import json
import os
import shutil
import tempfile
import unittest

from transformers import BatchEncoding, CanineTokenizer
from transformers.testing_utils import require_tokenizers, require_torch
from transformers.tokenization_utils import AddedToken
from transformers.utils import cached_property

from ...test_tokenization_common import TokenizerTesterMixin


class     lowercase     (  A__					,							unittest.TestCase  ):
							lowercase__    :							Union[str, Any]										=				CanineTokenizer
							lowercase__    :							Optional[Any]										=				False




							def 						__snake_case(    self :       Optional[Any]   )       ->					Dict:



												'''simple docstring'''

												super().setUp()
												SCREAMING_SNAKE_CASE           =							CanineTokenizer()
												tokenizer.save_pretrained(self.tmpdirname   )




							@cached_property
							def 						__snake_case(    self :       Optional[int]   )       ->					Union[str, Any]:



												'''simple docstring'''

												return CanineTokenizer.from_pretrained("google/canine-s"   )




							def 						__snake_case(    self :       Union[str, Any]						,				**_UpperCamelCase :       Union[str, Any]   )       ->					Any:



												'''simple docstring'''

												SCREAMING_SNAKE_CASE           =							self.tokenizer_class.from_pretrained(self.tmpdirname						,				**_lowerCamelCase   )
												SCREAMING_SNAKE_CASE           =							1_024
												return tokenizer




							@require_torch
							def 						__snake_case(    self :       Any   )       ->					Optional[int]:



												'''simple docstring'''

												SCREAMING_SNAKE_CASE           =							self.canine_tokenizer
												SCREAMING_SNAKE_CASE           =							['Life is like a box of chocolates.', 'You never know what you\'re gonna get.']
												# fmt: off
												SCREAMING_SNAKE_CASE           =							[57_344, 76, 105, 102, 101, 32, 105, 115, 32, 108, 105, 107, 101, 32, 97, 32, 98, 111, 120, 32, 111, 102, 32, 99, 104, 111, 99, 111, 108, 97, 116, 101, 115, 46, 57_345, 0, 0, 0, 0]
												# fmt: on
												SCREAMING_SNAKE_CASE           =							tokenizer(_lowerCamelCase						,				padding=_lowerCamelCase						,				return_tensors="pt"   )
												self.assertIsInstance(_lowerCamelCase						,				_lowerCamelCase   )

												SCREAMING_SNAKE_CASE           =							list(batch.input_ids.numpy()[0]   )

												self.assertListEqual(_lowerCamelCase						,				_lowerCamelCase   )

												self.assertEqual((2, 39)						,				batch.input_ids.shape   )
												self.assertEqual((2, 39)						,				batch.attention_mask.shape   )




							@require_torch
							def 						__snake_case(    self :       int   )       ->					Union[str, Any]:



												'''simple docstring'''

												SCREAMING_SNAKE_CASE           =							self.canine_tokenizer
												SCREAMING_SNAKE_CASE           =							['Once there was a man.', 'He wrote a test in HuggingFace Tranformers.']
												SCREAMING_SNAKE_CASE           =							tokenizer(_lowerCamelCase						,				padding=_lowerCamelCase						,				return_tensors="pt"   )
												# check if input_ids, attention_mask and token_type_ids are returned
												self.assertIn("input_ids"						,				_lowerCamelCase   )
												self.assertIn("attention_mask"						,				_lowerCamelCase   )
												self.assertIn("token_type_ids"						,				_lowerCamelCase   )




							@require_torch
							def 						__snake_case(    self :       List[Any]   )       ->					List[Any]:



												'''simple docstring'''

												SCREAMING_SNAKE_CASE           =							self.canine_tokenizer
												SCREAMING_SNAKE_CASE           =							[
												    'What\'s the weater?',
												    'It\'s about 25 degrees.',
												]
												SCREAMING_SNAKE_CASE           =							tokenizer(
												    text_target=_lowerCamelCase						,				max_length=32						,				padding="max_length"						,				truncation=_lowerCamelCase						,				return_tensors="pt"   )
												self.assertEqual(32						,				targets["input_ids"].shape[1]   )




							def 						__snake_case(    self :       Optional[Any]   )       ->					Tuple:



												'''simple docstring'''

												SCREAMING_SNAKE_CASE           =							self.get_tokenizers()
												for tokenizer in tokenizers:
																	with self.subTest(F"{tokenizer.__class__.__name__}"   ):
																						self.assertNotEqual(tokenizer.model_max_length						,				42   )

																						# Now let's start the test
												SCREAMING_SNAKE_CASE           =							self.get_tokenizers()
												for tokenizer in tokenizers:
																	with self.subTest(F"{tokenizer.__class__.__name__}"   ):
																						# Isolate this from the other tests because we save additional tokens/etc
																						SCREAMING_SNAKE_CASE           =							tempfile.mkdtemp()

																						SCREAMING_SNAKE_CASE           =							' He is very happy, UNwant\u00E9d,running'
																						SCREAMING_SNAKE_CASE           =							tokenizer.encode(_lowerCamelCase						,				add_special_tokens=_lowerCamelCase   )
																						tokenizer.save_pretrained(_lowerCamelCase   )

																						SCREAMING_SNAKE_CASE           =							tokenizer.__class__.from_pretrained(_lowerCamelCase   )
																						SCREAMING_SNAKE_CASE           =							after_tokenizer.encode(_lowerCamelCase						,				add_special_tokens=_lowerCamelCase   )
																						self.assertListEqual(_lowerCamelCase						,				_lowerCamelCase   )

																						shutil.rmtree(_lowerCamelCase   )

												SCREAMING_SNAKE_CASE           =							self.get_tokenizers(model_max_length=42   )
												for tokenizer in tokenizers:
																	with self.subTest(F"{tokenizer.__class__.__name__}"   ):
																						# Isolate this from the other tests because we save additional tokens/etc
																						SCREAMING_SNAKE_CASE           =							tempfile.mkdtemp()

																						SCREAMING_SNAKE_CASE           =							' He is very happy, UNwant\u00E9d,running'

																						SCREAMING_SNAKE_CASE           =							tokenizer.additional_special_tokens

																						# We can add a new special token for Canine as follows:
																						SCREAMING_SNAKE_CASE           =							chr(0xE_0_0_7   )
																						additional_special_tokens.append(_lowerCamelCase   )
																						tokenizer.add_special_tokens({"additional_special_tokens": additional_special_tokens}   )
																						SCREAMING_SNAKE_CASE           =							tokenizer.encode(_lowerCamelCase						,				add_special_tokens=_lowerCamelCase   )
																						tokenizer.save_pretrained(_lowerCamelCase   )

																						SCREAMING_SNAKE_CASE           =							tokenizer.__class__.from_pretrained(_lowerCamelCase   )
																						SCREAMING_SNAKE_CASE           =							after_tokenizer.encode(_lowerCamelCase						,				add_special_tokens=_lowerCamelCase   )
																						self.assertListEqual(_lowerCamelCase						,				_lowerCamelCase   )
																						self.assertIn(_lowerCamelCase						,				after_tokenizer.additional_special_tokens   )
																						self.assertEqual(after_tokenizer.model_max_length						,				42   )

																						SCREAMING_SNAKE_CASE           =							tokenizer.__class__.from_pretrained(_lowerCamelCase						,				model_max_length=43   )
																						self.assertEqual(tokenizer.model_max_length						,				43   )

																						shutil.rmtree(_lowerCamelCase   )




							def 						__snake_case(    self :       Optional[Any]   )       ->					Tuple:



												'''simple docstring'''

												SCREAMING_SNAKE_CASE           =							self.get_tokenizers(do_lower_case=_lowerCamelCase   )
												for tokenizer in tokenizers:
																	with self.subTest(F"{tokenizer.__class__.__name__}"   ):
																						SCREAMING_SNAKE_CASE           =							self.get_clean_sequence(_lowerCamelCase   )

																						# a special token for Canine can be defined as follows:
																						SCREAMING_SNAKE_CASE           =							0xE_0_0_5
																						SCREAMING_SNAKE_CASE           =							chr(_lowerCamelCase   )

																						tokenizer.add_special_tokens({"cls_token": special_token}   )
																						SCREAMING_SNAKE_CASE           =							tokenizer.encode(_lowerCamelCase						,				add_special_tokens=_lowerCamelCase   )
																						self.assertEqual(len(_lowerCamelCase   )						,				1   )

																						SCREAMING_SNAKE_CASE           =							tokenizer.decode(ids + encoded_special_token						,				clean_up_tokenization_spaces=_lowerCamelCase   )
																						SCREAMING_SNAKE_CASE           =							tokenizer.encode(_lowerCamelCase						,				add_special_tokens=_lowerCamelCase   )

																						SCREAMING_SNAKE_CASE           =							tokenizer.encode(_lowerCamelCase						,				add_special_tokens=_lowerCamelCase   )
																						SCREAMING_SNAKE_CASE           =							tokenizer.encode(_lowerCamelCase						,				add_special_tokens=_lowerCamelCase   )
																						self.assertEqual(_lowerCamelCase						,				input_encoded + special_token_id   )

																						SCREAMING_SNAKE_CASE           =							tokenizer.decode(_lowerCamelCase						,				skip_special_tokens=_lowerCamelCase   )
																						self.assertTrue(special_token not in decoded   )




							def 						__snake_case(    self :       Union[str, Any]   )       ->					Dict:



												'''simple docstring'''

												SCREAMING_SNAKE_CASE           =							self.get_tokenizers(do_lower_case=_lowerCamelCase   )
												for tokenizer in tokenizers:
																	with self.subTest(F"{tokenizer.__class__.__name__}"   ):
																						SCREAMING_SNAKE_CASE           =							chr(0xE_0_0_5   )
																						SCREAMING_SNAKE_CASE           =							chr(0xE_0_0_6   )

																						# `add_tokens` method stores special tokens only in `tokenizer.unique_no_split_tokens`. (in tokenization_utils.py)
																						tokenizer.add_tokens([SPECIAL_TOKEN_1]						,				special_tokens=_lowerCamelCase   )
																						# `add_special_tokens` method stores special tokens in `tokenizer.additional_special_tokens`,
																						# which also occur in `tokenizer.all_special_tokens`. (in tokenization_utils_base.py)
																						tokenizer.add_special_tokens({"additional_special_tokens": [SPECIAL_TOKEN_2]}   )

																						SCREAMING_SNAKE_CASE           =							tokenizer.tokenize(_lowerCamelCase   )
																						SCREAMING_SNAKE_CASE           =							tokenizer.tokenize(_lowerCamelCase   )

																						self.assertEqual(len(_lowerCamelCase   )						,				1   )
																						self.assertEqual(len(_lowerCamelCase   )						,				1   )
																						self.assertEqual(token_a[0]						,				_lowerCamelCase   )
																						self.assertEqual(token_a[0]						,				_lowerCamelCase   )




							@require_tokenizers
							def 						__snake_case(    self :       Any   )       ->					Any:



												'''simple docstring'''

												SCREAMING_SNAKE_CASE           =							self.get_tokenizers(do_lower_case=_lowerCamelCase   )
												for tokenizer in tokenizers:
																	with self.subTest(F"{tokenizer.__class__.__name__}"   ):
																						# a special token for Canine can be defined as follows:
																						SCREAMING_SNAKE_CASE           =							0xE_0_0_6
																						SCREAMING_SNAKE_CASE           =							chr(_lowerCamelCase   )

																						SCREAMING_SNAKE_CASE           =							AddedToken(_lowerCamelCase						,				lstrip=_lowerCamelCase   )
																						tokenizer.add_special_tokens({"additional_special_tokens": [new_token]}   )

																						with tempfile.TemporaryDirectory() as tmp_dir_name:
																											tokenizer.save_pretrained(_lowerCamelCase   )
																											tokenizer.from_pretrained(_lowerCamelCase   )




							def 						__snake_case(    self :       Tuple   )       ->					str:



												'''simple docstring'''

												SCREAMING_SNAKE_CASE           =							[]
												if self.test_slow_tokenizer:
																	tokenizer_list.append((self.tokenizer_class, self.get_tokenizer())   )

												if self.test_rust_tokenizer:
																	tokenizer_list.append((self.rust_tokenizer_class, self.get_rust_tokenizer())   )

												for tokenizer_class, tokenizer_utils in tokenizer_list:
																	with tempfile.TemporaryDirectory() as tmp_dir:
																						tokenizer_utils.save_pretrained(_lowerCamelCase   )

																						with open(os.path.join(_lowerCamelCase						,				"special_tokens_map.json"   )						,				encoding="utf-8"   ) as json_file:
																											SCREAMING_SNAKE_CASE           =							json.load(_lowerCamelCase   )

																						with open(os.path.join(_lowerCamelCase						,				"tokenizer_config.json"   )						,				encoding="utf-8"   ) as json_file:
																											SCREAMING_SNAKE_CASE           =							json.load(_lowerCamelCase   )

																						# a special token for Canine can be defined as follows:
																						SCREAMING_SNAKE_CASE           =							0xE_0_0_6
																						SCREAMING_SNAKE_CASE           =							chr(_lowerCamelCase   )

																						SCREAMING_SNAKE_CASE           =							[new_token_a]
																						SCREAMING_SNAKE_CASE           =							[new_token_a]

																						with open(os.path.join(_lowerCamelCase						,				"special_tokens_map.json"   )						,				"w"						,				encoding="utf-8"   ) as outfile:
																											json.dump(_lowerCamelCase						,				_lowerCamelCase   )
																						with open(os.path.join(_lowerCamelCase						,				"tokenizer_config.json"   )						,				"w"						,				encoding="utf-8"   ) as outfile:
																											json.dump(_lowerCamelCase						,				_lowerCamelCase   )

																						# the following checks allow us to verify that our test works as expected, i.e. that the tokenizer takes
																						# into account the new value of additional_special_tokens given in the "tokenizer_config.json" and
																						# "special_tokens_map.json" files
																						SCREAMING_SNAKE_CASE           =							tokenizer_class.from_pretrained(_lowerCamelCase						,				extra_ids=0   )
																						self.assertIn(_lowerCamelCase						,				tokenizer_without_change_in_init.additional_special_tokens   )
																						# self.assertIn("an_additional_special_token",tokenizer_without_change_in_init.get_vocab()) # ByT5Tokenization no vocab
																						self.assertEqual(
																						    [new_token_a]						,				tokenizer_without_change_in_init.convert_ids_to_tokens(
																						        tokenizer_without_change_in_init.convert_tokens_to_ids([new_token_a]   )   )						,				)

																						SCREAMING_SNAKE_CASE           =							0xE_0_0_7
																						SCREAMING_SNAKE_CASE           =							chr(_lowerCamelCase   )
																						# Now we test that we can change the value of additional_special_tokens in the from_pretrained
																						SCREAMING_SNAKE_CASE           =							[AddedToken(_lowerCamelCase						,				lstrip=_lowerCamelCase   )]
																						SCREAMING_SNAKE_CASE           =							tokenizer_class.from_pretrained(
																						    _lowerCamelCase						,				additional_special_tokens=_lowerCamelCase						,				extra_ids=0   )

																						self.assertIn(_lowerCamelCase						,				tokenizer.additional_special_tokens   )
																						# self.assertIn(new_token_2,tokenizer.get_vocab()) # ByT5Tokenization no vocab
																						self.assertEqual(
																						    [new_token_a]						,				tokenizer.convert_ids_to_tokens(tokenizer.convert_tokens_to_ids([new_token_a]   )   )   )




							@require_tokenizers
							def 						__snake_case(    self :       Tuple   )       ->					Optional[Any]:



												'''simple docstring'''

												SCREAMING_SNAKE_CASE           =							self.get_tokenizers(do_lower_case=_lowerCamelCase   )
												for tokenizer in tokenizers:
																	with self.subTest(F"{tokenizer.__class__.__name__}"   ):
																						SCREAMING_SNAKE_CASE           =							'hello world'
																						if self.space_between_special_tokens:
																											SCREAMING_SNAKE_CASE           =							'[CLS] hello world [SEP]'
																						else:
																											SCREAMING_SNAKE_CASE           =							input
																						SCREAMING_SNAKE_CASE           =							tokenizer.encode(_lowerCamelCase						,				add_special_tokens=_lowerCamelCase   )
																						SCREAMING_SNAKE_CASE           =							tokenizer.decode(_lowerCamelCase						,				spaces_between_special_tokens=self.space_between_special_tokens   )
																						self.assertIn(_lowerCamelCase						,				[output, output.lower()]   )




							def 						__snake_case(    self :       Union[str, Any]   )       ->					Any:



												'''simple docstring'''

												SCREAMING_SNAKE_CASE           =							self.get_tokenizers()
												for tokenizer in tokenizers:
																	with self.subTest(F"{tokenizer.__class__.__name__}"   ):
																						SCREAMING_SNAKE_CASE           =							[
																						    'bos_token',
																						    'eos_token',
																						    'unk_token',
																						    'sep_token',
																						    'pad_token',
																						    'cls_token',
																						    'mask_token',
																						]

												SCREAMING_SNAKE_CASE           =							'a'
												SCREAMING_SNAKE_CASE           =							ord(_lowerCamelCase   )

												for attr in attributes_list:
																	setattr(_lowerCamelCase						,				attr + "_id"						,				_lowerCamelCase   )
																	self.assertEqual(getattr(_lowerCamelCase						,				_lowerCamelCase   )						,				_lowerCamelCase   )
																	self.assertEqual(getattr(_lowerCamelCase						,				attr + "_id"   )						,				_lowerCamelCase   )

																	setattr(_lowerCamelCase						,				attr + "_id"						,				_lowerCamelCase   )
																	self.assertEqual(getattr(_lowerCamelCase						,				_lowerCamelCase   )						,				_lowerCamelCase   )
																	self.assertEqual(getattr(_lowerCamelCase						,				attr + "_id"   )						,				_lowerCamelCase   )

												setattr(_lowerCamelCase						,				"additional_special_tokens_ids"						,				[]   )
												self.assertListEqual(getattr(_lowerCamelCase						,				"additional_special_tokens"   )						,				[]   )
												self.assertListEqual(getattr(_lowerCamelCase						,				"additional_special_tokens_ids"   )						,				[]   )

												SCREAMING_SNAKE_CASE           =							0xE_0_0_6
												SCREAMING_SNAKE_CASE           =							chr(_lowerCamelCase   )
												setattr(_lowerCamelCase						,				"additional_special_tokens_ids"						,				[additional_special_token_id]   )
												self.assertListEqual(getattr(_lowerCamelCase						,				"additional_special_tokens"   )						,				[additional_special_token]   )
												self.assertListEqual(getattr(_lowerCamelCase						,				"additional_special_tokens_ids"   )						,				[additional_special_token_id]   )




							def 						__snake_case(    self :       Union[str, Any]   )       ->					List[str]:



												'''simple docstring'''

												pass




							def 						__snake_case(    self :       List[str]   )       ->					Optional[Any]:



												'''simple docstring'''

												pass




							def 						__snake_case(    self :       Union[str, Any]   )       ->					List[str]:



												'''simple docstring'''

												pass




							def 						__snake_case(    self :       Optional[Any]   )       ->					Optional[Any]:



												'''simple docstring'''

												pass




							def 						__snake_case(    self :       Optional[int]   )       ->					Union[str, Any]:



												'''simple docstring'''

												pass




							def 						__snake_case(    self :       Union[str, Any]   )       ->					Optional[int]:



												'''simple docstring'''

												pass




							def 						__snake_case(    self :       Optional[int]   )       ->					Union[str, Any]:



												'''simple docstring'''

												pass





							def 						__snake_case(    self :       Dict   )       ->					Dict:



												'''simple docstring'''

												pass






"""simple docstring"""






# This code is adapted from OpenAI's release
# https://github.com/openai/human-eval/blob/master/human_eval/execution.py

import contextlib
import faulthandler
import io
import multiprocessing
import os
import platform
import signal
import tempfile




def       A_  (				__lowercase						,	__lowercase						,	__lowercase						,	__lowercase	):
 UpperCamelCase_     :					Tuple   	=multiprocessing.Manager()
 UpperCamelCase_     :					Dict   	=manager.list()

 UpperCamelCase_     :					Union[str, Any]   	=multiprocessing.Process(target=__lowercase						,	args=(check_program, result, timeout)	)
 p.start()
 p.join(timeout=timeout + 1	)
 if p.is_alive():
  p.kill()

 if not result:
  result.append('timed out'	)

 return {
     "task_id": task_id,
     "passed": result[0] == "passed",
     "result": result[0],
     "completion_id": completion_id,
 }




def       A_  (				__lowercase						,	__lowercase						,	__lowercase	):
 with create_tempdir():
  # These system calls are needed when cleaning up tempdir.
  import os
  import shutil

  UpperCamelCase_     :					Tuple   	=shutil.rmtree
  UpperCamelCase_     :					List[str]   	=os.rmdir
  UpperCamelCase_     :					Any   	=os.chdir

  # Disable functionalities that can make destructive changes to the test.
  reliability_guard()

  # Run program.
  try:
   UpperCamelCase_     :					List[str]   	={}
   with swallow_io():
    with time_limit(__lowercase	):
     exec(__lowercase						,	__lowercase	)
   result.append('passed'	)
  except TimeoutException:
   result.append('timed out'	)
  except BaseException as e:
   result.append(F'''failed: {e}'''	)

  # Needed for cleaning up.
  UpperCamelCase_     :					Optional[Any]   	=rmtree
  UpperCamelCase_     :					str   	=rmdir
  UpperCamelCase_     :					Dict   	=chdir




@contextlib.contextmanager
def       A_  (				__lowercase	):
 def signal_handler(__lowercase						,	__lowercase	):
  raise TimeoutException('Timed out!'	)

 signal.setitimer(signal.ITIMER_REAL						,	__lowercase	)
 signal.signal(signal.SIGALRM						,	__lowercase	)
 try:
  yield
 finally:
  signal.setitimer(signal.ITIMER_REAL						,	0	)




@contextlib.contextmanager
def       A_  (				):
 UpperCamelCase_     :					str   	=WriteOnlyStringIO()
 with contextlib.redirect_stdout(__lowercase	):
  with contextlib.redirect_stderr(__lowercase	):
   with redirect_stdin(__lowercase	):
    yield




@contextlib.contextmanager
def       A_  (				):
 with tempfile.TemporaryDirectory() as dirname:
  with chdir(__lowercase	):
   yield dirname





class 				a__					(						A__       ):
     pass





class 				a__					(						io.StringIO       ):



     def  lowerCamelCase_						(							self :Any      ,  *_lowerCamelCase :Any      ,  **_lowerCamelCase :Tuple   ):







      '''simple docstring'''



      raise OSError



     def  lowerCamelCase_						(							self :Union[str, Any]      ,  *_lowerCamelCase :Any      ,  **_lowerCamelCase :Tuple   ):







      '''simple docstring'''



      raise OSError



     def  lowerCamelCase_						(							self :Tuple      ,  *_lowerCamelCase :str      ,  **_lowerCamelCase :List[str]   ):







      '''simple docstring'''



      raise OSError




     def  lowerCamelCase_						(							self :List[str]      ,  *_lowerCamelCase :Optional[int]      ,  **_lowerCamelCase :str   ):







      '''simple docstring'''



      return False





class 				a__					(						contextlib._RedirectStream       ):  # type: ignore
     UpperCAmelCase__         =      '''stdin'''




@contextlib.contextmanager
def       A_  (				__lowercase	):
 if root == ".":
  yield
  return
 UpperCamelCase_     :					List[str]   	=os.getcwd()
 os.chdir(__lowercase	)
 try:
  yield
 except BaseException as exc:
  raise exc
 finally:
  os.chdir(__lowercase	)





def       A_  (				__lowercase=None	):

 if maximum_memory_bytes is not None:
  import resource

  resource.setrlimit(resource.RLIMIT_AS						,	(maximum_memory_bytes, maximum_memory_bytes)	)
  resource.setrlimit(resource.RLIMIT_DATA						,	(maximum_memory_bytes, maximum_memory_bytes)	)
  if not platform.uname().system == "Darwin":
   resource.setrlimit(resource.RLIMIT_STACK						,	(maximum_memory_bytes, maximum_memory_bytes)	)

 faulthandler.disable()

 import builtins

 UpperCamelCase_     :					Any   	=None
 UpperCamelCase_     :					Any   	=None

 import os

 UpperCamelCase_     :					Union[str, Any]   	='1'

 UpperCamelCase_     :					Union[str, Any]   	=None
 UpperCamelCase_     :					Optional[Any]   	=None
 UpperCamelCase_     :					Optional[Any]   	=None
 UpperCamelCase_     :					Optional[Any]   	=None
 UpperCamelCase_     :					Dict   	=None
 UpperCamelCase_     :					List[Any]   	=None
 UpperCamelCase_     :					Any   	=None
 UpperCamelCase_     :					str   	=None
 UpperCamelCase_     :					Optional[int]   	=None
 UpperCamelCase_     :					Union[str, Any]   	=None
 UpperCamelCase_     :					str   	=None
 UpperCamelCase_     :					str   	=None
 UpperCamelCase_     :					List[Any]   	=None
 UpperCamelCase_     :					Optional[Any]   	=None
 UpperCamelCase_     :					str   	=None
 UpperCamelCase_     :					List[str]   	=None
 UpperCamelCase_     :					Optional[Any]   	=None
 UpperCamelCase_     :					int   	=None
 UpperCamelCase_     :					Optional[Any]   	=None
 UpperCamelCase_     :					Tuple   	=None
 UpperCamelCase_     :					List[Any]   	=None
 UpperCamelCase_     :					Tuple   	=None
 UpperCamelCase_     :					Dict   	=None
 UpperCamelCase_     :					Optional[int]   	=None
 UpperCamelCase_     :					str   	=None
 UpperCamelCase_     :					Union[str, Any]   	=None
 UpperCamelCase_     :					int   	=None

 import shutil

 UpperCamelCase_     :					List[str]   	=None
 UpperCamelCase_     :					Optional[Any]   	=None
 UpperCamelCase_     :					Dict   	=None

 import subprocess

 UpperCamelCase_     :					Optional[int]   	=None  # type: ignore

 UpperCamelCase_     :					Union[str, Any]   	=None

 import sys

 UpperCamelCase_     :					Union[str, Any]   	=None
 UpperCamelCase_     :					Tuple   	=None
 UpperCamelCase_     :					Union[str, Any]   	=None
 UpperCamelCase_     :					Dict   	=None
 UpperCamelCase_     :					Any   	=None
