

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 				lowercase       ( lowercase_			,						unittest.TestCase    ):
    __SCREAMING_SNAKE_CASE      :				int     =    LongformerTokenizer
    __SCREAMING_SNAKE_CASE      :				Dict     =    True
    __SCREAMING_SNAKE_CASE      :				Union[str, Any]     =    LongformerTokenizerFast
    __SCREAMING_SNAKE_CASE      :				Optional[Any]     =    True




    def 					a							(      self ):
           super().setUp()

           # Adapted from Sennrich et al. 2015 and https://github.com/rsennrich/subword-nmt
           snake_case_           =					[
               'l',
               'o',
               'w',
               'e',
               'r',
               's',
               't',
               'i',
               'd',
               'n',
               '\u0120',
               '\u0120l',
               '\u0120n',
               '\u0120lo',
               '\u0120low',
               'er',
               '\u0120lowest',
               '\u0120newer',
               '\u0120wider',
               '<unk>',
           ]
           snake_case_           =					dict(zip(snake_case   ,     range(len(snake_case ) ) ) )
           snake_case_           =					['#version: 0.2', '\u0120 l', '\u0120l o', '\u0120lo w', 'e r', '']
           snake_case_           =					{'unk_token': '<unk>'}

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




    def 					a							(      self   ,     **snake_case ):
           kwargs.update(self.special_tokens_map )
           return self.tokenizer_class.from_pretrained(self.tmpdirname   ,     **snake_case )




    def 					a							(      self   ,     **snake_case ):
           kwargs.update(self.special_tokens_map )
           return self.rust_tokenizer_class.from_pretrained(self.tmpdirname   ,     **snake_case )




    def 					a							(      self   ,     snake_case ):
           snake_case_           =					'lower newer'
           snake_case_           =					'lower newer'
           return input_text, output_text




    def 					a							(      self ):
           snake_case_           =					self.tokenizer_class(self.vocab_file   ,     self.merges_file   ,     **self.special_tokens_map )
           snake_case_           =					'lower newer'
           snake_case_           =					['l', 'o', 'w', 'er', '\u0120', 'n', 'e', 'w', 'er']
           snake_case_           =					tokenizer.tokenize(snake_case )  # , add_prefix_space=True)
           self.assertListEqual(snake_case   ,     snake_case )

           snake_case_           =					tokens + [tokenizer.unk_token]
           snake_case_           =					[0, 1, 2, 15, 10, 9, 3, 2, 15, 19]
           self.assertListEqual(tokenizer.convert_tokens_to_ids(snake_case )   ,     snake_case )




    def 					a							(      self ):
           snake_case_           =					self.get_tokenizer()

           self.assertListEqual(tokenizer.encode('Hello world!'   ,     add_special_tokens=snake_case )   ,     [0, 3_1414, 232, 328, 2] )
           self.assertListEqual(
               tokenizer.encode('Hello world! cécé herlolip 418'   ,     add_special_tokens=snake_case )   ,     [0, 3_1414, 232, 328, 740, 1140, 1_2695, 69, 4_6078, 1588, 2]   ,     )




    @slow
    def 					a							(      self ):
           snake_case_           =					self.tokenizer_class.from_pretrained('allenai/longformer-base-4096' )

           snake_case_           =					tokenizer.encode('sequence builders'   ,     add_special_tokens=snake_case )
           snake_case_           =					tokenizer.encode('multi-sequence build'   ,     add_special_tokens=snake_case )

           snake_case_           =					tokenizer.encode(
               'sequence builders'   ,     add_special_tokens=snake_case   ,     add_prefix_space=snake_case )
           snake_case_           =					tokenizer.encode(
               'sequence builders'   ,     'multi-sequence build'   ,     add_special_tokens=snake_case   ,     add_prefix_space=snake_case )

           snake_case_           =					tokenizer.build_inputs_with_special_tokens(snake_case )
           snake_case_           =					tokenizer.build_inputs_with_special_tokens(snake_case   ,     snake_case )

           assert encoded_sentence == encoded_text_from_decode
           assert encoded_pair == encoded_pair_from_decode




    def 					a							(      self ):
           snake_case_           =					self.get_tokenizer()

           snake_case_           =					'Encode this sequence.'
           snake_case_           =					tokenizer.byte_encoder[' '.encode('utf-8' )[0]]

           # Testing encoder arguments
           snake_case_           =					tokenizer.encode(snake_case   ,     add_special_tokens=snake_case   ,     add_prefix_space=snake_case )
           snake_case_           =					tokenizer.convert_ids_to_tokens(encoded[0] )[0]
           self.assertNotEqual(snake_case   ,     snake_case )

           snake_case_           =					tokenizer.encode(snake_case   ,     add_special_tokens=snake_case   ,     add_prefix_space=snake_case )
           snake_case_           =					tokenizer.convert_ids_to_tokens(encoded[0] )[0]
           self.assertEqual(snake_case   ,     snake_case )

           tokenizer.add_special_tokens({'bos_token': '<s>'} )
           snake_case_           =					tokenizer.encode(snake_case   ,     add_special_tokens=snake_case )
           snake_case_           =					tokenizer.convert_ids_to_tokens(encoded[1] )[0]
           self.assertNotEqual(snake_case   ,     snake_case )

           # Testing spaces after special tokens
           snake_case_           =					'<mask>'
           tokenizer.add_special_tokens(
               {'mask_token': AddedToken(snake_case   ,     lstrip=snake_case   ,     rstrip=snake_case )} )  # mask token has a left space
           snake_case_           =					tokenizer.convert_tokens_to_ids(snake_case )

           snake_case_           =					'Encode <mask> sequence'
           snake_case_           =					'Encode <mask>sequence'

           snake_case_           =					tokenizer.encode(snake_case )
           snake_case_           =					encoded.index(snake_case )
           snake_case_           =					tokenizer.convert_ids_to_tokens(encoded[mask_loc + 1] )[0]
           self.assertEqual(snake_case   ,     snake_case )

           snake_case_           =					tokenizer.encode(snake_case )
           snake_case_           =					encoded.index(snake_case )
           snake_case_           =					tokenizer.convert_ids_to_tokens(encoded[mask_loc + 1] )[0]
           self.assertNotEqual(snake_case   ,     snake_case )




    def 					a							(      self ):
           pass




    def 					a							(      self ):
           for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
                  with self.subTest(F'''{tokenizer.__class__.__name__} ({pretrained_name})''' ):
                         snake_case_           =					self.rust_tokenizer_class.from_pretrained(snake_case   ,     **snake_case )
                         snake_case_           =					self.tokenizer_class.from_pretrained(snake_case   ,     **snake_case )
                         snake_case_           =					'A, <mask> AllenNLP sentence.'
                         snake_case_           =					tokenizer_r.encode_plus(snake_case   ,     add_special_tokens=snake_case   ,     return_token_type_ids=snake_case )
                         snake_case_           =					tokenizer_p.encode_plus(snake_case   ,     add_special_tokens=snake_case   ,     return_token_type_ids=snake_case )

                         # 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'] )   ,     )

                         snake_case_           =					tokenizer_r.convert_ids_to_tokens(tokens_r['input_ids'] )
                         snake_case_           =					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, 250, 6, 5_0264, 3823, 487, 2_1992, 3645, 4, 2] )
                         self.assertSequenceEqual(tokens_r['input_ids']   ,     [0, 250, 6, 5_0264, 3823, 487, 2_1992, 3645, 4, 2] )

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




    def 					a							(      self ):
           for trim_offsets, add_prefix_space in itertools.product([True, False]   ,     repeat=2 ):
                  snake_case_           =					self.rust_tokenizer_class.from_pretrained(
                      self.tmpdirname   ,     use_fast=snake_case   ,     add_prefix_space=snake_case   ,     trim_offsets=snake_case )

                  snake_case_           =					json.loads(tokenizer_r.backend_tokenizer.pre_tokenizer.__getstate__() )
                  snake_case_           =					json.loads(tokenizer_r.backend_tokenizer.post_processor.__getstate__() )

                  self.assertEqual(pre_tokenizer_state['add_prefix_space']   ,     snake_case )

                  self.assertEqual(post_processor_state['add_prefix_space']   ,     snake_case )
                  self.assertEqual(post_processor_state['trim_offsets']   ,     snake_case )




    def 					a							(      self ):
           # 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})''' ):
                         snake_case_           =					'hello'  # `hello` is a token in the vocabulary of `pretrained_name`
                         snake_case_           =					F'''{text_of_1_token} {text_of_1_token}'''

                         snake_case_           =					self.rust_tokenizer_class.from_pretrained(
                             snake_case   ,     use_fast=snake_case   ,     add_prefix_space=snake_case   ,     trim_offsets=snake_case )
                         snake_case_           =					tokenizer_r(snake_case   ,     return_offsets_mapping=snake_case   ,     add_special_tokens=snake_case )
                         self.assertEqual(encoding.offset_mapping[0]   ,     (0, len(snake_case )) )
                         self.assertEqual(
                             encoding.offset_mapping[1]   ,     (len(snake_case ) + 1, len(snake_case ) + 1 + len(snake_case ))   ,     )

                         snake_case_           =					self.rust_tokenizer_class.from_pretrained(
                             snake_case   ,     use_fast=snake_case   ,     add_prefix_space=snake_case   ,     trim_offsets=snake_case )
                         snake_case_           =					tokenizer_r(snake_case   ,     return_offsets_mapping=snake_case   ,     add_special_tokens=snake_case )
                         self.assertEqual(encoding.offset_mapping[0]   ,     (0, len(snake_case )) )
                         self.assertEqual(
                             encoding.offset_mapping[1]   ,     (len(snake_case ) + 1, len(snake_case ) + 1 + len(snake_case ))   ,     )

                         snake_case_           =					self.rust_tokenizer_class.from_pretrained(
                             snake_case   ,     use_fast=snake_case   ,     add_prefix_space=snake_case   ,     trim_offsets=snake_case )
                         snake_case_           =					tokenizer_r(snake_case   ,     return_offsets_mapping=snake_case   ,     add_special_tokens=snake_case )
                         self.assertEqual(encoding.offset_mapping[0]   ,     (0, len(snake_case )) )
                         self.assertEqual(
                             encoding.offset_mapping[1]   ,     (len(snake_case ), len(snake_case ) + 1 + len(snake_case ))   ,     )

                         snake_case_           =					self.rust_tokenizer_class.from_pretrained(
                             snake_case   ,     use_fast=snake_case   ,     add_prefix_space=snake_case   ,     trim_offsets=snake_case )
                         snake_case_           =					tokenizer_r(snake_case   ,     return_offsets_mapping=snake_case   ,     add_special_tokens=snake_case )
                         self.assertEqual(encoding.offset_mapping[0]   ,     (0, len(snake_case )) )
                         self.assertEqual(
                             encoding.offset_mapping[1]   ,     (len(snake_case ), len(snake_case ) + 1 + len(snake_case ))   ,     )

                         snake_case_           =					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)),
                         # )

                         snake_case_           =					self.rust_tokenizer_class.from_pretrained(
                             snake_case   ,     use_fast=snake_case   ,     add_prefix_space=snake_case   ,     trim_offsets=snake_case )
                         snake_case_           =					tokenizer_r(snake_case   ,     return_offsets_mapping=snake_case   ,     add_special_tokens=snake_case )
                         self.assertEqual(encoding.offset_mapping[0]   ,     (1, 1 + len(snake_case )) )
                         self.assertEqual(
                             encoding.offset_mapping[1]   ,     (1 + len(snake_case ) + 1, 1 + len(snake_case ) + 1 + len(snake_case ))   ,     )

                         snake_case_           =					self.rust_tokenizer_class.from_pretrained(
                             snake_case   ,     use_fast=snake_case   ,     add_prefix_space=snake_case   ,     trim_offsets=snake_case )
                         snake_case_           =					tokenizer_r(snake_case   ,     return_offsets_mapping=snake_case   ,     add_special_tokens=snake_case )
                         self.assertEqual(encoding.offset_mapping[0]   ,     (0, 1 + len(snake_case )) )
                         self.assertEqual(
                             encoding.offset_mapping[1]   ,     (1 + len(snake_case ), 1 + len(snake_case ) + 1 + len(snake_case ))   ,     )

                         snake_case_           =					self.rust_tokenizer_class.from_pretrained(
                             snake_case   ,     use_fast=snake_case   ,     add_prefix_space=snake_case   ,     trim_offsets=snake_case )
                         snake_case_           =					tokenizer_r(snake_case   ,     return_offsets_mapping=snake_case   ,     add_special_tokens=snake_case )
                         self.assertEqual(encoding.offset_mapping[0]   ,     (0, 1 + len(snake_case )) )
                         self.assertEqual(
                             encoding.offset_mapping[1]   ,     (1 + len(snake_case ), 1 + len(snake_case ) + 1 + len(snake_case ))   ,     )







import warnings

from ...utils import logging
from .image_processing_deformable_detr import DeformableDetrImageProcessor


_UpperCAmelCase	:     Any		       = logging.get_logger(__name__)







class 				lowercase       ( lowercase_    ):




				def __init__(      self   ,     *snake_case   ,     **snake_case ):
											warnings.warn(
											    'The class DeformableDetrFeatureExtractor is deprecated and will be removed in version 5 of Transformers.'
											    ' Please use DeformableDetrImageProcessor instead.'   ,     snake_case   ,     )
											super().__init__(*snake_case   ,     **snake_case )




