




'''simple docstring'''




import unittest

from transformers import YosoConfig, is_torch_available
from transformers.testing_utils import require_torch, slow, torch_device

from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTesterMixin, floats_tensor, ids_tensor, random_attention_mask
from ...test_pipeline_mixin import PipelineTesterMixin


if is_torch_available():
     import torch

     from transformers import (
         YosoForMaskedLM,
         YosoForMultipleChoice,
         YosoForQuestionAnswering,
         YosoForSequenceClassification,
         YosoForTokenClassification,
         YosoModel,
     )
     from transformers.models.yoso.modeling_yoso import YOSO_PRETRAINED_MODEL_ARCHIVE_LIST


class 						__UpperCamelCase :






       def __init__(							self,	lowerCAmelCase,	lowerCAmelCase=13,	lowerCAmelCase=7,	lowerCAmelCase=True,	lowerCAmelCase=True,	lowerCAmelCase=True,	lowerCAmelCase=True,	lowerCAmelCase=99,	lowerCAmelCase=32,	lowerCAmelCase=5,	lowerCAmelCase=4,	lowerCAmelCase=37,	lowerCAmelCase="gelu",	lowerCAmelCase=0.1,	lowerCAmelCase=0.1,	lowerCAmelCase=512,	lowerCAmelCase=16,	lowerCAmelCase=2,	lowerCAmelCase=0.0_2,	lowerCAmelCase=3,	lowerCAmelCase=4,	lowerCAmelCase=None,	):



              """simple docstring"""







              lowerCamelCase_							=parent
              lowerCamelCase_							=batch_size
              lowerCamelCase_							=seq_length
              lowerCamelCase_							=is_training
              lowerCamelCase_							=use_input_mask
              lowerCamelCase_							=use_token_type_ids
              lowerCamelCase_							=use_labels
              lowerCamelCase_							=vocab_size
              lowerCamelCase_							=hidden_size
              lowerCamelCase_							=num_hidden_layers
              lowerCamelCase_							=num_attention_heads
              lowerCamelCase_							=intermediate_size
              lowerCamelCase_							=hidden_act
              lowerCamelCase_							=hidden_dropout_prob
              lowerCamelCase_							=attention_probs_dropout_prob
              lowerCamelCase_							=max_position_embeddings
              lowerCamelCase_							=type_vocab_size
              lowerCamelCase_							=type_sequence_label_size
              lowerCamelCase_							=initializer_range
              lowerCamelCase_							=num_labels
              lowerCamelCase_							=num_choices
              lowerCamelCase_							=scope






       def   lowercase__  (							self						):



              """simple docstring"""







              lowerCamelCase_							=ids_tensor([self.batch_size, self.seq_length],	self.vocab_size						)

              lowerCamelCase_							=None
              if self.use_input_mask:
                     lowerCamelCase_							=random_attention_mask([self.batch_size, self.seq_length]						)

              lowerCamelCase_							=None
              if self.use_token_type_ids:
                     lowerCamelCase_							=ids_tensor([self.batch_size, self.seq_length],	self.type_vocab_size						)

              lowerCamelCase_							=None
              lowerCamelCase_							=None
              lowerCamelCase_							=None
              if self.use_labels:
                     lowerCamelCase_							=ids_tensor([self.batch_size],	self.type_sequence_label_size						)
                     lowerCamelCase_							=ids_tensor([self.batch_size, self.seq_length],	self.num_labels						)
                     lowerCamelCase_							=ids_tensor([self.batch_size],	self.num_choices						)

              lowerCamelCase_							=self.get_config()

              return config, input_ids, token_type_ids, input_mask, sequence_labels, token_labels, choice_labels






       def   lowercase__  (							self						):



              """simple docstring"""







              return YosoConfig(
                  vocab_size=self.vocab_size,	hidden_size=self.hidden_size,	num_hidden_layers=self.num_hidden_layers,	num_attention_heads=self.num_attention_heads,	intermediate_size=self.intermediate_size,	hidden_act=self.hidden_act,	hidden_dropout_prob=self.hidden_dropout_prob,	attention_probs_dropout_prob=self.attention_probs_dropout_prob,	max_position_embeddings=self.max_position_embeddings,	type_vocab_size=self.type_vocab_size,	is_decoder=lowerCAmelCase,	initializer_range=self.initializer_range,	)






       def   lowercase__  (							self						):



              """simple docstring"""







              lowerCamelCase_							=self.get_config()
              lowerCamelCase_							=300
              return config






       def   lowercase__  (							self						):



              """simple docstring"""







              (
                  (
                  lowerCamelCase_   
              ),   (
                  lowerCamelCase_   
              ),   (
                  lowerCamelCase_   
              ),   (
                  lowerCamelCase_   
              ),   (
                  lowerCamelCase_   
              ),   (
                  lowerCamelCase_   
              ),   (
                  lowerCamelCase_   
              ),      
              )							=self.prepare_config_and_inputs()

              lowerCamelCase_							=True
              lowerCamelCase_							=floats_tensor([self.batch_size, self.seq_length, self.hidden_size]						)
              lowerCamelCase_							=ids_tensor([self.batch_size, self.seq_length],	vocab_size=2						)

              return (
                  config,
                  input_ids,
                  token_type_ids,
                  input_mask,
                  sequence_labels,
                  token_labels,
                  choice_labels,
                  encoder_hidden_states,
                  encoder_attention_mask,
              )






       def   lowercase__  (							self,	lowerCAmelCase,	lowerCAmelCase,	lowerCAmelCase,	lowerCAmelCase,	lowerCAmelCase,	lowerCAmelCase,	lowerCAmelCase						):



              """simple docstring"""







              lowerCamelCase_							=YosoModel(config=lowerCAmelCase						)
              model.to(lowerCAmelCase						)
              model.eval()
              lowerCamelCase_							=model(lowerCAmelCase,	attention_mask=lowerCAmelCase,	token_type_ids=lowerCAmelCase						)
              lowerCamelCase_							=model(lowerCAmelCase,	token_type_ids=lowerCAmelCase						)
              lowerCamelCase_							=model(lowerCAmelCase						)
              self.parent.assertEqual(result.last_hidden_state.shape,	(self.batch_size, self.seq_length, self.hidden_size)						)






       def   lowercase__  (							self,	lowerCAmelCase,	lowerCAmelCase,	lowerCAmelCase,	lowerCAmelCase,	lowerCAmelCase,	lowerCAmelCase,	lowerCAmelCase,	lowerCAmelCase,	lowerCAmelCase,	):



              """simple docstring"""







              lowerCamelCase_							=True
              lowerCamelCase_							=YosoModel(lowerCAmelCase						)
              model.to(lowerCAmelCase						)
              model.eval()
              lowerCamelCase_							=model(
                  lowerCAmelCase,	attention_mask=lowerCAmelCase,	token_type_ids=lowerCAmelCase,	encoder_hidden_states=lowerCAmelCase,	encoder_attention_mask=lowerCAmelCase,	)
              lowerCamelCase_							=model(
                  lowerCAmelCase,	attention_mask=lowerCAmelCase,	token_type_ids=lowerCAmelCase,	encoder_hidden_states=lowerCAmelCase,	)
              lowerCamelCase_							=model(lowerCAmelCase,	attention_mask=lowerCAmelCase,	token_type_ids=lowerCAmelCase						)
              self.parent.assertEqual(result.last_hidden_state.shape,	(self.batch_size, self.seq_length, self.hidden_size)						)






       def   lowercase__  (							self,	lowerCAmelCase,	lowerCAmelCase,	lowerCAmelCase,	lowerCAmelCase,	lowerCAmelCase,	lowerCAmelCase,	lowerCAmelCase						):



              """simple docstring"""







              lowerCamelCase_							=YosoForMaskedLM(config=lowerCAmelCase						)
              model.to(lowerCAmelCase						)
              model.eval()
              lowerCamelCase_							=model(lowerCAmelCase,	attention_mask=lowerCAmelCase,	token_type_ids=lowerCAmelCase,	labels=lowerCAmelCase						)
              self.parent.assertEqual(result.logits.shape,	(self.batch_size, self.seq_length, self.vocab_size)						)






       def   lowercase__  (							self,	lowerCAmelCase,	lowerCAmelCase,	lowerCAmelCase,	lowerCAmelCase,	lowerCAmelCase,	lowerCAmelCase,	lowerCAmelCase						):



              """simple docstring"""







              lowerCamelCase_							=YosoForQuestionAnswering(config=lowerCAmelCase						)
              model.to(lowerCAmelCase						)
              model.eval()
              lowerCamelCase_							=model(
                  lowerCAmelCase,	attention_mask=lowerCAmelCase,	token_type_ids=lowerCAmelCase,	start_positions=lowerCAmelCase,	end_positions=lowerCAmelCase,	)
              self.parent.assertEqual(result.start_logits.shape,	(self.batch_size, self.seq_length)						)
              self.parent.assertEqual(result.end_logits.shape,	(self.batch_size, self.seq_length)						)






       def   lowercase__  (							self,	lowerCAmelCase,	lowerCAmelCase,	lowerCAmelCase,	lowerCAmelCase,	lowerCAmelCase,	lowerCAmelCase,	lowerCAmelCase						):



              """simple docstring"""







              lowerCamelCase_							=self.num_labels
              lowerCamelCase_							=YosoForSequenceClassification(lowerCAmelCase						)
              model.to(lowerCAmelCase						)
              model.eval()
              lowerCamelCase_							=model(lowerCAmelCase,	attention_mask=lowerCAmelCase,	token_type_ids=lowerCAmelCase,	labels=lowerCAmelCase						)
              self.parent.assertEqual(result.logits.shape,	(self.batch_size, self.num_labels)						)






       def   lowercase__  (							self,	lowerCAmelCase,	lowerCAmelCase,	lowerCAmelCase,	lowerCAmelCase,	lowerCAmelCase,	lowerCAmelCase,	lowerCAmelCase						):



              """simple docstring"""







              lowerCamelCase_							=self.num_labels
              lowerCamelCase_							=YosoForTokenClassification(config=lowerCAmelCase						)
              model.to(lowerCAmelCase						)
              model.eval()
              lowerCamelCase_							=model(lowerCAmelCase,	attention_mask=lowerCAmelCase,	token_type_ids=lowerCAmelCase,	labels=lowerCAmelCase						)
              self.parent.assertEqual(result.logits.shape,	(self.batch_size, self.seq_length, self.num_labels)						)






       def   lowercase__  (							self,	lowerCAmelCase,	lowerCAmelCase,	lowerCAmelCase,	lowerCAmelCase,	lowerCAmelCase,	lowerCAmelCase,	lowerCAmelCase						):



              """simple docstring"""







              lowerCamelCase_							=self.num_choices
              lowerCamelCase_							=YosoForMultipleChoice(config=lowerCAmelCase						)
              model.to(lowerCAmelCase						)
              model.eval()
              lowerCamelCase_							=input_ids.unsqueeze(1						).expand(-1,	self.num_choices,	-1						).contiguous()
              lowerCamelCase_							=token_type_ids.unsqueeze(1						).expand(-1,	self.num_choices,	-1						).contiguous()
              lowerCamelCase_							=input_mask.unsqueeze(1						).expand(-1,	self.num_choices,	-1						).contiguous()
              lowerCamelCase_							=model(
                  lowerCAmelCase,	attention_mask=lowerCAmelCase,	token_type_ids=lowerCAmelCase,	labels=lowerCAmelCase,	)
              self.parent.assertEqual(result.logits.shape,	(self.batch_size, self.num_choices)						)






       def   lowercase__  (							self						):



              """simple docstring"""







              lowerCamelCase_							=self.prepare_config_and_inputs()
              (
                  (
                  lowerCamelCase_   
              ),   (
                  lowerCamelCase_   
              ),   (
                  lowerCamelCase_   
              ),   (
                  lowerCamelCase_   
              ),   (
                  lowerCamelCase_   
              ),   (
                  lowerCamelCase_   
              ),   (
                  lowerCamelCase_   
              ),      
              )							=config_and_inputs
              lowerCamelCase_							={'''input_ids''': input_ids, '''token_type_ids''': token_type_ids, '''attention_mask''': input_mask}
              return config, inputs_dict





@require_torch
class 						__UpperCamelCase (				lowerCamelCase__    ,      lowerCamelCase__    ,      unittest.TestCase       ):
       lowercase			:					Dict   		=(
           (
               YosoModel,
               YosoForMaskedLM,
               YosoForMultipleChoice,
               YosoForQuestionAnswering,
               YosoForSequenceClassification,
               YosoForTokenClassification,
           )
           if is_torch_available()
           else ()
       )
       lowercase			:					Optional[Any]   		=False
       lowercase			:					Tuple   		=False
       lowercase			:					List[str]   		=False

       lowercase			:					Union[str, Any]   		=()
       lowercase			:					str   		=(
           {
               'feature-extraction': YosoModel,
               'fill-mask': YosoForMaskedLM,
               'question-answering': YosoForQuestionAnswering,
               'text-classification': YosoForSequenceClassification,
               'token-classification': YosoForTokenClassification,
               'zero-shot': YosoForSequenceClassification,
           }
           if is_torch_available()
           else {}
       )






       def   lowercase__  (							self						):



              """simple docstring"""







              lowerCamelCase_							=YosoModelTester(self						)
              lowerCamelCase_							=ConfigTester(self,	config_class=lowerCAmelCase,	hidden_size=37						)






       def   lowercase__  (							self						):



              """simple docstring"""







              self.config_tester.run_common_tests()






       def   lowercase__  (							self						):



              """simple docstring"""







              lowerCamelCase_							=self.model_tester.prepare_config_and_inputs()
              self.model_tester.create_and_check_model(*lowerCAmelCase						)






       def   lowercase__  (							self						):



              """simple docstring"""







              lowerCamelCase_							=self.model_tester.prepare_config_and_inputs()
              for type in ["absolute", "relative_key", "relative_key_query"]:
                     lowerCamelCase_							=type
                     self.model_tester.create_and_check_model(*lowerCAmelCase						)






       def   lowercase__  (							self						):



              """simple docstring"""







              lowerCamelCase_							=self.model_tester.prepare_config_and_inputs()
              self.model_tester.create_and_check_for_masked_lm(*lowerCAmelCase						)






       def   lowercase__  (							self						):



              """simple docstring"""







              lowerCamelCase_							=self.model_tester.prepare_config_and_inputs()
              self.model_tester.create_and_check_for_multiple_choice(*lowerCAmelCase						)






       def   lowercase__  (							self						):



              """simple docstring"""







              lowerCamelCase_							=self.model_tester.prepare_config_and_inputs()
              self.model_tester.create_and_check_for_question_answering(*lowerCAmelCase						)






       def   lowercase__  (							self						):



              """simple docstring"""







              lowerCamelCase_							=self.model_tester.prepare_config_and_inputs()
              self.model_tester.create_and_check_for_sequence_classification(*lowerCAmelCase						)






       def   lowercase__  (							self						):



              """simple docstring"""







              lowerCamelCase_							=self.model_tester.prepare_config_and_inputs()
              self.model_tester.create_and_check_for_token_classification(*lowerCAmelCase						)






       @slow
       def   lowercase__  (							self						):



              """simple docstring"""







              for model_name in YOSO_PRETRAINED_MODEL_ARCHIVE_LIST[:1]:
                     lowerCamelCase_							=YosoModel.from_pretrained(lowerCAmelCase						)
                     self.assertIsNotNone(lowerCAmelCase						)






       def   lowercase__  (							self						):



              """simple docstring"""







              return





@require_torch
class 						__UpperCamelCase (				unittest.TestCase       ):






       @slow
       def   lowercase__  (							self						):



              """simple docstring"""







              lowerCamelCase_							=YosoModel.from_pretrained('''uw-madison/yoso-4096'''						)
              lowerCamelCase_							=torch.tensor([[0, 1, 2, 3, 4, 5]]						)

              with torch.no_grad():
                     lowerCamelCase_							=model(lowerCAmelCase						)[0]

              lowerCamelCase_							=torch.Size((1, 6, 768)						)
              self.assertEqual(output.shape,	lowerCAmelCase						)

              lowerCamelCase_							=torch.tensor(
                  [[[-0.0_6_1_1, 0.1_2_4_2, 0.0_8_4_0], [0.0_2_8_0, -0.0_0_4_8, 0.1_1_2_5], [0.0_1_0_6, 0.0_2_2_6, 0.0_7_5_1]]]						)

              self.assertTrue(torch.allclose(output[:, :3, :3],	lowerCAmelCase,	atol=1e-4						)						)






       @slow
       def   lowercase__  (							self						):



              """simple docstring"""







              lowerCamelCase_							=YosoForMaskedLM.from_pretrained('''uw-madison/yoso-4096'''						)
              lowerCamelCase_							=torch.tensor([[0, 1, 2, 3, 4, 5]]						)

              with torch.no_grad():
                     lowerCamelCase_							=model(lowerCAmelCase						)[0]

              lowerCamelCase_							=50_265

              lowerCamelCase_							=torch.Size((1, 6, vocab_size)						)
              self.assertEqual(output.shape,	lowerCAmelCase						)

              lowerCamelCase_							=torch.tensor(
                  [[[-2.1_3_1_3, -3.7_2_8_5, -2.2_4_0_7], [-2.7_0_4_7, -3.3_3_1_4, -2.6_4_0_8], [0.0_6_2_9, -2.5_1_6_6, -0.3_3_5_6]]]						)

              self.assertTrue(torch.allclose(output[:, :3, :3],	lowerCAmelCase,	atol=1e-4						)						)






       @slow
       def   lowercase__  (							self						):



              """simple docstring"""







              lowerCamelCase_							=YosoForMaskedLM.from_pretrained('''uw-madison/yoso-4096'''						)
              lowerCamelCase_							=torch.arange(4_096						).unsqueeze(0						)

              with torch.no_grad():
                     lowerCamelCase_							=model(lowerCAmelCase						)[0]

              lowerCamelCase_							=50_265

              lowerCamelCase_							=torch.Size((1, 4_096, vocab_size)						)
              self.assertEqual(output.shape,	lowerCAmelCase						)

              lowerCamelCase_							=torch.tensor(
                  [[[-2.3_9_1_4, -4.3_7_4_2, -5.0_9_5_6], [-4.0_9_8_8, -4.2_3_8_4, -7.0_4_0_6], [-3.1_4_2_7, -3.7_1_9_2, -6.6_8_0_0]]]						)

              self.assertTrue(torch.allclose(output[:, :3, :3],	lowerCAmelCase,	atol=1e-4						)						)










'''simple docstring'''




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

from tokenizers import processors

from ...tokenization_utils import AddedToken, BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging


if is_sentencepiece_available():
     from .tokenization_mbartaa import MBartaaTokenizer
else:
     a_   :	Tuple							   = None


a_   :	List[Any]							   = logging.get_logger(__name__)

a_   :	Any							   = {"""vocab_file""": """sentencepiece.bpe.model""", """tokenizer_file""": """tokenizer.json"""}

a_   :	Any							   = {
    """vocab_file""": {
        """facebook/mbart-large-50-one-to-many-mmt""": (
            """https://huggingface.co/facebook/mbart-large-50-one-to-many-mmt/resolve/main/sentencepiece.bpe.model"""
        ),
    },
    """tokenizer_file""": {
        """facebook/mbart-large-50-one-to-many-mmt""": (
            """https://huggingface.co/facebook/mbart-large-50-one-to-many-mmt/resolve/main/tokenizer.json"""
        ),
    },
}

a_   :	Dict							   = {
    """facebook/mbart-large-50-one-to-many-mmt""": 10_24,
}

# fmt: off
a_   :	List[str]							   = ["""ar_AR""", """cs_CZ""", """de_DE""", """en_XX""", """es_XX""", """et_EE""", """fi_FI""", """fr_XX""", """gu_IN""", """hi_IN""", """it_IT""", """ja_XX""", """kk_KZ""", """ko_KR""", """lt_LT""", """lv_LV""", """my_MM""", """ne_NP""", """nl_XX""", """ro_RO""", """ru_RU""", """si_LK""", """tr_TR""", """vi_VN""", """zh_CN""", """af_ZA""", """az_AZ""", """bn_IN""", """fa_IR""", """he_IL""", """hr_HR""", """id_ID""", """ka_GE""", """km_KH""", """mk_MK""", """ml_IN""", """mn_MN""", """mr_IN""", """pl_PL""", """ps_AF""", """pt_XX""", """sv_SE""", """sw_KE""", """ta_IN""", """te_IN""", """th_TH""", """tl_XX""", """uk_UA""", """ur_PK""", """xh_ZA""", """gl_ES""", """sl_SI"""]


class 						__UpperCamelCase (				lowerCamelCase__       ):
       lowercase			:					Any   		=VOCAB_FILES_NAMES
       lowercase			:					str   		=PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
       lowercase			:					Dict   		=PRETRAINED_VOCAB_FILES_MAP
       lowercase			:					str   		=['input_ids', 'attention_mask']
       lowercase			:					List[Any]   		=MBartaaTokenizer

       lowercase			:					List[int]   		=[]
       lowercase			:					List[int]   		=[]






       def __init__(							self,	lowerCAmelCase=None,	lowerCAmelCase=None,	lowerCAmelCase=None,	lowerCAmelCase=None,	lowerCAmelCase="</s>",	lowerCAmelCase="</s>",	lowerCAmelCase="<s>",	lowerCAmelCase="<unk>",	lowerCAmelCase="<pad>",	lowerCAmelCase="<mask>",	**lowerCAmelCase,	):



              """simple docstring"""







              lowerCamelCase_							=AddedToken(lowerCAmelCase,	lstrip=lowerCAmelCase,	rstrip=lowerCAmelCase						) if isinstance(lowerCAmelCase,	lowerCAmelCase						) else mask_token

              lowerCamelCase_							=kwargs.get('''additional_special_tokens''',	[]						)
              kwargs["additional_special_tokens"] += [
                  code for code in FAIRSEQ_LANGUAGE_CODES if code not in kwargs["additional_special_tokens"]
              ]

              super().__init__(
                  lowerCAmelCase,	src_lang=lowerCAmelCase,	tgt_lang=lowerCAmelCase,	tokenizer_file=lowerCAmelCase,	eos_token=lowerCAmelCase,	sep_token=lowerCAmelCase,	cls_token=lowerCAmelCase,	unk_token=lowerCAmelCase,	pad_token=lowerCAmelCase,	mask_token=lowerCAmelCase,	**lowerCAmelCase,	)

              lowerCamelCase_							=vocab_file
              lowerCamelCase_							=False if not self.vocab_file else True

              lowerCamelCase_							={
                  lang_code: self.convert_tokens_to_ids(lowerCAmelCase						) for lang_code in FAIRSEQ_LANGUAGE_CODES
              }

              lowerCamelCase_							=src_lang if src_lang is not None else '''en_XX'''
              lowerCamelCase_							=tgt_lang
              lowerCamelCase_							=self.lang_code_to_id[self._src_lang]
              self.set_src_lang_special_tokens(self._src_lang						)






       @property
       def   lowercase__  (							self						):



              """simple docstring"""







              return self._src_lang






       @src_lang.setter
       def   lowercase__  (							self,	lowerCAmelCase						):



              """simple docstring"""







              lowerCamelCase_							=new_src_lang
              self.set_src_lang_special_tokens(self._src_lang						)






       def   lowercase__  (							self,	lowerCAmelCase,	lowerCAmelCase = None						):



              """simple docstring"""







              if token_ids_a is None:
                     return self.prefix_tokens + token_ids_a + self.suffix_tokens
              # We don't expect to process pairs, but leave the pair logic for API consistency
              return self.prefix_tokens + token_ids_a + token_ids_a + self.suffix_tokens






       def   lowercase__  (							self,	lowerCAmelCase,	lowerCAmelCase = "en_XX",	lowerCAmelCase = None,	lowerCAmelCase = "ro_RO",	**lowerCAmelCase,	):



              """simple docstring"""







              lowerCamelCase_							=src_lang
              lowerCamelCase_							=tgt_lang
              return super().prepare_seqaseq_batch(lowerCAmelCase,	lowerCAmelCase,	**lowerCAmelCase						)






       def   lowercase__  (							self						):



              """simple docstring"""







              return self.set_src_lang_special_tokens(self.src_lang						)






       def   lowercase__  (							self						):



              """simple docstring"""







              return self.set_tgt_lang_special_tokens(self.tgt_lang						)






       def   lowercase__  (							self,	lowerCAmelCase						):



              """simple docstring"""







              lowerCamelCase_							=self.convert_tokens_to_ids(lowerCAmelCase						)
              lowerCamelCase_							=[self.cur_lang_code_id]
              lowerCamelCase_							=[self.eos_token_id]

              lowerCamelCase_							=self.convert_ids_to_tokens(self.prefix_tokens						)
              lowerCamelCase_							=self.convert_ids_to_tokens(self.suffix_tokens						)

              lowerCamelCase_							=processors.TemplateProcessing(
                  single=prefix_tokens_str + ['''$A'''] + suffix_tokens_str,	pair=prefix_tokens_str + ['''$A''', '''$B'''] + suffix_tokens_str,	special_tokens=list(zip(prefix_tokens_str + suffix_tokens_str,	self.prefix_tokens + self.suffix_tokens						)						),	)






       def   lowercase__  (							self,	lowerCAmelCase						):



              """simple docstring"""







              lowerCamelCase_							=self.convert_tokens_to_ids(lowerCAmelCase						)
              lowerCamelCase_							=[self.cur_lang_code_id]
              lowerCamelCase_							=[self.eos_token_id]

              lowerCamelCase_							=self.convert_ids_to_tokens(self.prefix_tokens						)
              lowerCamelCase_							=self.convert_ids_to_tokens(self.suffix_tokens						)

              lowerCamelCase_							=processors.TemplateProcessing(
                  single=prefix_tokens_str + ['''$A'''] + suffix_tokens_str,	pair=prefix_tokens_str + ['''$A''', '''$B'''] + suffix_tokens_str,	special_tokens=list(zip(prefix_tokens_str + suffix_tokens_str,	self.prefix_tokens + self.suffix_tokens						)						),	)






       def   lowercase__  (							self,	lowerCAmelCase,	lowerCAmelCase,	lowerCAmelCase,	lowerCAmelCase,	**lowerCAmelCase						):



              """simple docstring"""







              if src_lang is None or tgt_lang is None:
                     raise ValueError('''Translation requires a `src_lang` and a `tgt_lang` for this model'''						)
              lowerCamelCase_							=src_lang
              lowerCamelCase_							=self(lowerCAmelCase,	add_special_tokens=lowerCAmelCase,	return_tensors=lowerCAmelCase,	**lowerCAmelCase						)
              lowerCamelCase_							=self.convert_tokens_to_ids(lowerCAmelCase						)
              lowerCamelCase_							=tgt_lang_id
              return inputs






       def   lowercase__  (							self,	lowerCAmelCase,	lowerCAmelCase = None						):



              """simple docstring"""







              if not self.can_save_slow_tokenizer:
                     raise ValueError(
                         '''Your fast tokenizer does not have the necessary information to save the vocabulary for a slow '''
                         '''tokenizer.'''						)

              if not os.path.isdir(lowerCAmelCase						):
                     logger.error(f'''Vocabulary path ({save_directory}) should be a directory'''						)
                     return
              lowerCamelCase_							=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,)




