
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		( SCREAMING_SNAKE_CASE__	,  unittest.TestCase		):
       lowercase_	:	str	 =LongformerTokenizer
       lowercase_	:	Dict	 =True
       lowercase_	:	Dict	 =LongformerTokenizerFast
       lowercase_	:	str	 =True




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

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

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




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




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




       def 			A__				(    self       ,A__):
            lowercase						     =						'''lower newer'''
            lowercase						     =						'''lower newer'''
            return input_text, output_text




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

            lowercase						     =						tokens + [tokenizer.unk_token]
            lowercase						     =						[0, 1, 2, 1_5, 1_0, 9, 3, 2, 1_5, 1_9]
            self.assertListEqual(tokenizer.convert_tokens_to_ids(A__)       ,A__)




       def 			A__				(    self):
            lowercase						     =						self.get_tokenizer()

            self.assertListEqual(tokenizer.encode('''Hello world!'''       ,add_special_tokens=A__)       ,[0, 3_1_4_1_4, 2_3_2, 3_2_8, 2])
            self.assertListEqual(
                tokenizer.encode('''Hello world! cécé herlolip 418'''       ,add_special_tokens=A__)       ,[0, 3_1_4_1_4, 2_3_2, 3_2_8, 7_4_0, 1_1_4_0, 1_2_6_9_5, 6_9, 4_6_0_7_8, 1_5_8_8, 2]       ,)




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

            lowercase						     =						tokenizer.encode('''sequence builders'''       ,add_special_tokens=A__)
            lowercase						     =						tokenizer.encode('''multi-sequence build'''       ,add_special_tokens=A__)

            lowercase						     =						tokenizer.encode(
                '''sequence builders'''       ,add_special_tokens=A__       ,add_prefix_space=A__)
            lowercase						     =						tokenizer.encode(
                '''sequence builders'''       ,'''multi-sequence build'''       ,add_special_tokens=A__       ,add_prefix_space=A__)

            lowercase						     =						tokenizer.build_inputs_with_special_tokens(A__)
            lowercase						     =						tokenizer.build_inputs_with_special_tokens(A__       ,A__)

            assert encoded_sentence == encoded_text_from_decode
            assert encoded_pair == encoded_pair_from_decode




       def 			A__				(    self):
            lowercase						     =						self.get_tokenizer()

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

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

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

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

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

            lowercase						     =						'''Encode <mask> sequence'''
            lowercase						     =						'''Encode <mask>sequence'''

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

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




       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})'):
                      lowercase						     =						self.rust_tokenizer_class.from_pretrained(A__       ,**A__)
                      lowercase						     =						self.tokenizer_class.from_pretrained(A__       ,**A__)
                      lowercase						     =						'''A, <mask> AllenNLP sentence.'''
                      lowercase						     =						tokenizer_r.encode_plus(A__       ,add_special_tokens=A__       ,return_token_type_ids=A__)
                      lowercase						     =						tokenizer_p.encode_plus(A__       ,add_special_tokens=A__       ,return_token_type_ids=A__)

                      # 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'''])       ,)

                      lowercase						     =						tokenizer_r.convert_ids_to_tokens(tokens_r['''input_ids'''])
                      lowercase						     =						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_5_0, 6, 5_0_2_6_4, 3_8_2_3, 4_8_7, 2_1_9_9_2, 3_6_4_5, 4, 2])
                      self.assertSequenceEqual(tokens_r['''input_ids''']       ,[0, 2_5_0, 6, 5_0_2_6_4, 3_8_2_3, 4_8_7, 2_1_9_9_2, 3_6_4_5, 4, 2])

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




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

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

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

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





       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})'):
                      lowercase						     =						'''hello'''  # `hello` is a token in the vocabulary of `pretrained_name`
                      lowercase						     =						f'{text_of_1_token} {text_of_1_token}'

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

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

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

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

                      lowercase						     =						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)),
                      # )

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

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

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






from __future__ import annotations

import unittest

from transformers import is_tf_available
from transformers.testing_utils import require_sentencepiece, require_tf, require_tokenizers, slow


if is_tf_available():
							import numpy as np
							import tensorflow as tf

							from transformers import TFXLMRobertaModel







@require_tf
@require_sentencepiece
@require_tokenizers
class     lowercase		( unittest.TestCase		):




							@slow
							def 			A__				(    self):
												lowercase						     =						TFXLMRobertaModel.from_pretrained('''jplu/tf-xlm-roberta-base''')

												lowercase						     =						{
												    '''input_ids''': tf.convert_to_tensor([[0, 2_6_4_6, 1_0_2_6_9, 8_3, 9_9_9_4_2, 2]]       ,dtype=tf.intaa),  # "My dog is cute"
												    '''attention_mask''': tf.convert_to_tensor([[1, 1, 1, 1, 1, 1]]       ,dtype=tf.intaa),
												}

												lowercase						     =						model(A__)['''last_hidden_state''']
												lowercase						     =						tf.TensorShape((1, 6, 7_6_8))
												self.assertEqual(output.shape       ,A__)
												# compare the actual values for a slice.
												lowercase						     =						tf.convert_to_tensor(
												    [
												        [
												            [0.0681762, 0.10894451, 0.06772504],
												            [-0.06423668, 0.02366615, 0.04329344],
												            [-0.06057295, 0.09974135, -0.00070584],
												        ]
												    ]       ,dtype=tf.floataa       ,)

												self.assertTrue(np.allclose(output[:, :3, :3].numpy()       ,expected_slice.numpy()       ,atol=1E-4))




