'''simple docstring'''





from __future__ import annotations

import math




class 	__A				:



    def __init__(self   :   str       ,      __a   :   int			):
         UpperCAmelCase_	   =       size
         # approximate the overall size of segment tree with given value
         UpperCAmelCase_	   =       [0 for i in range(0       ,      4 * size			)]
         # create array to store lazy update
         UpperCAmelCase_	   =       [0 for i in range(0       ,      4 * size			)]
         UpperCAmelCase_	   =       [0 for i in range(0       ,      4 * size			)]  # flag for lazy update



    def  _lowercase						(self   :   Optional[Any]       ,      __a   :   int			):
         return idx * 2



    def  _lowercase						(self   :   Union[str, Any]       ,      __a   :   int			):
         return idx * 2 + 1



    def  _lowercase						(self   :   Any       ,      __a   :   int       ,      __a   :   int       ,      __a   :   int       ,      __a   :   list[int]			):
         if left_element == right_element:
              UpperCAmelCase_	   =       a[left_element - 1]
         else:
              UpperCAmelCase_	   =       (left_element + right_element) // 2
              self.build(self.left(__a			)       ,      __a       ,      __a       ,      __a			)
              self.build(self.right(__a			)       ,      mid + 1       ,      __a       ,      __a			)
              UpperCAmelCase_	   =       max(
                  self.segment_tree[self.left(__a			)]       ,      self.segment_tree[self.right(__a			)]			)



    def  _lowercase						(self   :   List[Any]       ,      __a   :   int       ,      __a   :   int       ,      __a   :   int       ,      __a   :   int       ,      __a   :   int       ,      __a   :   int			):
         if self.flag[idx] is True:
              UpperCAmelCase_	   =       self.lazy[idx]
              UpperCAmelCase_	   =       False
              if left_element != right_element:
                   UpperCAmelCase_	   =       self.lazy[idx]
                   UpperCAmelCase_	   =       self.lazy[idx]
                   UpperCAmelCase_	   =       True
                   UpperCAmelCase_	   =       True

         if right_element < a or left_element > b:
              return True
         if left_element >= a and right_element <= b:
              UpperCAmelCase_	   =       val
              if left_element != right_element:
                   UpperCAmelCase_	   =       val
                   UpperCAmelCase_	   =       val
                   UpperCAmelCase_	   =       True
                   UpperCAmelCase_	   =       True
              return True
         UpperCAmelCase_	   =       (left_element + right_element) // 2
         self.update(self.left(__a			)       ,      __a       ,      __a       ,      __a       ,      __a       ,      __a			)
         self.update(self.right(__a			)       ,      mid + 1       ,      __a       ,      __a       ,      __a       ,      __a			)
         UpperCAmelCase_	   =       max(
             self.segment_tree[self.left(__a			)]       ,      self.segment_tree[self.right(__a			)]			)
         return True



    def  _lowercase						(self   :   int       ,      __a   :   int       ,      __a   :   int       ,      __a   :   int       ,      __a   :   int       ,      __a   :   int			):
         if self.flag[idx] is True:
              UpperCAmelCase_	   =       self.lazy[idx]
              UpperCAmelCase_	   =       False
              if left_element != right_element:
                   UpperCAmelCase_	   =       self.lazy[idx]
                   UpperCAmelCase_	   =       self.lazy[idx]
                   UpperCAmelCase_	   =       True
                   UpperCAmelCase_	   =       True
         if right_element < a or left_element > b:
              return -math.inf
         if left_element >= a and right_element <= b:
              return self.segment_tree[idx]
         UpperCAmelCase_	   =       (left_element + right_element) // 2
         UpperCAmelCase_	   =       self.query(self.left(__a			)       ,      __a       ,      __a       ,      __a       ,      __a			)
         UpperCAmelCase_	   =       self.query(self.right(__a			)       ,      mid + 1       ,      __a       ,      __a       ,      __a			)
         return max(__a       ,      __a			)






    def __str__(self   :   List[Any]			):
         return str([self.query(1       ,      1       ,      self.size       ,      __a       ,      __a			) for i in range(1       ,      self.size + 1			)]			)


if __name__ == "__main__":
    SCREAMING_SNAKE_CASE_:					str  =[1, 2, -4, 7, 3, -5, 6, 11, -20, 9, 14, 15, 5, 2, -8]
    SCREAMING_SNAKE_CASE_:					str  =15
    SCREAMING_SNAKE_CASE_:					Any  =SegmentTree(size)
    segt.build(1, 1, size, A)
    print(segt.query(1, 1, size, 4, 6))
    print(segt.query(1, 1, size, 7, 11))
    print(segt.query(1, 1, size, 7, 12))
    segt.update(1, 1, size, 1, 3, 1_11)
    print(segt.query(1, 1, size, 1, 15))
    segt.update(1, 1, size, 7, 8, 2_35)
    print(segt)





'''simple docstring'''





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

    SCREAMING_SNAKE_CASE_:					Dict  =True
except ImportError:
    SCREAMING_SNAKE_CASE_:					str  =False


try:
    from torch.hub import _get_torch_home

    SCREAMING_SNAKE_CASE_:					Optional[Any]  =_get_torch_home()
except ImportError:
    SCREAMING_SNAKE_CASE_:					Union[str, Any]  =os.path.expanduser(
        os.getenv('TORCH_HOME', os.path.join(os.getenv('XDG_CACHE_HOME', '~/.cache'), 'torch'))
    )

SCREAMING_SNAKE_CASE_:					int  =os.path.join(torch_cache_home, 'transformers')

SCREAMING_SNAKE_CASE_:					Tuple  ='https://cdn.huggingface.co'
SCREAMING_SNAKE_CASE_:					str  ='https://s3.amazonaws.com/models.huggingface.co/bert'
SCREAMING_SNAKE_CASE_:					str  ='/'.join(str(Path(__file__).resolve()).split('/')[:-1])
SCREAMING_SNAKE_CASE_:					Optional[Any]  =os.path.join(PATH, 'config.yaml')
SCREAMING_SNAKE_CASE_:					Optional[Any]  =os.path.join(PATH, 'attributes.txt')
SCREAMING_SNAKE_CASE_:					Any  =os.path.join(PATH, 'objects.txt')
SCREAMING_SNAKE_CASE_:					Optional[int]  =os.getenv('PYTORCH_PRETRAINED_BERT_CACHE', default_cache_path)
SCREAMING_SNAKE_CASE_:					int  =os.getenv('PYTORCH_TRANSFORMERS_CACHE', PYTORCH_PRETRAINED_BERT_CACHE)
SCREAMING_SNAKE_CASE_:					List[str]  =os.getenv('TRANSFORMERS_CACHE', PYTORCH_TRANSFORMERS_CACHE)
SCREAMING_SNAKE_CASE_:					str  ='pytorch_model.bin'
SCREAMING_SNAKE_CASE_:					Dict  ='config.yaml'





def      lowerCAmelCase_    ( snake_case_	:			Optional[int]=OBJECTS ,   snake_case_	:			Optional[Any]=ATTRIBUTES      )   ->				Any:


     '''simple docstring'''




     UpperCAmelCase_	   =       []
     with open(snake_case_      ) as f:
          for object in f.readlines():
               vg_classes.append(object.split(","      )[0].lower().strip()      )

     UpperCAmelCase_	   =       []
     with open(snake_case_      ) as f:
          for object in f.readlines():
               vg_attrs.append(object.split(","      )[0].lower().strip()      )
     return vg_classes, vg_attrs





def      lowerCAmelCase_    ( snake_case_	:			Optional[int]      )   ->				List[str]:


     '''simple docstring'''




     UpperCAmelCase_	   =       OrderedDict()
     with open(snake_case_ ,   "rb"      ) as f:
          UpperCAmelCase_	   =       pkl.load(snake_case_      )["model"]
     for k in copy.deepcopy(list(ckp.keys()      )      ):
          UpperCAmelCase_	   =       ckp.pop(snake_case_      )
          if isinstance(snake_case_ ,   np.ndarray      ):
               UpperCAmelCase_	   =       torch.tensor(snake_case_      )
          else:
               assert isinstance(snake_case_ ,   torch.tensor      ), type(snake_case_      )
          UpperCAmelCase_	   =       v
     return r




class 	__A				:
    a__	:						Optional[Any]	       =  {}



    def __init__(self   :   Union[str, Any]       ,      __a   :   dict       ,      __a   :   str = "root"       ,      __a   :   str=0			):
         UpperCAmelCase_	   =       name
         UpperCAmelCase_	   =       level
         UpperCAmelCase_	   =       {}
         for k, v in dictionary.items():
              if v is None:
                   raise ValueError()
              UpperCAmelCase_	   =       copy.deepcopy(__a			)
              UpperCAmelCase_	   =       copy.deepcopy(__a			)
              if isinstance(__a       ,      __a			):
                   UpperCAmelCase_	   =       Config(__a       ,      name=__a       ,      level=level + 1			)
              UpperCAmelCase_	   =       v
              setattr(self       ,      __a       ,      __a			)

         UpperCAmelCase_	   =       d



    def __repr__(self   :   List[Any]			):
         return str(list((self._pointer.keys())			)			)



    def __setattr__(self   :   int       ,      __a   :   str       ,      __a   :   Dict			):
         UpperCAmelCase_	   =       val
         UpperCAmelCase_	   =       val
         UpperCAmelCase_	   =       key.split("."			)
         UpperCAmelCase_	   =       len(__a			) - 1
         UpperCAmelCase_	   =       self._pointer
         if len(__a			) > 1:
              for i, l in enumerate(__a			):
                   if hasattr(self       ,      __a			) and isinstance(getattr(self       ,      __a			)       ,      __a			):
                        setattr(getattr(self       ,      __a			)       ,      ".".join(levels[i:]			)       ,      __a			)
                   if l == last_level:
                        UpperCAmelCase_	   =       val
                   else:
                        UpperCAmelCase_	   =       pointer[l]



    def  _lowercase						(self   :   Optional[Any]			):
         return self._pointer



    def  _lowercase						(self   :   int       ,      __a   :   Union[str, Any]       ,      __a   :   str			):
         with open(f"""{file_name}"""       ,      "w"			) as stream:
              dump(__a       ,      __a			)



    def  _lowercase						(self   :   Any       ,      __a   :   Optional[Any]       ,      __a   :   List[str]			):
         with open(f"""{file_name}"""       ,      "w"			) as stream:
              json.dump(__a       ,      __a			)



    @staticmethod
    def  _lowercase						(__a   :   str			):
         with open(__a			) as stream:
              UpperCAmelCase_	   =       load(__a       ,      Loader=__a			)
         return data



    def __str__(self   :   Dict			):
         UpperCAmelCase_	   =       "    "
         if self._name != "root":
              UpperCAmelCase_	   =       f"""{t * (self._level-1)}{self._name}:\n"""
         else:
              UpperCAmelCase_	   =       ""
         UpperCAmelCase_	   =       self._level
         for i, (k, v) in enumerate(self._pointer.items()			):
              if isinstance(__a       ,      __a			):
                   r += f"""{t * (self._level)}{v}\n"""
                   self._level += 1
              else:
                   r += f"""{t * (self._level)}{k}: {v} ({type(__a			).__name__})\n"""
              UpperCAmelCase_	   =       level
         return r[:-1]



    @classmethod
    def  _lowercase						(cls   :   Tuple       ,      __a   :   str       ,      **__a   :   Dict			):
         UpperCAmelCase_   ,			UpperCAmelCase_	   =       cls.get_config_dict(__a       ,      **__a			)
         return cls(__a			)






    @classmethod
    def  _lowercase						(cls   :   Any       ,      __a   :   str       ,      **__a   :   Dict			):
         UpperCAmelCase_	   =       kwargs.pop("cache_dir"       ,      __a			)
         UpperCAmelCase_	   =       kwargs.pop("force_download"       ,      __a			)
         UpperCAmelCase_	   =       kwargs.pop("resume_download"       ,      __a			)
         UpperCAmelCase_	   =       kwargs.pop("proxies"       ,      __a			)
         UpperCAmelCase_	   =       kwargs.pop("local_files_only"       ,      __a			)

         if os.path.isdir(__a			):
              UpperCAmelCase_	   =       os.path.join(__a       ,      __a			)
         elif os.path.isfile(__a			) or is_remote_url(__a			):
              UpperCAmelCase_	   =       pretrained_model_name_or_path
         else:
              UpperCAmelCase_	   =       hf_bucket_url(__a       ,      filename=__a       ,      use_cdn=__a			)

         try:
              # Load from URL or cache if already cached
              UpperCAmelCase_	   =       cached_path(
                  __a       ,      cache_dir=__a       ,      force_download=__a       ,      proxies=__a       ,      resume_download=__a       ,      local_files_only=__a       ,      )
              # Load config dict
              if resolved_config_file is None:
                   raise EnvironmentError

              UpperCAmelCase_	   =       Config.load_yaml(__a			)

         except EnvironmentError:
              UpperCAmelCase_	   =       "Can't load config for"
              raise EnvironmentError(__a			)

         if resolved_config_file == config_file:
              print("loading configuration file from path"			)
         else:
              print("loading configuration file cache"			)

         return Config.load_yaml(__a			), kwargs





def      lowerCAmelCase_    ( snake_case_	:			str      )   ->				Tuple:


     '''simple docstring'''




     UpperCAmelCase_	   =       torch.load("dump.pt" ,   map_location=in_tensor.device      )
     UpperCAmelCase_	   =       in_tensor.numpy()
     UpperCAmelCase_	   =       out_tensor.numpy()[0]
     print(na.shape ,   na[0, 0, :5]      )
     print(na.shape ,   na[0, 0, :5]      )
     assert np.allclose(snake_case_ ,   snake_case_ ,   rtol=0.01 ,   atol=0.1      ), (
         f"""{sum([1 for x in np.isclose(snake_case_ ,   snake_case_ ,   rtol=0.01 ,   atol=0.1      ).flatten() if x is False]      )/len(na.flatten()      )*1_00:.4f} %"""
         " element-wise mismatch"
     )
     raise Exception("tensors are all good"      )

     # Hugging face functions below





def      lowerCAmelCase_    ( snake_case_	:			Optional[Any]      )   ->				List[Any]:


     '''simple docstring'''




     UpperCAmelCase_	   =       urlparse(snake_case_      )
     return parsed.scheme in ("http", "https")





def      lowerCAmelCase_    ( snake_case_	:			str ,   snake_case_	:			str ,   snake_case_	:			Optional[int]=True      )   ->				str:


     '''simple docstring'''




     UpperCAmelCase_	   =       CLOUDFRONT_DISTRIB_PREFIX if use_cdn else S3_BUCKET_PREFIX
     UpperCAmelCase_	   =       "/" not in model_id
     if legacy_format:
          return f"""{endpoint}/{model_id}-{filename}"""
     else:
          return f"""{endpoint}/{model_id}/{filename}"""





def      lowerCAmelCase_    ( snake_case_	:			List[Any] ,   snake_case_	:			Union[str, Any] ,   snake_case_	:			Optional[int]=None ,   snake_case_	:			List[Any]=0 ,   snake_case_	:			int=None ,   )   ->				Optional[Any]:


     '''simple docstring'''




     UpperCAmelCase_	   =       "python/{}".format(sys.version.split()[0]      )
     if _torch_available:
          ua += "; torch/{}".format(torch.__version__      )
     if isinstance(snake_case_ ,   snake_case_      ):
          ua += "; " + "; ".join("{}/{}".format(snake_case_ ,   snake_case_      ) for k, v in user_agent.items()      )
     elif isinstance(snake_case_ ,   snake_case_      ):
          ua += "; " + user_agent
     UpperCAmelCase_	   =       {"user-agent": ua}
     if resume_size > 0:
          UpperCAmelCase_	   =       "bytes=%d-" % (resume_size,)
     UpperCAmelCase_	   =       requests.get(snake_case_ ,   stream=snake_case_ ,   proxies=snake_case_ ,   headers=snake_case_      )
     if response.status_code == 4_16:  # Range not satisfiable
          return
     UpperCAmelCase_	   =       response.headers.get("Content-Length"      )
     UpperCAmelCase_	   =       resume_size + int(snake_case_      ) if content_length is not None else None
     UpperCAmelCase_	   =       tqdm(
         unit="B" ,   unit_scale=snake_case_ ,   total=snake_case_ ,   initial=snake_case_ ,   desc="Downloading" ,   )
     for chunk in response.iter_content(chunk_size=10_24      ):
          if chunk:  # filter out keep-alive new chunks
               progress.update(len(snake_case_      )      )
               temp_file.write(snake_case_      )
     progress.close()





def      lowerCAmelCase_    ( snake_case_	:			Optional[int] ,   snake_case_	:			str=None ,   snake_case_	:			List[str]=False ,   snake_case_	:			List[str]=None ,   snake_case_	:			int=10 ,   snake_case_	:			Any=False ,   snake_case_	:			int=None ,   snake_case_	:			str=False ,   )   ->				str:


     '''simple docstring'''




     if cache_dir is None:
          UpperCAmelCase_	   =       TRANSFORMERS_CACHE
     if isinstance(snake_case_ ,   snake_case_      ):
          UpperCAmelCase_	   =       str(snake_case_      )

     os.makedirs(snake_case_ ,   exist_ok=snake_case_      )

     UpperCAmelCase_	   =       None
     if not local_files_only:
          try:
               UpperCAmelCase_	   =       requests.head(snake_case_ ,   allow_redirects=snake_case_ ,   proxies=snake_case_ ,   timeout=snake_case_      )
               if response.status_code == 2_00:
                    UpperCAmelCase_	   =       response.headers.get("ETag"      )
          except (EnvironmentError, requests.exceptions.Timeout):
               # etag is already None
               pass

     UpperCAmelCase_	   =       url_to_filename(snake_case_ ,   snake_case_      )

     # get cache path to put the file
     UpperCAmelCase_	   =       os.path.join(snake_case_ ,   snake_case_      )

     # 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(snake_case_      ):
               return cache_path
          else:
               UpperCAmelCase_	   =       [
                   file
                   for file in fnmatch.filter(os.listdir(snake_case_      ) ,   filename + ".*"      )
                   if not file.endswith(".json"      ) and not file.endswith(".lock"      )
               ]
               if len(snake_case_      ) > 0:
                    return os.path.join(snake_case_ ,   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(snake_case_      ) and not force_download:
          return cache_path

     # Prevent parallel downloads of the same file with a lock.
     UpperCAmelCase_	   =       cache_path + ".lock"
     with FileLock(snake_case_      ):
          # If the download just completed while the lock was activated.
          if os.path.exists(snake_case_      ) and not force_download:
               # Even if returning early like here, the lock will be released.
               return cache_path

          if resume_download:
               UpperCAmelCase_	   =       cache_path + ".incomplete"

               @contextmanager
               def _resumable_file_manager():
                    with open(snake_case_ ,   "a+b"      ) as f:
                         yield f

               UpperCAmelCase_	   =       _resumable_file_manager
               if os.path.exists(snake_case_      ):
                    UpperCAmelCase_	   =       os.stat(snake_case_      ).st_size
               else:
                    UpperCAmelCase_	   =       0
          else:
               UpperCAmelCase_	   =       partial(tempfile.NamedTemporaryFile ,   dir=snake_case_ ,   delete=snake_case_      )
               UpperCAmelCase_	   =       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" ,   snake_case_ ,   temp_file.name ,   )

               http_get(
                   snake_case_ ,   snake_case_ ,   proxies=snake_case_ ,   resume_size=snake_case_ ,   user_agent=snake_case_ ,   )

          os.replace(temp_file.name ,   snake_case_      )

          UpperCAmelCase_	   =       {"url": url, "etag": etag}
          UpperCAmelCase_	   =       cache_path + ".json"
          with open(snake_case_ ,   "w"      ) as meta_file:
               json.dump(snake_case_ ,   snake_case_      )

     return cache_path





def      lowerCAmelCase_    ( snake_case_	:			Optional[Any] ,   snake_case_	:			Any=None      )   ->				Tuple:


     '''simple docstring'''




     UpperCAmelCase_	   =       url.encode("utf-8"      )
     UpperCAmelCase_	   =       shaaaa(snake_case_      )
     UpperCAmelCase_	   =       url_hash.hexdigest()

     if etag:
          UpperCAmelCase_	   =       etag.encode("utf-8"      )
          UpperCAmelCase_	   =       shaaaa(snake_case_      )
          filename += "." + etag_hash.hexdigest()

     if url.endswith(".h5"      ):
          filename += ".h5"

     return filename





def      lowerCAmelCase_    ( snake_case_	:			str ,   snake_case_	:			Tuple=None ,   snake_case_	:			int=False ,   snake_case_	:			Any=None ,   snake_case_	:			List[Any]=False ,   snake_case_	:			Any=None ,   snake_case_	:			Any=False ,   snake_case_	:			List[str]=False ,   snake_case_	:			str=False ,   )   ->				Union[str, Any]:


     '''simple docstring'''




     if cache_dir is None:
          UpperCAmelCase_	   =       TRANSFORMERS_CACHE
     if isinstance(snake_case_ ,   snake_case_      ):
          UpperCAmelCase_	   =       str(snake_case_      )
     if isinstance(snake_case_ ,   snake_case_      ):
          UpperCAmelCase_	   =       str(snake_case_      )

     if is_remote_url(snake_case_      ):
          # URL, so get it from the cache (downloading if necessary)
          UpperCAmelCase_	   =       get_from_cache(
              snake_case_ ,   cache_dir=snake_case_ ,   force_download=snake_case_ ,   proxies=snake_case_ ,   resume_download=snake_case_ ,   user_agent=snake_case_ ,   local_files_only=snake_case_ ,   )
     elif os.path.exists(snake_case_      ):
          # File, and it exists.
          UpperCAmelCase_	   =       url_or_filename
     elif urlparse(snake_case_      ).scheme == "":
          # File, but it doesn't exist.
          raise EnvironmentError("file {} not found".format(snake_case_      )      )
     else:
          # Something unknown
          raise ValueError("unable to parse {} as a URL or as a local path".format(snake_case_      )      )

     if extract_compressed_file:
          if not is_zipfile(snake_case_      ) and not tarfile.is_tarfile(snake_case_      ):
               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_   ,			UpperCAmelCase_	   =       os.path.split(snake_case_      )
          UpperCAmelCase_	   =       output_file.replace("." ,   "-"      ) + "-extracted"
          UpperCAmelCase_	   =       os.path.join(snake_case_ ,   snake_case_      )

          if os.path.isdir(snake_case_      ) and os.listdir(snake_case_      ) and not force_extract:
               return output_path_extracted

          # Prevent parallel extractions
          UpperCAmelCase_	   =       output_path + ".lock"
          with FileLock(snake_case_      ):
               shutil.rmtree(snake_case_ ,   ignore_errors=snake_case_      )
               os.makedirs(snake_case_      )
               if is_zipfile(snake_case_      ):
                    with ZipFile(snake_case_ ,   "r"      ) as zip_file:
                         zip_file.extractall(snake_case_      )
                         zip_file.close()
               elif tarfile.is_tarfile(snake_case_      ):
                    UpperCAmelCase_	   =       tarfile.open(snake_case_      )
                    tar_file.extractall(snake_case_      )
                    tar_file.close()
               else:
                    raise EnvironmentError("Archive format of {} could not be identified".format(snake_case_      )      )

          return output_path_extracted

     return output_path





def      lowerCAmelCase_    ( snake_case_	:			Any ,   snake_case_	:			Optional[int]=","      )   ->				int:


     '''simple docstring'''




     assert isinstance(snake_case_ ,   snake_case_      )
     if os.path.isfile(snake_case_      ):
          with open(snake_case_      ) as f:
               UpperCAmelCase_	   =       eval(f.read()      )
     else:
          UpperCAmelCase_	   =       requests.get(snake_case_      )
          try:
               UpperCAmelCase_	   =       requests.json()
          except Exception:
               UpperCAmelCase_	   =       req.content.decode()
               assert data is not None, "could not connect"
               try:
                    UpperCAmelCase_	   =       eval(snake_case_      )
               except Exception:
                    UpperCAmelCase_	   =       data.split("\n"      )
          req.close()
     return data





def      lowerCAmelCase_    ( snake_case_	:			List[str]      )   ->				Any:


     '''simple docstring'''




     UpperCAmelCase_	   =       requests.get(snake_case_      )
     UpperCAmelCase_	   =       np.array(Image.open(BytesIO(response.content      )      )      )
     return img





def      lowerCAmelCase_    ( snake_case_	:			Optional[Any]      )   ->				Union[str, Any]:


     '''simple docstring'''




     UpperCAmelCase_	   =       url.split("/"      )[-1]
     if fn not in os.listdir(os.getcwd()      ):
          wget.download(snake_case_      )
     with open(snake_case_ ,   "rb"      ) as stream:
          UpperCAmelCase_	   =       pkl.load(snake_case_      )
     UpperCAmelCase_	   =       weights.pop("model"      )
     UpperCAmelCase_	   =       {}
     for k, v in model.items():
          UpperCAmelCase_	   =       torch.from_numpy(snake_case_      )
          if "running_var" in k:
               UpperCAmelCase_	   =       torch.tensor([0]      )
               UpperCAmelCase_	   =       k.replace("running_var" ,   "num_batches_tracked"      )
               UpperCAmelCase_	   =       zero
     return new





def      lowerCAmelCase_    ( )   ->				int:


     '''simple docstring'''




     print(f"""{os.path.abspath(os.path.join(snake_case_ ,   os.pardir      )      )}/demo.ipynb"""      )





def      lowerCAmelCase_    ( snake_case_	:			Any ,   snake_case_	:			Any="RGB"      )   ->				Dict:


     '''simple docstring'''




     assert isinstance(snake_case_ ,   snake_case_      )
     if os.path.isfile(snake_case_      ):
          UpperCAmelCase_	   =       cva.imread(snake_case_      )
     else:
          UpperCAmelCase_	   =       get_image_from_url(snake_case_      )
          assert img is not None, f"""could not connect to: {im}"""
     UpperCAmelCase_	   =       cva.cvtColor(snake_case_ ,   cva.COLOR_BGR2RGB      )
     if input_format == "RGB":
          UpperCAmelCase_	   =       img[:, :, ::-1]
     return img






def      lowerCAmelCase_    ( snake_case_	:			Tuple ,   snake_case_	:			Union[str, Any]=1      )   ->				str:


     '''simple docstring'''




     return (images[i : i + batch] for i in range(0 ,   len(snake_case_      ) ,   snake_case_      ))




