
'''simple docstring'''

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  _UpperCAmelCase ( lowerCAmelCase__	,unittest.TestCase    ):

					"""simple docstring"""

					a_    	=					CLIPTokenizer
					a_    	=					CLIPTokenizerFast
					a_    	=					True
					a_    	=					{}
					a_    	=					False


					def 							_lowerCAmelCase  (      self ):

							'''simple docstring'''

							super().setUp()

							# fmt: off
							a_      :	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
							a_      :	int      =							dict(zip(lowerCAmelCase_							,		range(len(lowerCAmelCase_ ) ) ) )
							a_      :	List[str]      =							["""#version: 0.2""", """l o""", """lo w</w>""", """e r</w>"""]
							a_      :	Any      =							{"""unk_token""": """<unk>"""}

							a_      :	int      =							os.path.join(self.tmpdirname							,		VOCAB_FILES_NAMES["""vocab_file"""] )
							a_      :	Dict      =							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(lowerCAmelCase_ ) + """\n""" )
							with open(self.merges_file							,		"""w"""							,		encoding="""utf-8""" ) as fp:
									fp.write("""\n""".join(lowerCAmelCase_ ) )


					def 							_lowerCAmelCase  (      self							,		**lowerCAmelCase_ ):

							'''simple docstring'''

							kwargs.update(self.special_tokens_map )
							return CLIPTokenizer.from_pretrained(self.tmpdirname							,		**lowerCAmelCase_ )


					def 							_lowerCAmelCase  (      self							,		**lowerCAmelCase_ ):

							'''simple docstring'''

							kwargs.update(self.special_tokens_map )
							return CLIPTokenizerFast.from_pretrained(self.tmpdirname							,		**lowerCAmelCase_ )


					def 							_lowerCAmelCase  (      self							,		lowerCAmelCase_ ):

							'''simple docstring'''

							a_      :	str      =							"""lower newer"""
							a_      :	List[Any]      =							"""lower newer"""
							return input_text, output_text


					def 							_lowerCAmelCase  (      self ):

							'''simple docstring'''

							a_      :	Dict      =							CLIPTokenizer(self.vocab_file							,		self.merges_file							,		**self.special_tokens_map )
							a_      :	Optional[Any]      =							"""lower newer"""
							a_      :	int      =							["""lo""", """w""", """er</w>""", """n""", """e""", """w""", """er</w>"""]
							a_      :	List[str]      =							tokenizer.tokenize(lowerCAmelCase_ )
							self.assertListEqual(lowerCAmelCase_							,		lowerCAmelCase_ )

							a_      :	Optional[Any]      =							tokens + [tokenizer.unk_token]
							a_      :	Optional[int]      =							[10, 2, 16, 9, 3, 2, 16, 20]
							self.assertListEqual(tokenizer.convert_tokens_to_ids(lowerCAmelCase_ )							,		lowerCAmelCase_ )


					@require_ftfy
					def 							_lowerCAmelCase  (      self ):

							'''simple docstring'''

							for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
									with self.subTest(f'''{tokenizer.__class__.__name__} ({pretrained_name})''' ):
											a_      :	Optional[int]      =							self.tokenizer_class.from_pretrained(lowerCAmelCase_							,		**lowerCAmelCase_ )
											a_      :	Dict      =							self.rust_tokenizer_class.from_pretrained(lowerCAmelCase_							,		**lowerCAmelCase_ )

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

											self.assertListEqual(lowerCAmelCase_							,		lowerCAmelCase_ )

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

											self.assertListEqual(lowerCAmelCase_							,		lowerCAmelCase_ )

											# Test that the tokenization is identical on unicode of space type
											a_      :	Optional[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:
													a_      :	Optional[int]      =							tokenizer_s.tokenize(lowerCAmelCase_ )
													a_      :	Tuple      =							tokenizer_r.tokenize(lowerCAmelCase_ )

													self.assertListEqual(lowerCAmelCase_							,		lowerCAmelCase_ )

											# Test that the tokenization is identical on unicode of line break type
											a_      :	Any      =							[
											    """\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:
													a_      :	Any      =							tokenizer_s.tokenize(lowerCAmelCase_ )
													a_      :	List[Any]      =							tokenizer_r.tokenize(lowerCAmelCase_ )

													self.assertListEqual(lowerCAmelCase_							,		lowerCAmelCase_ )


					def 							_lowerCAmelCase  (      self ):

							'''simple docstring'''

							for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
									with self.subTest(f'''{tokenizer.__class__.__name__} ({pretrained_name})''' ):
											a_      :	List[Any]      =							"""hello"""  # `hello` is a token in the vocabulary of `pretrained_name`
											a_      :	Tuple      =							f'''{text_of_1_token} {text_of_1_token}'''

											a_      :	List[str]      =							self.rust_tokenizer_class.from_pretrained(
											    lowerCAmelCase_							,		use_fast=lowerCAmelCase_							,		)
											a_      :	List[str]      =							tokenizer_r(lowerCAmelCase_							,		return_offsets_mapping=lowerCAmelCase_							,		add_special_tokens=lowerCAmelCase_ )
											self.assertEqual(encoding.offset_mapping[0]							,		(0, len(lowerCAmelCase_ )) )
											self.assertEqual(
											    encoding.offset_mapping[1]							,		(len(lowerCAmelCase_ ) + 1, len(lowerCAmelCase_ ) + 1 + len(lowerCAmelCase_ ))							,		)

											a_      :	Dict      =							f''' {text}'''

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


					def 							_lowerCAmelCase  (      self ):

							'''simple docstring'''

							with self.assertRaises(lowerCAmelCase_ ) 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 							_lowerCAmelCase  (      self ):

							'''simple docstring'''

							super().test_tokenization_python_rust_equals()






					def 							_lowerCAmelCase  (      self ):

							'''simple docstring'''

							pass




'''simple docstring'''

import os
from shutil import copyfile
from typing import List, Optional, Tuple

import sentencepiece as spm

from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging


__snake_case:  Optional[Any]								=			logging.get_logger(__name__)

__snake_case:  Tuple								=			{"vocab_file": "sentencepiece.model"}

__snake_case:  int								=			{
    "vocab_file": {
        "google/rembert": "https://huggingface.co/google/rembert/resolve/main/sentencepiece.model",
    },
}

__snake_case:  Union[str, Any]								=			{
    "google/rembert": 2_56,
}


class  _UpperCAmelCase ( lowerCAmelCase__    ):

     """simple docstring"""

     a_    	=					VOCAB_FILES_NAMES
     a_    	=					PRETRAINED_VOCAB_FILES_MAP
     a_    	=					PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES


     def __init__(      self							,		lowerCAmelCase_							,		lowerCAmelCase_=False							,		lowerCAmelCase_=True							,		lowerCAmelCase_=True							,		lowerCAmelCase_="[CLS]"							,		lowerCAmelCase_="[SEP]"							,		lowerCAmelCase_="[UNK]"							,		lowerCAmelCase_="[SEP]"							,		lowerCAmelCase_="[PAD]"							,		lowerCAmelCase_="[CLS]"							,		lowerCAmelCase_="[MASK]"							,		**lowerCAmelCase_							,		):

       '''simple docstring'''

       super().__init__(
           do_lower_case=lowerCAmelCase_							,		remove_space=lowerCAmelCase_							,		keep_accents=lowerCAmelCase_							,		bos_token=lowerCAmelCase_							,		eos_token=lowerCAmelCase_							,		unk_token=lowerCAmelCase_							,		sep_token=lowerCAmelCase_							,		pad_token=lowerCAmelCase_							,		cls_token=lowerCAmelCase_							,		mask_token=lowerCAmelCase_							,		**lowerCAmelCase_							,		)

       a_      :	int      =							do_lower_case
       a_      :	int      =							remove_space
       a_      :	Dict      =							keep_accents
       a_      :	Union[str, Any]      =							vocab_file

       a_      :	List[str]      =							spm.SentencePieceProcessor()
       self.sp_model.Load(lowerCAmelCase_ )


     @property
     def 							_lowerCAmelCase  (      self ):

       '''simple docstring'''

       return len(self.sp_model )


     def 							_lowerCAmelCase  (      self ):

       '''simple docstring'''

       a_      :	Dict      =							{self.convert_ids_to_tokens(lowerCAmelCase_ ): i for i in range(self.vocab_size )}
       vocab.update(self.added_tokens_encoder )
       return vocab


     def __getstate__(      self ):

       '''simple docstring'''

       a_      :	Union[str, Any]      =							self.__dict__.copy()
       a_      :	Optional[Any]      =							None
       return state


     def __setstate__(      self							,		lowerCAmelCase_ ):

       '''simple docstring'''

       a_      :	int      =							d
       a_      :	Optional[int]      =							spm.SentencePieceProcessor()
       self.sp_model.Load(self.vocab_file )


     def 							_lowerCAmelCase  (      self							,		lowerCAmelCase_							,		lowerCAmelCase_=False ):

       '''simple docstring'''

       a_      :	Tuple      =							self.sp_model.EncodeAsPieces(lowerCAmelCase_ )
       return pieces


     def 							_lowerCAmelCase  (      self							,		lowerCAmelCase_ ):

       '''simple docstring'''

       return self.sp_model.PieceToId(lowerCAmelCase_ )


     def 							_lowerCAmelCase  (      self							,		lowerCAmelCase_ ):

       '''simple docstring'''

       return self.sp_model.IdToPiece(lowerCAmelCase_ )


     def 							_lowerCAmelCase  (      self							,		lowerCAmelCase_ ):

       '''simple docstring'''

       a_      :	Tuple      =							self.sp_model.decode_pieces(lowerCAmelCase_ )
       return out_string


     def 							_lowerCAmelCase  (      self							,		lowerCAmelCase_							,		lowerCAmelCase_ = None ):

       '''simple docstring'''

       a_      :	List[Any]      =							[self.sep_token_id]
       a_      :	Tuple      =							[self.cls_token_id]
       if token_ids_a is None:
         return cls + token_ids_a + sep
       return cls + token_ids_a + sep + token_ids_a + sep


     def 							_lowerCAmelCase  (      self							,		lowerCAmelCase_							,		lowerCAmelCase_ = None							,		lowerCAmelCase_ = False ):

       '''simple docstring'''

       if already_has_special_tokens:
         if token_ids_a is not None:
           raise ValueError(
               """You should not supply a second sequence if the provided sequence of """
               """ids is already formatted with special tokens for the model.""" )
         return [1 if x in [self.sep_token_id, self.cls_token_id] else 0 for x in token_ids_a]

       if token_ids_a is not None:
         return [1] + ([0] * len(lowerCAmelCase_ )) + [1] + ([0] * len(lowerCAmelCase_ )) + [1]
       return [1] + ([0] * len(lowerCAmelCase_ )) + [1]


     def 							_lowerCAmelCase  (      self							,		lowerCAmelCase_							,		lowerCAmelCase_ = None ):

       '''simple docstring'''

       a_      :	Optional[int]      =							[self.sep_token_id]
       a_      :	Optional[Any]      =							[self.cls_token_id]

       if token_ids_a is None:
         return len(cls + token_ids_a + sep ) * [0]
       return len(cls + token_ids_a + sep ) * [0] + len(token_ids_a + sep ) * [1]






     def 							_lowerCAmelCase  (      self							,		lowerCAmelCase_							,		lowerCAmelCase_ = None ):

       '''simple docstring'''

       if not os.path.isdir(lowerCAmelCase_ ):
         logger.error("""Vocabulary path ({}) should be a directory""".format(lowerCAmelCase_ ) )
         return
       a_      :	List[str]      =							os.path.join(
           lowerCAmelCase_							,		(filename_prefix + """-""" if filename_prefix else """""") + VOCAB_FILES_NAMES["""vocab_file"""] )

       if os.path.abspath(self.vocab_file ) != os.path.abspath(lowerCAmelCase_ ):
         copyfile(self.vocab_file							,		lowerCAmelCase_ )

       return (out_vocab_file,)


