




"""simple docstring"""


import itertools
import json
import os
import unittest

from transformers import AddedToken, LongformerTokenizer, LongformerTokenizerFast
from transformers.models.longformer.tokenization_longformer import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers, slow

from ...test_tokenization_common import TokenizerTesterMixin


@require_tokenizers
class _lowerCamelCase    (					a_       ,	unittest.TestCase						):
   _lowerCamelCase    :Any     				=     LongformerTokenizer
   _lowerCamelCase    :int     				=     True
   _lowerCamelCase    :int     				=     LongformerTokenizerFast
   _lowerCamelCase    :List[str]     				=     True






   def 	_lowerCAmelCase   (		self       :		Dict   )			->						Tuple:

         """simple docstring"""
         super().setUp()

         # Adapted from Sennrich et al. 2015 and https://github.com/rsennrich/subword-nmt
         lowerCAmelCase__      :			Optional[int]   =	[
             """l""",
             """o""",
             """w""",
             """e""",
             """r""",
             """s""",
             """t""",
             """i""",
             """d""",
             """n""",
             """\u0120""",
             """\u0120l""",
             """\u0120n""",
             """\u0120lo""",
             """\u0120low""",
             """er""",
             """\u0120lowest""",
             """\u0120newer""",
             """\u0120wider""",
             """<unk>""",
         ]
         lowerCAmelCase__      :			str   =	dict(zip(UpperCamelCase   ,     range(len(UpperCamelCase   )   )   )   )
         lowerCAmelCase__      :			Dict   =	["""#version: 0.2""", """\u0120 l""", """\u0120l o""", """\u0120lo w""", """e r""", """"""]
         lowerCAmelCase__      :			Union[str, Any]   =	{"""unk_token""": """<unk>"""}

         lowerCAmelCase__      :			Optional[int]   =	os.path.join(self.tmpdirname   ,     VOCAB_FILES_NAMES["""vocab_file"""]   )
         lowerCAmelCase__      :			Any   =	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 	_lowerCAmelCase   (		self       :		Optional[int]   ,     **UpperCamelCase       :		int   )			->						Optional[int]:

         """simple docstring"""
         kwargs.update(self.special_tokens_map   )
         return self.tokenizer_class.from_pretrained(self.tmpdirname   ,     **UpperCamelCase   )






   def 	_lowerCAmelCase   (		self       :		int   ,     **UpperCamelCase       :		Union[str, Any]   )			->						str:

         """simple docstring"""
         kwargs.update(self.special_tokens_map   )
         return self.rust_tokenizer_class.from_pretrained(self.tmpdirname   ,     **UpperCamelCase   )






   def 	_lowerCAmelCase   (		self       :		Optional[int]   ,     UpperCamelCase       :		List[Any]   )			->						Optional[Any]:

         """simple docstring"""
         lowerCAmelCase__      :			Optional[Any]   =	"""lower newer"""
         lowerCAmelCase__      :			Any   =	"""lower newer"""
         return input_text, output_text






   def 	_lowerCAmelCase   (		self       :		Any   )			->						Optional[int]:

         """simple docstring"""
         lowerCAmelCase__      :			Union[str, Any]   =	self.tokenizer_class(self.vocab_file   ,     self.merges_file   ,     **self.special_tokens_map   )
         lowerCAmelCase__      :			Any   =	"""lower newer"""
         lowerCAmelCase__      :			Union[str, Any]   =	["""l""", """o""", """w""", """er""", """\u0120""", """n""", """e""", """w""", """er"""]
         lowerCAmelCase__      :			int   =	tokenizer.tokenize(UpperCamelCase   )  # , add_prefix_space=True)
         self.assertListEqual(UpperCamelCase   ,     UpperCamelCase   )

         lowerCAmelCase__      :			Any   =	tokens + [tokenizer.unk_token]
         lowerCAmelCase__      :			List[str]   =	[0, 1, 2, 15, 10, 9, 3, 2, 15, 19]
         self.assertListEqual(tokenizer.convert_tokens_to_ids(UpperCamelCase   )   ,     UpperCamelCase   )






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

         """simple docstring"""
         lowerCAmelCase__      :			Dict   =	self.get_tokenizer()

         self.assertListEqual(tokenizer.encode("""Hello world!"""   ,     add_special_tokens=UpperCamelCase   )   ,     [0, 3_14_14, 2_32, 3_28, 2]   )
         self.assertListEqual(
             tokenizer.encode("""Hello world! cécé herlolip 418"""   ,     add_special_tokens=UpperCamelCase   )   ,     [0, 3_14_14, 2_32, 3_28, 7_40, 11_40, 1_26_95, 69, 4_60_78, 15_88, 2]   ,     )






   @slow
   def 	_lowerCAmelCase   (		self       :		List[str]   )			->						Tuple:

         """simple docstring"""
         lowerCAmelCase__      :			List[Any]   =	self.tokenizer_class.from_pretrained("""allenai/longformer-base-4096"""   )

         lowerCAmelCase__      :			Any   =	tokenizer.encode("""sequence builders"""   ,     add_special_tokens=UpperCamelCase   )
         lowerCAmelCase__      :			List[str]   =	tokenizer.encode("""multi-sequence build"""   ,     add_special_tokens=UpperCamelCase   )

         lowerCAmelCase__      :			Dict   =	tokenizer.encode(
             """sequence builders"""   ,     add_special_tokens=UpperCamelCase   ,     add_prefix_space=UpperCamelCase   )
         lowerCAmelCase__      :			Dict   =	tokenizer.encode(
             """sequence builders"""   ,     """multi-sequence build"""   ,     add_special_tokens=UpperCamelCase   ,     add_prefix_space=UpperCamelCase   )

         lowerCAmelCase__      :			List[Any]   =	tokenizer.build_inputs_with_special_tokens(UpperCamelCase   )
         lowerCAmelCase__      :			Tuple   =	tokenizer.build_inputs_with_special_tokens(UpperCamelCase   ,     UpperCamelCase   )

         assert encoded_sentence == encoded_text_from_decode
         assert encoded_pair == encoded_pair_from_decode






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

         """simple docstring"""
         lowerCAmelCase__      :			Optional[Any]   =	self.get_tokenizer()

         lowerCAmelCase__      :			Optional[int]   =	"""Encode this sequence."""
         lowerCAmelCase__      :			List[str]   =	tokenizer.byte_encoder[""" """.encode("""utf-8"""   )[0]]

         # Testing encoder arguments
         lowerCAmelCase__      :			str   =	tokenizer.encode(UpperCamelCase   ,     add_special_tokens=UpperCamelCase   ,     add_prefix_space=UpperCamelCase   )
         lowerCAmelCase__      :			Tuple   =	tokenizer.convert_ids_to_tokens(encoded[0]   )[0]
         self.assertNotEqual(UpperCamelCase   ,     UpperCamelCase   )

         lowerCAmelCase__      :			Dict   =	tokenizer.encode(UpperCamelCase   ,     add_special_tokens=UpperCamelCase   ,     add_prefix_space=UpperCamelCase   )
         lowerCAmelCase__      :			List[str]   =	tokenizer.convert_ids_to_tokens(encoded[0]   )[0]
         self.assertEqual(UpperCamelCase   ,     UpperCamelCase   )

         tokenizer.add_special_tokens({"""bos_token""": """<s>"""}   )
         lowerCAmelCase__      :			Union[str, Any]   =	tokenizer.encode(UpperCamelCase   ,     add_special_tokens=UpperCamelCase   )
         lowerCAmelCase__      :			str   =	tokenizer.convert_ids_to_tokens(encoded[1]   )[0]
         self.assertNotEqual(UpperCamelCase   ,     UpperCamelCase   )

         # Testing spaces after special tokens
         lowerCAmelCase__      :			str   =	"""<mask>"""
         tokenizer.add_special_tokens(
             {"""mask_token""": AddedToken(UpperCamelCase   ,     lstrip=UpperCamelCase   ,     rstrip=UpperCamelCase   )}   )  # mask token has a left space
         lowerCAmelCase__      :			Any   =	tokenizer.convert_tokens_to_ids(UpperCamelCase   )

         lowerCAmelCase__      :			Optional[int]   =	"""Encode <mask> sequence"""
         lowerCAmelCase__      :			List[Any]   =	"""Encode <mask>sequence"""

         lowerCAmelCase__      :			Dict   =	tokenizer.encode(UpperCamelCase   )
         lowerCAmelCase__      :			str   =	encoded.index(UpperCamelCase   )
         lowerCAmelCase__      :			Dict   =	tokenizer.convert_ids_to_tokens(encoded[mask_loc + 1]   )[0]
         self.assertEqual(UpperCamelCase   ,     UpperCamelCase   )

         lowerCAmelCase__      :			Tuple   =	tokenizer.encode(UpperCamelCase   )
         lowerCAmelCase__      :			Union[str, Any]   =	encoded.index(UpperCamelCase   )
         lowerCAmelCase__      :			Union[str, Any]   =	tokenizer.convert_ids_to_tokens(encoded[mask_loc + 1]   )[0]
         self.assertNotEqual(UpperCamelCase   ,     UpperCamelCase   )






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

         """simple docstring"""
         pass






   def 	_lowerCAmelCase   (		self       :		Any   )			->						Any:

         """simple docstring"""
         for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
               with self.subTest(f"""{tokenizer.__class__.__name__} ({pretrained_name})"""   ):
                     lowerCAmelCase__      :			Optional[Any]   =	self.rust_tokenizer_class.from_pretrained(UpperCamelCase   ,     **UpperCamelCase   )
                     lowerCAmelCase__      :			List[Any]   =	self.tokenizer_class.from_pretrained(UpperCamelCase   ,     **UpperCamelCase   )
                     lowerCAmelCase__      :			List[str]   =	"""A, <mask> AllenNLP sentence."""
                     lowerCAmelCase__      :			Any   =	tokenizer_r.encode_plus(UpperCamelCase   ,     add_special_tokens=UpperCamelCase   ,     return_token_type_ids=UpperCamelCase   )
                     lowerCAmelCase__      :			Tuple   =	tokenizer_p.encode_plus(UpperCamelCase   ,     add_special_tokens=UpperCamelCase   ,     return_token_type_ids=UpperCamelCase   )

                     # token_type_ids should put 0 everywhere
                     self.assertEqual(sum(tokens_r["""token_type_ids"""]   )   ,     sum(tokens_p["""token_type_ids"""]   )   )

                     # attention_mask should put 1 everywhere, so sum over length should be 1
                     self.assertEqual(
                         sum(tokens_r["""attention_mask"""]   ) / len(tokens_r["""attention_mask"""]   )   ,     sum(tokens_p["""attention_mask"""]   ) / len(tokens_p["""attention_mask"""]   )   ,     )

                     lowerCAmelCase__      :			Any   =	tokenizer_r.convert_ids_to_tokens(tokens_r["""input_ids"""]   )
                     lowerCAmelCase__      :			Union[str, Any]   =	tokenizer_p.convert_ids_to_tokens(tokens_p["""input_ids"""]   )

                     # Rust correctly handles the space before the mask while python doesnt
                     self.assertSequenceEqual(tokens_p["""input_ids"""]   ,     [0, 2_50, 6, 5_02_64, 38_23, 4_87, 2_19_92, 36_45, 4, 2]   )
                     self.assertSequenceEqual(tokens_r["""input_ids"""]   ,     [0, 2_50, 6, 5_02_64, 38_23, 4_87, 2_19_92, 36_45, 4, 2]   )

                     self.assertSequenceEqual(
                         UpperCamelCase   ,     ["""<s>""", """A""", """,""", """<mask>""", """ĠAllen""", """N""", """LP""", """Ġsentence""", """.""", """</s>"""]   )
                     self.assertSequenceEqual(
                         UpperCamelCase   ,     ["""<s>""", """A""", """,""", """<mask>""", """ĠAllen""", """N""", """LP""", """Ġsentence""", """.""", """</s>"""]   )






   def 	_lowerCAmelCase   (		self       :		List[str]   )			->						Dict:

         """simple docstring"""
         for trim_offsets, add_prefix_space in itertools.product([True, False]   ,     repeat=2   ):
               lowerCAmelCase__      :			Optional[int]   =	self.rust_tokenizer_class.from_pretrained(
                   self.tmpdirname   ,     use_fast=UpperCamelCase   ,     add_prefix_space=UpperCamelCase   ,     trim_offsets=UpperCamelCase   )

               lowerCAmelCase__      :			Union[str, Any]   =	json.loads(tokenizer_r.backend_tokenizer.pre_tokenizer.__getstate__()   )
               lowerCAmelCase__      :			Any   =	json.loads(tokenizer_r.backend_tokenizer.post_processor.__getstate__()   )

               self.assertEqual(pre_tokenizer_state["""add_prefix_space"""]   ,     UpperCamelCase   )

               self.assertEqual(post_processor_state["""add_prefix_space"""]   ,     UpperCamelCase   )
               self.assertEqual(post_processor_state["""trim_offsets"""]   ,     UpperCamelCase   )






   def 	_lowerCAmelCase   (		self       :		Dict   )			->						List[str]:

         """simple docstring"""
         # Test which aims to verify that the offsets are well adapted to the argument `add_prefix_space` and
         # `trim_offsets`
         for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
               with self.subTest(f"""{tokenizer.__class__.__name__} ({pretrained_name})"""   ):
                     lowerCAmelCase__      :			List[str]   =	"""hello"""  # `hello` is a token in the vocabulary of `pretrained_name`
                     lowerCAmelCase__      :			Any   =	f"""{text_of_1_token} {text_of_1_token}"""

                     lowerCAmelCase__      :			Optional[Any]   =	self.rust_tokenizer_class.from_pretrained(
                         UpperCamelCase   ,     use_fast=UpperCamelCase   ,     add_prefix_space=UpperCamelCase   ,     trim_offsets=UpperCamelCase   )
                     lowerCAmelCase__      :			Optional[Any]   =	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   ))   ,     )

                     lowerCAmelCase__      :			Union[str, Any]   =	self.rust_tokenizer_class.from_pretrained(
                         UpperCamelCase   ,     use_fast=UpperCamelCase   ,     add_prefix_space=UpperCamelCase   ,     trim_offsets=UpperCamelCase   )
                     lowerCAmelCase__      :			Union[str, Any]   =	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   ))   ,     )

                     lowerCAmelCase__      :			Union[str, Any]   =	self.rust_tokenizer_class.from_pretrained(
                         UpperCamelCase   ,     use_fast=UpperCamelCase   ,     add_prefix_space=UpperCamelCase   ,     trim_offsets=UpperCamelCase   )
                     lowerCAmelCase__      :			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   ), len(UpperCamelCase   ) + 1 + len(UpperCamelCase   ))   ,     )

                     lowerCAmelCase__      :			Union[str, Any]   =	self.rust_tokenizer_class.from_pretrained(
                         UpperCamelCase   ,     use_fast=UpperCamelCase   ,     add_prefix_space=UpperCamelCase   ,     trim_offsets=UpperCamelCase   )
                     lowerCAmelCase__      :			Tuple   =	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   ), len(UpperCamelCase   ) + 1 + len(UpperCamelCase   ))   ,     )

                     lowerCAmelCase__      :			Tuple   =	f""" {text}"""

                     # tokenizer_r = self.rust_tokenizer_class.from_pretrained(
                     #     pretrained_name, use_fast=True, add_prefix_space=True, trim_offsets=True
                     # )
                     # encoding = tokenizer_r(text, return_offsets_mapping=True, add_special_tokens=False)
                     # self.assertEqual(encoding.offset_mapping[0], (1, 1 + len(text_of_1_token)))
                     # self.assertEqual(
                     #     encoding.offset_mapping[1],
                     #     (1 + len(text_of_1_token) + 1, 1 + len(text_of_1_token) + 1 + len(text_of_1_token)),
                     # )

                     lowerCAmelCase__      :			Optional[int]   =	self.rust_tokenizer_class.from_pretrained(
                         UpperCamelCase   ,     use_fast=UpperCamelCase   ,     add_prefix_space=UpperCamelCase   ,     trim_offsets=UpperCamelCase   )
                     lowerCAmelCase__      :			List[Any]   =	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   ))   ,     )

                     lowerCAmelCase__      :			Optional[Any]   =	self.rust_tokenizer_class.from_pretrained(
                         UpperCamelCase   ,     use_fast=UpperCamelCase   ,     add_prefix_space=UpperCamelCase   ,     trim_offsets=UpperCamelCase   )
                     lowerCAmelCase__      :			int   =	tokenizer_r(UpperCamelCase   ,     return_offsets_mapping=UpperCamelCase   ,     add_special_tokens=UpperCamelCase   )
                     self.assertEqual(encoding.offset_mapping[0]   ,     (0, 1 + len(UpperCamelCase   ))   )
                     self.assertEqual(
                         encoding.offset_mapping[1]   ,     (1 + len(UpperCamelCase   ), 1 + len(UpperCamelCase   ) + 1 + len(UpperCamelCase   ))   ,     )

                     lowerCAmelCase__      :			int   =	self.rust_tokenizer_class.from_pretrained(
                         UpperCamelCase   ,     use_fast=UpperCamelCase   ,     add_prefix_space=UpperCamelCase   ,     trim_offsets=UpperCamelCase   )
                     lowerCAmelCase__      :			Optional[Any]   =	tokenizer_r(UpperCamelCase   ,     return_offsets_mapping=UpperCamelCase   ,     add_special_tokens=UpperCamelCase   )
                     self.assertEqual(encoding.offset_mapping[0]   ,     (0, 1 + len(UpperCamelCase   ))   )
                     self.assertEqual(
                         encoding.offset_mapping[1]   ,     (1 + len(UpperCamelCase   ), 1 + len(UpperCamelCase   ) + 1 + len(UpperCamelCase   ))   ,     )











"""simple docstring"""


import warnings

from ...utils import logging
from .image_processing_clip import CLIPImageProcessor


_A													=      logging.get_logger(__name__)


class _lowerCamelCase    (					a_						):






   def __init__(		self       :		Union[str, Any]   ,     *UpperCamelCase       :		int   ,     **UpperCamelCase       :		List[Any]   )			->						None:

         """simple docstring"""
         warnings.warn(
             """The class CLIPFeatureExtractor is deprecated and will be removed in version 5 of Transformers. Please"""
             """ use CLIPImageProcessor instead."""   ,     UpperCamelCase   ,     )
         super().__init__(*UpperCamelCase   ,     **UpperCamelCase   )





