code: 
  
  
  from typing import TYPE_CHECKING
  
  from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
  
  
  UpperCamelCase__				       =			{'configuration_dinat': ['DINAT_PRETRAINED_CONFIG_ARCHIVE_MAP', 'DinatConfig']}
  
  
  try:
     if not is_torch_available():
        raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
     pass
  else:
     UpperCamelCase__				       =			[
         'DINAT_PRETRAINED_MODEL_ARCHIVE_LIST',
         'DinatForImageClassification',
         'DinatModel',
         'DinatPreTrainedModel',
         'DinatBackbone',
     ]
  
  if TYPE_CHECKING:
     from .configuration_dinat import DINAT_PRETRAINED_CONFIG_ARCHIVE_MAP, DinatConfig
  
     try:
        if not is_torch_available():
           raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
        pass
     else:
        from .modeling_dinat import (
            DINAT_PRETRAINED_MODEL_ARCHIVE_LIST,
            DinatBackbone,
            DinatForImageClassification,
            DinatModel,
            DinatPreTrainedModel,
        )
  
  else:
     import sys
  
     UpperCamelCase__				       =			_LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)
style_context: 
  
  
  import copy
  import fnmatch
  import json
  import os
  import pickle as pkl
  import shutil
  import sys
  import tarfile
  import tempfile
  from collections import OrderedDict
  from contextlib import contextmanager
  from functools import partial
  from hashlib import shaaaa
  from io import BytesIO
  from pathlib import Path
  from urllib.parse import urlparse
  from zipfile import ZipFile, is_zipfile
  
  import cva
  import numpy as np
  import requests
  import wget
  from filelock import FileLock
  from PIL import Image
  from tqdm.auto import tqdm
  from yaml import Loader, dump, load
  
  
  try:
     import torch
  
     UpperCamelCase__				       =			True
  except ImportError:
     UpperCamelCase__				       =			False
  
  
  try:
     from torch.hub import _get_torch_home
  
     UpperCamelCase__				       =			_get_torch_home()
  except ImportError:
     UpperCamelCase__				       =			os.path.expanduser(
         os.getenv('TORCH_HOME', os.path.join(os.getenv('XDG_CACHE_HOME', '~/.cache'), 'torch'))
     )
  
  UpperCamelCase__				       =			os.path.join(torch_cache_home, 'transformers')
  
  UpperCamelCase__				       =			'https://cdn.huggingface.co'
  UpperCamelCase__				       =			'https://s3.amazonaws.com/models.huggingface.co/bert'
  UpperCamelCase__				       =			'/'.join(str(Path(__file__).resolve()).split('/')[:-1])
  UpperCamelCase__				       =			os.path.join(PATH, 'config.yaml')
  UpperCamelCase__				       =			os.path.join(PATH, 'attributes.txt')
  UpperCamelCase__				       =			os.path.join(PATH, 'objects.txt')
  UpperCamelCase__				       =			os.getenv('PYTORCH_PRETRAINED_BERT_CACHE', default_cache_path)
  UpperCamelCase__				       =			os.getenv('PYTORCH_TRANSFORMERS_CACHE', PYTORCH_PRETRAINED_BERT_CACHE)
  UpperCamelCase__				       =			os.getenv('TRANSFORMERS_CACHE', PYTORCH_TRANSFORMERS_CACHE)
  UpperCamelCase__				       =			'pytorch_model.bin'
  UpperCamelCase__				       =			'config.yaml'
  
  def   UpperCamelCase__   (    UpperCAmelCase_=OBJECTS    ,     UpperCAmelCase_=ATTRIBUTES			)						->							Any:
  
  
  
  
         '''simple docstring'''
  
  
  
  
  
  
         _lowercase					:				Dict           =			[]
         with open(UpperCAmelCase_			) as f:
                for object in f.readlines():
                       vg_classes.append(object.split(''','''			)[0].lower().strip()			)
  
         _lowercase					:				str           =			[]
         with open(UpperCAmelCase_			) as f:
                for object in f.readlines():
                       vg_attrs.append(object.split(''','''			)[0].lower().strip()			)
         return vg_classes, vg_attrs
  
  def   UpperCamelCase__   (    UpperCAmelCase_			)						->							Union[str, Any]:
  
  
  
  
         '''simple docstring'''
  
  
  
  
  
  
         _lowercase					:				Optional[int]           =			OrderedDict()
         with open(UpperCAmelCase_    ,     '''rb'''			) as f:
                _lowercase					:				Union[str, Any]           =			pkl.load(UpperCAmelCase_			)['''model''']
         for k in copy.deepcopy(list(ckp.keys()			)			):
                _lowercase					:				Union[str, Any]           =			ckp.pop(UpperCAmelCase_			)
                if isinstance(UpperCAmelCase_    ,     np.ndarray			):
                       _lowercase					:				Dict           =			torch.tensor(UpperCAmelCase_			)
                else:
                       assert isinstance(UpperCAmelCase_    ,     torch.tensor			), type(UpperCAmelCase_			)
                _lowercase					:				Dict           =			v
         return r
  
  class 						UpperCAmelCase__   :
  
  
  
       '''simple docstring'''
       UpperCAmelCase_         =  {}
  
  
  
  
       def __init__( self       :       Union[str, Any]	,      UpperCamelCase       :       dict	,      UpperCamelCase       :       str = "root"	,      UpperCamelCase       :       Optional[int]=0		):
  
  
  
  
  
              """simple docstring"""
  
  
  
              _lowercase					:				Any           =			name
              _lowercase					:				Tuple           =			level
              _lowercase					:				str           =			{}
              for k, v in dictionary.items():
                     if v is None:
                            raise ValueError()
                     _lowercase					:				Union[str, Any]           =			copy.deepcopy(UpperCamelCase		)
                     _lowercase					:				List[Any]           =			copy.deepcopy(UpperCamelCase		)
                     if isinstance(UpperCamelCase	,      UpperCamelCase		):
                            _lowercase					:				Any           =			Config(UpperCamelCase	,      name=UpperCamelCase	,      level=level + 1		)
                     _lowercase					:				Tuple           =			v
                     setattr(self	,      UpperCamelCase	,      UpperCamelCase		)
  
              _lowercase					:				Union[str, Any]           =			d
  
  
  
  
       def __repr__( self       :       Tuple		):
  
  
  
  
  
              """simple docstring"""
  
  
  
              return str(list((self._pointer.keys())		)		)
  
  
  
  
       def __setattr__( self       :       Union[str, Any]	,      UpperCamelCase       :       Optional[Any]	,      UpperCamelCase       :       Tuple		):
  
  
  
  
  
              """simple docstring"""
  
  
  
              _lowercase					:				Any           =			val
              _lowercase					:				Optional[int]           =			val
              _lowercase					:				List[Any]           =			key.split('''.'''		)
              _lowercase					:				Dict           =			len(UpperCamelCase		) - 1
              _lowercase					:				Optional[Any]           =			self._pointer
              if len(UpperCamelCase		) > 1:
                     for i, l in enumerate(UpperCamelCase		):
                            if hasattr(self	,      UpperCamelCase		) and isinstance(getattr(self	,      UpperCamelCase		)	,      UpperCamelCase		):
                                   setattr(getattr(self	,      UpperCamelCase		)	,      '''.'''.join(levels[i:]		)	,      UpperCamelCase		)
                            if l == last_level:
                                   _lowercase					:				Union[str, Any]           =			val
                            else:
                                   _lowercase					:				Tuple           =			pointer[l]
  
  
  
  
       def   lowerCAmelCase_   ( self       :       int		):
  
  
  
  
  
              """simple docstring"""
  
  
  
              return self._pointer
  
  
  
  
       def   lowerCAmelCase_   ( self       :       Dict	,      UpperCamelCase       :       List[Any]	,      UpperCamelCase       :       int		):
  
  
  
  
  
              """simple docstring"""
  
  
  
              with open(F'{file_name}'	,      '''w'''		) as stream:
                     dump(UpperCamelCase	,      UpperCamelCase		)
  
  
  
  
       def   lowerCAmelCase_   ( self       :       int	,      UpperCamelCase       :       str	,      UpperCamelCase       :       Dict		):
  
  
  
  
  
              """simple docstring"""
  
  
  
              with open(F'{file_name}'	,      '''w'''		) as stream:
                     json.dump(UpperCamelCase	,      UpperCamelCase		)
  
  
  
  
       @staticmethod
       def   lowerCAmelCase_   ( UpperCamelCase       :       List[str]		):
  
  
  
  
  
              """simple docstring"""
  
  
  
              with open(UpperCamelCase		) as stream:
                     _lowercase					:				Union[str, Any]           =			load(UpperCamelCase	,      Loader=UpperCamelCase		)
              return data
  
  
  
  
       def __str__( self       :       int		):
  
  
  
  
  
              """simple docstring"""
  
  
  
              _lowercase					:				Dict           =			'''    '''
              if self._name != "root":
                     _lowercase					:				int           =			F'{t * (self._level-1)}{self._name}:\n'
              else:
                     _lowercase					:				int           =			''''''
              _lowercase					:				List[Any]           =			self._level
              for i, (k, v) in enumerate(self._pointer.items()		):
                     if isinstance(UpperCamelCase	,      UpperCamelCase		):
                            r += F'{t * (self._level)}{v}\n'
                            self._level += 1
                     else:
                            r += F'{t * (self._level)}{k}: {v} ({type(UpperCamelCase		).__name__})\n'
                     _lowercase					:				Any           =			level
              return r[:-1]
  
  
  
  
       @classmethod
       def   lowerCAmelCase_   ( cls       :       List[str]	,      UpperCamelCase       :       str	,      **UpperCamelCase       :       str		):
  
  
  
  
  
              """simple docstring"""
  
  
  
              _lowercase       ,	_lowercase					:				Dict           =			cls.get_config_dict(UpperCamelCase	,      **UpperCamelCase		)
              return cls(UpperCamelCase		)
  
  
  
  
       @classmethod
       def   lowerCAmelCase_   ( cls       :       List[str]	,      UpperCamelCase       :       str	,      **UpperCamelCase       :       int		):
  
  
  
  
  
              """simple docstring"""
  
  
  
              _lowercase					:				Any           =			kwargs.pop('''cache_dir'''	,      UpperCamelCase		)
              _lowercase					:				str           =			kwargs.pop('''force_download'''	,      UpperCamelCase		)
              _lowercase					:				List[Any]           =			kwargs.pop('''resume_download'''	,      UpperCamelCase		)
              _lowercase					:				str           =			kwargs.pop('''proxies'''	,      UpperCamelCase		)
              _lowercase					:				List[Any]           =			kwargs.pop('''local_files_only'''	,      UpperCamelCase		)
  
              if os.path.isdir(UpperCamelCase		):
                     _lowercase					:				List[Any]           =			os.path.join(UpperCamelCase	,      UpperCamelCase		)
              elif os.path.isfile(UpperCamelCase		) or is_remote_url(UpperCamelCase		):
                     _lowercase					:				Dict           =			pretrained_model_name_or_path
              else:
                     _lowercase					:				List[str]           =			hf_bucket_url(UpperCamelCase	,      filename=UpperCamelCase	,      use_cdn=UpperCamelCase		)
  
              try:
                     # Load from URL or cache if already cached
                     _lowercase					:				str           =			cached_path(
                         UpperCamelCase	,      cache_dir=UpperCamelCase	,      force_download=UpperCamelCase	,      proxies=UpperCamelCase	,      resume_download=UpperCamelCase	,      local_files_only=UpperCamelCase	,      )
                     # Load config dict
                     if resolved_config_file is None:
                            raise EnvironmentError
  
                     _lowercase					:				Dict           =			Config.load_yaml(UpperCamelCase		)
  
              except EnvironmentError:
                     _lowercase					:				Any           =			'''Can\'t load config for'''
                     raise EnvironmentError(UpperCamelCase		)
  
              if resolved_config_file == config_file:
                     print('''loading configuration file from path'''		)
              else:
                     print('''loading configuration file cache'''		)
  
              return Config.load_yaml(UpperCamelCase		), kwargs
  
  
  
  
  def   UpperCamelCase__   (    UpperCAmelCase_			)						->							Union[str, Any]:
  
  
  
  
         '''simple docstring'''
  
  
  
  
  
  
         _lowercase					:				Optional[Any]           =			torch.load('''dump.pt'''    ,     map_location=in_tensor.device			)
         _lowercase					:				Optional[Any]           =			in_tensor.numpy()
         _lowercase					:				Tuple           =			out_tensor.numpy()[0]
         print(na.shape    ,     na[0, 0, :5]			)
         print(na.shape    ,     na[0, 0, :5]			)
         assert np.allclose(UpperCAmelCase_    ,     UpperCAmelCase_    ,     rtol=0.01    ,     atol=0.1			), (
             F'{sum([1 for x in np.isclose(UpperCAmelCase_    ,     UpperCAmelCase_    ,     rtol=0.01    ,     atol=0.1			).flatten() if x is False]			)/len(na.flatten()			)*100:.4f} %'
             " element-wise mismatch"
         )
         raise Exception('''tensors are all good'''			)
  
         # Hugging face functions below
  
  def   UpperCamelCase__   (    UpperCAmelCase_			)						->							Optional[Any]:
  
  
  
  
         '''simple docstring'''
  
  
  
  
  
  
         _lowercase					:				Dict           =			urlparse(UpperCAmelCase_			)
         return parsed.scheme in ("http", "https")
  
  def   UpperCamelCase__   (    UpperCAmelCase_    ,     UpperCAmelCase_    ,     UpperCAmelCase_=True			)						->							str:
  
  
  
  
         '''simple docstring'''
  
  
  
  
  
  
         _lowercase					:				Tuple           =			CLOUDFRONT_DISTRIB_PREFIX if use_cdn else S3_BUCKET_PREFIX
         _lowercase					:				Optional[Any]           =			'''/''' not in model_id
         if legacy_format:
                return F'{endpoint}/{model_id}-{filename}'
         else:
                return F'{endpoint}/{model_id}/{filename}'
  
  def   UpperCamelCase__   (    UpperCAmelCase_    ,     UpperCAmelCase_    ,     UpperCAmelCase_=None    ,     UpperCAmelCase_=0    ,     UpperCAmelCase_=None    ,     )						->							int:
  
  
  
  
         '''simple docstring'''
  
  
  
  
  
  
         _lowercase					:				List[Any]           =			'''python/{}'''.format(sys.version.split()[0]			)
         if _torch_available:
                ua += "; torch/{}".format(torch.__version__			)
         if isinstance(UpperCAmelCase_    ,     UpperCAmelCase_			):
                ua += "; " + "; ".join('''{}/{}'''.format(UpperCAmelCase_    ,     UpperCAmelCase_			) for k, v in user_agent.items()			)
         elif isinstance(UpperCAmelCase_    ,     UpperCAmelCase_			):
                ua += "; " + user_agent
         _lowercase					:				Optional[Any]           =			{'''user-agent''': ua}
         if resume_size > 0:
                _lowercase					:				List[Any]           =			'''bytes=%d-''' % (resume_size,)
         _lowercase					:				str           =			requests.get(UpperCAmelCase_    ,     stream=UpperCAmelCase_    ,     proxies=UpperCAmelCase_    ,     headers=UpperCAmelCase_			)
         if response.status_code == 416:  # Range not satisfiable
                return
         _lowercase					:				List[Any]           =			response.headers.get('''Content-Length'''			)
         _lowercase					:				Optional[Any]           =			resume_size + int(UpperCAmelCase_			) if content_length is not None else None
         _lowercase					:				Optional[int]           =			tqdm(
             unit='''B'''    ,     unit_scale=UpperCAmelCase_    ,     total=UpperCAmelCase_    ,     initial=UpperCAmelCase_    ,     desc='''Downloading'''    ,     )
         for chunk in response.iter_content(chunk_size=1024			):
                if chunk:  # filter out keep-alive new chunks
                       progress.update(len(UpperCAmelCase_			)			)
                       temp_file.write(UpperCAmelCase_			)
         progress.close()
  
  def   UpperCamelCase__   (    UpperCAmelCase_    ,     UpperCAmelCase_=None    ,     UpperCAmelCase_=False    ,     UpperCAmelCase_=None    ,     UpperCAmelCase_=10    ,     UpperCAmelCase_=False    ,     UpperCAmelCase_=None    ,     UpperCAmelCase_=False    ,     )						->							List[str]:
  
  
  
  
         '''simple docstring'''
  
  
  
  
  
  
         if cache_dir is None:
                _lowercase					:				Dict           =			TRANSFORMERS_CACHE
         if isinstance(UpperCAmelCase_    ,     UpperCAmelCase_			):
                _lowercase					:				int           =			str(UpperCAmelCase_			)
  
         os.makedirs(UpperCAmelCase_    ,     exist_ok=UpperCAmelCase_			)
  
         _lowercase					:				Union[str, Any]           =			None
         if not local_files_only:
                try:
                       _lowercase					:				Union[str, Any]           =			requests.head(UpperCAmelCase_    ,     allow_redirects=UpperCAmelCase_    ,     proxies=UpperCAmelCase_    ,     timeout=UpperCAmelCase_			)
                       if response.status_code == 200:
                              _lowercase					:				Tuple           =			response.headers.get('''ETag'''			)
                except (EnvironmentError, requests.exceptions.Timeout):
                       # etag is already None
                       pass
  
         _lowercase					:				Any           =			url_to_filename(UpperCAmelCase_    ,     UpperCAmelCase_			)
  
         # get cache path to put the file
         _lowercase					:				Any           =			os.path.join(UpperCAmelCase_    ,     UpperCAmelCase_			)
  
         # etag is None = we don't have a connection, or url doesn't exist, or is otherwise inaccessible.
         # try to get the last downloaded one
         if etag is None:
                if os.path.exists(UpperCAmelCase_			):
                       return cache_path
                else:
                       _lowercase					:				Optional[Any]           =			[
                           file
                           for file in fnmatch.filter(os.listdir(UpperCAmelCase_			)    ,     filename + '''.*'''			)
                           if not file.endswith('''.json'''			) and not file.endswith('''.lock'''			)
                       ]
                       if len(UpperCAmelCase_			) > 0:
                              return os.path.join(UpperCAmelCase_    ,     matching_files[-1]			)
                       else:
                              # If files cannot be found and local_files_only=True,
                              # the models might've been found if local_files_only=False
                              # Notify the user about that
                              if local_files_only:
                                     raise ValueError(
                                         '''Cannot find the requested files in the cached path and outgoing traffic has been'''
                                         ''' disabled. To enable model look-ups and downloads online, set \'local_files_only\''''
                                         ''' to False.'''			)
                              return None
  
      # From now on, etag is not None.
         if os.path.exists(UpperCAmelCase_			) and not force_download:
                return cache_path
  
         # Prevent parallel downloads of the same file with a lock.
         _lowercase					:				List[str]           =			cache_path + '''.lock'''
         with FileLock(UpperCAmelCase_			):
                # If the download just completed while the lock was activated.
                if os.path.exists(UpperCAmelCase_			) and not force_download:
                       # Even if returning early like here, the lock will be released.
                       return cache_path
  
                if resume_download:
                       _lowercase					:				Dict           =			cache_path + '''.incomplete'''
  
                       @contextmanager
                       def _resumable_file_manager():
                              with open(UpperCAmelCase_    ,     '''a+b'''			) as f:
                                     yield f
  
                       _lowercase					:				str           =			_resumable_file_manager
                       if os.path.exists(UpperCAmelCase_			):
                              _lowercase					:				List[Any]           =			os.stat(UpperCAmelCase_			).st_size
                       else:
                              _lowercase					:				List[Any]           =			0
                else:
                       _lowercase					:				Optional[Any]           =			partial(tempfile.NamedTemporaryFile    ,     dir=UpperCAmelCase_    ,     delete=UpperCAmelCase_			)
                       _lowercase					:				List[str]           =			0
  
                # Download to temporary file, then copy to cache dir once finished.
                # Otherwise you get corrupt cache entries if the download gets interrupted.
                with temp_file_manager() as temp_file:
                       print(
                           '''%s not found in cache or force_download set to True, downloading to %s'''    ,     UpperCAmelCase_    ,     temp_file.name    ,     )
  
                       http_get(
                           UpperCAmelCase_    ,     UpperCAmelCase_    ,     proxies=UpperCAmelCase_    ,     resume_size=UpperCAmelCase_    ,     user_agent=UpperCAmelCase_    ,     )
  
                os.replace(temp_file.name    ,     UpperCAmelCase_			)
  
                _lowercase					:				int           =			{'''url''': url, '''etag''': etag}
                _lowercase					:				Union[str, Any]           =			cache_path + '''.json'''
                with open(UpperCAmelCase_    ,     '''w'''			) as meta_file:
                       json.dump(UpperCAmelCase_    ,     UpperCAmelCase_			)
  
         return cache_path
  
  def   UpperCamelCase__   (    UpperCAmelCase_    ,     UpperCAmelCase_=None			)						->							List[Any]:
  
  
  
  
         '''simple docstring'''
  
  
  
  
  
  
         _lowercase					:				Dict           =			url.encode('''utf-8'''			)
         _lowercase					:				List[str]           =			shaaaa(UpperCAmelCase_			)
         _lowercase					:				str           =			url_hash.hexdigest()
  
         if etag:
                _lowercase					:				Dict           =			etag.encode('''utf-8'''			)
                _lowercase					:				Tuple           =			shaaaa(UpperCAmelCase_			)
                filename += "." + etag_hash.hexdigest()
  
         if url.endswith('''.h5'''			):
                filename += ".h5"
  
         return filename
  
  def   UpperCamelCase__   (    UpperCAmelCase_    ,     UpperCAmelCase_=None    ,     UpperCAmelCase_=False    ,     UpperCAmelCase_=None    ,     UpperCAmelCase_=False    ,     UpperCAmelCase_=None    ,     UpperCAmelCase_=False    ,     UpperCAmelCase_=False    ,     UpperCAmelCase_=False    ,     )						->							int:
  
  
  
  
         '''simple docstring'''
  
  
  
  
  
  
         if cache_dir is None:
                _lowercase					:				Union[str, Any]           =			TRANSFORMERS_CACHE
         if isinstance(UpperCAmelCase_    ,     UpperCAmelCase_			):
                _lowercase					:				Tuple           =			str(UpperCAmelCase_			)
         if isinstance(UpperCAmelCase_    ,     UpperCAmelCase_			):
                _lowercase					:				List[str]           =			str(UpperCAmelCase_			)
  
         if is_remote_url(UpperCAmelCase_			):
                # URL, so get it from the cache (downloading if necessary)
                _lowercase					:				Union[str, Any]           =			get_from_cache(
                    UpperCAmelCase_    ,     cache_dir=UpperCAmelCase_    ,     force_download=UpperCAmelCase_    ,     proxies=UpperCAmelCase_    ,     resume_download=UpperCAmelCase_    ,     user_agent=UpperCAmelCase_    ,     local_files_only=UpperCAmelCase_    ,     )
         elif os.path.exists(UpperCAmelCase_			):
                # File, and it exists.
                _lowercase					:				str           =			url_or_filename
         elif urlparse(UpperCAmelCase_			).scheme == "":
                # File, but it doesn't exist.
                raise EnvironmentError('''file {} not found'''.format(UpperCAmelCase_			)			)
         else:
                # Something unknown
                raise ValueError('''unable to parse {} as a URL or as a local path'''.format(UpperCAmelCase_			)			)
  
         if extract_compressed_file:
                if not is_zipfile(UpperCAmelCase_			) and not tarfile.is_tarfile(UpperCAmelCase_			):
                       return output_path
  
                # Path where we extract compressed archives
                # We avoid '.' in dir name and add "-extracted" at the end: "./model.zip" => "./model-zip-extracted/"
                _lowercase       ,	_lowercase					:				Any           =			os.path.split(UpperCAmelCase_			)
                _lowercase					:				str           =			output_file.replace('''.'''    ,     '''-'''			) + '''-extracted'''
                _lowercase					:				Union[str, Any]           =			os.path.join(UpperCAmelCase_    ,     UpperCAmelCase_			)
  
                if os.path.isdir(UpperCAmelCase_			) and os.listdir(UpperCAmelCase_			) and not force_extract:
                       return output_path_extracted
  
                # Prevent parallel extractions
                _lowercase					:				Union[str, Any]           =			output_path + '''.lock'''
                with FileLock(UpperCAmelCase_			):
                       shutil.rmtree(UpperCAmelCase_    ,     ignore_errors=UpperCAmelCase_			)
                       os.makedirs(UpperCAmelCase_			)
                       if is_zipfile(UpperCAmelCase_			):
                              with ZipFile(UpperCAmelCase_    ,     '''r'''			) as zip_file:
                                     zip_file.extractall(UpperCAmelCase_			)
                                     zip_file.close()
                       elif tarfile.is_tarfile(UpperCAmelCase_			):
                              _lowercase					:				Dict           =			tarfile.open(UpperCAmelCase_			)
                              tar_file.extractall(UpperCAmelCase_			)
                              tar_file.close()
                       else:
                              raise EnvironmentError('''Archive format of {} could not be identified'''.format(UpperCAmelCase_			)			)
  
                return output_path_extracted
  
         return output_path
  
  def   UpperCamelCase__   (    UpperCAmelCase_    ,     UpperCAmelCase_=","			)						->							Union[str, Any]:
  
  
  
  
         '''simple docstring'''
  
  
  
  
  
  
         assert isinstance(UpperCAmelCase_    ,     UpperCAmelCase_			)
         if os.path.isfile(UpperCAmelCase_			):
                with open(UpperCAmelCase_			) as f:
                       _lowercase					:				Any           =			eval(f.read()			)
         else:
                _lowercase					:				Tuple           =			requests.get(UpperCAmelCase_			)
                try:
                       _lowercase					:				List[str]           =			requests.json()
                except Exception:
                       _lowercase					:				List[Any]           =			req.content.decode()
                       assert data is not None, "could not connect"
                       try:
                              _lowercase					:				Dict           =			eval(UpperCAmelCase_			)
                       except Exception:
                              _lowercase					:				Any           =			data.split('''\n'''			)
                req.close()
         return data
  
  def   UpperCamelCase__   (    UpperCAmelCase_			)						->							str:
  
  
  
  
         '''simple docstring'''
  
  
  
  
  
  
         _lowercase					:				List[Any]           =			requests.get(UpperCAmelCase_			)
         _lowercase					:				Optional[Any]           =			np.array(Image.open(BytesIO(response.content			)			)			)
         return img
  
  def   UpperCamelCase__   (    UpperCAmelCase_			)						->							Optional[int]:
  
  
  
  
         '''simple docstring'''
  
  
  
  
  
  
         _lowercase					:				Dict           =			url.split('''/'''			)[-1]
         if fn not in os.listdir(os.getcwd()			):
                wget.download(UpperCAmelCase_			)
         with open(UpperCAmelCase_    ,     '''rb'''			) as stream:
                _lowercase					:				List[str]           =			pkl.load(UpperCAmelCase_			)
         _lowercase					:				str           =			weights.pop('''model'''			)
         _lowercase					:				Optional[int]           =			{}
         for k, v in model.items():
                _lowercase					:				str           =			torch.from_numpy(UpperCAmelCase_			)
                if "running_var" in k:
                       _lowercase					:				List[Any]           =			torch.tensor([0]			)
                       _lowercase					:				Union[str, Any]           =			k.replace('''running_var'''    ,     '''num_batches_tracked'''			)
                       _lowercase					:				List[Any]           =			zero
         return new
  
  def   UpperCamelCase__   (    )						->							int:
  
  
  
  
         '''simple docstring'''
  
  
  
  
  
  
         print(F'{os.path.abspath(os.path.join(UpperCAmelCase_    ,     os.pardir			)			)}/demo.ipynb'			)
  
  def   UpperCamelCase__   (    UpperCAmelCase_    ,     UpperCAmelCase_="RGB"			)						->							List[str]:
  
  
  
  
         '''simple docstring'''
  
  
  
  
  
  
         assert isinstance(UpperCAmelCase_    ,     UpperCAmelCase_			)
         if os.path.isfile(UpperCAmelCase_			):
                _lowercase					:				Any           =			cva.imread(UpperCAmelCase_			)
         else:
                _lowercase					:				Optional[int]           =			get_image_from_url(UpperCAmelCase_			)
                assert img is not None, F'could not connect to: {im}'
         _lowercase					:				List[Any]           =			cva.cvtColor(UpperCAmelCase_    ,     cva.COLOR_BGR2RGB			)
         if input_format == "RGB":
                _lowercase					:				Optional[int]           =			img[:, :, ::-1]
         return img
  
  
  
  
  
  
  
  def   UpperCamelCase__   (    UpperCAmelCase_    ,     UpperCAmelCase_=1			)						->							Dict:
  
  
  
  
         '''simple docstring'''
  
  
  
  
  
  
         return (images[i : i + batch] for i in range(0    ,     len(UpperCAmelCase_			)    ,     UpperCAmelCase_			))