






import json
import os
import unittest

from transformers import CLIPTokenizer, CLIPTokenizerFast
from transformers.models.clip.tokenization_clip import VOCAB_FILES_NAMES
from transformers.testing_utils import require_ftfy, require_tokenizers

from ...test_tokenization_common import TokenizerTesterMixin



@require_tokenizers
class   lowerCamelCase      (_snake_case ,  unittest.TestCase			):







		'''simple docstring'''



		_snake_case    :    int       						=  CLIPTokenizer
		_snake_case    :    Tuple       						=  CLIPTokenizerFast
		_snake_case    :    List[Any]       						=  True
		_snake_case    :    Dict       						=  {}
		_snake_case    :    Optional[int]       						=  False



		def 					__UpperCAmelCase			(							self   )	->							Tuple:
							super().setUp()

							# fmt: off
							UpperCAmelCase_    :      str            =						['l', 'o', 'w', 'e', 'r', 's', 't', 'i', 'd', 'n', 'lo', 'l</w>', 'w</w>', 'r</w>', 't</w>', 'low</w>', 'er</w>', 'lowest</w>', 'newer</w>', 'wider', '<unk>', '<|startoftext|>', '<|endoftext|>']
							# fmt: on
							UpperCAmelCase_    :      Optional[int]            =						dict(zip(_UpperCamelCase				,		range(len(_UpperCamelCase   )   )   )   )
							UpperCAmelCase_    :      Tuple            =						['#version: 0.2', 'l o', 'lo w</w>', 'e r</w>']
							UpperCAmelCase_    :      Any            =						{'unk_token': '<unk>'}

							UpperCAmelCase_    :      int            =						os.path.join(self.tmpdirname				,		VOCAB_FILES_NAMES['vocab_file']   )
							UpperCAmelCase_    :      int            =						os.path.join(self.tmpdirname				,		VOCAB_FILES_NAMES['merges_file']   )
							with open(self.vocab_file				,		'w'				,		encoding='utf-8'   ) as fp:
												fp.write(json.dumps(_UpperCamelCase   ) + '\n'   )
							with open(self.merges_file				,		'w'				,		encoding='utf-8'   ) as fp:
												fp.write('\n'.join(_UpperCamelCase   )   )



		def 					__UpperCAmelCase			(							self				,		**_UpperCamelCase   )	->							Optional[Any]:
							kwargs.update(self.special_tokens_map   )
							return CLIPTokenizer.from_pretrained(self.tmpdirname				,		**_UpperCamelCase   )



		def 					__UpperCAmelCase			(							self				,		**_UpperCamelCase   )	->							Any:
							kwargs.update(self.special_tokens_map   )
							return CLIPTokenizerFast.from_pretrained(self.tmpdirname				,		**_UpperCamelCase   )



		def 					__UpperCAmelCase			(							self				,		_UpperCamelCase   )	->							Any:
							UpperCAmelCase_    :      List[str]            =						'lower newer'
							UpperCAmelCase_    :      Any            =						'lower newer'
							return input_text, output_text



		def 					__UpperCAmelCase			(							self   )	->							List[str]:
							UpperCAmelCase_    :      List[Any]            =						CLIPTokenizer(self.vocab_file				,		self.merges_file				,		**self.special_tokens_map   )
							UpperCAmelCase_    :      Tuple            =						'lower newer'
							UpperCAmelCase_    :      Any            =						['lo', 'w', 'er</w>', 'n', 'e', 'w', 'er</w>']
							UpperCAmelCase_    :      Optional[int]            =						tokenizer.tokenize(_UpperCamelCase   )
							self.assertListEqual(_UpperCamelCase				,		_UpperCamelCase   )

							UpperCAmelCase_    :      List[Any]            =						tokens + [tokenizer.unk_token]
							UpperCAmelCase_    :      List[Any]            =						[1_0, 2, 1_6, 9, 3, 2, 1_6, 2_0]
							self.assertListEqual(tokenizer.convert_tokens_to_ids(_UpperCamelCase   )				,		_UpperCamelCase   )



		@require_ftfy
		def 					__UpperCAmelCase			(							self   )	->							Optional[Any]:
							for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
												with self.subTest(f"{tokenizer.__class__.__name__} ({pretrained_name})"   ):
																	UpperCAmelCase_    :      List[Any]            =						self.tokenizer_class.from_pretrained(_UpperCamelCase				,		**_UpperCamelCase   )
																	UpperCAmelCase_    :      int            =						self.rust_tokenizer_class.from_pretrained(_UpperCamelCase				,		**_UpperCamelCase   )

																	UpperCAmelCase_    :      Optional[int]            =						'A\n\'ll 11p223RF☆ho!!to?\'d\'d\'\'d of a cat to-$\'\'d.'
																	UpperCAmelCase_    :      str            =						tokenizer_s.tokenize(_UpperCamelCase   )
																	UpperCAmelCase_    :      Optional[Any]            =						tokenizer_r.tokenize(_UpperCamelCase   )

																	self.assertListEqual(_UpperCamelCase				,		_UpperCamelCase   )

																	# Test that the tokenization is identical on an example containing a character (Latin Small Letter A
																	# with Tilde) encoded in 2 different ways
																	UpperCAmelCase_    :      Any            =						'xa\u0303y' + ' ' + 'x\xe3y'
																	UpperCAmelCase_    :      Optional[int]            =						tokenizer_s.tokenize(_UpperCamelCase   )
																	UpperCAmelCase_    :      Any            =						tokenizer_r.tokenize(_UpperCamelCase   )

																	self.assertListEqual(_UpperCamelCase				,		_UpperCamelCase   )

																	# Test that the tokenization is identical on unicode of space type
																	UpperCAmelCase_    :      int            =						[
																	    '\u0009',  # (horizontal tab, '\t')
																	    '\u000B',  # (vertical tab)
																	    '\u000C',  # (form feed)
																	    '\u0020',  # (space, ' ')
																	    '\u200E',  # (left-to-right mark):w
																	    '\u200F',  # (right-to-left mark)
																	]
																	for unicode_seq in spaces_unicodes:
																						UpperCAmelCase_    :      Optional[Any]            =						tokenizer_s.tokenize(_UpperCamelCase   )
																						UpperCAmelCase_    :      Union[str, Any]            =						tokenizer_r.tokenize(_UpperCamelCase   )

																						self.assertListEqual(_UpperCamelCase				,		_UpperCamelCase   )

																	# Test that the tokenization is identical on unicode of line break type
																	UpperCAmelCase_    :      str            =						[
																	    '\u000A',  # (line feed, '\n')
																	    '\r\n',  # (carriage return and line feed, '\r\n')
																	    '\u000D',  # (carriage return, '\r')
																	    '\r',  # (carriage return, '\r')
																	    '\u000D',  # (carriage return, '\r')
																	    '\u2028',  # (line separator)
																	    '\u2029',  # (paragraph separator)
																	    # "\u0085", # (next line)
																	]

																	# The tokenization is not identical for the character "\u0085" (next line). The slow version using ftfy transforms
																	# it into the Horizontal Ellipsis character "…" ("\u2026") while the fast version transforms it into a
																	# space (and thus into an empty list).

																	for unicode_seq in line_break_unicodes:
																						UpperCAmelCase_    :      Any            =						tokenizer_s.tokenize(_UpperCamelCase   )
																						UpperCAmelCase_    :      int            =						tokenizer_r.tokenize(_UpperCamelCase   )

																						self.assertListEqual(_UpperCamelCase				,		_UpperCamelCase   )



		def 					__UpperCAmelCase			(							self   )	->							Dict:
							# Test which aims to verify that the offsets are well adapted to the argument `add_prefix_space`
							for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
												with self.subTest(f"{tokenizer.__class__.__name__} ({pretrained_name})"   ):
																	UpperCAmelCase_    :      str            =						'hello'  # `hello` is a token in the vocabulary of `pretrained_name`
																	UpperCAmelCase_    :      Optional[int]            =						f"{text_of_1_token} {text_of_1_token}"

																	UpperCAmelCase_    :      Union[str, Any]            =						self.rust_tokenizer_class.from_pretrained(
																	    _UpperCamelCase				,		use_fast=_UpperCamelCase				,		)
																	UpperCAmelCase_    :      int            =						tokenizer_r(_UpperCamelCase				,		return_offsets_mapping=_UpperCamelCase				,		add_special_tokens=_UpperCamelCase   )
																	self.assertEqual(encoding.offset_mapping[0]				,		(0, len(_UpperCamelCase   ))   )
																	self.assertEqual(
																	    encoding.offset_mapping[1]				,		(len(_UpperCamelCase   ) + 1, len(_UpperCamelCase   ) + 1 + len(_UpperCamelCase   ))				,		)

																	UpperCAmelCase_    :      Optional[int]            =						f" {text}"

																	UpperCAmelCase_    :      Tuple            =						self.rust_tokenizer_class.from_pretrained(
																	    _UpperCamelCase				,		use_fast=_UpperCamelCase				,		)
																	UpperCAmelCase_    :      int            =						tokenizer_r(_UpperCamelCase				,		return_offsets_mapping=_UpperCamelCase				,		add_special_tokens=_UpperCamelCase   )
																	self.assertEqual(encoding.offset_mapping[0]				,		(1, 1 + len(_UpperCamelCase   ))   )
																	self.assertEqual(
																	    encoding.offset_mapping[1]				,		(1 + len(_UpperCamelCase   ) + 1, 1 + len(_UpperCamelCase   ) + 1 + len(_UpperCamelCase   ))				,		)



		def 					__UpperCAmelCase			(							self   )	->							Any:
							# Test related to the breaking change introduced in transformers v4.17.0
							# We need to check that an error in raised when the user try to load a previous version of the tokenizer.
							with self.assertRaises(_UpperCamelCase   ) as context:
												self.rust_tokenizer_class.from_pretrained('robot-test/old-clip-tokenizer'   )

							self.assertTrue(
							    context.exception.args[0].startswith(
							        'The `backend_tokenizer` provided does not match the expected format.'   )   )



		@require_ftfy
		def 					__UpperCAmelCase			(							self   )	->							Optional[Any]:
							super().test_tokenization_python_rust_equals()



		def 					__UpperCAmelCase			(							self   )	->							List[Any]:
							# CLIP always lower cases letters
							pass












def 			__magic_name__				( A		:					str   ):






			'''simple docstring'''







			a    =			""
			for ch in key:
						if ch == " " or ch not in key_no_dups and ch.isalpha():
									key_no_dups += ch
			return key_no_dups




def 			__magic_name__				( A		:					str   ):






			'''simple docstring'''







			a    =			[chr(i + 65   ) for i in range(26   )]
			# Remove duplicate characters from key
			a    =			remove_duplicates(key.upper()   )
			a    =			len(A   )
			# First fill cipher with key characters
			a    =			{alphabet[i]: char for i, char in enumerate(A   )}
			# Then map remaining characters in alphabet to
			# the alphabet from the beginning
			for i in range(len(A   ),  26   ):
						a    =			alphabet[i - offset]
						# Ensure we are not mapping letters to letters previously mapped
						while char in key:
									offset -= 1
									a    =			alphabet[i - offset]
						a    =			char
			return cipher_alphabet




def 			__magic_name__				( A		:					str,  A		:					dict[str, str]   ):






			'''simple docstring'''







			return "".join(cipher_map.get(A,  A   ) for ch in message.upper()   )




def 			__magic_name__				( A		:					str,  A		:					dict[str, str]   ):






			'''simple docstring'''







			a    =			{v: k for k, v in cipher_map.items()}
			return "".join(rev_cipher_map.get(A,  A   ) for ch in message.upper()   )




def 			__magic_name__				( ):






			'''simple docstring'''







			a    =			input("Enter message to encode or decode: "   ).strip()
			a    =			input("Enter keyword: "   ).strip()
			a    =			input("Encipher or decipher? E/D:"   ).strip()[0].lower()
			try:
						a    =			{"e": encipher, "d": decipher}[option]
			except KeyError:
						raise KeyError("invalid input option"   )
			a    =			create_cipher_map(A   )
			print(func(A,  A   )   )


if __name__ == "__main__":
		import doctest

		doctest.testmod()
		main()






