code: 
  
  
  
  
  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
  
   __snake_case							      =						True
  except ImportError:
   __snake_case							      =						False
  
  
  try:
   from torch.hub import _get_torch_home
  
   __snake_case							      =						_get_torch_home()
  except ImportError:
   __snake_case							      =						os.path.expanduser(
       os.getenv("""TORCH_HOME""", os.path.join(os.getenv("""XDG_CACHE_HOME""", """~/.cache"""), """torch"""))
   )
  
  __snake_case							      =						os.path.join(torch_cache_home, """transformers""")
  
  __snake_case							      =						"""https://cdn.huggingface.co"""
  __snake_case							      =						"""https://s3.amazonaws.com/models.huggingface.co/bert"""
  __snake_case							      =						"""/""".join(str(Path(__file__).resolve()).split("""/""")[:-1])
  __snake_case							      =						os.path.join(PATH, """config.yaml""")
  __snake_case							      =						os.path.join(PATH, """attributes.txt""")
  __snake_case							      =						os.path.join(PATH, """objects.txt""")
  __snake_case							      =						os.getenv("""PYTORCH_PRETRAINED_BERT_CACHE""", default_cache_path)
  __snake_case							      =						os.getenv("""PYTORCH_TRANSFORMERS_CACHE""", PYTORCH_PRETRAINED_BERT_CACHE)
  __snake_case							      =						os.getenv("""TRANSFORMERS_CACHE""", PYTORCH_TRANSFORMERS_CACHE)
  __snake_case							      =						"""pytorch_model.bin"""
  __snake_case							      =						"""config.yaml"""
  
  
  def 						_A     (       SCREAMING_SNAKE_CASE__						:			Tuple=OBJECTS  ,						SCREAMING_SNAKE_CASE__						:			Dict=ATTRIBUTES ):
      UpperCamelCase :Tuple										=     []
      with open(__lowerCamelCase ) as f:
          for object in f.readlines():
              vg_classes.append(object.split(''',''' )[0].lower().strip() )
  
      UpperCamelCase :str										=     []
      with open(__lowerCamelCase ) as f:
          for object in f.readlines():
              vg_attrs.append(object.split(''',''' )[0].lower().strip() )
      return vg_classes, vg_attrs
  
  
  def 						_A     (       SCREAMING_SNAKE_CASE__						:			str ):
      UpperCamelCase :List[Any]										=     OrderedDict()
      with open(__lowerCamelCase  ,						'''rb''' ) as f:
          UpperCamelCase :Optional[int]										=     pkl.load(__lowerCamelCase )["""model"""]
      for k in copy.deepcopy(list(ckp.keys() ) ):
          UpperCamelCase :Any										=     ckp.pop(__lowerCamelCase )
          if isinstance(__lowerCamelCase  ,						np.ndarray ):
              UpperCamelCase :str										=     torch.tensor(__lowerCamelCase )
          else:
              assert isinstance(__lowerCamelCase  ,						torch.tensor ), type(__lowerCamelCase )
          UpperCamelCase :Optional[Any]										=     v
      return r
  
  
  
  
  
  
  
  class     UpperCAmelCase_		:
  
  
  
        """simple docstring"""
        UpperCamelCase_       :      Union[str, Any]     ={}
        def __init__(       self					,       SCREAMING_SNAKE_CASE_					,       SCREAMING_SNAKE_CASE_ = "root"					,       SCREAMING_SNAKE_CASE_=0				)       ->   Union[str, Any]:
            UpperCamelCase :Dict										=     name
            UpperCamelCase :str										=     level
            UpperCamelCase :List[str]										=     {}
            for k, v in dictionary.items():
                if v is None:
                    raise ValueError()
                UpperCamelCase :Any										=     copy.deepcopy(_lowerCAmelCase				)
                UpperCamelCase :Optional[Any]										=     copy.deepcopy(_lowerCAmelCase				)
                if isinstance(_lowerCAmelCase					,       _lowerCAmelCase				):
                    UpperCamelCase :int										=     Config(_lowerCAmelCase					,       name=_lowerCAmelCase					,       level=level + 1				)
                UpperCamelCase :str										=     v
                setattr(self					,       _lowerCAmelCase					,       _lowerCAmelCase				)
  
            UpperCamelCase :List[Any]										=     d
        def __repr__(       self				)       ->   Union[str, Any]:
            return str(list((self._pointer.keys())				)				)
        def __setattr__(       self					,       SCREAMING_SNAKE_CASE_					,       SCREAMING_SNAKE_CASE_				)       ->   Union[str, Any]:
            UpperCamelCase :Any										=     val
            UpperCamelCase :Dict										=     val
            UpperCamelCase :str										=     key.split('''.'''				)
            UpperCamelCase :Optional[Any]										=     len(_lowerCAmelCase				) - 1
            UpperCamelCase :List[Any]										=     self._pointer
            if len(_lowerCAmelCase				) > 1:
                for i, l in enumerate(_lowerCAmelCase				):
                    if hasattr(self					,       _lowerCAmelCase				) and isinstance(getattr(self					,       _lowerCAmelCase				)					,       _lowerCAmelCase				):
                        setattr(getattr(self					,       _lowerCAmelCase				)					,       '''.'''.join(levels[i:]				)					,       _lowerCAmelCase				)
                    if l == last_level:
                        UpperCamelCase :Tuple										=     val
                    else:
                        UpperCamelCase :str										=     pointer[l]
        def 					UpperCAmelCase		(       self				)       ->   Optional[int]:
            return self._pointer
        def 					UpperCAmelCase		(       self					,       SCREAMING_SNAKE_CASE_					,       SCREAMING_SNAKE_CASE_				)       ->   Union[str, Any]:
            with open(F'''{file_name}'''					,       '''w'''				) as stream:
                dump(_lowerCAmelCase					,       _lowerCAmelCase				)
        def 					UpperCAmelCase		(       self					,       SCREAMING_SNAKE_CASE_					,       SCREAMING_SNAKE_CASE_				)       ->   Optional[Any]:
            with open(F'''{file_name}'''					,       '''w'''				) as stream:
                json.dump(_lowerCAmelCase					,       _lowerCAmelCase				)
        @staticmethod
        def 					UpperCAmelCase		(       SCREAMING_SNAKE_CASE_				)       ->   int:
            with open(_lowerCAmelCase				) as stream:
                UpperCamelCase :Union[str, Any]										=     load(_lowerCAmelCase					,       Loader=_lowerCAmelCase				)
            return data
        def __str__(       self				)       ->   Any:
            UpperCamelCase :str										=     """    """
            if self._name != "root":
                UpperCamelCase :List[Any]										=     F'''{t * (self._level-1)}{self._name}:\n'''
            else:
                UpperCamelCase :str										=     """"""
            UpperCamelCase :str										=     self._level
            for i, (k, v) in enumerate(self._pointer.items()				):
                if isinstance(_lowerCAmelCase					,       _lowerCAmelCase				):
                    r += F'''{t * (self._level)}{v}\n'''
                    self._level += 1
                else:
                    r += F'''{t * (self._level)}{k}: {v} ({type(_lowerCAmelCase				).__name__})\n'''
                UpperCamelCase :Union[str, Any]										=     level
            return r[:-1]
        @classmethod
        def 					UpperCAmelCase		(       cls					,       SCREAMING_SNAKE_CASE_					,       **SCREAMING_SNAKE_CASE_				)       ->   int:
            UpperCamelCase :Tuple										=     cls.get_config_dict(_lowerCAmelCase					,       **_lowerCAmelCase				)
            return cls(_lowerCAmelCase				)
  
  
  
  
        @classmethod
        def 					UpperCAmelCase		(       cls					,       SCREAMING_SNAKE_CASE_					,       **SCREAMING_SNAKE_CASE_				)       ->   Optional[int]:
            UpperCamelCase :List[Any]										=     kwargs.pop('''cache_dir'''					,       _lowerCAmelCase				)
            UpperCamelCase :Tuple										=     kwargs.pop('''force_download'''					,       _lowerCAmelCase				)
            UpperCamelCase :List[Any]										=     kwargs.pop('''resume_download'''					,       _lowerCAmelCase				)
            UpperCamelCase :Optional[Any]										=     kwargs.pop('''proxies'''					,       _lowerCAmelCase				)
            UpperCamelCase :Tuple										=     kwargs.pop('''local_files_only'''					,       _lowerCAmelCase				)
  
            if os.path.isdir(_lowerCAmelCase				):
                UpperCamelCase :Any										=     os.path.join(_lowerCAmelCase					,       _lowerCAmelCase				)
            elif os.path.isfile(_lowerCAmelCase				) or is_remote_url(_lowerCAmelCase				):
                UpperCamelCase :List[Any]										=     pretrained_model_name_or_path
            else:
                UpperCamelCase :List[str]										=     hf_bucket_url(_lowerCAmelCase					,       filename=_lowerCAmelCase					,       use_cdn=_lowerCAmelCase				)
  
            try:
                # Load from URL or cache if already cached
                UpperCamelCase :List[Any]										=     cached_path(
                    _lowerCAmelCase					,       cache_dir=_lowerCAmelCase					,       force_download=_lowerCAmelCase					,       proxies=_lowerCAmelCase					,       resume_download=_lowerCAmelCase					,       local_files_only=_lowerCAmelCase					,       )
                # Load config dict
                if resolved_config_file is None:
                    raise EnvironmentError
  
                UpperCamelCase :Union[str, Any]										=     Config.load_yaml(_lowerCAmelCase				)
  
            except EnvironmentError:
                UpperCamelCase :Optional[Any]										=     """Can't load config for"""
                raise EnvironmentError(_lowerCAmelCase				)
  
            if resolved_config_file == config_file:
                print('''loading configuration file from path'''				)
            else:
                print('''loading configuration file cache'''				)
  
            return Config.load_yaml(_lowerCAmelCase				), kwargs
  
  
  
  
  
  
  
  def 						_A     (       SCREAMING_SNAKE_CASE__						:			Tuple ):
      UpperCamelCase :List[Any]										=     torch.load('''dump.pt'''  ,						map_location=in_tensor.device )
      UpperCamelCase :Tuple										=     in_tensor.numpy()
      UpperCamelCase :Optional[Any]										=     out_tensor.numpy()[0]
      print(na.shape  ,						na[0, 0, :5] )
      print(na.shape  ,						na[0, 0, :5] )
      assert np.allclose(__lowerCamelCase  ,						__lowerCamelCase  ,						rtol=0.01  ,						atol=0.1 ), (
          F'''{sum([1 for x in np.isclose(__lowerCamelCase  ,						__lowerCamelCase  ,						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 						_A     (       SCREAMING_SNAKE_CASE__						:			Dict ):
      UpperCamelCase :Tuple										=     urlparse(__lowerCamelCase )
      return parsed.scheme in ("http", "https")
  
  
  def 						_A     (       SCREAMING_SNAKE_CASE__						:			Optional[Any]  ,						SCREAMING_SNAKE_CASE__						:			int  ,						SCREAMING_SNAKE_CASE__						:			List[Any]=True ):
      UpperCamelCase :Optional[int]										=     CLOUDFRONT_DISTRIB_PREFIX if use_cdn else S3_BUCKET_PREFIX
      UpperCamelCase :Optional[int]										=     """/""" not in model_id
      if legacy_format:
          return F'''{endpoint}/{model_id}-{filename}'''
      else:
          return F'''{endpoint}/{model_id}/{filename}'''
  
  
  def 						_A     (       SCREAMING_SNAKE_CASE__						:			int  ,						SCREAMING_SNAKE_CASE__						:			Union[str, Any]  ,						SCREAMING_SNAKE_CASE__						:			str=None  ,						SCREAMING_SNAKE_CASE__						:			Tuple=0  ,						SCREAMING_SNAKE_CASE__						:			str=None  ,						):
      UpperCamelCase :Dict										=     """python/{}""".format(sys.version.split()[0] )
      if _torch_available:
          ua += "; torch/{}".format(torch.__version__ )
      if isinstance(__lowerCamelCase  ,						__lowerCamelCase ):
          ua += "; " + "; ".join('''{}/{}'''.format(__lowerCamelCase  ,						__lowerCamelCase ) for k, v in user_agent.items() )
      elif isinstance(__lowerCamelCase  ,						__lowerCamelCase ):
          ua += "; " + user_agent
      UpperCamelCase :Any										=     {"""user-agent""": ua}
      if resume_size > 0:
          UpperCamelCase :Union[str, Any]										=     """bytes=%d-""" % (resume_size,)
      UpperCamelCase :str										=     requests.get(__lowerCamelCase  ,						stream=__lowerCamelCase  ,						proxies=__lowerCamelCase  ,						headers=__lowerCamelCase )
      if response.status_code == 416:  # Range not satisfiable
          return
      UpperCamelCase :int										=     response.headers.get('''Content-Length''' )
      UpperCamelCase :List[str]										=     resume_size + int(__lowerCamelCase ) if content_length is not None else None
      UpperCamelCase :Tuple										=     tqdm(
          unit='''B'''  ,						unit_scale=__lowerCamelCase  ,						total=__lowerCamelCase  ,						initial=__lowerCamelCase  ,						desc='''Downloading'''  ,						)
      for chunk in response.iter_content(chunk_size=1024 ):
          if chunk:  # filter out keep-alive new chunks
              progress.update(len(__lowerCamelCase ) )
              temp_file.write(__lowerCamelCase )
      progress.close()
  
  
  def 						_A     (       SCREAMING_SNAKE_CASE__						:			Union[str, Any]  ,						SCREAMING_SNAKE_CASE__						:			List[str]=None  ,						SCREAMING_SNAKE_CASE__						:			List[Any]=False  ,						SCREAMING_SNAKE_CASE__						:			Dict=None  ,						SCREAMING_SNAKE_CASE__						:			List[str]=10  ,						SCREAMING_SNAKE_CASE__						:			str=False  ,						SCREAMING_SNAKE_CASE__						:			List[Any]=None  ,						SCREAMING_SNAKE_CASE__						:			List[str]=False  ,						):
      if cache_dir is None:
          UpperCamelCase :Optional[Any]										=     TRANSFORMERS_CACHE
      if isinstance(__lowerCamelCase  ,						__lowerCamelCase ):
          UpperCamelCase :Union[str, Any]										=     str(__lowerCamelCase )
  
      os.makedirs(__lowerCamelCase  ,						exist_ok=__lowerCamelCase )
  
      UpperCamelCase :Any										=     None
      if not local_files_only:
          try:
              UpperCamelCase :Optional[int]										=     requests.head(__lowerCamelCase  ,						allow_redirects=__lowerCamelCase  ,						proxies=__lowerCamelCase  ,						timeout=__lowerCamelCase )
              if response.status_code == 200:
                  UpperCamelCase :Union[str, Any]										=     response.headers.get('''ETag''' )
          except (EnvironmentError, requests.exceptions.Timeout):
              # etag is already None
              pass
  
      UpperCamelCase :str										=     url_to_filename(__lowerCamelCase  ,						__lowerCamelCase )
  
      # get cache path to put the file
      UpperCamelCase :Tuple										=     os.path.join(__lowerCamelCase  ,						__lowerCamelCase )
  
      # 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(__lowerCamelCase ):
              return cache_path
          else:
              UpperCamelCase :List[Any]										=     [
                  file
                  for file in fnmatch.filter(os.listdir(__lowerCamelCase )  ,						filename + '''.*''' )
                  if not file.endswith('''.json''' ) and not file.endswith('''.lock''' )
              ]
              if len(__lowerCamelCase ) > 0:
                  return os.path.join(__lowerCamelCase  ,						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(__lowerCamelCase ) and not force_download:
          return cache_path
  
      # Prevent parallel downloads of the same file with a lock.
      UpperCamelCase :Dict										=     cache_path + """.lock"""
      with FileLock(__lowerCamelCase ):
          # If the download just completed while the lock was activated.
          if os.path.exists(__lowerCamelCase ) and not force_download:
              # Even if returning early like here, the lock will be released.
              return cache_path
  
          if resume_download:
              UpperCamelCase :Union[str, Any]										=     cache_path + """.incomplete"""
  
              @contextmanager
              def _resumable_file_manager():
                  with open(__lowerCamelCase  ,						'''a+b''' ) as f:
                      yield f
  
              UpperCamelCase :Any										=     _resumable_file_manager
              if os.path.exists(__lowerCamelCase ):
                  UpperCamelCase :str										=     os.stat(__lowerCamelCase ).st_size
              else:
                  UpperCamelCase :Any										=     0
          else:
              UpperCamelCase :Optional[Any]										=     partial(tempfile.NamedTemporaryFile  ,						dir=__lowerCamelCase  ,						delete=__lowerCamelCase )
              UpperCamelCase :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'''  ,						__lowerCamelCase  ,						temp_file.name  ,						)
  
              http_get(
                  __lowerCamelCase  ,						__lowerCamelCase  ,						proxies=__lowerCamelCase  ,						resume_size=__lowerCamelCase  ,						user_agent=__lowerCamelCase  ,						)
  
          os.replace(temp_file.name  ,						__lowerCamelCase )
  
          UpperCamelCase :Optional[int]										=     {"""url""": url, """etag""": etag}
          UpperCamelCase :Any										=     cache_path + """.json"""
          with open(__lowerCamelCase  ,						'''w''' ) as meta_file:
              json.dump(__lowerCamelCase  ,						__lowerCamelCase )
  
      return cache_path
  
  
  def 						_A     (       SCREAMING_SNAKE_CASE__						:			Tuple  ,						SCREAMING_SNAKE_CASE__						:			Tuple=None ):
      UpperCamelCase :List[Any]										=     url.encode('''utf-8''' )
      UpperCamelCase :List[str]										=     shaaaa(__lowerCamelCase )
      UpperCamelCase :Optional[Any]										=     url_hash.hexdigest()
  
      if etag:
          UpperCamelCase :Optional[int]										=     etag.encode('''utf-8''' )
          UpperCamelCase :Dict										=     shaaaa(__lowerCamelCase )
          filename += "." + etag_hash.hexdigest()
  
      if url.endswith('''.h5''' ):
          filename += ".h5"
  
      return filename
  
  
  def 						_A     (       SCREAMING_SNAKE_CASE__						:			Tuple  ,						SCREAMING_SNAKE_CASE__						:			Optional[int]=None  ,						SCREAMING_SNAKE_CASE__						:			List[str]=False  ,						SCREAMING_SNAKE_CASE__						:			Dict=None  ,						SCREAMING_SNAKE_CASE__						:			int=False  ,						SCREAMING_SNAKE_CASE__						:			Dict=None  ,						SCREAMING_SNAKE_CASE__						:			Any=False  ,						SCREAMING_SNAKE_CASE__						:			Optional[Any]=False  ,						SCREAMING_SNAKE_CASE__						:			Optional[int]=False  ,						):
      if cache_dir is None:
          UpperCamelCase :List[str]										=     TRANSFORMERS_CACHE
      if isinstance(__lowerCamelCase  ,						__lowerCamelCase ):
          UpperCamelCase :Optional[Any]										=     str(__lowerCamelCase )
      if isinstance(__lowerCamelCase  ,						__lowerCamelCase ):
          UpperCamelCase :int										=     str(__lowerCamelCase )
  
      if is_remote_url(__lowerCamelCase ):
          # URL, so get it from the cache (downloading if necessary)
          UpperCamelCase :Tuple										=     get_from_cache(
              __lowerCamelCase  ,						cache_dir=__lowerCamelCase  ,						force_download=__lowerCamelCase  ,						proxies=__lowerCamelCase  ,						resume_download=__lowerCamelCase  ,						user_agent=__lowerCamelCase  ,						local_files_only=__lowerCamelCase  ,						)
      elif os.path.exists(__lowerCamelCase ):
          # File, and it exists.
          UpperCamelCase :List[Any]										=     url_or_filename
      elif urlparse(__lowerCamelCase ).scheme == "":
          # File, but it doesn't exist.
          raise EnvironmentError('''file {} not found'''.format(__lowerCamelCase ) )
      else:
          # Something unknown
          raise ValueError('''unable to parse {} as a URL or as a local path'''.format(__lowerCamelCase ) )
  
      if extract_compressed_file:
          if not is_zipfile(__lowerCamelCase ) and not tarfile.is_tarfile(__lowerCamelCase ):
              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/"
          UpperCamelCase :Optional[int]										=     os.path.split(__lowerCamelCase )
          UpperCamelCase :Any										=     output_file.replace('''.'''  ,						'''-''' ) + """-extracted"""
          UpperCamelCase :Dict										=     os.path.join(__lowerCamelCase  ,						__lowerCamelCase )
  
          if os.path.isdir(__lowerCamelCase ) and os.listdir(__lowerCamelCase ) and not force_extract:
              return output_path_extracted
  
          # Prevent parallel extractions
          UpperCamelCase :List[Any]										=     output_path + """.lock"""
          with FileLock(__lowerCamelCase ):
              shutil.rmtree(__lowerCamelCase  ,						ignore_errors=__lowerCamelCase )
              os.makedirs(__lowerCamelCase )
              if is_zipfile(__lowerCamelCase ):
                  with ZipFile(__lowerCamelCase  ,						'''r''' ) as zip_file:
                      zip_file.extractall(__lowerCamelCase )
                      zip_file.close()
              elif tarfile.is_tarfile(__lowerCamelCase ):
                  UpperCamelCase :Optional[int]										=     tarfile.open(__lowerCamelCase )
                  tar_file.extractall(__lowerCamelCase )
                  tar_file.close()
              else:
                  raise EnvironmentError('''Archive format of {} could not be identified'''.format(__lowerCamelCase ) )
  
          return output_path_extracted
  
      return output_path
  
  
  def 						_A     (       SCREAMING_SNAKE_CASE__						:			int  ,						SCREAMING_SNAKE_CASE__						:			int="," ):
      assert isinstance(__lowerCamelCase  ,						__lowerCamelCase )
      if os.path.isfile(__lowerCamelCase ):
          with open(__lowerCamelCase ) as f:
              UpperCamelCase :Any										=     eval(f.read() )
      else:
          UpperCamelCase :Any										=     requests.get(__lowerCamelCase )
          try:
              UpperCamelCase :Union[str, Any]										=     requests.json()
          except Exception:
              UpperCamelCase :Optional[Any]										=     req.content.decode()
              assert data is not None, "could not connect"
              try:
                  UpperCamelCase :Union[str, Any]										=     eval(__lowerCamelCase )
              except Exception:
                  UpperCamelCase :int										=     data.split('''\n''' )
          req.close()
      return data
  
  
  def 						_A     (       SCREAMING_SNAKE_CASE__						:			Optional[Any] ):
      UpperCamelCase :Optional[int]										=     requests.get(__lowerCamelCase )
      UpperCamelCase :Tuple										=     np.array(Image.open(BytesIO(response.content ) ) )
      return img
  
  
  def 						_A     (       SCREAMING_SNAKE_CASE__						:			str ):
      UpperCamelCase :str										=     url.split('''/''' )[-1]
      if fn not in os.listdir(os.getcwd() ):
          wget.download(__lowerCamelCase )
      with open(__lowerCamelCase  ,						'''rb''' ) as stream:
          UpperCamelCase :Union[str, Any]										=     pkl.load(__lowerCamelCase )
      UpperCamelCase :int										=     weights.pop('''model''' )
      UpperCamelCase :Any										=     {}
      for k, v in model.items():
          UpperCamelCase :Tuple										=     torch.from_numpy(__lowerCamelCase )
          if "running_var" in k:
              UpperCamelCase :Tuple										=     torch.tensor([0] )
              UpperCamelCase :List[Any]										=     k.replace('''running_var'''  ,						'''num_batches_tracked''' )
              UpperCamelCase :Tuple										=     zero
      return new
  
  
  def 						_A     (       ):
      print(F'''{os.path.abspath(os.path.join(__lowerCamelCase  ,						os.pardir ) )}/demo.ipynb''' )
  
  
  def 						_A     (       SCREAMING_SNAKE_CASE__						:			Any  ,						SCREAMING_SNAKE_CASE__						:			int="RGB" ):
      assert isinstance(__lowerCamelCase  ,						__lowerCamelCase )
      if os.path.isfile(__lowerCamelCase ):
          UpperCamelCase :Any										=     cva.imread(__lowerCamelCase )
      else:
          UpperCamelCase :Dict										=     get_image_from_url(__lowerCamelCase )
          assert img is not None, F'''could not connect to: {im}'''
      UpperCamelCase :Dict										=     cva.cvtColor(__lowerCamelCase  ,						cva.COLOR_BGR2RGB )
      if input_format == "RGB":
          UpperCamelCase :Tuple										=     img[:, :, ::-1]
      return img
  
  
  
  def 						_A     (       SCREAMING_SNAKE_CASE__						:			int  ,						SCREAMING_SNAKE_CASE__						:			Any=1 ):
      return (images[i : i + batch] for i in range(0  ,						len(__lowerCamelCase )  ,						__lowerCamelCase ))
  
  
  
  
  
  
style_context: 
  
  
  
  
  
  
  from __future__ import annotations
  
  from typing import Generic, TypeVar
  
  __snake_case							      =						TypeVar("""T""")
  
  
  
  
  
  
  
  class     UpperCAmelCase_		(      lowercase				):
  
  
  
        """simple docstring"""
        pass
  
  
  
  
  
  
  
  class     UpperCAmelCase_		(      lowercase				):
  
  
  
        """simple docstring"""
        pass
  
  
  
  
  
  
  
  class     UpperCAmelCase_		(      Generic[T]				):
  
  
  
        """simple docstring"""
        def __init__(       self					,       SCREAMING_SNAKE_CASE_ = 10				)       ->   List[str]:
            UpperCamelCase :list[T]										=     []
            UpperCamelCase :Any										=     limit
        def __bool__(       self				)       ->   bool:
            return bool(self.stack				)
        def __str__(       self				)       ->   str:
            return str(self.stack				)
        def 					UpperCAmelCase		(       self					,       SCREAMING_SNAKE_CASE_				)       ->   None:
            if len(self.stack				) >= self.limit:
                raise StackOverflowError
            self.stack.append(SCREAMING_SNAKE_CASE_				)
        def 					UpperCAmelCase		(       self				)       ->   T:
            if not self.stack:
                raise StackUnderflowError
            return self.stack.pop()
        def 					UpperCAmelCase		(       self				)       ->   T:
            if not self.stack:
                raise StackUnderflowError
            return self.stack[-1]
        def 					UpperCAmelCase		(       self				)       ->   bool:
            return not bool(self.stack				)
        def 					UpperCAmelCase		(       self				)       ->   bool:
            return self.size() == self.limit
        def 					UpperCAmelCase		(       self				)       ->   int:
            return len(self.stack				)
  
  
  
  
        def __contains__(       self					,       SCREAMING_SNAKE_CASE_				)       ->   bool:
            return item in self.stack
  
  
  
  
  
  
  
  def 						_A     (       ):
      UpperCamelCase :Stack[int]										=     Stack(10 )
      assert bool(SCREAMING_SNAKE_CASE__ ) is False
      assert stack.is_empty() is True
      assert stack.is_full() is False
      assert str(SCREAMING_SNAKE_CASE__ ) == "[]"
  
      try:
          UpperCamelCase :Optional[int]										=     stack.pop()
          raise AssertionError  # This should not happen
      except StackUnderflowError:
          assert True  # This should happen
  
      try:
          UpperCamelCase :Union[str, Any]										=     stack.peek()
          raise AssertionError  # This should not happen
      except StackUnderflowError:
          assert True  # This should happen
  
      for i in range(10 ):
          assert stack.size() == i
          stack.push(SCREAMING_SNAKE_CASE__ )
  
      assert bool(SCREAMING_SNAKE_CASE__ )
      assert not stack.is_empty()
      assert stack.is_full()
      assert str(SCREAMING_SNAKE_CASE__ ) == str(list(range(10 ) ) )
      assert stack.pop() == 9
      assert stack.peek() == 8
  
      stack.push(100 )
      assert str(SCREAMING_SNAKE_CASE__ ) == str([0, 1, 2, 3, 4, 5, 6, 7, 8, 100] )
  
      try:
          stack.push(200 )
          raise AssertionError  # This should not happen
      except StackOverflowError:
          assert True  # This should happen
  
      assert not stack.is_empty()
      assert stack.size() == 10
  
      assert 5 in stack
      assert 55 not in stack
  
  
  if __name__ == "__main__":
   test_stack()
  
  
  
  
  
  