import itertools
import json
import os
import unittest

from transformers import AddedToken, RobertaTokenizer, RobertaTokenizerFast
from transformers.models.roberta.tokenization_roberta import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers, slow

from ...test_tokenization_common import TokenizerTesterMixin




@require_tokenizers
class 					_UpperCAmelCase			(     __SCREAMING_SNAKE_CASE,			unittest.TestCase  ):



 '''simple docstring'''




 __A			       =					RobertaTokenizer
 __A			       =					RobertaTokenizerFast
 __A			       =					True
 __A			       =					{'''cls_token''': '''<s>'''}







 def 		__UpperCAmelCase				(		self				:   Tuple)						->	Optional[int]:


   """simple docstring"""







   super().setUp()

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

   _UpperCamelCase           =    os.path.join(self.tmpdirname							, VOCAB_FILES_NAMES["vocab_file"])
   _UpperCamelCase           =    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				:   Dict							, **lowercase_				:   List[str])						->	Optional[Any]:


   """simple docstring"""







   kwargs.update(self.special_tokens_map)
   return self.tokenizer_class.from_pretrained(self.tmpdirname							, **UpperCamelCase__)







 def 		__UpperCAmelCase				(		self				:   List[Any]							, **lowercase_				:   Dict)						->	Tuple:


   """simple docstring"""







   kwargs.update(self.special_tokens_map)
   return RobertaTokenizerFast.from_pretrained(self.tmpdirname							, **UpperCamelCase__)







 def 		__UpperCAmelCase				(		self				:   List[Any]							, lowercase_				:   str)						->	List[Any]:


   """simple docstring"""







   _UpperCamelCase           =    '''lower newer'''
   _UpperCamelCase           =    '''lower newer'''
   return input_text, output_text







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


   """simple docstring"""







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

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







 def 		__UpperCAmelCase				(		self				:   str)						->	Tuple:


   """simple docstring"""







   _UpperCamelCase           =    self.get_tokenizer()

   self.assertListEqual(tokenizer.encode("Hello world!"							, add_special_tokens=UpperCamelCase__)							, [0, 31414, 232, 328, 2])
   self.assertListEqual(
       tokenizer.encode("Hello world! cécé herlolip 418"							, add_special_tokens=UpperCamelCase__)							, [0, 31414, 232, 328, 740, 1140, 12695, 69, 46078, 1588, 2]							, )







 @slow
 def 		__UpperCAmelCase				(		self				:   Dict)						->	Optional[Any]:


   """simple docstring"""







   _UpperCamelCase           =    self.tokenizer_class.from_pretrained("roberta-base")

   _UpperCamelCase           =    tokenizer.encode("sequence builders"							, add_special_tokens=UpperCamelCase__)
   _UpperCamelCase           =    tokenizer.encode("multi-sequence build"							, add_special_tokens=UpperCamelCase__)

   _UpperCamelCase           =    tokenizer.encode(
       "sequence builders"							, add_special_tokens=UpperCamelCase__							, add_prefix_space=UpperCamelCase__)
   _UpperCamelCase           =    tokenizer.encode(
       "sequence builders"							, "multi-sequence build"							, add_special_tokens=UpperCamelCase__							, add_prefix_space=UpperCamelCase__)

   _UpperCamelCase           =    tokenizer.build_inputs_with_special_tokens(UpperCamelCase__)
   _UpperCamelCase           =    tokenizer.build_inputs_with_special_tokens(UpperCamelCase__							, UpperCamelCase__)

   assert encoded_sentence == encoded_text_from_decode
   assert encoded_pair == encoded_pair_from_decode







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


   """simple docstring"""







   _UpperCamelCase           =    self.get_tokenizer()

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

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

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

   tokenizer.add_special_tokens({"bos_token": "<s>"})
   _UpperCamelCase           =    tokenizer.encode(UpperCamelCase__							, add_special_tokens=UpperCamelCase__)
   _UpperCamelCase           =    tokenizer.convert_ids_to_tokens(encoded[1])[0]
   self.assertNotEqual(UpperCamelCase__							, UpperCamelCase__)

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

   _UpperCamelCase           =    '''Encode <mask> sequence'''
   _UpperCamelCase           =    '''Encode <mask>sequence'''

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

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







 def 		__UpperCAmelCase				(		self				:   Tuple)						->	Optional[int]:


   """simple docstring"""







   pass







 def 		__UpperCAmelCase				(		self				:   List[str])						->	Any:


   """simple docstring"""







   for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
     with self.subTest(f'{tokenizer.__class__.__name__} ({pretrained_name})'):
       _UpperCamelCase           =    self.rust_tokenizer_class.from_pretrained(UpperCamelCase__							, **UpperCamelCase__)
       _UpperCamelCase           =    self.tokenizer_class.from_pretrained(UpperCamelCase__							, **UpperCamelCase__)
       _UpperCamelCase           =    '''A, <mask> AllenNLP sentence.'''
       _UpperCamelCase           =    tokenizer_r.encode_plus(UpperCamelCase__							, add_special_tokens=UpperCamelCase__							, return_token_type_ids=UpperCamelCase__)
       _UpperCamelCase           =    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"])							, )

       _UpperCamelCase           =    tokenizer_r.convert_ids_to_tokens(tokens_r["input_ids"])
       _UpperCamelCase           =    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, 50264, 3823, 487, 21992, 3645, 4, 2])
       self.assertSequenceEqual(tokens_r["input_ids"]							, [0, 250, 6, 50264, 3823, 487, 21992, 3645, 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 		__UpperCAmelCase				(		self				:   Dict)						->	int:


   """simple docstring"""







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

     _UpperCamelCase           =    json.loads(tokenizer_r.backend_tokenizer.pre_tokenizer.__getstate__())
     _UpperCamelCase           =    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 		__UpperCAmelCase				(		self				:   Dict)						->	Dict:


   """simple docstring"""







   for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
     with self.subTest(f'{tokenizer.__class__.__name__} ({pretrained_name})'):
       _UpperCamelCase           =    '''hello'''  # `hello` is a token in the vocabulary of `pretrained_name`
       _UpperCamelCase           =    f'{text_of_1_token} {text_of_1_token}'

       _UpperCamelCase           =    self.rust_tokenizer_class.from_pretrained(
           UpperCamelCase__							, use_fast=UpperCamelCase__							, add_prefix_space=UpperCamelCase__							, trim_offsets=UpperCamelCase__)
       _UpperCamelCase           =    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           =    self.rust_tokenizer_class.from_pretrained(
           UpperCamelCase__							, use_fast=UpperCamelCase__							, add_prefix_space=UpperCamelCase__							, trim_offsets=UpperCamelCase__)
       _UpperCamelCase           =    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           =    self.rust_tokenizer_class.from_pretrained(
           UpperCamelCase__							, use_fast=UpperCamelCase__							, add_prefix_space=UpperCamelCase__							, trim_offsets=UpperCamelCase__)
       _UpperCamelCase           =    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__))							, )

       _UpperCamelCase           =    self.rust_tokenizer_class.from_pretrained(
           UpperCamelCase__							, use_fast=UpperCamelCase__							, add_prefix_space=UpperCamelCase__							, trim_offsets=UpperCamelCase__)
       _UpperCamelCase           =    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__))							, )

       _UpperCamelCase           =    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)),
       # )

       _UpperCamelCase           =    self.rust_tokenizer_class.from_pretrained(
           UpperCamelCase__							, use_fast=UpperCamelCase__							, add_prefix_space=UpperCamelCase__							, trim_offsets=UpperCamelCase__)
       _UpperCamelCase           =    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__))							, )

       _UpperCamelCase           =    self.rust_tokenizer_class.from_pretrained(
           UpperCamelCase__							, use_fast=UpperCamelCase__							, add_prefix_space=UpperCamelCase__							, trim_offsets=UpperCamelCase__)
       _UpperCamelCase           =    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__))							, )

       _UpperCamelCase           =    self.rust_tokenizer_class.from_pretrained(
           UpperCamelCase__							, use_fast=UpperCamelCase__							, add_prefix_space=UpperCamelCase__							, trim_offsets=UpperCamelCase__)
       _UpperCamelCase           =    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'''
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 TFCamembertModel






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







		"""simple docstring"""

		@slow
		def       lowerCAmelCase				(      self				:			Optional[Any]      )						->			Optional[Any]:






				"""simple docstring"""







				snake_case  :       Any     			=						TFCamembertModel.from_pretrained('''jplu/tf-camembert-base'''      )

				snake_case  :       List[Any]     			=						tf.convert_to_tensor(
				    [[5, 121, 11, 660, 16, 730, 2_5543, 110, 83, 6]]  ,	dtype=tf.intaa  ,	)  # J'aime le camembert !"

				snake_case  :       Any     			=						model(UpperCamelCase__      )['''last_hidden_state''']
				snake_case  :       int     			=						tf.TensorShape((1, 10, 768)      )
				self.assertEqual(output.shape  ,	UpperCamelCase__      )
				# compare the actual values for a slice.
				snake_case  :       Dict     			=						tf.convert_to_tensor(
				    [[[-0.0_254, 0.0_235, 0.1_027], [0.0_606, -0.1_811, -0.0_418], [-0.1_561, -0.1_127, 0.2_687]]]  ,	dtype=tf.floataa  ,	)
				# camembert = torch.hub.load('pytorch/fairseq', 'camembert.v0')
				# camembert.eval()
				# expected_slice = roberta.model.forward(input_ids)[0][:, :3, :3].detach()

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


