'''simple docstring'''




import json
import os
import re
import shutil
import tempfile
import unittest
from typing import Tuple

from transformers import AddedToken, BatchEncoding, ByTaTokenizer
from transformers.utils import cached_property, is_tf_available, is_torch_available

from ...test_tokenization_common import TokenizerTesterMixin


if is_torch_available():
  __UpperCAmelCase												="pt"
elif is_tf_available():
  __UpperCAmelCase												="tf"
else:
  __UpperCAmelCase												="jax"




class    a__				(       UpperCAmelCase__							,       unittest.TestCase			):
     lowerCamelCase  :					Union[str, Any]							=ByTaTokenizer
     lowerCamelCase  :					int							=False






     def        SCREAMING_SNAKE_CASE__       (			self		:		Tuple   ):





         """simple docstring"""



         super().setUp()
         __lowerCamelCase          =  ByTaTokenizer()
         tokenizer.save_pretrained(self.tmpdirname   )






     @cached_property
     def        SCREAMING_SNAKE_CASE__       (			self		:		Dict   ):





         """simple docstring"""



         return ByTaTokenizer.from_pretrained('''google/byt5-small'''   )






     def        SCREAMING_SNAKE_CASE__       (			self		:		List[Any]  ,    **a		:		Optional[Any]   ):





         """simple docstring"""



         return self.tokenizer_class.from_pretrained(self.tmpdirname  ,    **a   )






     def        SCREAMING_SNAKE_CASE__       (			self		:		Optional[int]  ,    a		:		Tuple  ,    a		:		Union[str, Any]=False  ,    a		:		str=20  ,    a		:		Tuple=5   ):





         """simple docstring"""



         __lowerCamelCase          =  []
         for i in range(len(a   )   ):
             try:
                 __lowerCamelCase          =  tokenizer.decode([i]  ,    clean_up_tokenization_spaces=a   )
             except UnicodeDecodeError:
                 pass
             toks.append((i, tok)   )

         __lowerCamelCase          =  list(filter(lambda a   : re.match(R'''^[ a-zA-Z]+$'''  ,    t[1]   )  ,    a   )   )
         __lowerCamelCase          =  list(filter(lambda a   : [t[0]] == tokenizer.encode(t[1]  ,    add_special_tokens=a   )  ,    a   )   )
         if max_length is not None and len(a   ) > max_length:
             __lowerCamelCase          =  toks[:max_length]
         if min_length is not None and len(a   ) < min_length and len(a   ) > 0:
             while len(a   ) < min_length:
                 __lowerCamelCase          =  toks + toks
        # toks_str = [t[1] for t in toks]
         __lowerCamelCase          =  [t[0] for t in toks]

         # Ensure consistency
         __lowerCamelCase          =  tokenizer.decode(a  ,    clean_up_tokenization_spaces=a   )
         if " " not in output_txt and len(a   ) > 1:
             __lowerCamelCase          =  (
                 tokenizer.decode([toks_ids[0]]  ,    clean_up_tokenization_spaces=a   )
                 + ''' '''
                 + tokenizer.decode(toks_ids[1:]  ,    clean_up_tokenization_spaces=a   )
             )
         if with_prefix_space:
             __lowerCamelCase          =  ''' ''' + output_txt
         __lowerCamelCase          =  tokenizer.encode(a  ,    add_special_tokens=a   )
         return output_txt, output_ids






     def        SCREAMING_SNAKE_CASE__       (			self		:		Union[str, Any]   ):





         """simple docstring"""



         __lowerCamelCase          =  self.ta_base_tokenizer
         __lowerCamelCase          =  tokenizer(['''hi</s>''', '''I went to the gym</s>''', '''</s>''']   )
         __lowerCamelCase          =  tokenizer(['''hi''', '''I went to the gym''', '''''']   )
         self.assertListEqual(batch_with_eos_added['''input_ids''']  ,    batch_without_eos_added['''input_ids''']   )






     def        SCREAMING_SNAKE_CASE__       (			self		:		List[Any]   ):





         """simple docstring"""



         __lowerCamelCase          =  self.ta_base_tokenizer
         __lowerCamelCase          =  '''Unicode €.'''
         __lowerCamelCase          =  tokenizer(a   )
         __lowerCamelCase          =  [88, 1_13, 1_08, 1_02, 1_14, 1_03, 1_04, 35, 2_29, 1_33, 1_75, 49, 1]
         self.assertEqual(encoded['''input_ids''']  ,    a   )

         # decoding
         __lowerCamelCase          =  tokenizer.decode(a   )
         self.assertEqual(a  ,    '''Unicode €.</s>'''   )

         __lowerCamelCase          =  tokenizer('''e è é ê ë'''   )
         __lowerCamelCase          =  [1_04, 35, 1_98, 1_71, 35, 1_98, 1_72, 35, 1_98, 1_73, 35, 1_98, 1_74, 1]
         self.assertEqual(encoded['''input_ids''']  ,    a   )
         # decoding
         __lowerCamelCase          =  tokenizer.decode(a   )
         self.assertEqual(a  ,    '''e è é ê ë</s>'''   )

         # encode/decode, but with `encode` instead of `__call__`
         self.assertEqual(tokenizer.decode(tokenizer.encode('''e è é ê ë'''   )   )  ,    '''e è é ê ë</s>'''   )






     def        SCREAMING_SNAKE_CASE__       (			self		:		str   ):





         """simple docstring"""



         __lowerCamelCase          =  self.ta_base_tokenizer
         __lowerCamelCase          =  ['''A long paragraph for summarization.''', '''Another paragraph for summarization.''']
         # fmt: off
         __lowerCamelCase          =  [68, 35, 1_11, 1_14, 1_13, 1_06, 35, 1_15, 1_00, 1_17, 1_00, 1_06, 1_17, 1_00, 1_15, 1_07, 35, 1_05, 1_14, 1_17, 35, 1_18, 1_20, 1_12, 1_12, 1_00, 1_17, 1_08, 1_25, 1_00, 1_19, 1_08, 1_14, 1_13, 49, 1, 0]
         # fmt: on
         __lowerCamelCase          =  tokenizer(a  ,    padding=a  ,    return_tensors=a   )
         self.assertIsInstance(a  ,    a   )

         if FRAMEWORK != "jax":
             __lowerCamelCase          =  list(batch.input_ids.numpy()[0]   )
         else:
             __lowerCamelCase          =  list(batch.input_ids.tolist()[0]   )

         self.assertListEqual(a  ,    a   )

         self.assertEqual((2, 37)  ,    batch.input_ids.shape   )
         self.assertEqual((2, 37)  ,    batch.attention_mask.shape   )






     def        SCREAMING_SNAKE_CASE__       (			self		:		Tuple   ):





         """simple docstring"""



         __lowerCamelCase          =  self.ta_base_tokenizer
         __lowerCamelCase          =  ['''A long paragraph for summarization.''', '''Another paragraph for summarization.''']
         __lowerCamelCase          =  tokenizer(a  ,    padding=a  ,    return_tensors=a   )
         # check if input_ids are returned and no decoder_input_ids
         self.assertIn('''input_ids'''  ,    a   )
         self.assertIn('''attention_mask'''  ,    a   )
         self.assertNotIn('''decoder_input_ids'''  ,    a   )
         self.assertNotIn('''decoder_attention_mask'''  ,    a   )






     def        SCREAMING_SNAKE_CASE__       (			self		:		Union[str, Any]   ):





         """simple docstring"""



         __lowerCamelCase          =  self.ta_base_tokenizer
         __lowerCamelCase          =  [
             '''Summary of the text.''',
             '''Another summary.''',
         ]
         __lowerCamelCase          =  tokenizer(
             text_target=a  ,    max_length=32  ,    padding='''max_length'''  ,    truncation=a  ,    return_tensors=a   )
         self.assertEqual(32  ,    targets['''input_ids'''].shape[1]   )






     def        SCREAMING_SNAKE_CASE__       (			self		:		Optional[Any]   ):





         """simple docstring"""



         __lowerCamelCase          =  self.ta_base_tokenizer
         __lowerCamelCase          =  ['''A long paragraph for summarization. </s>''']
         __lowerCamelCase          =  ['''Summary of the text. </s>''']
         # fmt: off
         __lowerCamelCase          =  [68, 35, 1_11, 1_14, 1_13, 1_06, 35, 1_15, 1_00, 1_17, 1_00, 1_06, 1_17, 1_00, 1_15, 1_07, 35, 1_05, 1_14, 1_17, 35, 1_18, 1_20, 1_12, 1_12, 1_00, 1_17, 1_08, 1_25, 1_00, 1_19, 1_08, 1_14, 1_13, 49, 35, 1]
         __lowerCamelCase          =  [86, 1_20, 1_12, 1_12, 1_00, 1_17, 1_24, 35, 1_14, 1_05, 35, 1_19, 1_07, 1_04, 35, 1_19, 1_04, 1_23, 1_19, 49, 35, 1]
         # fmt: on

         __lowerCamelCase          =  tokenizer(a  ,    text_target=a   )

         self.assertEqual(a  ,    batch['''input_ids'''][0]   )
         self.assertEqual(a  ,    batch['''labels'''][0]   )






     def        SCREAMING_SNAKE_CASE__       (			self		:		List[Any]   ):





         """simple docstring"""



         __lowerCamelCase          =  self.get_tokenizers()
         for tokenizer in tokenizers:
             with self.subTest(f"""{tokenizer.__class__.__name__}"""   ):
                 self.assertNotEqual(tokenizer.model_max_length  ,    42   )

        # Now let's start the test
         __lowerCamelCase          =  self.get_tokenizers()
         for tokenizer in tokenizers:
             with self.subTest(f"""{tokenizer.__class__.__name__}"""   ):
                 # Isolate this from the other tests because we save additional tokens/etc
                 __lowerCamelCase          =  tempfile.mkdtemp()

                 __lowerCamelCase          =  ''' He is very happy, UNwant\u00E9d,running'''
                 __lowerCamelCase          =  tokenizer.encode(a  ,    add_special_tokens=a   )
                 tokenizer.save_pretrained(a   )

                 __lowerCamelCase          =  tokenizer.__class__.from_pretrained(a   )
                 __lowerCamelCase          =  after_tokenizer.encode(a  ,    add_special_tokens=a   )
                 self.assertListEqual(a  ,    a   )

                 shutil.rmtree(a   )

         __lowerCamelCase          =  self.get_tokenizers(model_max_length=42   )
         for tokenizer in tokenizers:
             with self.subTest(f"""{tokenizer.__class__.__name__}"""   ):
                 # Isolate this from the other tests because we save additional tokens/etc
                 __lowerCamelCase          =  tempfile.mkdtemp()

                 __lowerCamelCase          =  ''' He is very happy, UNwant\u00E9d,running'''
                 tokenizer.add_tokens(['''bim''', '''bambam''']   )
                 __lowerCamelCase          =  tokenizer.additional_special_tokens
                 additional_special_tokens.append('''new_additional_special_token'''   )
                 tokenizer.add_special_tokens({'''additional_special_tokens''': additional_special_tokens}   )
                 __lowerCamelCase          =  tokenizer.encode(a  ,    add_special_tokens=a   )
                 tokenizer.save_pretrained(a   )

                 __lowerCamelCase          =  tokenizer.__class__.from_pretrained(a   )
                 __lowerCamelCase          =  after_tokenizer.encode(a  ,    add_special_tokens=a   )
                 self.assertListEqual(a  ,    a   )
                 self.assertIn('''new_additional_special_token'''  ,    after_tokenizer.additional_special_tokens   )
                 self.assertEqual(after_tokenizer.model_max_length  ,    42   )

                 __lowerCamelCase          =  tokenizer.__class__.from_pretrained(a  ,    model_max_length=43   )
                 self.assertEqual(tokenizer.model_max_length  ,    43   )

                 shutil.rmtree(a   )






     def        SCREAMING_SNAKE_CASE__       (			self		:		Optional[Any]   ):





         """simple docstring"""



         __lowerCamelCase          =  []
         if self.test_slow_tokenizer:
             tokenizer_list.append((self.tokenizer_class, self.get_tokenizer())   )

         if self.test_rust_tokenizer:
             tokenizer_list.append((self.rust_tokenizer_class, self.get_rust_tokenizer())   )

         for tokenizer_class, tokenizer_utils in tokenizer_list:
             with tempfile.TemporaryDirectory() as tmp_dir:
                 tokenizer_utils.save_pretrained(a   )

                 with open(os.path.join(a  ,    '''special_tokens_map.json'''   )  ,    encoding='''utf-8'''   ) as json_file:
                     __lowerCamelCase          =  json.load(a   )

                 with open(os.path.join(a  ,    '''tokenizer_config.json'''   )  ,    encoding='''utf-8'''   ) as json_file:
                     __lowerCamelCase          =  json.load(a   )

                 __lowerCamelCase          =  [f"""<extra_id_{i}>""" for i in range(1_25   )]

                 __lowerCamelCase          =  added_tokens_extra_ids + [
                     '''an_additional_special_token'''
                 ]
                 __lowerCamelCase          =  added_tokens_extra_ids + [
                     '''an_additional_special_token'''
                 ]

                 with open(os.path.join(a  ,    '''special_tokens_map.json'''   )  ,    '''w'''  ,    encoding='''utf-8'''   ) as outfile:
                     json.dump(a  ,    a   )
                 with open(os.path.join(a  ,    '''tokenizer_config.json'''   )  ,    '''w'''  ,    encoding='''utf-8'''   ) as outfile:
                     json.dump(a  ,    a   )

                 # the following checks allow us to verify that our test works as expected, i.e. that the tokenizer takes
                 # into account the new value of additional_special_tokens given in the "tokenizer_config.json" and
                 # "special_tokens_map.json" files
                 __lowerCamelCase          =  tokenizer_class.from_pretrained(
                     a  ,    )
                 self.assertIn(
                     '''an_additional_special_token'''  ,    tokenizer_without_change_in_init.additional_special_tokens   )
                 # self.assertIn("an_additional_special_token",tokenizer_without_change_in_init.get_vocab()) # ByT5Tokenization no vocab
                 self.assertEqual(
                     ['''an_additional_special_token''']  ,    tokenizer_without_change_in_init.convert_ids_to_tokens(
                         tokenizer_without_change_in_init.convert_tokens_to_ids(['''an_additional_special_token''']   )   )  ,    )

                 # Now we test that we can change the value of additional_special_tokens in the from_pretrained
                 __lowerCamelCase          =  added_tokens_extra_ids + [AddedToken('''a_new_additional_special_token'''  ,    lstrip=a   )]
                 __lowerCamelCase          =  tokenizer_class.from_pretrained(
                     a  ,    additional_special_tokens=a  ,    )

                 self.assertIn('''a_new_additional_special_token'''  ,    tokenizer.additional_special_tokens   )
                 self.assertEqual(
                     ['''a_new_additional_special_token''']  ,    tokenizer.convert_ids_to_tokens(
                         tokenizer.convert_tokens_to_ids(['''a_new_additional_special_token''']   )   )  ,    )






     def        SCREAMING_SNAKE_CASE__       (			self		:		Optional[Any]   ):





         """simple docstring"""



         __lowerCamelCase          =  []
         if self.test_slow_tokenizer:
             tokenizer_list.append((self.tokenizer_class, self.get_tokenizer())   )

         if self.test_rust_tokenizer:
             tokenizer_list.append((self.rust_tokenizer_class, self.get_rust_tokenizer())   )

         for tokenizer_class, tokenizer_utils in tokenizer_list:
             with tempfile.TemporaryDirectory() as tmp_dir:
                 tokenizer_utils.save_pretrained(a   )

                 __lowerCamelCase          =  tokenizer_class.from_pretrained(a   )

                 self.assertTrue(tokenizer.decode([2_55]   ) == ''''''   )






     def        SCREAMING_SNAKE_CASE__       (			self		:		List[str]   ):





         """simple docstring"""



         pass






     def        SCREAMING_SNAKE_CASE__       (			self		:		Optional[Any]   ):





         """simple docstring"""



         pass






     def        SCREAMING_SNAKE_CASE__       (			self		:		Union[str, Any]   ):





         """simple docstring"""



         pass






     def        SCREAMING_SNAKE_CASE__       (			self		:		List[Any]   ):





         """simple docstring"""



         pass






     def        SCREAMING_SNAKE_CASE__       (			self		:		List[Any]   ):





         """simple docstring"""



         __lowerCamelCase          =  self.get_tokenizers(fast=a  ,    do_lower_case=a   )
         for tokenizer in tokenizers:
             with self.subTest(f"""{tokenizer.__class__.__name__}"""   ):
                 __lowerCamelCase          =  ['''t''', '''h''', '''i''', '''s''', ''' ''', '''i''', '''s''', ''' ''', '''a''', ''' ''', '''t''', '''e''', '''x''', '''t''', '''</s>''']
                 __lowerCamelCase          =  tokenizer.convert_tokens_to_string(a   )

                 self.assertIsInstance(a  ,    a   )






     def        SCREAMING_SNAKE_CASE__       (			self		:		Optional[Any]   ):





         """simple docstring"""



         __lowerCamelCase          =  self.get_tokenizers()
         for tokenizer in tokenizers:
             with self.subTest(f"""{tokenizer.__class__.__name__}"""   ):
                 __lowerCamelCase          =  [
                     '''bos_token''',
                     '''eos_token''',
                     '''unk_token''',
                     '''sep_token''',
                     '''pad_token''',
                     '''cls_token''',
                     '''mask_token''',
                 ]

                 __lowerCamelCase          =  0
                 __lowerCamelCase          =  tokenizer.convert_ids_to_tokens(
                     a  ,    skip_special_tokens=a   )

                 for attr in attributes_list:
                     setattr(a  ,    attr + '''_id'''  ,    a   )
                     self.assertEqual(getattr(a  ,    a   )  ,    a   )
                     self.assertEqual(getattr(a  ,    attr + '''_id'''   )  ,    a   )

                     setattr(a  ,    attr + '''_id'''  ,    a   )
                     self.assertEqual(getattr(a  ,    a   )  ,    a   )
                     self.assertEqual(getattr(a  ,    attr + '''_id'''   )  ,    a   )

                 setattr(a  ,    '''additional_special_tokens_ids'''  ,    []   )
                 self.assertListEqual(getattr(a  ,    '''additional_special_tokens'''   )  ,    []   )
                 self.assertListEqual(getattr(a  ,    '''additional_special_tokens_ids'''   )  ,    []   )

                 setattr(a  ,    '''additional_special_tokens_ids'''  ,    [token_id_to_test_setters]   )
                 self.assertListEqual(getattr(a  ,    '''additional_special_tokens'''   )  ,    [token_to_test_setters]   )
                 self.assertListEqual(getattr(a  ,    '''additional_special_tokens_ids'''   )  ,    [token_id_to_test_setters]   )

'''simple docstring'''




# Copyright 2023 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
from ..models.auto import AutoModelForSeqaSeqLM, AutoTokenizer
from .base import PipelineTool


__UpperCAmelCase												={
    "Acehnese Arabic": "ace_Arab",
    "Acehnese Latin": "ace_Latn",
    "Mesopotamian Arabic": "acm_Arab",
    "Ta'izzi-Adeni Arabic": "acq_Arab",
    "Tunisian Arabic": "aeb_Arab",
    "Afrikaans": "afr_Latn",
    "South Levantine Arabic": "ajp_Arab",
    "Akan": "aka_Latn",
    "Amharic": "amh_Ethi",
    "North Levantine Arabic": "apc_Arab",
    "Modern Standard Arabic": "arb_Arab",
    "Modern Standard Arabic Romanized": "arb_Latn",
    "Najdi Arabic": "ars_Arab",
    "Moroccan Arabic": "ary_Arab",
    "Egyptian Arabic": "arz_Arab",
    "Assamese": "asm_Beng",
    "Asturian": "ast_Latn",
    "Awadhi": "awa_Deva",
    "Central Aymara": "ayr_Latn",
    "South Azerbaijani": "azb_Arab",
    "North Azerbaijani": "azj_Latn",
    "Bashkir": "bak_Cyrl",
    "Bambara": "bam_Latn",
    "Balinese": "ban_Latn",
    "Belarusian": "bel_Cyrl",
    "Bemba": "bem_Latn",
    "Bengali": "ben_Beng",
    "Bhojpuri": "bho_Deva",
    "Banjar Arabic": "bjn_Arab",
    "Banjar Latin": "bjn_Latn",
    "Standard Tibetan": "bod_Tibt",
    "Bosnian": "bos_Latn",
    "Buginese": "bug_Latn",
    "Bulgarian": "bul_Cyrl",
    "Catalan": "cat_Latn",
    "Cebuano": "ceb_Latn",
    "Czech": "ces_Latn",
    "Chokwe": "cjk_Latn",
    "Central Kurdish": "ckb_Arab",
    "Crimean Tatar": "crh_Latn",
    "Welsh": "cym_Latn",
    "Danish": "dan_Latn",
    "German": "deu_Latn",
    "Southwestern Dinka": "dik_Latn",
    "Dyula": "dyu_Latn",
    "Dzongkha": "dzo_Tibt",
    "Greek": "ell_Grek",
    "English": "eng_Latn",
    "Esperanto": "epo_Latn",
    "Estonian": "est_Latn",
    "Basque": "eus_Latn",
    "Ewe": "ewe_Latn",
    "Faroese": "fao_Latn",
    "Fijian": "fij_Latn",
    "Finnish": "fin_Latn",
    "Fon": "fon_Latn",
    "French": "fra_Latn",
    "Friulian": "fur_Latn",
    "Nigerian Fulfulde": "fuv_Latn",
    "Scottish Gaelic": "gla_Latn",
    "Irish": "gle_Latn",
    "Galician": "glg_Latn",
    "Guarani": "grn_Latn",
    "Gujarati": "guj_Gujr",
    "Haitian Creole": "hat_Latn",
    "Hausa": "hau_Latn",
    "Hebrew": "heb_Hebr",
    "Hindi": "hin_Deva",
    "Chhattisgarhi": "hne_Deva",
    "Croatian": "hrv_Latn",
    "Hungarian": "hun_Latn",
    "Armenian": "hye_Armn",
    "Igbo": "ibo_Latn",
    "Ilocano": "ilo_Latn",
    "Indonesian": "ind_Latn",
    "Icelandic": "isl_Latn",
    "Italian": "ita_Latn",
    "Javanese": "jav_Latn",
    "Japanese": "jpn_Jpan",
    "Kabyle": "kab_Latn",
    "Jingpho": "kac_Latn",
    "Kamba": "kam_Latn",
    "Kannada": "kan_Knda",
    "Kashmiri Arabic": "kas_Arab",
    "Kashmiri Devanagari": "kas_Deva",
    "Georgian": "kat_Geor",
    "Central Kanuri Arabic": "knc_Arab",
    "Central Kanuri Latin": "knc_Latn",
    "Kazakh": "kaz_Cyrl",
    "Kabiyè": "kbp_Latn",
    "Kabuverdianu": "kea_Latn",
    "Khmer": "khm_Khmr",
    "Kikuyu": "kik_Latn",
    "Kinyarwanda": "kin_Latn",
    "Kyrgyz": "kir_Cyrl",
    "Kimbundu": "kmb_Latn",
    "Northern Kurdish": "kmr_Latn",
    "Kikongo": "kon_Latn",
    "Korean": "kor_Hang",
    "Lao": "lao_Laoo",
    "Ligurian": "lij_Latn",
    "Limburgish": "lim_Latn",
    "Lingala": "lin_Latn",
    "Lithuanian": "lit_Latn",
    "Lombard": "lmo_Latn",
    "Latgalian": "ltg_Latn",
    "Luxembourgish": "ltz_Latn",
    "Luba-Kasai": "lua_Latn",
    "Ganda": "lug_Latn",
    "Luo": "luo_Latn",
    "Mizo": "lus_Latn",
    "Standard Latvian": "lvs_Latn",
    "Magahi": "mag_Deva",
    "Maithili": "mai_Deva",
    "Malayalam": "mal_Mlym",
    "Marathi": "mar_Deva",
    "Minangkabau Arabic ": "min_Arab",
    "Minangkabau Latin": "min_Latn",
    "Macedonian": "mkd_Cyrl",
    "Plateau Malagasy": "plt_Latn",
    "Maltese": "mlt_Latn",
    "Meitei Bengali": "mni_Beng",
    "Halh Mongolian": "khk_Cyrl",
    "Mossi": "mos_Latn",
    "Maori": "mri_Latn",
    "Burmese": "mya_Mymr",
    "Dutch": "nld_Latn",
    "Norwegian Nynorsk": "nno_Latn",
    "Norwegian Bokmål": "nob_Latn",
    "Nepali": "npi_Deva",
    "Northern Sotho": "nso_Latn",
    "Nuer": "nus_Latn",
    "Nyanja": "nya_Latn",
    "Occitan": "oci_Latn",
    "West Central Oromo": "gaz_Latn",
    "Odia": "ory_Orya",
    "Pangasinan": "pag_Latn",
    "Eastern Panjabi": "pan_Guru",
    "Papiamento": "pap_Latn",
    "Western Persian": "pes_Arab",
    "Polish": "pol_Latn",
    "Portuguese": "por_Latn",
    "Dari": "prs_Arab",
    "Southern Pashto": "pbt_Arab",
    "Ayacucho Quechua": "quy_Latn",
    "Romanian": "ron_Latn",
    "Rundi": "run_Latn",
    "Russian": "rus_Cyrl",
    "Sango": "sag_Latn",
    "Sanskrit": "san_Deva",
    "Santali": "sat_Olck",
    "Sicilian": "scn_Latn",
    "Shan": "shn_Mymr",
    "Sinhala": "sin_Sinh",
    "Slovak": "slk_Latn",
    "Slovenian": "slv_Latn",
    "Samoan": "smo_Latn",
    "Shona": "sna_Latn",
    "Sindhi": "snd_Arab",
    "Somali": "som_Latn",
    "Southern Sotho": "sot_Latn",
    "Spanish": "spa_Latn",
    "Tosk Albanian": "als_Latn",
    "Sardinian": "srd_Latn",
    "Serbian": "srp_Cyrl",
    "Swati": "ssw_Latn",
    "Sundanese": "sun_Latn",
    "Swedish": "swe_Latn",
    "Swahili": "swh_Latn",
    "Silesian": "szl_Latn",
    "Tamil": "tam_Taml",
    "Tatar": "tat_Cyrl",
    "Telugu": "tel_Telu",
    "Tajik": "tgk_Cyrl",
    "Tagalog": "tgl_Latn",
    "Thai": "tha_Thai",
    "Tigrinya": "tir_Ethi",
    "Tamasheq Latin": "taq_Latn",
    "Tamasheq Tifinagh": "taq_Tfng",
    "Tok Pisin": "tpi_Latn",
    "Tswana": "tsn_Latn",
    "Tsonga": "tso_Latn",
    "Turkmen": "tuk_Latn",
    "Tumbuka": "tum_Latn",
    "Turkish": "tur_Latn",
    "Twi": "twi_Latn",
    "Central Atlas Tamazight": "tzm_Tfng",
    "Uyghur": "uig_Arab",
    "Ukrainian": "ukr_Cyrl",
    "Umbundu": "umb_Latn",
    "Urdu": "urd_Arab",
    "Northern Uzbek": "uzn_Latn",
    "Venetian": "vec_Latn",
    "Vietnamese": "vie_Latn",
    "Waray": "war_Latn",
    "Wolof": "wol_Latn",
    "Xhosa": "xho_Latn",
    "Eastern Yiddish": "ydd_Hebr",
    "Yoruba": "yor_Latn",
    "Yue Chinese": "yue_Hant",
    "Chinese Simplified": "zho_Hans",
    "Chinese Traditional": "zho_Hant",
    "Standard Malay": "zsm_Latn",
    "Zulu": "zul_Latn",
}




class    a__				(       UpperCAmelCase__			):
     lowerCamelCase  :					Any							="facebook/nllb-200-distilled-600M"
     lowerCamelCase  :					Optional[Any]							=(
         "This is a tool that translates text from a language to another. It takes three inputs: `text`, which should "
         "be the text to translate, `src_lang`, which should be the language of the text to translate and `tgt_lang`, "
         "which should be the language for the desired ouput language. Both `src_lang` and `tgt_lang` are written in "
         "plain English, such as 'Romanian', or 'Albanian'. It returns the text translated in `tgt_lang`."
     )
     lowerCamelCase  :					Tuple							="translator"
     lowerCamelCase  :					Any							=AutoTokenizer
     lowerCamelCase  :					Dict							=AutoModelForSeqaSeqLM
     lowerCamelCase  :					Union[str, Any]							=LANGUAGE_CODES

     lowerCamelCase  :					Any							=["text", "text", "text"]
     lowerCamelCase  :					Union[str, Any]							=["text"]






     def        SCREAMING_SNAKE_CASE__       (			self		:		Optional[int]  ,    a		:		Any  ,    a		:		List[str]  ,    a		:		Any   ):





         """simple docstring"""



         if src_lang not in self.lang_to_code:
             raise ValueError(f"""{src_lang} is not a supported language."""   )
         if tgt_lang not in self.lang_to_code:
             raise ValueError(f"""{tgt_lang} is not a supported language."""   )
         __lowerCamelCase          =  self.lang_to_code[src_lang]
         __lowerCamelCase          =  self.lang_to_code[tgt_lang]
         return self.pre_processor._build_translation_inputs(
             a  ,    return_tensors='''pt'''  ,    src_lang=a  ,    tgt_lang=a   )






     def        SCREAMING_SNAKE_CASE__       (			self		:		str  ,    a		:		Optional[Any]   ):





         """simple docstring"""



         return self.model.generate(**a   )






     def        SCREAMING_SNAKE_CASE__       (			self		:		Optional[int]  ,    a		:		str   ):





         """simple docstring"""



         return self.post_processor.decode(outputs[0].tolist()  ,    skip_special_tokens=a   )
