_format:
               return True if not return_extractor else (True, cls.extractors[extractor_format])
         return False if not return_extractor else (False, None)


   @classmethod
   def       lowercase_				(cls					:						str	,  __UpperCAmelCase					:						Union[Path, str]		)						->    str:  # <Added version="2.4.0"/>
         """simple docstring"""



         UpperCAmelCase__								=  cls._get_magic_number_max_length()
         UpperCAmelCase__								=  cls._read_magic_number(__UpperCAmelCase	,  __UpperCAmelCase		)
         for extractor_format, extractor in cls.extractors.items():
               if extractor.is_extractable(__UpperCAmelCase	,  magic_number=__UpperCAmelCase		):
                     return extractor_format





   @classmethod
   def       lowercase_				(cls					:						Dict	,  __UpperCAmelCase					:						Union[Path, str]	,  __UpperCAmelCase					:						Union[Path, str]	,  __UpperCAmelCase					:						Optional[str] = None	,  __UpperCAmelCase					:						Optional[BaseExtractor] = "deprecated"	,  )						->    None:
         """simple docstring"""



         os.makedirs(os.path.dirname(__UpperCAmelCase		)	,  exist_ok=__UpperCAmelCase		)
         # Prevent parallel extractions
         UpperCAmelCase__								=  str(Path(__UpperCAmelCase		).with_suffix(".lock"		)		)
         with FileLock(__UpperCAmelCase		):
               shutil.rmtree(__UpperCAmelCase	,  ignore_errors=__UpperCAmelCase		)
               if extractor_format or extractor != "deprecated":
                     if extractor != "deprecated" or not isinstance(__UpperCAmelCase	,  __UpperCAmelCase		):  # passed as positional arg
                           warnings.warn(
                               "Parameter 'extractor' was deprecated in version 2.4.0 and will be removed in 3.0.0. "
                               "Use 'extractor_format' instead."	,  category=__UpperCAmelCase	,  )
                           UpperCAmelCase__								=  extractor if extractor != "deprecated" else extractor_format
                     else:
                           UpperCAmelCase__								=  cls.extractors[extractor_format]
                     return extractor.extract(__UpperCAmelCase	,  __UpperCAmelCase		)
               else:
                     warnings.warn(
                         "Parameter 'extractor_format' was made required in version 2.4.0 and not passing it will raise an "
                         "exception in 3.0.0."	,  category=__UpperCAmelCase	,  )
                     for extractor in cls.extractors.values():
                           if extractor.is_extractable(__UpperCAmelCase		):
                                 return extractor.extract(__UpperCAmelCase	,  __UpperCAmelCase		)




import argparse
import json
from pathlib import Path

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

from transformers import DeiTConfig, DeiTForImageClassificationWithTeacher, DeiTImageProcessor
from transformers.utils import logging


logging.set_verbosity_info()
UpperCamelCase__    							= logging.get_logger(__name__)




def        lowerCAmelCase_			(					__A,  __A=False							)					->    Any:







      '''simple docstring'''


      UpperCAmelCase__								=  []
      for i in range(config.num_hidden_layers							):
            # encoder layers: output projection, 2 feedforward neural networks and 2 layernorms
            rename_keys.append((f"""blocks.{i}.norm1.weight""", f"""deit.encoder.layer.{i}.layernorm_before.weight""")							)
            rename_keys.append((f"""blocks.{i}.norm1.bias""", f"""deit.encoder.layer.{i}.layernorm_before.bias""")							)
            rename_keys.append((f"""blocks.{i}.attn.proj.weight""", f"""deit.encoder.layer.{i}.attention.output.dense.weight""")							)
            rename_keys.append((f"""blocks.{i}.attn.proj.bias""", f"""deit.encoder.layer.{i}.attention.output.dense.bias""")							)
            rename_keys.append((f"""blocks.{i}.norm2.weight""", f"""deit.encoder.layer.{i}.layernorm_after.weight""")							)
            rename_keys.append((f"""blocks.{i}.norm2.bias""", f"""deit.encoder.layer.{i}.layernorm_after.bias""")							)
            rename_keys.append((f"""blocks.{i}.mlp.fc1.weight""", f"""deit.encoder.layer.{i}.intermediate.dense.weight""")							)
            rename_keys.append((f"""blocks.{i}.mlp.fc1.bias""", f"""deit.encoder.layer.{i}.intermediate.dense.bias""")							)
            rename_keys.append((f"""blocks.{i}.mlp.fc2.weight""", f"""deit.encoder.layer.{i}.output.dense.weight""")							)
            rename_keys.append((f"""blocks.{i}.mlp.fc2.bias""", f"""deit.encoder.layer.{i}.output.dense.bias""")							)

      # projection layer + position embeddings
      rename_keys.extend(
          [
              ("cls_token", "deit.embeddings.cls_token"),
              ("dist_token", "deit.embeddings.distillation_token"),
              ("patch_embed.proj.weight", "deit.embeddings.patch_embeddings.projection.weight"),
              ("patch_embed.proj.bias", "deit.embeddings.patch_embeddings.projection.bias"),
              ("pos_embed", "deit.embeddings.position_embeddings"),
          ]							)

      if base_model:
            # layernorm + pooler
            rename_keys.extend(
                [
                    ("norm.weight", "layernorm.weight"),
                    ("norm.bias", "layernorm.bias"),
                    ("pre_logits.fc.weight", "pooler.dense.weight"),
                    ("pre_logits.fc.bias", "pooler.dense.bias"),
                ]							)

            # if just the base model, we should remove "deit" from all keys that start with "deit"
            UpperCAmelCase__								=  [(pair[0], pair[1][4:]) if pair[1].startswith("deit"							) else pair for pair in rename_keys]
      else:
            # layernorm + classification heads
            rename_keys.extend(
                [
                    ("norm.weight", "deit.layernorm.weight"),
                    ("norm.bias", "deit.layernorm.bias"),
                    ("head.weight", "cls_classifier.weight"),
                    ("head.bias", "cls_classifier.bias"),
                    ("head_dist.weight", "distillation_classifier.weight"),
                    ("head_dist.bias", "distillation_classifier.bias"),
                ]							)

      return rename_keys




def        lowerCAmelCase_			(					__A,  __A,  __A=False							)					->    Tuple:







      '''simple docstring'''


      for i in range(config.num_hidden_layers							):
            if base_model:
                  UpperCAmelCase__								=  ""
            else:
                  UpperCAmelCase__								=  "deit."
            # read in weights + bias of input projection layer (in timm, this is a single matrix + bias)
            UpperCAmelCase__								=  state_dict.pop(f"""blocks.{i}.attn.qkv.weight"""							)
            UpperCAmelCase__								=  state_dict.pop(f"""blocks.{i}.attn.qkv.bias"""							)
            # next, add query, keys and values (in that order) to the state dict
            UpperCAmelCase__								=  in_proj_weight[
                : config.hidden_size, :
            ]
            UpperCAmelCase__								=  in_proj_bias[: config.hidden_size]
            UpperCAmelCase__								=  in_proj_weight[
                config.hidden_size : config.hidden_size * 2, :
            ]
            UpperCAmelCase__								=  in_proj_bias[
                config.hidden_size : config.hidden_size * 2
            ]
            UpperCAmelCase__								=  in_proj_weight[
                -config.hidden_size :, :
            ]
            UpperCAmelCase__								=  in_proj_bias[-config.hidden_size :]




def        lowerCAmelCase_			(					__A,  __A,  __A							)					->    Dict:







      '''simple docstring'''


      UpperCAmelCase__								=  dct.pop(__A							)
      UpperCAmelCase__								=  val




def        lowerCAmelCase_			(					)					->    Dict:







      '''simple docstring'''


      UpperCAmelCase__								=  "http://images.cocodataset.org/val2017/000000039769.jpg"
      UpperCAmelCase__								=  Image.open(requests.get(__A,  stream=__A							).raw							)
      return im




@torch.no_grad()
def        lowerCAmelCase_			(					__A,  __A							)					->    Optional[Any]:







      '''simple docstring'''


      UpperCAmelCase__								=  DeiTConfig()
      # all deit models have fine-tuned heads
      UpperCAmelCase__								=  False
      # dataset (fine-tuned on ImageNet 2012), patch_size and image_size
      UpperCAmelCase__								=  1_000
      UpperCAmelCase__								=  "huggingface/label-files"
      UpperCAmelCase__								=  "imagenet-1k-id2label.json"
      UpperCAmelCase__								=  json.load(open(hf_hub_download(__A,  __A,  repo_type="dataset"							),  "r"							)							)
      UpperCAmelCase__								=  {int(__A							): v for k, v in idalabel.items()}
      UpperCAmelCase__								=  idalabel
      UpperCAmelCase__								=  {v: k for k, v in idalabel.items()}
      UpperCAmelCase__								=  int(deit_name[-6:-4]							)
      UpperCAmelCase__								=  int(deit_name[-3:]							)
      # size of the architecture
      if deit_name[9:].startswith("tiny"							):
            UpperCAmelCase__								=  192
            UpperCAmelCase__								=  768
            UpperCAmelCase__								=  12
            UpperCAmelCase__								=  3
      elif deit_name[9:].startswith("small"							):
            UpperCAmelCase__								=  384
            UpperCAmelCase__								=  1_536
            UpperCAmelCase__								=  12
            UpperCAmelCase__								=  6
      if deit_name[9:].startswith("base"							):
            pass
      elif deit_name[4:].startswith("large"							):
            UpperCAmelCase__								=  1_024
            UpperCAmelCase__								=  4_096
            UpperCAmelCase__								=  24
            UpperCAmelCase__								=  16

      # load original model from timm
      UpperCAmelCase__								=  timm.create_model(__A,  pretrained=__A							)
      timm_model.eval()

      # load state_dict of original model, remove and rename some keys
      UpperCAmelCase__								=  timm_model.state_dict()
      UpperCAmelCase__								=  create_rename_keys(__A,  __A							)
      for src, dest in rename_keys:
            rename_key(__A,  __A,  __A							)
      read_in_q_k_v(__A,  __A,  __A							)

      # load HuggingFace model
      UpperCAmelCase__								=  DeiTForImageClassificationWithTeacher(__A							).eval()
      model.load_state_dict(__A							)

      # Check outputs on an image, prepared by DeiTImageProcessor
      UpperCAmelCase__								=  int(
          (256 / 224) * config.image_size							)  # to maintain same ratio w.r.t. 224 images, see https://github.com/facebookresearch/deit/blob/ab5715372db8c6cad5740714b2216d55aeae052e/datasets.py#L103
      UpperCAmelCase__								=  DeiTImageProcessor(size=__A,  crop_size=config.image_size							)
      UpperCAmelCase__								=  image_processor(images=prepare_img(),  return_tensors="pt"							)
      UpperCAmelCase__								=  encoding["pixel_values"]
      UpperCAmelCase__								=  model(__A							)

      UpperCAmelCase__								=  timm_model(__A							)
      assert timm_logits.shape == outputs.logits.shape
      assert torch.allclose(__A,  outputs.logits,  atol=1e-3							)

      Path(__A							).mkdir(exist_ok=__A							)
      print(f"""Saving model {deit_name} to {pytorch_dump_folder_path}"""							)
      model.save_pretrained(__A							)
      print(f"""Saving image processor to {pytorch_dump_folder_path}"""							)
      image_processor.save_pretrained(__A							)


if __name__ == "__main__":
      UpperCamelCase__    							= argparse.ArgumentParser()
      # Required parameters
      parser.add_argument(
          '--deit_name',
          default='vit_deit_base_distilled_patch16_224',
          type=str,
          help='Name of the DeiT 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.'
      )

      UpperCamelCase__    							= parser.parse_args()
      convert_deit_checkpoint(args.deit_name, args.pytorch_dump_folder_path)



