import os
import sys
import tempfile
import unittest
import unittest.mock as mock
from pathlib import Path

from huggingface_hub import HfFolder, delete_repo
from huggingface_hub.file_download import http_get
from requests.exceptions import HTTPError

from transformers import (
    AlbertTokenizer,
    AutoTokenizer,
    BertTokenizer,
    BertTokenizerFast,
    GPTaTokenizerFast,
    is_tokenizers_available,
)
from transformers.testing_utils import TOKEN, USER, is_staging_test, require_tokenizers
from transformers.tokenization_utils import Trie


sys.path.append(str(Path(__file__).parent.parent / 'utils'))

from test_module.custom_tokenization import CustomTokenizer  # noqa E402


if is_tokenizers_available():
				from test_module.custom_tokenization_fast import CustomTokenizerFast



class        lowercase_   (					unittest.TestCase		):



							def 	UpperCamelCase	(						self    ):
													# A mock response for an HTTP head request to emulate server down
													_snake_case						:					Tuple    =   mock.Mock()
													_snake_case						:					Optional[Any]    =   500
													_snake_case						:					List[str]    =   {}
													_snake_case						:					str    =   HTTPError
													_snake_case						:					Tuple    =   {}

													# Download this model to make sure it's in the cache.
													_snake_case						:					Optional[Any]    =   BertTokenizer.from_pretrained("hf-internal-testing/tiny-random-bert"    )

													# Under the mock environment we get a 500 error when trying to reach the tokenizer.
													with mock.patch("requests.Session.request"				,    return_value=lowercase_    ) as mock_head:
																			_snake_case						:					Tuple    =   BertTokenizer.from_pretrained("hf-internal-testing/tiny-random-bert"    )
																			# This check we did call the fake head request
																			mock_head.assert_called()



							@require_tokenizers
							def 	UpperCamelCase	(						self    ):
													# A mock response for an HTTP head request to emulate server down
													_snake_case						:					str    =   mock.Mock()
													_snake_case						:					List[str]    =   500
													_snake_case						:					List[Any]    =   {}
													_snake_case						:					Tuple    =   HTTPError
													_snake_case						:					Tuple    =   {}

													# Download this model to make sure it's in the cache.
													_snake_case						:					Optional[Any]    =   GPTaTokenizerFast.from_pretrained("gpt2"    )

													# Under the mock environment we get a 500 error when trying to reach the tokenizer.
													with mock.patch("requests.Session.request"				,    return_value=lowercase_    ) as mock_head:
																			_snake_case						:					Union[str, Any]    =   GPTaTokenizerFast.from_pretrained("gpt2"    )
																			# This check we did call the fake head request
																			mock_head.assert_called()



							def 	UpperCamelCase	(						self    ):
													# This test is for deprecated behavior and can be removed in v5
													try:
																			_snake_case						:					str    =   tempfile.mktemp()
																			with open(lowercase_				,    "wb"    ) as f:
																									http_get("https://huggingface.co/albert-base-v1/resolve/main/spiece.model"				,    lowercase_    )

																			_snake_case						:					Tuple    =   AlbertTokenizer.from_pretrained(lowercase_    )
													finally:
																			os.remove(lowercase_    )

													# Supporting this legacy load introduced a weird bug where the tokenizer would load local files if they are in
													# the current folder and have the right name.
													if os.path.isfile("tokenizer.json"    ):
																			# We skip the test if the user has a `tokenizer.json` in this folder to avoid deleting it.
																			return
													try:
																			with open("tokenizer.json"				,    "wb"    ) as f:
																									http_get("https://huggingface.co/hf-internal-testing/tiny-random-bert/blob/main/tokenizer.json"				,    lowercase_    )
																			_snake_case						:					Tuple    =   AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-gpt2"    )
																			# The tiny random BERT has a vocab size of 1024, tiny gpt2 as a vocab size of 1000
																			self.assertEqual(tokenizer.vocab_size				,    1_000    )
																			# Tokenizer should depend on the remote checkpoint, not the local tokenizer.json file.

													finally:
																			os.remove("tokenizer.json"    )



							def 	UpperCamelCase	(						self    ):
													# This test is for deprecated behavior and can be removed in v5
													_snake_case						:					int    =   AlbertTokenizer.from_pretrained("https://huggingface.co/albert-base-v1/resolve/main/spiece.model"    )




@is_staging_test
class        lowercase_   (					unittest.TestCase		):
							_lowerCamelCase						=		['[UNK]', '[CLS]', '[SEP]', '[PAD]', '[MASK]', 'bla', 'blou']



							@classmethod
							def 	UpperCamelCase	(						cls    ):
													_snake_case						:					int    =   TOKEN
													HfFolder.save_token(lowercase_    )



							@classmethod
							def 	UpperCamelCase	(						cls    ):
													try:
																			delete_repo(token=cls._token				,    repo_id="test-tokenizer"    )
													except HTTPError:
																			pass

													try:
																			delete_repo(token=cls._token				,    repo_id="valid_org/test-tokenizer-org"    )
													except HTTPError:
																			pass

													try:
																			delete_repo(token=cls._token				,    repo_id="test-dynamic-tokenizer"    )
													except HTTPError:
																			pass



							def 	UpperCamelCase	(						self    ):
													with tempfile.TemporaryDirectory() as tmp_dir:
																			_snake_case						:					int    =   os.path.join(lowercase_				,    "vocab.txt"    )
																			with open(lowercase_				,    "w"				,    encoding="utf-8"    ) as vocab_writer:
																									vocab_writer.write("".join([x + "\n" for x in self.vocab_tokens]    )    )
																			_snake_case						:					List[str]    =   BertTokenizer(lowercase_    )

													tokenizer.push_to_hub("test-tokenizer"				,    use_auth_token=self._token    )
													_snake_case						:					List[Any]    =   BertTokenizer.from_pretrained(f"""{USER}/test-tokenizer"""    )
													self.assertDictEqual(new_tokenizer.vocab				,    tokenizer.vocab    )

													# Reset repo
													delete_repo(token=self._token				,    repo_id="test-tokenizer"    )

													# Push to hub via save_pretrained
													with tempfile.TemporaryDirectory() as tmp_dir:
																			tokenizer.save_pretrained(lowercase_				,    repo_id="test-tokenizer"				,    push_to_hub=lowercase_				,    use_auth_token=self._token    )

													_snake_case						:					List[Any]    =   BertTokenizer.from_pretrained(f"""{USER}/test-tokenizer"""    )
													self.assertDictEqual(new_tokenizer.vocab				,    tokenizer.vocab    )



							def 	UpperCamelCase	(						self    ):
													with tempfile.TemporaryDirectory() as tmp_dir:
																			_snake_case						:					Any    =   os.path.join(lowercase_				,    "vocab.txt"    )
																			with open(lowercase_				,    "w"				,    encoding="utf-8"    ) as vocab_writer:
																									vocab_writer.write("".join([x + "\n" for x in self.vocab_tokens]    )    )
																			_snake_case						:					int    =   BertTokenizer(lowercase_    )

													tokenizer.push_to_hub("valid_org/test-tokenizer-org"				,    use_auth_token=self._token    )
													_snake_case						:					str    =   BertTokenizer.from_pretrained("valid_org/test-tokenizer-org"    )
													self.assertDictEqual(new_tokenizer.vocab				,    tokenizer.vocab    )

													# Reset repo
													delete_repo(token=self._token				,    repo_id="valid_org/test-tokenizer-org"    )

													# Push to hub via save_pretrained
													with tempfile.TemporaryDirectory() as tmp_dir:
																			tokenizer.save_pretrained(
																			    lowercase_				,    repo_id="valid_org/test-tokenizer-org"				,    push_to_hub=lowercase_				,    use_auth_token=self._token    )

													_snake_case						:					Optional[Any]    =   BertTokenizer.from_pretrained("valid_org/test-tokenizer-org"    )
													self.assertDictEqual(new_tokenizer.vocab				,    tokenizer.vocab    )



							@require_tokenizers
							def 	UpperCamelCase	(						self    ):
													CustomTokenizer.register_for_auto_class()
													with tempfile.TemporaryDirectory() as tmp_dir:
																			_snake_case						:					Tuple    =   os.path.join(lowercase_				,    "vocab.txt"    )
																			with open(lowercase_				,    "w"				,    encoding="utf-8"    ) as vocab_writer:
																									vocab_writer.write("".join([x + "\n" for x in self.vocab_tokens]    )    )
																			_snake_case						:					Dict    =   CustomTokenizer(lowercase_    )

													# No fast custom tokenizer
													tokenizer.push_to_hub("test-dynamic-tokenizer"				,    use_auth_token=self._token    )

													_snake_case						:					Dict    =   AutoTokenizer.from_pretrained(f"""{USER}/test-dynamic-tokenizer"""				,    trust_remote_code=lowercase_    )
													# Can't make an isinstance check because the new_model.config is from the CustomTokenizer class of a dynamic module
													self.assertEqual(tokenizer.__class__.__name__				,    "CustomTokenizer"    )

													# Fast and slow custom tokenizer
													CustomTokenizerFast.register_for_auto_class()
													with tempfile.TemporaryDirectory() as tmp_dir:
																			_snake_case						:					List[Any]    =   os.path.join(lowercase_				,    "vocab.txt"    )
																			with open(lowercase_				,    "w"				,    encoding="utf-8"    ) as vocab_writer:
																									vocab_writer.write("".join([x + "\n" for x in self.vocab_tokens]    )    )

																			_snake_case						:					Union[str, Any]    =   BertTokenizerFast.from_pretrained(lowercase_    )
																			bert_tokenizer.save_pretrained(lowercase_    )
																			_snake_case						:					List[Any]    =   CustomTokenizerFast.from_pretrained(lowercase_    )

													tokenizer.push_to_hub("test-dynamic-tokenizer"				,    use_auth_token=self._token    )

													_snake_case						:					Dict    =   AutoTokenizer.from_pretrained(f"""{USER}/test-dynamic-tokenizer"""				,    trust_remote_code=lowercase_    )
													# Can't make an isinstance check because the new_model.config is from the FakeConfig class of a dynamic module
													self.assertEqual(tokenizer.__class__.__name__				,    "CustomTokenizerFast"    )
													_snake_case						:					List[str]    =   AutoTokenizer.from_pretrained(
													    f"""{USER}/test-dynamic-tokenizer"""				,    use_fast=lowercase_				,    trust_remote_code=lowercase_    )
													# Can't make an isinstance check because the new_model.config is from the FakeConfig class of a dynamic module
													self.assertEqual(tokenizer.__class__.__name__				,    "CustomTokenizer"    )




class        lowercase_   (					unittest.TestCase		):



							def 	UpperCamelCase	(						self    ):
													_snake_case						:					int    =   Trie()
													trie.add("Hello 友達"    )
													self.assertEqual(trie.data				,    {"H": {"e": {"l": {"l": {"o": {" ": {"友": {"達": {"": 1}}}}}}}}}    )
													trie.add("Hello"    )
													trie.data
													self.assertEqual(trie.data				,    {"H": {"e": {"l": {"l": {"o": {"": 1, " ": {"友": {"達": {"": 1}}}}}}}}}    )



							def 	UpperCamelCase	(						self    ):
													_snake_case						:					Optional[Any]    =   Trie()
													self.assertEqual(trie.split("[CLS] This is a extra_id_100"    )				,    ["[CLS] This is a extra_id_100"]    )
													trie.add("[CLS]"    )
													trie.add("extra_id_1"    )
													trie.add("extra_id_100"    )
													self.assertEqual(trie.split("[CLS] This is a extra_id_100"    )				,    ["[CLS]", " This is a ", "extra_id_100"]    )



							def 	UpperCamelCase	(						self    ):
													_snake_case						:					int    =   Trie()
													trie.add("A"    )
													self.assertEqual(trie.split("ABC"    )				,    ["A", "BC"]    )
													self.assertEqual(trie.split("BCA"    )				,    ["BC", "A"]    )



							def 	UpperCamelCase	(						self    ):
													_snake_case						:					int    =   Trie()
													trie.add("TOKEN]"    )
													trie.add("[SPECIAL_TOKEN]"    )
													self.assertEqual(trie.split("This is something [SPECIAL_TOKEN]"    )				,    ["This is something ", "[SPECIAL_TOKEN]"]    )



							def 	UpperCamelCase	(						self    ):
													_snake_case						:					Optional[int]    =   Trie()
													trie.add("A"    )
													trie.add("P"    )
													trie.add("[SPECIAL_TOKEN]"    )
													self.assertEqual(trie.split("This is something [SPECIAL_TOKEN]"    )				,    ["This is something ", "[SPECIAL_TOKEN]"]    )



							def 	UpperCamelCase	(						self    ):
													_snake_case						:					Optional[Any]    =   Trie()
													trie.add("AB"    )
													trie.add("B"    )
													trie.add("C"    )
													self.assertEqual(trie.split("ABC"    )				,    ["AB", "C"]    )



							def 	UpperCamelCase	(						self    ):
													_snake_case						:					Dict    =   Trie()
													trie.add("ABC"    )
													trie.add("B"    )
													trie.add("CD"    )
													self.assertEqual(trie.split("ABCD"    )				,    ["ABC", "D"]    )



							def 	UpperCamelCase	(						self    ):
													# Even if the offsets are wrong, we necessarily output correct string
													# parts.
													_snake_case						:					Any    =   Trie()
													_snake_case						:					Tuple    =   trie.cut_text("ABC"				,    [0, 0, 2, 1, 2, 3]    )
													self.assertEqual(lowercase_				,    ["AB", "C"]    )
from __future__ import annotations

import string
from itertools import cycle, product
from pathlib import Path

__SCREAMING_SNAKE_CASE						:   str         =			(
    string.ascii_letters + string.digits + string.punctuation + string.whitespace
)
__SCREAMING_SNAKE_CASE						:   list[int]         =			[ord(letter) for letter in string.ascii_lowercase]
__SCREAMING_SNAKE_CASE						:   set[int]         =			{ord(char) for char in VALID_CHARS}

__SCREAMING_SNAKE_CASE						:   list[str]         =			["the", "be", "to", "of", "and", "in", "that", "have"]
def  snake_case						(__lowercase ,      __lowercase						)	->	str | None:

						'''simple docstring'''



						_snake_case						:					str    =   ""
						_snake_case						:					int
						_snake_case						:					int
						_snake_case						:					int

						for keychar, cipherchar in zip(cycle(__lowercase						) ,      __lowercase						):
												_snake_case						:					str    =   cipherchar ^ keychar
												if decodedchar not in VALID_INTS:
																		return None
												decoded += chr(__lowercase						)

						return decoded
def  snake_case						(__lowercase						)	->	list[str]:

						'''simple docstring'''



						_snake_case						:					list[str]    =   []
						for key in product(__lowercase ,      repeat=3						):
												_snake_case						:					Union[str, Any]    =   try_key(__lowercase ,      __lowercase						)
												if encoded is not None:
																		possibles.append(__lowercase						)
						return possibles
def  snake_case						(__lowercase ,      __lowercase						)	->	list[str]:

						'''simple docstring'''



						return [possible for possible in possibles if common_word in possible.lower()]
def  snake_case						(__lowercase = "p059_cipher.txt"						)	->	int:

						'''simple docstring'''



						_snake_case						:					list[int]
						_snake_case						:					list[str]
						_snake_case						:					str
						_snake_case						:					str
						_snake_case						:					str    =   Path(__lowercase						).parent.joinpath(__lowercase						).read_text(encoding="utf-8"						)

						_snake_case						:					Dict    =   [int(__lowercase						) for number in data.strip().split(","						)]

						_snake_case						:					Tuple    =   filter_valid_chars(__lowercase						)
						for common_word in COMMON_WORDS:
												_snake_case						:					Optional[int]    =   filter_common_word(__lowercase ,      __lowercase						)
												if len(__lowercase						) == 1:
																		break

						_snake_case						:					int    =   possibles[0]
						return sum(ord(__lowercase						) for char in decoded_text						)


if __name__ == "__main__":
				print(F'''{solution() = }''')