
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

   lowercase_ 				=			True
except ImportError:
   lowercase_ 				=			False


try:
   from torch.hub import _get_torch_home

   lowercase_ 				=			_get_torch_home()
except ImportError:
   lowercase_ 				=			os.path.expanduser(
       os.getenv("""TORCH_HOME""", os.path.join(os.getenv("""XDG_CACHE_HOME""", """~/.cache"""), """torch"""))
   )

lowercase_ 				=			os.path.join(torch_cache_home, """transformers""")

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


def 							a__					(							snake_case=OBJECTS       ,			snake_case=ATTRIBUTES							):





  """simple docstring"""
  __SCREAMING_SNAKE_CASE      :	Dict					=		[]
  with open(snake_case							) as f:
    for object in f.readlines():
      vg_classes.append(object.split(''','''							)[0].lower().strip()							)

  __SCREAMING_SNAKE_CASE      :	List[str]					=		[]
  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 							a__					(							snake_case							):





  """simple docstring"""
  __SCREAMING_SNAKE_CASE      :	Optional[int]					=		OrderedDict()
  with open(snake_case       ,			'''rb'''							) as f:
    __SCREAMING_SNAKE_CASE      :	Dict					=		pkl.load(snake_case							)['''model''']
  for k in copy.deepcopy(list(ckp.keys()							)							):
    __SCREAMING_SNAKE_CASE      :	int					=		ckp.pop(snake_case							)
    if isinstance(snake_case       ,			np.ndarray							):
      __SCREAMING_SNAKE_CASE      :	List[str]					=		torch.tensor(snake_case							)
    else:
      assert isinstance(snake_case       ,			torch.tensor							), type(snake_case							)
    __SCREAMING_SNAKE_CASE      :	Any					=		v
  return r





class     __UpperCamelCase :






     """simple docstring"""







     lowerCAmelCase_							   =			{}



     def __init__(				self							:							Dict     ,						_A							:							dict     ,						_A							:							str = "root"     ,						_A							:							str=0 ):







       """simple docstring"""




       __SCREAMING_SNAKE_CASE      :	Optional[int]					=		name
       __SCREAMING_SNAKE_CASE      :	Dict					=		level
       __SCREAMING_SNAKE_CASE      :	Tuple					=		{}
       for k, v in dictionary.items():
         if v is None:
           raise ValueError()
         __SCREAMING_SNAKE_CASE      :	List[Any]					=		copy.deepcopy(_A )
         __SCREAMING_SNAKE_CASE      :	Dict					=		copy.deepcopy(_A )
         if isinstance(_A     ,						_A ):
           __SCREAMING_SNAKE_CASE      :	Optional[int]					=		Config(_A     ,						name=_A     ,						level=level + 1 )
         __SCREAMING_SNAKE_CASE      :	str					=		v
         setattr(self     ,						_A     ,						_A )

       __SCREAMING_SNAKE_CASE      :	Optional[int]					=		d



     def __repr__(				self							:							List[str] ):







       """simple docstring"""




       return str(list((self._pointer.keys()) ) )



     def __setattr__(				self							:							List[str]     ,						_A							:							List[str]     ,						_A							:							Any ):







       """simple docstring"""




       __SCREAMING_SNAKE_CASE      :	Dict					=		val
       __SCREAMING_SNAKE_CASE      :	Optional[Any]					=		val
       __SCREAMING_SNAKE_CASE      :	Dict					=		key.split('''.''' )
       __SCREAMING_SNAKE_CASE      :	List[str]					=		len(_A ) - 1
       __SCREAMING_SNAKE_CASE      :	Optional[int]					=		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:
             __SCREAMING_SNAKE_CASE      :	List[str]					=		val
           else:
             __SCREAMING_SNAKE_CASE      :	Optional[int]					=		pointer[l]



     def  UpperCAmelCase__							(				self							:							Optional[int] ):







       """simple docstring"""




       return self._pointer



     def  UpperCAmelCase__							(				self							:							Any     ,						_A							:							int     ,						_A							:							Tuple ):







       """simple docstring"""




       with open(F'''{file_name}'''     ,						'''w''' ) as stream:
         dump(_A     ,						_A )



     def  UpperCAmelCase__							(				self							:							Optional[Any]     ,						_A							:							List[Any]     ,						_A							:							Tuple ):







       """simple docstring"""




       with open(F'''{file_name}'''     ,						'''w''' ) as stream:
         json.dump(_A     ,						_A )



     @staticmethod
     def  UpperCAmelCase__							(				_A							:							List[Any] ):







       """simple docstring"""




       with open(_A ) as stream:
         __SCREAMING_SNAKE_CASE      :	Optional[Any]					=		load(_A     ,						Loader=_A )
       return data



     def __str__(				self							:							List[Any] ):







       """simple docstring"""




       __SCREAMING_SNAKE_CASE      :	List[Any]					=		'''    '''
       if self._name != "root":
         __SCREAMING_SNAKE_CASE      :	Optional[Any]					=		F'''{t * (self._level-1)}{self._name}:\n'''
       else:
         __SCREAMING_SNAKE_CASE      :	Optional[int]					=		''''''
       __SCREAMING_SNAKE_CASE      :	str					=		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'''
         __SCREAMING_SNAKE_CASE      :	Optional[Any]					=		level
       return r[:-1]



     @classmethod
     def  UpperCAmelCase__							(				cls							:							Optional[Any]     ,						_A							:							str     ,						**_A							:							Tuple ):







       """simple docstring"""




       __SCREAMING_SNAKE_CASE,		__SCREAMING_SNAKE_CASE      :	Any					=		cls.get_config_dict(_A     ,						**_A )
       return cls(_A )




     @classmethod
     def  UpperCAmelCase__							(				cls							:							Union[str, Any]     ,						_A							:							str     ,						**_A							:							Optional[int] ):







       """simple docstring"""




       __SCREAMING_SNAKE_CASE      :	List[Any]					=		kwargs.pop('''cache_dir'''     ,						_A )
       __SCREAMING_SNAKE_CASE      :	str					=		kwargs.pop('''force_download'''     ,						_A )
       __SCREAMING_SNAKE_CASE      :	Any					=		kwargs.pop('''resume_download'''     ,						_A )
       __SCREAMING_SNAKE_CASE      :	Tuple					=		kwargs.pop('''proxies'''     ,						_A )
       __SCREAMING_SNAKE_CASE      :	Any					=		kwargs.pop('''local_files_only'''     ,						_A )

       if os.path.isdir(_A ):
         __SCREAMING_SNAKE_CASE      :	Union[str, Any]					=		os.path.join(_A     ,						_A )
       elif os.path.isfile(_A ) or is_remote_url(_A ):
         __SCREAMING_SNAKE_CASE      :	Dict					=		pretrained_model_name_or_path
       else:
         __SCREAMING_SNAKE_CASE      :	List[str]					=		hf_bucket_url(_A     ,						filename=_A     ,						use_cdn=_A )

       try:
         # Load from URL or cache if already cached
         __SCREAMING_SNAKE_CASE      :	str					=		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

         __SCREAMING_SNAKE_CASE      :	str					=		Config.load_yaml(_A )

       except EnvironmentError:
         __SCREAMING_SNAKE_CASE      :	Optional[int]					=		'''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 							a__					(							snake_case							):





  """simple docstring"""
  __SCREAMING_SNAKE_CASE      :	Union[str, Any]					=		torch.load('''dump.pt'''       ,			map_location=in_tensor.device							)
  __SCREAMING_SNAKE_CASE      :	int					=		in_tensor.numpy()
  __SCREAMING_SNAKE_CASE      :	List[Any]					=		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 							a__					(							snake_case							):





  """simple docstring"""
  __SCREAMING_SNAKE_CASE      :	Tuple					=		urlparse(snake_case							)
  return parsed.scheme in ("http", "https")


def 							a__					(							snake_case       ,			snake_case       ,			snake_case=True							):





  """simple docstring"""
  __SCREAMING_SNAKE_CASE      :	str					=		CLOUDFRONT_DISTRIB_PREFIX if use_cdn else S3_BUCKET_PREFIX
  __SCREAMING_SNAKE_CASE      :	Optional[Any]					=		'''/''' not in model_id
  if legacy_format:
    return F'''{endpoint}/{model_id}-{filename}'''
  else:
    return F'''{endpoint}/{model_id}/{filename}'''


def 							a__					(							snake_case       ,			snake_case       ,			snake_case=None       ,			snake_case=0       ,			snake_case=None       ,			):





  """simple docstring"""
  __SCREAMING_SNAKE_CASE      :	Any					=		'''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
  __SCREAMING_SNAKE_CASE      :	Dict					=		{'''user-agent''': ua}
  if resume_size > 0:
    __SCREAMING_SNAKE_CASE      :	List[Any]					=		'''bytes=%d-''' % (resume_size,)
  __SCREAMING_SNAKE_CASE      :	Union[str, Any]					=		requests.get(snake_case       ,			stream=snake_case       ,			proxies=snake_case       ,			headers=snake_case							)
  if response.status_code == 416:  # Range not satisfiable
    return
  __SCREAMING_SNAKE_CASE      :	str					=		response.headers.get('''Content-Length'''							)
  __SCREAMING_SNAKE_CASE      :	Dict					=		resume_size + int(snake_case							) if content_length is not None else None
  __SCREAMING_SNAKE_CASE      :	Dict					=		tqdm(
      unit='''B'''       ,			unit_scale=snake_case       ,			total=snake_case       ,			initial=snake_case       ,			desc='''Downloading'''       ,			)
  for chunk in response.iter_content(chunk_size=1_024							):
    if chunk:  # filter out keep-alive new chunks
      progress.update(len(snake_case							)							)
      temp_file.write(snake_case							)
  progress.close()


def 							a__					(							snake_case       ,			snake_case=None       ,			snake_case=False       ,			snake_case=None       ,			snake_case=10       ,			snake_case=False       ,			snake_case=None       ,			snake_case=False       ,			):





  """simple docstring"""
  if cache_dir is None:
    __SCREAMING_SNAKE_CASE      :	Optional[int]					=		TRANSFORMERS_CACHE
  if isinstance(snake_case       ,			snake_case							):
    __SCREAMING_SNAKE_CASE      :	Optional[Any]					=		str(snake_case							)

  os.makedirs(snake_case       ,			exist_ok=snake_case							)

  __SCREAMING_SNAKE_CASE      :	Tuple					=		None
  if not local_files_only:
    try:
      __SCREAMING_SNAKE_CASE      :	List[Any]					=		requests.head(snake_case       ,			allow_redirects=snake_case       ,			proxies=snake_case       ,			timeout=snake_case							)
      if response.status_code == 200:
        __SCREAMING_SNAKE_CASE      :	str					=		response.headers.get('''ETag'''							)
    except (EnvironmentError, requests.exceptions.Timeout):
      # etag is already None
      pass

  __SCREAMING_SNAKE_CASE      :	Tuple					=		url_to_filename(snake_case       ,			snake_case							)

  # get cache path to put the file
  __SCREAMING_SNAKE_CASE      :	Union[str, Any]					=		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:
      __SCREAMING_SNAKE_CASE      :	List[str]					=		[
          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.
  __SCREAMING_SNAKE_CASE      :	List[str]					=		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:
      __SCREAMING_SNAKE_CASE      :	Optional[int]					=		cache_path + '''.incomplete'''

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

      __SCREAMING_SNAKE_CASE      :	Dict					=		_resumable_file_manager
      if os.path.exists(snake_case							):
        __SCREAMING_SNAKE_CASE      :	Optional[Any]					=		os.stat(snake_case							).st_size
      else:
        __SCREAMING_SNAKE_CASE      :	str					=		0
    else:
      __SCREAMING_SNAKE_CASE      :	Dict					=		partial(tempfile.NamedTemporaryFile       ,			dir=snake_case       ,			delete=snake_case							)
      __SCREAMING_SNAKE_CASE      :	Tuple					=		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							)

    __SCREAMING_SNAKE_CASE      :	Dict					=		{'''url''': url, '''etag''': etag}
    __SCREAMING_SNAKE_CASE      :	List[str]					=		cache_path + '''.json'''
    with open(snake_case       ,			'''w'''							) as meta_file:
      json.dump(snake_case       ,			snake_case							)

  return cache_path


def 							a__					(							snake_case       ,			snake_case=None							):





  """simple docstring"""
  __SCREAMING_SNAKE_CASE      :	int					=		url.encode('''utf-8'''							)
  __SCREAMING_SNAKE_CASE      :	Tuple					=		shaaaa(snake_case							)
  __SCREAMING_SNAKE_CASE      :	str					=		url_hash.hexdigest()

  if etag:
    __SCREAMING_SNAKE_CASE      :	Any					=		etag.encode('''utf-8'''							)
    __SCREAMING_SNAKE_CASE      :	Optional[int]					=		shaaaa(snake_case							)
    filename += "." + etag_hash.hexdigest()

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

  return filename


def 							a__					(							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       ,			):





  """simple docstring"""
  if cache_dir is None:
    __SCREAMING_SNAKE_CASE      :	Union[str, Any]					=		TRANSFORMERS_CACHE
  if isinstance(snake_case       ,			snake_case							):
    __SCREAMING_SNAKE_CASE      :	Optional[int]					=		str(snake_case							)
  if isinstance(snake_case       ,			snake_case							):
    __SCREAMING_SNAKE_CASE      :	List[Any]					=		str(snake_case							)

  if is_remote_url(snake_case							):
    # URL, so get it from the cache (downloading if necessary)
    __SCREAMING_SNAKE_CASE      :	Optional[Any]					=		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.
    __SCREAMING_SNAKE_CASE      :	Optional[Any]					=		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/"
    __SCREAMING_SNAKE_CASE,		__SCREAMING_SNAKE_CASE      :	Optional[Any]					=		os.path.split(snake_case							)
    __SCREAMING_SNAKE_CASE      :	Optional[Any]					=		output_file.replace('''.'''       ,			'''-'''							) + '''-extracted'''
    __SCREAMING_SNAKE_CASE      :	str					=		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
    __SCREAMING_SNAKE_CASE      :	Dict					=		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							):
        __SCREAMING_SNAKE_CASE      :	Optional[Any]					=		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 							a__					(							snake_case       ,			snake_case=","							):





  """simple docstring"""
  assert isinstance(snake_case       ,			snake_case							)
  if os.path.isfile(snake_case							):
    with open(snake_case							) as f:
      __SCREAMING_SNAKE_CASE      :	Optional[int]					=		eval(f.read()							)
  else:
    __SCREAMING_SNAKE_CASE      :	int					=		requests.get(snake_case							)
    try:
      __SCREAMING_SNAKE_CASE      :	str					=		requests.json()
    except Exception:
      __SCREAMING_SNAKE_CASE      :	List[Any]					=		req.content.decode()
      assert data is not None, "could not connect"
      try:
        __SCREAMING_SNAKE_CASE      :	Union[str, Any]					=		eval(snake_case							)
      except Exception:
        __SCREAMING_SNAKE_CASE      :	Any					=		data.split('''\n'''							)
    req.close()
  return data


def 							a__					(							snake_case							):





  """simple docstring"""
  __SCREAMING_SNAKE_CASE      :	Union[str, Any]					=		requests.get(snake_case							)
  __SCREAMING_SNAKE_CASE      :	Optional[Any]					=		np.array(Image.open(BytesIO(response.content							)							)							)
  return img


def 							a__					(							snake_case							):





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


def 							a__					(							):





  """simple docstring"""
  print(F'''{os.path.abspath(os.path.join(snake_case       ,			os.pardir							)							)}/demo.ipynb'''							)


def 							a__					(							snake_case       ,			snake_case="RGB"							):





  """simple docstring"""
  assert isinstance(snake_case       ,			snake_case							)
  if os.path.isfile(snake_case							):
    __SCREAMING_SNAKE_CASE      :	List[Any]					=		cva.imread(snake_case							)
  else:
    __SCREAMING_SNAKE_CASE      :	List[Any]					=		get_image_from_url(snake_case							)
    assert img is not None, F'''could not connect to: {im}'''
  __SCREAMING_SNAKE_CASE      :	int					=		cva.cvtColor(snake_case       ,			cva.COLOR_BGR2RGB							)
  if input_format == "RGB":
    __SCREAMING_SNAKE_CASE      :	Dict					=		img[:, :, ::-1]
  return img


def 							a__					(							snake_case       ,			snake_case=1							):





  """simple docstring"""
  return (images[i : i + batch] for i in range(0       ,			len(snake_case							)       ,			snake_case							))







from math import pi, sqrt, tan

def      UpperCAmelCase_    (    _UpperCAmelCase							:float				)	->				float:
     '''simple docstring'''


     if side_length < 0:
          raise ValueError('''surface_area_cube() only accepts non-negative values'''				)
     return 6 * side_length**2

def      UpperCAmelCase_    (    _UpperCAmelCase							:float  ,						_UpperCAmelCase							:float  ,						_UpperCAmelCase							:float				)	->				float:
     '''simple docstring'''


     if length < 0 or breadth < 0 or height < 0:
          raise ValueError('''surface_area_cuboid() only accepts non-negative values'''				)
     return 2 * ((length * breadth) + (breadth * height) + (length * height))

def      UpperCAmelCase_    (    _UpperCAmelCase							:float				)	->				float:
     '''simple docstring'''


     if radius < 0:
          raise ValueError('''surface_area_sphere() only accepts non-negative values'''				)
     return 4 * pi * radius**2

def      UpperCAmelCase_    (    _UpperCAmelCase							:float				)	->				float:
     '''simple docstring'''


     if radius < 0:
          raise ValueError('''surface_area_hemisphere() only accepts non-negative values'''				)
     return 3 * pi * radius**2

def      UpperCAmelCase_    (    _UpperCAmelCase							:float  ,						_UpperCAmelCase							:float				)	->				float:
     '''simple docstring'''


     if radius < 0 or height < 0:
          raise ValueError('''surface_area_cone() only accepts non-negative values'''				)
     return pi * radius * (radius + (height**2 + radius**2) ** 0.5)

def      UpperCAmelCase_    (    _UpperCAmelCase							:float  ,						_UpperCAmelCase							:float  ,						_UpperCAmelCase							:float				)	->				float:
     '''simple docstring'''


     if radius_a < 0 or radius_a < 0 or height < 0:
          raise ValueError(
              '''surface_area_conical_frustum() only accepts non-negative values'''				)
     A_          =       (height**2 + (radius_a - radius_a) ** 2) ** 0.5
     return pi * ((slant_height * (radius_a + radius_a)) + radius_a**2 + radius_a**2)

def      UpperCAmelCase_    (    _UpperCAmelCase							:float  ,						_UpperCAmelCase							:float				)	->				float:
     '''simple docstring'''


     if radius < 0 or height < 0:
          raise ValueError('''surface_area_cylinder() only accepts non-negative values'''				)
     return 2 * pi * radius * (height + radius)

def      UpperCAmelCase_    (    _UpperCAmelCase							:float  ,						_UpperCAmelCase							:float				)	->				float:
     '''simple docstring'''


     if torus_radius < 0 or tube_radius < 0:
          raise ValueError('''surface_area_torus() only accepts non-negative values'''				)
     if torus_radius < tube_radius:
          raise ValueError(
              '''surface_area_torus() does not support spindle or self intersecting tori'''				)
     return 4 * pow(_UpperCAmelCase  ,						2				) * torus_radius * tube_radius

def      UpperCAmelCase_    (    _UpperCAmelCase							:float  ,						_UpperCAmelCase							:float				)	->				float:
     '''simple docstring'''


     if length < 0 or width < 0:
          raise ValueError('''area_rectangle() only accepts non-negative values'''				)
     return length * width

def      UpperCAmelCase_    (    _UpperCAmelCase							:float				)	->				float:
     '''simple docstring'''


     if side_length < 0:
          raise ValueError('''area_square() only accepts non-negative values'''				)
     return side_length**2

def      UpperCAmelCase_    (    _UpperCAmelCase							:float  ,						_UpperCAmelCase							:float				)	->				float:
     '''simple docstring'''


     if base < 0 or height < 0:
          raise ValueError('''area_triangle() only accepts non-negative values'''				)
     return (base * height) / 2

def      UpperCAmelCase_    (    _UpperCAmelCase							:float  ,						_UpperCAmelCase							:float  ,						_UpperCAmelCase							:float				)	->				float:
     '''simple docstring'''


     if sidea < 0 or sidea < 0 or sidea < 0:
          raise ValueError('''area_triangle_three_sides() only accepts non-negative values'''				)
     elif sidea + sidea < sidea or sidea + sidea < sidea or sidea + sidea < sidea:
          raise ValueError('''Given three sides do not form a triangle'''				)
     A_          =       (sidea + sidea + sidea) / 2
     A_          =       sqrt(
         semi_perimeter
         * (semi_perimeter - sidea)
         * (semi_perimeter - sidea)
         * (semi_perimeter - sidea)				)
     return area

def      UpperCAmelCase_    (    _UpperCAmelCase							:float  ,						_UpperCAmelCase							:float				)	->				float:
     '''simple docstring'''


     if base < 0 or height < 0:
          raise ValueError('''area_parallelogram() only accepts non-negative values'''				)
     return base * height

def      UpperCAmelCase_    (    _UpperCAmelCase							:float  ,						_UpperCAmelCase							:float  ,						_UpperCAmelCase							:float				)	->				float:
     '''simple docstring'''


     if basea < 0 or basea < 0 or height < 0:
          raise ValueError('''area_trapezium() only accepts non-negative values'''				)
     return 1 / 2 * (basea + basea) * height

def      UpperCAmelCase_    (    _UpperCAmelCase							:float				)	->				float:
     '''simple docstring'''


     if radius < 0:
          raise ValueError('''area_circle() only accepts non-negative values'''				)
     return pi * radius**2

def      UpperCAmelCase_    (    _UpperCAmelCase							:float  ,						_UpperCAmelCase							:float				)	->				float:
     '''simple docstring'''


     if radius_x < 0 or radius_y < 0:
          raise ValueError('''area_ellipse() only accepts non-negative values'''				)
     return pi * radius_x * radius_y

def      UpperCAmelCase_    (    _UpperCAmelCase							:float  ,						_UpperCAmelCase							:float				)	->				float:
     '''simple docstring'''


     if diagonal_a < 0 or diagonal_a < 0:
          raise ValueError('''area_rhombus() only accepts non-negative values'''				)
     return 1 / 2 * diagonal_a * diagonal_a

def      UpperCAmelCase_    (    _UpperCAmelCase							:int  ,						_UpperCAmelCase							:float				)	->				float:
     '''simple docstring'''


     if not isinstance(_UpperCAmelCase  ,						_UpperCAmelCase				) or sides < 3:
          raise ValueError(
              '''area_reg_polygon() only accepts integers greater than or \
equal to three as number of sides'''				)
     elif length < 0:
          raise ValueError(
              '''area_reg_polygon() only accepts non-negative values as \
length of a side'''				)
     return (sides * length**2) / (4 * tan(pi / sides				))
     return (sides * length**2) / (4 * tan(pi / sides				))


if __name__ == "__main__":
      import doctest

      doctest.testmod(verbose=True)  # verbose so we can see methods missing tests

      print('[DEMO] Areas of various geometric shapes: \n')
      print(f'''Rectangle: {area_rectangle(10, 20) = }''')
      print(f'''Square: {area_square(10) = }''')
      print(f'''Triangle: {area_triangle(10, 10) = }''')
      print(f'''Triangle: {area_triangle_three_sides(5, 12, 13) = }''')
      print(f'''Parallelogram: {area_parallelogram(10, 20) = }''')
      print(f'''Rhombus: {area_rhombus(10, 20) = }''')
      print(f'''Trapezium: {area_trapezium(10, 20, 30) = }''')
      print(f'''Circle: {area_circle(20) = }''')
      print(f'''Ellipse: {area_ellipse(10, 20) = }''')
      print('\nSurface Areas of various geometric shapes: \n')
      print(f'''Cube: {surface_area_cube(20) = }''')
      print(f'''Cuboid: {surface_area_cuboid(10, 20, 30) = }''')
      print(f'''Sphere: {surface_area_sphere(20) = }''')
      print(f'''Hemisphere: {surface_area_hemisphere(20) = }''')
      print(f'''Cone: {surface_area_cone(10, 20) = }''')
      print(f'''Conical Frustum: {surface_area_conical_frustum(10, 20, 30) = }''')
      print(f'''Cylinder: {surface_area_cylinder(10, 20) = }''')
      print(f'''Torus: {surface_area_torus(20, 10) = }''')
      print(f'''Equilateral Triangle: {area_reg_polygon(3, 10) = }''')
      print(f'''Square: {area_reg_polygon(4, 10) = }''')
      print(f'''Reqular Pentagon: {area_reg_polygon(5, 10) = }''')



