


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


snake_case__				:	List[Any]					       =					get_logger(__name__)





class   SCREAMING_SNAKE_CASE_			:




       '''simple docstring'''



       def __init__(						self				:				Any		,				__a				:				Optional[str] = None							)					->Any:
          lowerCamelCase_						:   int		= (
              os.path.join(__a		,				config.EXTRACTED_DATASETS_DIR							) if cache_dir else config.EXTRACTED_DATASETS_PATH
          )
          lowerCamelCase_						:   Optional[Any]		= Extractor



       def 				_lowerCAmelCase							(						self				:				Tuple		,				__a				:				str							)					->str:
          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"
          lowerCamelCase_						:   List[Any]		= os.path.abspath(__a							)
          return os.path.join(self.extract_dir		,				hash_url_to_filename(__a							)							)



       def 				_lowerCAmelCase							(						self				:				Optional[int]		,				__a				:				str		,				__a				:				bool							)					->bool:
          return force_extract or (
              not os.path.isfile(__a							) and not (os.path.isdir(__a							) and os.listdir(__a							))
          )




       def 				_lowerCAmelCase							(						self				:				str		,				__a				:				str		,				__a				:				bool = False							)					->str:
          lowerCamelCase_						:   Optional[int]		= self.extractor.infer_extractor_format(__a							)
          if not extractor_format:
             return input_path
          lowerCamelCase_						:   Any		= self._get_output_path(__a							)
          if self._do_extract(__a		,				__a							):
             self.extractor.extract(__a		,				__a		,				__a							)
          return output_path







class   SCREAMING_SNAKE_CASE_			(a__						):




       '''simple docstring'''



       @classmethod
       @abstractmethod
       def 				_lowerCAmelCase							(						cls				:				Dict		,				__a				:				Union[Path, str]		,				**__a				:				Optional[int]							)					->bool:
          ...




       @staticmethod
       @abstractmethod
       def 				_lowerCAmelCase							(						__a				:				Union[Path, str]		,				__a				:				Union[Path, str]							)					->None:
          ...







class   SCREAMING_SNAKE_CASE_			(a__						,       a__						):




       '''simple docstring'''



       _a   							=							[]



       @staticmethod
       def 				_lowerCAmelCase							(						__a				:				Union[Path, str]		,				__a				:				int							)					->List[str]:
          with open(__a		,				"""rb"""							) as f:
             return f.read(__a							)




       @classmethod
       def 				_lowerCAmelCase							(						cls				:				str		,				__a				:				Union[Path, str]		,				__a				:				bytes = b""							)					->bool:
          if not magic_number:
             lowerCamelCase_						:   Dict		= max(len(__a							) for cls_magic_number in cls.magic_numbers							)
             try:
                lowerCamelCase_						:   Optional[Any]		= cls.read_magic_number(__a		,				__a							)
             except OSError:
                return False
          return any(magic_number.startswith(__a							) for cls_magic_number in cls.magic_numbers							)







class   SCREAMING_SNAKE_CASE_			(a__						):




       '''simple docstring'''



       @classmethod
       def 				_lowerCAmelCase							(						cls				:				Tuple		,				__a				:				Union[Path, str]		,				**__a				:				Any							)					->bool:
          return tarfile.is_tarfile(__a							)



       @staticmethod
       def 				_lowerCAmelCase							(						__a				:				Any		,				__a				:				str							)					->Union[str, Any]:

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

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

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

          lowerCamelCase_						:   Union[str, Any]		= resolved(__a							)

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




       @staticmethod
       def 				_lowerCAmelCase							(						__a				:				Union[Path, str]		,				__a				:				Union[Path, str]							)					->None:
          os.makedirs(__a		,				exist_ok=__a							)
          lowerCamelCase_						:   List[Any]		= tarfile.open(__a							)
          tar_file.extractall(__a		,				members=TarExtractor.safemembers(__a		,				__a							)							)
          tar_file.close()







class   SCREAMING_SNAKE_CASE_			(a__						):




       '''simple docstring'''



       _a   							=							[b"\x1F\x8B"]



       @staticmethod
       def 				_lowerCAmelCase							(						__a				:				Union[Path, str]		,				__a				:				Union[Path, str]							)					->None:
          with gzip.open(__a		,				"""rb"""							) as gzip_file:
             with open(__a		,				"""wb"""							) as extracted_file:
                shutil.copyfileobj(__a		,				__a							)







class   SCREAMING_SNAKE_CASE_			(a__						):




       '''simple docstring'''



       _a   							=							[
           b"PK\x03\x04",
           b"PK\x05\x06",  # empty archive
           b"PK\x07\x08",  # spanned archive
       ]



       @classmethod
       def 				_lowerCAmelCase							(						cls				:				Tuple		,				__a				:				Union[Path, str]		,				__a				:				bytes = b""							)					->bool:
          if super().is_extractable(__a		,				magic_number=__a							):
             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(__a		,				"""rb"""							) as fp:
                lowerCamelCase_						:   int		= _EndRecData(__a							)
                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:
                         lowerCamelCase_						:   Optional[Any]		= fp.read(__a							)  # CD is where we expect it to be
                         if len(__a							) == sizeCentralDir:
                            lowerCamelCase_						:   Optional[Any]		= struct.unpack(__a		,				__a							)  # 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 				_lowerCAmelCase							(						__a				:				Union[Path, str]		,				__a				:				Union[Path, str]							)					->None:
          os.makedirs(__a		,				exist_ok=__a							)
          with zipfile.ZipFile(__a		,				"""r"""							) as zip_file:
             zip_file.extractall(__a							)
             zip_file.close()







class   SCREAMING_SNAKE_CASE_			(a__						):




       '''simple docstring'''



       _a   							=							[b"\xFD\x37\x7A\x58\x5A\x00"]



       @staticmethod
       def 				_lowerCAmelCase							(						__a				:				Union[Path, str]		,				__a				:				Union[Path, str]							)					->None:
          with lzma.open(__a							) as compressed_file:
             with open(__a		,				"""wb"""							) as extracted_file:
                shutil.copyfileobj(__a		,				__a							)







class   SCREAMING_SNAKE_CASE_			(a__						):




       '''simple docstring'''



       _a   							=							[b"Rar!\x1a\x07\x00", b"Rar!\x1a\x07\x01\x00"]  # RAR_ID  # RAR5_ID



       @staticmethod
       def 				_lowerCAmelCase							(						__a				:				Union[Path, str]		,				__a				:				Union[Path, str]							)					->None:
          if not config.RARFILE_AVAILABLE:
             raise ImportError("""Please pip install rarfile"""							)
          import rarfile

          os.makedirs(__a		,				exist_ok=__a							)
          lowerCamelCase_						:   Optional[int]		= rarfile.RarFile(__a							)
          rf.extractall(__a							)
          rf.close()







class   SCREAMING_SNAKE_CASE_			(a__						):




       '''simple docstring'''



       _a   							=							[b"\x28\xb5\x2F\xFD"]



       @staticmethod
       def 				_lowerCAmelCase							(						__a				:				Union[Path, str]		,				__a				:				Union[Path, str]							)					->None:
          if not config.ZSTANDARD_AVAILABLE:
             raise ImportError("""Please pip install zstandard"""							)
          import zstandard as zstd

          lowerCamelCase_						:   str		= zstd.ZstdDecompressor()
          with open(__a		,				"""rb"""							) as ifh, open(__a		,				"""wb"""							) as ofh:
             dctx.copy_stream(__a		,				__a							)







class   SCREAMING_SNAKE_CASE_			(a__						):




       '''simple docstring'''



       _a   							=							[b"\x42\x5A\x68"]



       @staticmethod
       def 				_lowerCAmelCase							(						__a				:				Union[Path, str]		,				__a				:				Union[Path, str]							)					->None:
          with bza.open(__a		,				"""rb"""							) as compressed_file:
             with open(__a		,				"""wb"""							) as extracted_file:
                shutil.copyfileobj(__a		,				__a							)







class   SCREAMING_SNAKE_CASE_			(a__						):




       '''simple docstring'''



       _a   							=							[b"\x37\x7A\xBC\xAF\x27\x1C"]



       @staticmethod
       def 				_lowerCAmelCase							(						__a				:				Union[Path, str]		,				__a				:				Union[Path, str]							)					->None:
          if not config.PY7ZR_AVAILABLE:
             raise ImportError("""Please pip install py7zr"""							)
          import pyazr

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







class   SCREAMING_SNAKE_CASE_			(a__						):




       '''simple docstring'''



       _a   							=							[b"\x04\x22\x4D\x18"]



       @staticmethod
       def 				_lowerCAmelCase							(						__a				:				Union[Path, str]		,				__a				:				Union[Path, str]							)					->None:
          if not config.LZ4_AVAILABLE:
             raise ImportError("""Please pip install lz4"""							)
          import lza.frame

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







class   SCREAMING_SNAKE_CASE_			:




       '''simple docstring'''



       _a   							=							{
           "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 				_lowerCAmelCase							(						cls				:				List[str]							)					->Any:
          return max(
              len(__a							)
              for extractor in cls.extractors.values()
              if issubclass(__a		,				__a							)
              for extractor_magic_number in extractor.magic_numbers							)



       @staticmethod
       def 				_lowerCAmelCase							(						__a				:				Union[Path, str]		,				__a				:				int							)					->Dict:
          try:
             return MagicNumberBaseExtractor.read_magic_number(__a		,				magic_number_length=__a							)
          except OSError:
             return b""



       @classmethod
       def 				_lowerCAmelCase							(						cls				:				str		,				__a				:				Union[Path, str]		,				__a				:				bool = False							)					->bool:
          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=__a		,				)
          lowerCamelCase_						:   int		= cls.infer_extractor_format(__a							)
          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 				_lowerCAmelCase							(						cls				:				int		,				__a				:				Union[Path, str]							)					->str:  # <Added version="2.4.0"/>
          lowerCamelCase_						:   List[Any]		= cls._get_magic_number_max_length()
          lowerCamelCase_						:   str		= cls._read_magic_number(__a		,				__a							)
          for extractor_format, extractor in cls.extractors.items():
             if extractor.is_extractable(__a		,				magic_number=__a							):
                return extractor_format




       @classmethod
       def 				_lowerCAmelCase							(						cls				:				Dict		,				__a				:				Union[Path, str]		,				__a				:				Union[Path, str]		,				__a				:				Optional[str] = None		,				__a				:				Optional[BaseExtractor] = "deprecated"		,				)					->None:
          os.makedirs(os.path.dirname(__a							)		,				exist_ok=__a							)
          # Prevent parallel extractions
          lowerCamelCase_						:   List[str]		= str(Path(__a							).with_suffix(""".lock"""							)							)
          with FileLock(__a							):
             shutil.rmtree(__a		,				ignore_errors=__a							)
             if extractor_format or extractor != "deprecated":
                if extractor != "deprecated" or not isinstance(__a		,				__a							):  # 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=__a		,				)
                   lowerCamelCase_						:   List[Any]		= extractor if extractor != """deprecated""" else extractor_format
                else:
                   lowerCamelCase_						:   List[str]		= cls.extractors[extractor_format]
                return extractor.extract(__a		,				__a							)
             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=__a		,				)
                for extractor in cls.extractors.values():
                   if extractor.is_extractable(__a							):
                      return extractor.extract(__a		,				__a							)









import argparse
import json
from pathlib import Path

import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from timm import create_model
from timm.data import resolve_data_config
from timm.data.transforms_factory import create_transform

from transformers import BitConfig, BitForImageClassification, BitImageProcessor
from transformers.image_utils import PILImageResampling
from transformers.utils import logging


logging.set_verbosity_info()
snake_case__				:	Dict					       =					logging.get_logger(__name__)


def    __lowerCamelCase   (      A__						: Optional[Any]					)     ->    List[str]:
   lowerCamelCase_						:   int		= """huggingface/label-files"""
   lowerCamelCase_						:   Dict		= """imagenet-1k-id2label.json"""
   lowerCamelCase_						:   Optional[Any]		= json.load(open(hf_hub_download(A__						,						A__						,						repo_type="""dataset"""					)						,						"""r"""					)					)
   lowerCamelCase_						:   str		= {int(A__					): v for k, v in idalabel.items()}
   lowerCamelCase_						:   List[Any]		= {v: k for k, v in idalabel.items()}

   lowerCamelCase_						:   str		= """std_conv""" if """bit""" in model_name else False

   # note that when using BiT as backbone for ViT-hybrid checkpoints,
   # one needs to additionally set config.layer_type = "bottleneck", config.stem_type = "same",
   # config.conv_layer = "std_conv_same"
   lowerCamelCase_						:   Optional[Any]		= BitConfig(
       conv_layer=A__						,						num_labels=1000						,						idalabel=A__						,						labelaid=A__						,						)

   return config


def    __lowerCamelCase   (      A__						: str					)     ->    Any:
   if "stem.conv" in name:
      lowerCamelCase_						:   Any		= name.replace("""stem.conv"""						,						"""bit.embedder.convolution"""					)
   if "blocks" in name:
      lowerCamelCase_						:   Dict		= name.replace("""blocks"""						,						"""layers"""					)
   if "head.fc" in name:
      lowerCamelCase_						:   Optional[Any]		= name.replace("""head.fc"""						,						"""classifier.1"""					)
   if name.startswith("""norm"""					):
      lowerCamelCase_						:   int		= """bit.""" + name
   if "bit" not in name and "classifier" not in name:
      lowerCamelCase_						:   str		= """bit.encoder.""" + name

   return name


def    __lowerCamelCase   (      )     ->    List[Any]:
   lowerCamelCase_						:   List[Any]		= """http://images.cocodataset.org/val2017/000000039769.jpg"""
   lowerCamelCase_						:   Optional[Any]		= Image.open(requests.get(A__						,						stream=A__					).raw					)
   return im


@torch.no_grad()
def    __lowerCamelCase   (      A__						: List[Any]						,						A__						: List[str]						,						A__						: Tuple=False					)     ->    List[str]:
   lowerCamelCase_						:   Optional[Any]		= get_config(A__					)

   # load original model from timm
   lowerCamelCase_						:   Optional[Any]		= create_model(A__						,						pretrained=A__					)
   timm_model.eval()

   # load state_dict of original model
   lowerCamelCase_						:   Optional[int]		= timm_model.state_dict()
   for key in state_dict.copy().keys():
      lowerCamelCase_						:   int		= state_dict.pop(A__					)
      lowerCamelCase_						:   Union[str, Any]		= val.squeeze() if """head""" in key else val

   # load HuggingFace model
   lowerCamelCase_						:   Tuple		= BitForImageClassification(A__					)
   model.eval()
   model.load_state_dict(A__					)

   # create image processor
   lowerCamelCase_						:   Optional[Any]		= create_transform(**resolve_data_config({}						,						model=A__					)					)
   lowerCamelCase_						:   List[Any]		= transform.transforms

   lowerCamelCase_						:   List[Any]		= {
       """bilinear""": PILImageResampling.BILINEAR,
       """bicubic""": PILImageResampling.BICUBIC,
       """nearest""": PILImageResampling.NEAREST,
   }

   lowerCamelCase_						:   List[str]		= BitImageProcessor(
       do_resize=A__						,						size={"""shortest_edge""": timm_transforms[0].size}						,						resample=pillow_resamplings[timm_transforms[0].interpolation.value]						,						do_center_crop=A__						,						crop_size={"""height""": timm_transforms[1].size[0], """width""": timm_transforms[1].size[1]}						,						do_normalize=A__						,						image_mean=timm_transforms[-1].mean.tolist()						,						image_std=timm_transforms[-1].std.tolist()						,						)

   lowerCamelCase_						:   int		= prepare_img()
   lowerCamelCase_						:   int		= transform(A__					).unsqueeze(0					)
   lowerCamelCase_						:   List[str]		= processor(A__						,						return_tensors="""pt"""					).pixel_values

   # verify pixel values
   assert torch.allclose(A__						,						A__					)

   # verify logits
   with torch.no_grad():
      lowerCamelCase_						:   str		= model(A__					)
      lowerCamelCase_						:   int		= outputs.logits

   print("""Logits:"""						,						logits[0, :3]					)
   print("""Predicted class:"""						,						model.config.idalabel[logits.argmax(-1					).item()]					)
   lowerCamelCase_						:   List[Any]		= timm_model(A__					)
   assert timm_logits.shape == outputs.logits.shape
   assert torch.allclose(A__						,						outputs.logits						,						atol=1e-3					)
   print("""Looks ok!"""					)

   if pytorch_dump_folder_path is not None:
      Path(A__					).mkdir(exist_ok=A__					)
      print(f'''Saving model {model_name} and processor to {pytorch_dump_folder_path}'''					)
      model.save_pretrained(A__					)
      processor.save_pretrained(A__					)

   if push_to_hub:
      print(f'''Pushing model {model_name} and processor to the hub'''					)
      model.push_to_hub(f'''ybelkada/{model_name}'''					)
      processor.push_to_hub(f'''ybelkada/{model_name}'''					)


if __name__ == "__main__":
      snake_case__				:	Dict					       =					argparse.ArgumentParser()
      # Required parameters
      parser.add_argument(
          '--model_name',
          default='resnetv2_50x1_bitm',
          type=str,
          help='Name of the BiT 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.'
      )
      parser.add_argument(
          '--push_to_hub',
          action='store_true',
          help='Whether to push the model to the hub.',
      )

      snake_case__				:	int					       =					parser.parse_args()
      convert_bit_checkpoint(args.model_name, args.pytorch_dump_folder_path, args.push_to_hub)





