
'''simple docstring'''
import tempfile
import unittest
from pathlib import Path
from shutil import copyfile

from transformers import MaMaaaTokenizer, is_torch_available
from transformers.testing_utils import (
    get_tests_dir,
    nested_simplify,
    require_sentencepiece,
    require_tokenizers,
    require_torch,
    slow,
)
from transformers.utils import is_sentencepiece_available


if is_sentencepiece_available():
  from transformers.models.mam_aaa.tokenization_mam_aaa import VOCAB_FILES_NAMES, save_json

from ...test_tokenization_common import TokenizerTesterMixin


if is_sentencepiece_available():
  a_											=						get_tests_dir("fixtures/test_sentencepiece.model")


if is_torch_available():
  from transformers.models.mam_aaa.modeling_mam_aaa import shift_tokens_right

a_											=						12_8022
a_											=						12_8028






@require_sentencepiece
class    UpperCAmelCase_				(	snake_case__    ,						unittest.TestCase					):
 UpperCAmelCase_		    =						MaMaaaTokenizer
 UpperCAmelCase_		    =						False
 UpperCAmelCase_		    =						False
 UpperCAmelCase_		    =						True





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

     snake_case_ :    Any     			=						["</s>", "<unk>", "▁This", "▁is", "▁a", "▁t", "est", "\u0120", "<pad>"]
     snake_case_ :    Optional[Any]     			=						dict(zip(lowercase_ ,       range(len(lowercase_))))
     snake_case_ :    Tuple     			=						Path(self.tmpdirname)
     save_json(lowercase_ ,       save_dir / VOCAB_FILES_NAMES["vocab_file"])
     if not (save_dir / VOCAB_FILES_NAMES["spm_file"]).exists():
         copyfile(lowercase_ ,       save_dir / VOCAB_FILES_NAMES["spm_file"])

     snake_case_ :    List[str]     			=						MaMaaaTokenizer.from_pretrained(self.tmpdirname)
     tokenizer.save_pretrained(self.tmpdirname)





 def        snake_case__		(    self ,       **lowercase_):
     return MaMaaaTokenizer.from_pretrained(self.tmpdirname ,       **lowercase_)





 def        snake_case__		(    self ,       lowercase_):
     return (
         "This is a test",
         "This is a test",
     )





 def        snake_case__		(    self):
     snake_case_ :    int     			=						"</s>"
     snake_case_ :    int     			=						0

     self.assertEqual(self.get_tokenizer()._convert_token_to_id(lowercase_) ,       lowercase_)
     self.assertEqual(self.get_tokenizer()._convert_id_to_token(lowercase_) ,       lowercase_)





 def        snake_case__		(    self):
     snake_case_ :    Dict     			=						self.get_tokenizer()
     snake_case_ :    Optional[Any]     			=						list(tokenizer.get_vocab().keys())

     self.assertEqual(vocab_keys[0] ,       "</s>")
     self.assertEqual(vocab_keys[1] ,       "<unk>")
     self.assertEqual(vocab_keys[-1] ,       "<s>")
     self.assertEqual(len(lowercase_) ,       tokenizer.vocab_size + len(tokenizer.get_added_vocab()))





 @unittest.skip("Skip this test while all models are still to be uploaded.")
 def        snake_case__		(    self):
     pass





 def        snake_case__		(    self):
     snake_case_ :    Optional[int]     			=						self.get_tokenizer()

     snake_case_ :    str     			=						tokenizer.tokenize("This is a test")
     self.assertListEqual(lowercase_ ,       ["▁This", "▁is", "▁a", "▁t", "est"])

     self.assertListEqual(
         tokenizer.convert_tokens_to_ids(lowercase_) ,       [2, 3, 4, 5, 6] ,       )

     snake_case_ :    int     			=						tokenizer.convert_ids_to_tokens([2, 3, 4, 5, 6])
     self.assertListEqual(lowercase_ ,       ["▁This", "▁is", "▁a", "▁t", "est"])

     snake_case_ :    Optional[Any]     			=						tokenizer.convert_tokens_to_string(lowercase_)
     self.assertEqual(lowercase_ ,       "This is a test")





 @slow
 def        snake_case__		(    self):
     # fmt: off
     snake_case_ :    List[str]     			=						{"input_ids": [[12_80_22, 11_01_08, 3_97, 11, 3_82_72, 22_47, 12_48_11, 2_85, 1_81_05, 15_86, 2_07, 7, 3_95_34, 44_28, 3_97, 10_19, 1_81_05, 15_86, 2_07, 7, 4_13_37, 1_67_86, 2_41, 7, 2_02_14, 17, 12_56_90, 1_03_98, 7, 4_43_78, 5_80_69, 6_83_42, 77_98, 73_43, 11, 2_99, 3_33_10, 4, 1_58, 3_73_50, 9_40_77, 45_69, 2_99, 3_33_10, 90, 4, 5_28_40, 2_90, 4, 3_12_70, 1_12, 2_99, 6_82, 4, 5_28_40, 3_99_53, 1_40_79, 1_93, 5_25_19, 9_08_94, 1_78_94, 12_06_97, 11, 4_04_45, 5_51, 17, 10_19, 5_25_19, 9_08_94, 1_77_56, 9_63, 11, 4_04_45, 4_80, 17, 97_92, 11_20, 51_73, 13_93, 62_40, 1_67_86, 2_41, 12_09_96, 28, 12_45, 13_93, 11_82_40, 1_11_23, 10_19, 9_36_12, 26_91, 1_06_18, 9_80_58, 12_04_09, 19_28, 2_79, 4, 4_06_83, 3_67, 1_78, 2_07, 10_19, 1_03, 10_31_21, 5_06, 6_52_96, 5, 2], [12_80_22, 2_12_17, 3_67, 1_17, 12_54_50, 1_28, 7_19, 7, 73_08, 40, 9_36_12, 1_26_69, 11_16, 1_67_04, 71, 1_77_85, 36_99, 1_55_92, 35, 1_44, 95_84, 2_41, 1_19_43, 7_13, 9_50, 7_99, 22_47, 8_84_27, 1_50, 1_49, 11_88_13, 12_07_06, 10_19, 10_69_06, 8_15_18, 28, 12_24, 2_27_99, 3_97, 5, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1], [12_80_22, 16_58, 12_33_11, 51_55, 55_78, 47_22, 2_79, 1_49_47, 23_66, 11_20, 11_97, 14, 13_48, 92_32, 5, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1]], "attention_mask": [[1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1], [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]]}  # noqa: E501
     # fmt: on

     self.tokenizer_integration_test_util(
         expected_encoding=lowercase_ ,       model_name="facebook/m2m100_418M" ,       revision="c168bae485c864188cf9aa0e4108b0b6934dc91e" ,       )






@require_torch
@require_sentencepiece
@require_tokenizers
class    UpperCAmelCase_				(	unittest.TestCase					):
 UpperCAmelCase_		    =						"""facebook/m2m100_418M"""
 UpperCAmelCase_		    =						[
     """In my opinion, there are two levels of response from the French government.""",
     """NSA Affair Emphasizes Complete Lack of Debate on Intelligence""",
 ]
 UpperCAmelCase_		    =						[
     """Selon moi, il y a deux niveaux de réponse de la part du gouvernement français.""",
     """L'affaire NSA souligne l'absence totale de débat sur le renseignement""",
 ]

 # fmt: off
 UpperCAmelCase_		    =						[EN_CODE, 5_9_3, 1_9_4_9, 1_1_5_7_8_1, 4, 7_1_5_8_6, 4_2_3_4, 6_0_6_3_3, 1_2_6_2_3_3, 4_3_2, 1_2_3_8_0_8, 1_5_5_9_2, 1_1_9_7, 1_1_7_1_3_2, 1_2_0_6_1_8, 5, 2]





 @classmethod
 def        snake_case__		(    cls):
     snake_case_ :    MaMaaaTokenizer     			=						MaMaaaTokenizer.from_pretrained(
         cls.checkpoint_name ,       src_lang="en" ,       tgt_lang="fr")
     snake_case_ :    int     			=						1
     return cls





 def        snake_case__		(    self):
     self.assertEqual(self.tokenizer.get_lang_id("ar") ,       12_80_06)
     self.assertEqual(self.tokenizer.get_lang_id("en") ,       12_80_22)
     self.assertEqual(self.tokenizer.get_lang_id("ro") ,       12_80_76)
     self.assertEqual(self.tokenizer.get_lang_id("mr") ,       12_80_63)





 def        snake_case__		(    self):
     snake_case_ :    Union[str, Any]     			=						self.tokenizer.get_vocab()
     self.assertEqual(len(lowercase_) ,       self.tokenizer.vocab_size)
     self.assertEqual(vocab["<unk>"] ,       3)
     self.assertIn(self.tokenizer.get_lang_token("en") ,       lowercase_)





 def        snake_case__		(    self):
     snake_case_ :    int     			=						"en"
     snake_case_ :    Any     			=						self.tokenizer.batch_encode_plus(self.src_text).input_ids[0]
     self.assertListEqual(self.expected_src_tokens ,       lowercase_)





 def        snake_case__		(    self):
     self.assertIn(lowercase_ ,       self.tokenizer.all_special_ids)
     # fmt: off
     snake_case_ :    Optional[int]     			=						[FR_CODE, 53_64, 82, 86_42, 4, 2_94, 47, 8, 1_40_28, 1_36, 32_86, 97_06, 6, 9_07_97, 6, 14_40_12, 1_62, 8_81_28, 3_00_61, 5, 2]
     # fmt: on
     snake_case_ :    Any     			=						self.tokenizer.decode(lowercase_ ,       skip_special_tokens=lowercase_)
     snake_case_ :    str     			=						self.tokenizer.decode(generated_ids[1:] ,       skip_special_tokens=lowercase_)
     self.assertEqual(lowercase_ ,       lowercase_)
     self.assertNotIn(self.tokenizer.eos_token ,       lowercase_)





 def        snake_case__		(    self):
     snake_case_ :    Optional[Any]     			=						tempfile.mkdtemp()
     snake_case_ :    Any     			=						self.tokenizer.lang_token_to_id
     self.tokenizer.save_pretrained(lowercase_)
     snake_case_ :    int     			=						MaMaaaTokenizer.from_pretrained(lowercase_)
     self.assertDictEqual(new_tok.lang_token_to_id ,       lowercase_)





 @require_torch
 def        snake_case__		(    self):
     snake_case_ :    Union[str, Any]     			=						"en"
     snake_case_ :    Union[str, Any]     			=						"fr"

     snake_case_ :    Union[str, Any]     			=						self.tokenizer(self.src_text ,       text_target=self.tgt_text ,       padding=lowercase_ ,       return_tensors="pt")

     snake_case_ :    str     			=						shift_tokens_right(
         batch["labels"] ,       self.tokenizer.pad_token_id ,       self.tokenizer.eos_token_id)

     for k in batch:
         snake_case_ :    Optional[int]     			=						batch[k].tolist()
     # batch = {k: v.tolist() for k,v in batch.items()}
     # fairseq batch: https://gist.github.com/sshleifer/cba08bc2109361a74ac3760a7e30e4f4
     # batch.decoder_inputs_ids[0][0] ==
     assert batch.input_ids[1][0] == EN_CODE
     assert batch.input_ids[1][-1] == 2
     assert batch.labels[1][0] == FR_CODE
     assert batch.labels[1][-1] == 2
     assert batch.decoder_input_ids[1][:2] == [2, FR_CODE]





 @require_torch
 def        snake_case__		(    self):
     snake_case_ :    List[str]     			=						"mr"
     self.assertListEqual(self.tokenizer.prefix_tokens ,       [self.tokenizer.get_lang_id("mr")])
     self.assertListEqual(self.tokenizer.suffix_tokens ,       [self.tokenizer.eos_token_id])

     snake_case_ :    int     			=						"zh"
     self.assertListEqual(self.tokenizer.prefix_tokens ,       [self.tokenizer.get_lang_id("zh")])
     self.assertListEqual(self.tokenizer.suffix_tokens ,       [self.tokenizer.eos_token_id])





 @require_torch
 def        snake_case__		(    self):
     snake_case_ :    List[str]     			=						"mr"
     self.tokenizer._switch_to_target_mode()
     self.assertListEqual(self.tokenizer.prefix_tokens ,       [self.tokenizer.get_lang_id("mr")])
     self.assertListEqual(self.tokenizer.suffix_tokens ,       [self.tokenizer.eos_token_id])
     self.tokenizer._switch_to_input_mode()
     self.assertListEqual(self.tokenizer.prefix_tokens ,       [self.tokenizer.get_lang_id(self.tokenizer.src_lang)])

     snake_case_ :    str     			=						"zh"
     self.tokenizer._switch_to_target_mode()
     self.assertListEqual(self.tokenizer.prefix_tokens ,       [self.tokenizer.get_lang_id("zh")])
     self.assertListEqual(self.tokenizer.suffix_tokens ,       [self.tokenizer.eos_token_id])
     self.tokenizer._switch_to_input_mode()
     self.assertListEqual(self.tokenizer.prefix_tokens ,       [self.tokenizer.get_lang_id(self.tokenizer.src_lang)])





 @require_torch
 def        snake_case__		(    self):
     snake_case_ :    Union[str, Any]     			=						self.tokenizer._build_translation_inputs("A test" ,       return_tensors="pt" ,       src_lang="en" ,       tgt_lang="ar")

     self.assertEqual(
         nested_simplify(lowercase_) ,       {
             # en_XX, A, test, EOS
             "input_ids": [[12_80_22, 58, 41_83, 2]],
             "attention_mask": [[1, 1, 1, 1]],
             # ar_AR
             "forced_bos_token_id": 12_80_06,
         } ,       )






'''simple docstring'''
from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available


a_											=						{
    "configuration_biogpt": ["BIOGPT_PRETRAINED_CONFIG_ARCHIVE_MAP", "BioGptConfig"],
    "tokenization_biogpt": ["BioGptTokenizer"],
}

try:
  if not is_torch_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  a_											=						[
      "BIOGPT_PRETRAINED_MODEL_ARCHIVE_LIST",
      "BioGptForCausalLM",
      "BioGptForTokenClassification",
      "BioGptForSequenceClassification",
      "BioGptModel",
      "BioGptPreTrainedModel",
  ]


if TYPE_CHECKING:
  from .configuration_biogpt import BIOGPT_PRETRAINED_CONFIG_ARCHIVE_MAP, BioGptConfig
  from .tokenization_biogpt import BioGptTokenizer

  try:
    if not is_torch_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .modeling_biogpt import (
        BIOGPT_PRETRAINED_MODEL_ARCHIVE_LIST,
        BioGptForCausalLM,
        BioGptForSequenceClassification,
        BioGptForTokenClassification,
        BioGptModel,
        BioGptPreTrainedModel,
    )


else:
  import sys

  a_											=						_LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)




