


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_ (							__snake_case=OBJECTS					,						__snake_case=ATTRIBUTES						)					->      List[str]:







 """simple docstring"""


 _lowercase											=[]
 with open(__snake_case						) as f:
  for object in f.readlines():
   vg_classes.append(object.split(''','''						)[0].lower().strip()						)

 _lowercase											=[]
 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     UpperCAmelCase_ (							__snake_case						)					->      Union[str, Any]:







 """simple docstring"""


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







class 				lowerCamelCase__       :
     SCREAMING_SNAKE_CASE__				      =      {}





     def __init__(self		,					UpperCAmelCase		,					UpperCAmelCase = "root"		,					UpperCAmelCase=0	)					->       Optional[Any]:
      _lowercase											=name
      _lowercase											=level
      _lowercase											={}
      for k, v in dictionary.items():
       if v is None:
        raise ValueError()
       _lowercase											=copy.deepcopy(UpperCAmelCase	)
       _lowercase											=copy.deepcopy(UpperCAmelCase	)
       if isinstance(UpperCAmelCase		,					UpperCAmelCase	):
        _lowercase											=Config(UpperCAmelCase		,					name=UpperCAmelCase		,					level=level + 1	)
       _lowercase											=v
       setattr(self		,					UpperCAmelCase		,					UpperCAmelCase	)

      _lowercase											=d





     def __repr__(self	)					->       Optional[int]:
      return str(list((self._pointer.keys())	)	)





     def __setattr__(self		,					UpperCAmelCase		,					UpperCAmelCase	)					->       Optional[int]:
      _lowercase											=val
      _lowercase											=val
      _lowercase											=key.split('''.'''	)
      _lowercase											=len(UpperCAmelCase	) - 1
      _lowercase											=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											=val
        else:
         _lowercase											=pointer[l]





     def 					__A (self	)					->       Any:
      return self._pointer





     def 					__A (self		,					UpperCAmelCase		,					UpperCAmelCase	)					->       List[Any]:
      with open(f"{file_name}"		,					'''w'''	) as stream:
       dump(UpperCAmelCase		,					UpperCAmelCase	)





     def 					__A (self		,					UpperCAmelCase		,					UpperCAmelCase	)					->       Optional[int]:
      with open(f"{file_name}"		,					'''w'''	) as stream:
       json.dump(UpperCAmelCase		,					UpperCAmelCase	)





     @staticmethod
     def 					__A (UpperCAmelCase	)					->       str:
      with open(UpperCAmelCase	) as stream:
       _lowercase											=load(UpperCAmelCase		,					Loader=UpperCAmelCase	)
      return data





     def __str__(self	)					->       Dict:
      _lowercase											='''    '''
      if self._name != "root":
       _lowercase											=f"{t * (self._level-1)}{self._name}:\n"
      else:
       _lowercase											=''''''
      _lowercase											=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											=level
      return r[:-1]





     @classmethod
     def 					__A (cls		,					UpperCAmelCase		,					**UpperCAmelCase	)					->       Union[str, Any]:
      _lowercase				,   _lowercase											=cls.get_config_dict(UpperCAmelCase		,					**UpperCAmelCase	)
      return cls(UpperCAmelCase	)





     @classmethod
     def 					__A (cls		,					UpperCAmelCase		,					**UpperCAmelCase	)					->       Optional[Any]:
      _lowercase											=kwargs.pop('''cache_dir'''		,					UpperCAmelCase	)
      _lowercase											=kwargs.pop('''force_download'''		,					UpperCAmelCase	)
      _lowercase											=kwargs.pop('''resume_download'''		,					UpperCAmelCase	)
      _lowercase											=kwargs.pop('''proxies'''		,					UpperCAmelCase	)
      _lowercase											=kwargs.pop('''local_files_only'''		,					UpperCAmelCase	)

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

      try:
       # Load from URL or cache if already cached
       _lowercase											=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											=Config.load_yaml(UpperCAmelCase	)

      except EnvironmentError:
       _lowercase											='''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_ (							__snake_case						)					->      Any:







 """simple docstring"""


 _lowercase											=torch.load('''dump.pt'''					,						map_location=in_tensor.device						)
 _lowercase											=in_tensor.numpy()
 _lowercase											=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()						)*100:.4f} %"
     " element-wise mismatch"
 )
 raise Exception('''tensors are all good'''						)

 # Hugging face functions below
def     UpperCAmelCase_ (							__snake_case						)					->      Optional[Any]:







 """simple docstring"""


 _lowercase											=urlparse(__snake_case						)
 return parsed.scheme in ("http", "https")
def     UpperCAmelCase_ (							__snake_case					,						__snake_case					,						__snake_case=True						)					->      str:







 """simple docstring"""


 _lowercase											=CLOUDFRONT_DISTRIB_PREFIX if use_cdn else S3_BUCKET_PREFIX
 _lowercase											='''/''' not in model_id
 if legacy_format:
  return F"{endpoint}/{model_id}-{filename}"
 else:
  return F"{endpoint}/{model_id}/{filename}"
def     UpperCAmelCase_ (							__snake_case					,						__snake_case					,						__snake_case=None					,						__snake_case=0					,						__snake_case=None					,						)					->      Optional[int]:







 """simple docstring"""


 _lowercase											='''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
 _lowercase											={'''user-agent''': ua}
 if resume_size > 0:
  _lowercase											='''bytes=%d-''' % (resume_size,)
 _lowercase											=requests.get(__snake_case					,						stream=__snake_case					,						proxies=__snake_case					,						headers=__snake_case						)
 if response.status_code == 416:  # Range not satisfiable
  return
 _lowercase											=response.headers.get('''Content-Length'''						)
 _lowercase											=resume_size + int(__snake_case						) if content_length is not None else None
 _lowercase											=tqdm(
     unit='''B'''					,						unit_scale=__snake_case					,						total=__snake_case					,						initial=__snake_case					,						desc='''Downloading'''					,						)
 for chunk in response.iter_content(chunk_size=1024						):
  if chunk:  # filter out keep-alive new chunks
   progress.update(len(__snake_case						)						)
   temp_file.write(__snake_case						)
 progress.close()
def     UpperCAmelCase_ (							__snake_case					,						__snake_case=None					,						__snake_case=False					,						__snake_case=None					,						__snake_case=10					,						__snake_case=False					,						__snake_case=None					,						__snake_case=False					,						)					->      Dict:







 """simple docstring"""


 if cache_dir is None:
  _lowercase											=TRANSFORMERS_CACHE
 if isinstance(__snake_case					,						__snake_case						):
  _lowercase											=str(__snake_case						)

 os.makedirs(__snake_case					,						exist_ok=__snake_case						)

 _lowercase											=None
 if not local_files_only:
  try:
   _lowercase											=requests.head(__snake_case					,						allow_redirects=__snake_case					,						proxies=__snake_case					,						timeout=__snake_case						)
   if response.status_code == 200:
    _lowercase											=response.headers.get('''ETag'''						)
  except (EnvironmentError, requests.exceptions.Timeout):
   # etag is already None
   pass

 _lowercase											=url_to_filename(__snake_case					,						__snake_case						)

 # get cache path to put the file
 _lowercase											=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:
   _lowercase											=[
       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.
 _lowercase											=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:
   _lowercase											=cache_path + '''.incomplete'''

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

   _lowercase											=_resumable_file_manager
   if os.path.exists(__snake_case						):
    _lowercase											=os.stat(__snake_case						).st_size
   else:
    _lowercase											=0
  else:
   _lowercase											=partial(tempfile.NamedTemporaryFile					,						dir=__snake_case					,						delete=__snake_case						)
   _lowercase											=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						)

  _lowercase											={'''url''': url, '''etag''': etag}
  _lowercase											=cache_path + '''.json'''
  with open(__snake_case					,						'''w'''						) as meta_file:
   json.dump(__snake_case					,						__snake_case						)

 return cache_path
def     UpperCAmelCase_ (							__snake_case					,						__snake_case=None						)					->      Dict:







 """simple docstring"""


 _lowercase											=url.encode('''utf-8'''						)
 _lowercase											=shaaaa(__snake_case						)
 _lowercase											=url_hash.hexdigest()

 if etag:
  _lowercase											=etag.encode('''utf-8'''						)
  _lowercase											=shaaaa(__snake_case						)
  filename += "." + etag_hash.hexdigest()

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

 return filename
def     UpperCAmelCase_ (							__snake_case					,						__snake_case=None					,						__snake_case=False					,						__snake_case=None					,						__snake_case=False					,						__snake_case=None					,						__snake_case=False					,						__snake_case=False					,						__snake_case=False					,						)					->      Union[str, Any]:







 """simple docstring"""


 if cache_dir is None:
  _lowercase											=TRANSFORMERS_CACHE
 if isinstance(__snake_case					,						__snake_case						):
  _lowercase											=str(__snake_case						)
 if isinstance(__snake_case					,						__snake_case						):
  _lowercase											=str(__snake_case						)

 if is_remote_url(__snake_case						):
  # URL, so get it from the cache (downloading if necessary)
  _lowercase											=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.
  _lowercase											=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/"
  _lowercase				,   _lowercase											=os.path.split(__snake_case						)
  _lowercase											=output_file.replace('''.'''					,						'''-'''						) + '''-extracted'''
  _lowercase											=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
  _lowercase											=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						):
    _lowercase											=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     UpperCAmelCase_ (							__snake_case					,						__snake_case=","						)					->      Union[str, Any]:







 """simple docstring"""


 assert isinstance(__snake_case					,						__snake_case						)
 if os.path.isfile(__snake_case						):
  with open(__snake_case						) as f:
   _lowercase											=eval(f.read()						)
 else:
  _lowercase											=requests.get(__snake_case						)
  try:
   _lowercase											=requests.json()
  except Exception:
   _lowercase											=req.content.decode()
   assert data is not None, "could not connect"
   try:
    _lowercase											=eval(__snake_case						)
   except Exception:
    _lowercase											=data.split('''\n'''						)
  req.close()
 return data
def     UpperCAmelCase_ (							__snake_case						)					->      Optional[Any]:







 """simple docstring"""


 _lowercase											=requests.get(__snake_case						)
 _lowercase											=np.array(Image.open(BytesIO(response.content						)						)						)
 return img
def     UpperCAmelCase_ (							__snake_case						)					->      Any:







 """simple docstring"""


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







 """simple docstring"""


 print(F"{os.path.abspath(os.path.join(__snake_case					,						os.pardir						)						)}/demo.ipynb"						)
def     UpperCAmelCase_ (							__snake_case					,						__snake_case="RGB"						)					->      int:







 """simple docstring"""


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



def     UpperCAmelCase_ (							__snake_case					,						__snake_case=1						)					->      Tuple:







 """simple docstring"""


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





from __future__ import annotations

UpperCAmelCase__            =							[2, 1, 4, 5, 6, 0, 8, 9, 1, 2, 0, 6, 4, 2, 0, 6, 5, 3, 2, 7]







class 				lowerCamelCase__       :





     def __init__(self		,					UpperCAmelCase	)					->       None:
      _lowercase											=-1
      _lowercase											=-1
      _lowercase											=[-1] * length
      _lowercase											=None
      _lowercase											=None





     def __repr__(self	)					->       str:
      return f"Node(min_value={self.minn} max_value={self.maxx})"



def     UpperCAmelCase_ (							__snake_case						)					->      Node | None:







 """simple docstring"""


 _lowercase											=Node(len(__snake_case						)						)
 _lowercase				,   _lowercase											=min(__snake_case						), max(__snake_case						)
 # Leaf node case where the node contains only one unique value
 if root.minn == root.maxx:
  return root
 _lowercase											=(root.minn + root.maxx) // 2

 _lowercase											=[]
 _lowercase											=[]

 for index, num in enumerate(__snake_case						):
  if num <= pivot:
   left_arr.append(__snake_case						)
  else:
   right_arr.append(__snake_case						)
  _lowercase											=len(__snake_case						)
 _lowercase											=build_tree(__snake_case						)
 _lowercase											=build_tree(__snake_case						)
 return root
def     UpperCAmelCase_ (							__snake_case					,						__snake_case					,						__snake_case						)					->      int:







 """simple docstring"""


 if index < 0 or node is None:
  return 0
 # Leaf node cases
 if node.minn == node.maxx:
  return index + 1 if node.minn == num else 0
 _lowercase											=(node.minn + node.maxx) // 2
 if num <= pivot:
  # go the left subtree and map index to the left subtree
  return rank_till_index(node.left					,						__snake_case					,						node.map_left[index] - 1						)
 else:
  # go to the right subtree and map index to the right subtree
  return rank_till_index(node.right					,						__snake_case					,						index - node.map_left[index]						)
def     UpperCAmelCase_ (							__snake_case					,						__snake_case					,						__snake_case					,						__snake_case						)					->      int:







 """simple docstring"""


 if start > end:
  return 0
 _lowercase											=rank_till_index(__snake_case					,						__snake_case					,						__snake_case						)
 _lowercase											=rank_till_index(__snake_case					,						__snake_case					,						start - 1						)
 return rank_till_end - rank_before_start
def     UpperCAmelCase_ (							__snake_case					,						__snake_case					,						__snake_case					,						__snake_case						)					->      int:







 """simple docstring"""


 if index > (end - start) or start > end or node is None:
  return -1
 # Leaf node case
 if node.minn == node.maxx:
  return node.minn
 # Number of elements in the left subtree in interval [start, end]
 _lowercase											=node.map_left[end] - (
     node.map_left[start - 1] if start else 0
 )
 if num_elements_in_left_tree > index:
  return quantile(
      node.left					,						__snake_case					,						(node.map_left[start - 1] if start else 0)					,						node.map_left[end] - 1					,						)
 else:
  return quantile(
      node.right					,						index - num_elements_in_left_tree					,						start - (node.map_left[start - 1] if start else 0)					,						end - node.map_left[end]					,						)
def     UpperCAmelCase_ (							__snake_case					,						__snake_case					,						__snake_case					,						__snake_case					,						__snake_case						)					->      int:







 """simple docstring"""


 if (
     start > end
     or node is None
     or start_num > end_num
     or node.minn > end_num
     or node.maxx < start_num
 ):
  return 0
 if start_num <= node.minn and node.maxx <= end_num:
  return end - start + 1
 _lowercase											=range_counting(
     node.left					,						(node.map_left[start - 1] if start else 0)					,						node.map_left[end] - 1					,						__snake_case					,						__snake_case					,						)
 _lowercase											=range_counting(
     node.right					,						start - (node.map_left[start - 1] if start else 0)					,						end - node.map_left[end]					,						__snake_case					,						__snake_case					,						)
 return left + right


if __name__ == "__main__":
  import doctest

  doctest.testmod()

