

"""simple docstring"""




import shutil
import tempfile
import unittest

from transformers import SPIECE_UNDERLINE, BatchEncoding, MBartaaTokenizer, MBartaaTokenizerFast, is_torch_available
from transformers.testing_utils import (
    get_tests_dir,
    nested_simplify,
    require_sentencepiece,
    require_tokenizers,
    require_torch,
    slow,
)

from ...test_tokenization_common import TokenizerTesterMixin


SCREAMING_SNAKE_CASE_     :			List[str]	  =			get_tests_dir('''fixtures/test_sentencepiece.model''')

if is_torch_available():
     from transformers.models.mbart.modeling_mbart import shift_tokens_right

SCREAMING_SNAKE_CASE_     :			int	  =			25_0004
SCREAMING_SNAKE_CASE_     :			Optional[int]	  =			25_0020


@require_sentencepiece
@require_tokenizers
class 		_A       (			lowercase__				,       unittest.TestCase					):
      __a								=	MBartaaTokenizer
      __a								=	MBartaaTokenizerFast
      __a								=	True
      __a								=	True





      def 					_lowerCamelCase  (  self		)   ->					Tuple:
         super().setUp()

         # We have a SentencePiece fixture for testing
         lowerCamelCase__						=			MBartaaTokenizer(__lowerCamelCase    ,						src_lang="en_XX"    ,						tgt_lang="ro_RO"    ,						keep_accents=__lowerCamelCase		)
         tokenizer.save_pretrained(self.tmpdirname		)





      def 					_lowerCamelCase  (  self		)   ->					List[Any]:
         lowerCamelCase__						=			"<s>"
         lowerCamelCase__						=			0

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





      def 					_lowerCamelCase  (  self		)   ->					int:
         lowerCamelCase__						=			list(self.get_tokenizer().get_vocab().keys()		)

         self.assertEqual(vocab_keys[0]    ,						"<s>"		)
         self.assertEqual(vocab_keys[1]    ,						"<pad>"		)
         self.assertEqual(vocab_keys[-1]    ,						"<mask>"		)
         self.assertEqual(len(__lowerCamelCase		)    ,						1054		)





      def 					_lowerCamelCase  (  self		)   ->					Optional[int]:
         self.assertEqual(self.get_tokenizer().vocab_size    ,						1054		)





      def 					_lowerCamelCase  (  self		)   ->					Optional[int]:
         lowerCamelCase__						=			MBartaaTokenizer(__lowerCamelCase    ,						src_lang="en_XX"    ,						tgt_lang="ro_RO"    ,						keep_accents=__lowerCamelCase		)

         lowerCamelCase__						=			tokenizer.tokenize("This is a test"		)
         self.assertListEqual(__lowerCamelCase    ,						["▁This", "▁is", "▁a", "▁t", "est"]		)

         self.assertListEqual(
             tokenizer.convert_tokens_to_ids(__lowerCamelCase		)    ,						[value + tokenizer.fairseq_offset for value in [285, 46, 10, 170, 382]]    ,						)

         lowerCamelCase__						=			tokenizer.tokenize("I was born in 92000, and this is falsé."		)
         self.assertListEqual(
             __lowerCamelCase    ,						[SPIECE_UNDERLINE + "I", SPIECE_UNDERLINE + "was", SPIECE_UNDERLINE + "b", "or", "n", SPIECE_UNDERLINE + "in", SPIECE_UNDERLINE + "", "9", "2", "0", "0", "0", ",", SPIECE_UNDERLINE + "and", SPIECE_UNDERLINE + "this", SPIECE_UNDERLINE + "is", SPIECE_UNDERLINE + "f", "al", "s", "é", "."]    ,						)
         lowerCamelCase__						=			tokenizer.convert_tokens_to_ids(__lowerCamelCase		)
         self.assertListEqual(
             __lowerCamelCase    ,						[
                 value + tokenizer.fairseq_offset
                 for value in [8, 21, 84, 55, 24, 19, 7, 2, 602, 347, 347, 347, 3, 12, 66, 46, 72, 80, 6, 2, 4]
             ]    ,						)

         lowerCamelCase__						=			tokenizer.convert_ids_to_tokens(__lowerCamelCase		)
         self.assertListEqual(
             __lowerCamelCase    ,						[SPIECE_UNDERLINE + "I", SPIECE_UNDERLINE + "was", SPIECE_UNDERLINE + "b", "or", "n", SPIECE_UNDERLINE + "in", SPIECE_UNDERLINE + "", "<unk>", "2", "0", "0", "0", ",", SPIECE_UNDERLINE + "and", SPIECE_UNDERLINE + "this", SPIECE_UNDERLINE + "is", SPIECE_UNDERLINE + "f", "al", "s", "<unk>", "."]    ,						)





      @slow
      def 					_lowerCamelCase  (  self		)   ->					int:
         lowerCamelCase__						=			{"input_ids": [[250004, 11062, 82772, 7, 15, 82772, 538, 51529, 237, 17198, 1290, 206, 9, 215175, 1314, 136, 17198, 1290, 206, 9, 56359, 42, 122009, 9, 16466, 16, 87344, 4537, 9, 4717, 78381, 6, 159958, 7, 15, 24480, 618, 4, 527, 22693, 5428, 4, 2777, 24480, 9874, 4, 43523, 594, 4, 803, 18392, 33189, 18, 4, 43523, 24447, 12399, 100, 24955, 83658, 9626, 144057, 15, 839, 22335, 16, 136, 24955, 83658, 83479, 15, 39102, 724, 16, 678, 645, 2789, 1328, 4589, 42, 122009, 115774, 23, 805, 1328, 46876, 7, 136, 53894, 1940, 42227, 41159, 17721, 823, 425, 4, 27512, 98722, 206, 136, 5531, 4970, 919, 17336, 5, 2], [250004, 20080, 618, 83, 82775, 47, 479, 9, 1517, 73, 53894, 333, 80581, 110117, 18811, 5256, 1295, 51, 152526, 297, 7986, 390, 124416, 538, 35431, 214, 98, 15044, 25737, 136, 7108, 43701, 23, 756, 135355, 7, 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], [250004, 581, 63773, 119455, 6, 147797, 88203, 7, 645, 70, 21, 3285, 10269, 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]], "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, 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], [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]]}  # noqa: E501
         # fmt: on

         self.tokenizer_integration_test_util(
             expected_encoding=__lowerCamelCase    ,						model_name="facebook/mbart-large-50"    ,						revision="d3913889c59cd5c9e456b269c376325eabad57e2"    ,						)





      def 					_lowerCamelCase  (  self		)   ->					int:



         if not self.test_slow_tokenizer:
            # as we don't have a slow version, we can't compare the outputs between slow and fast versions
            return

         lowerCamelCase__						=			(self.rust_tokenizer_class, "hf-internal-testing/tiny-random-mbart50", {})
         for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
            with self.subTest(f'{tokenizer.__class__.__name__} ({pretrained_name})'		):
               lowerCamelCase__						=			self.rust_tokenizer_class.from_pretrained(__lowerCamelCase    ,						**__lowerCamelCase		)
               lowerCamelCase__						=			self.tokenizer_class.from_pretrained(__lowerCamelCase    ,						**__lowerCamelCase		)

               lowerCamelCase__						=			tempfile.mkdtemp()

               lowerCamelCase__						=			tokenizer_r.save_pretrained(__lowerCamelCase		)
               lowerCamelCase__						=			tokenizer_p.save_pretrained(__lowerCamelCase		)

               # Checks it save with the same files + the tokenizer.json file for the fast one
               self.assertTrue(any("tokenizer.json" in f for f in tokenizer_r_files		)		)
               lowerCamelCase__						=			tuple(f for f in tokenizer_r_files if "tokenizer.json" not in f		)
               self.assertSequenceEqual(__lowerCamelCase    ,						__lowerCamelCase		)

               # Checks everything loads correctly in the same way
               lowerCamelCase__						=			tokenizer_r.from_pretrained(__lowerCamelCase		)
               lowerCamelCase__						=			tokenizer_p.from_pretrained(__lowerCamelCase		)

               # Check special tokens are set accordingly on Rust and Python
               for key in tokenizer_pp.special_tokens_map:
                  self.assertTrue(hasattr(__lowerCamelCase    ,						__lowerCamelCase		)		)
                  # self.assertEqual(getattr(tokenizer_rp, key), getattr(tokenizer_pp, key))
                  # self.assertEqual(getattr(tokenizer_rp, key + "_id"), getattr(tokenizer_pp, key + "_id"))

               shutil.rmtree(__lowerCamelCase		)

               # Save tokenizer rust, legacy_format=True
               lowerCamelCase__						=			tempfile.mkdtemp()

               lowerCamelCase__						=			tokenizer_r.save_pretrained(__lowerCamelCase    ,						legacy_format=__lowerCamelCase		)
               lowerCamelCase__						=			tokenizer_p.save_pretrained(__lowerCamelCase		)

               # Checks it save with the same files
               self.assertSequenceEqual(__lowerCamelCase    ,						__lowerCamelCase		)

               # Checks everything loads correctly in the same way
               lowerCamelCase__						=			tokenizer_r.from_pretrained(__lowerCamelCase		)
               lowerCamelCase__						=			tokenizer_p.from_pretrained(__lowerCamelCase		)

               # Check special tokens are set accordingly on Rust and Python
               for key in tokenizer_pp.special_tokens_map:
                  self.assertTrue(hasattr(__lowerCamelCase    ,						__lowerCamelCase		)		)

               shutil.rmtree(__lowerCamelCase		)

               # Save tokenizer rust, legacy_format=False
               lowerCamelCase__						=			tempfile.mkdtemp()

               lowerCamelCase__						=			tokenizer_r.save_pretrained(__lowerCamelCase    ,						legacy_format=__lowerCamelCase		)
               lowerCamelCase__						=			tokenizer_p.save_pretrained(__lowerCamelCase		)

               # Checks it saved the tokenizer.json file
               self.assertTrue(any("tokenizer.json" in f for f in tokenizer_r_files		)		)

               # Checks everything loads correctly in the same way
               lowerCamelCase__						=			tokenizer_r.from_pretrained(__lowerCamelCase		)
               lowerCamelCase__						=			tokenizer_p.from_pretrained(__lowerCamelCase		)

               # Check special tokens are set accordingly on Rust and Python
               for key in tokenizer_pp.special_tokens_map:
                  self.assertTrue(hasattr(__lowerCamelCase    ,						__lowerCamelCase		)		)

               shutil.rmtree(__lowerCamelCase		)






@require_torch
@require_sentencepiece
@require_tokenizers
class 		_A       (			unittest.TestCase					):
      __a								=	'facebook/mbart-large-50-one-to-many-mmt'
      __a								=	[
          ' UN Chief Says There Is No Military Solution in Syria',
          ' Secretary-General Ban Ki-moon says his response to Russia\'s stepped up military support for Syria is that \"there is no military solution\" to the nearly five-year conflict and more weapons will only worsen the violence and misery for millions of people.',
      ]
      __a								=	[
          'Şeful ONU declară că nu există o soluţie militară în Siria',
          'Secretarul General Ban Ki-moon declară că răspunsul său la intensificarea sprijinului militar al Rusiei'
          ' pentru Siria este că \"nu există o soluţie militară\" la conflictul de aproape cinci ani şi că noi arme nu vor'
          ' face decât să înrăutăţească violenţele şi mizeria pentru milioane de oameni.',
      ]
      __a								=	[EN_CODE, 8274, 12_7873, 2_5916, 7, 8622, 2071, 438, 6_7485, 53, 18_7895, 23, 5_1712, 2]





      @classmethod
      def 					_lowerCamelCase  (  cls		)   ->					List[Any]:
         lowerCamelCase__						=			MBartaaTokenizer.from_pretrained(
             cls.checkpoint_name    ,						src_lang="en_XX"    ,						tgt_lang="ro_RO"		)
         lowerCamelCase__						=			1
         return cls





      def 					_lowerCamelCase  (  self		)   ->					Optional[Any]:
         self.assertEqual(self.tokenizer.fairseq_tokens_to_ids["ar_AR"]    ,						250001		)
         self.assertEqual(self.tokenizer.fairseq_tokens_to_ids["en_EN"]    ,						250004		)
         self.assertEqual(self.tokenizer.fairseq_tokens_to_ids["ro_RO"]    ,						250020		)
         self.assertEqual(self.tokenizer.fairseq_tokens_to_ids["mr_IN"]    ,						250038		)





      def 					_lowerCamelCase  (  self		)   ->					List[Any]:
         lowerCamelCase__						=			self.tokenizer.batch_encode_plus(self.src_text		).input_ids[0]
         self.assertListEqual(self.expected_src_tokens    ,						__lowerCamelCase		)





      def 					_lowerCamelCase  (  self		)   ->					Tuple:
         self.assertIn(__lowerCamelCase    ,						self.tokenizer.all_special_ids		)
         lowerCamelCase__						=			[RO_CODE, 884, 9019, 96, 9, 916, 86792, 36, 18743, 15596, 5, 2]
         lowerCamelCase__						=			self.tokenizer.decode(__lowerCamelCase    ,						skip_special_tokens=__lowerCamelCase		)
         lowerCamelCase__						=			self.tokenizer.decode(generated_ids[1:]    ,						skip_special_tokens=__lowerCamelCase		)
         self.assertEqual(__lowerCamelCase    ,						__lowerCamelCase		)
         self.assertNotIn(self.tokenizer.eos_token    ,						__lowerCamelCase		)





      def 					_lowerCamelCase  (  self		)   ->					List[Any]:
         lowerCamelCase__						=			["this is gunna be a long sentence " * 20]
         assert isinstance(src_text[0]    ,						__lowerCamelCase		)
         lowerCamelCase__						=			10
         lowerCamelCase__						=			self.tokenizer(__lowerCamelCase    ,						max_length=__lowerCamelCase    ,						truncation=__lowerCamelCase		).input_ids[0]
         self.assertEqual(ids[0]    ,						__lowerCamelCase		)
         self.assertEqual(ids[-1]    ,						2		)
         self.assertEqual(len(__lowerCamelCase		)    ,						__lowerCamelCase		)





      def 					_lowerCamelCase  (  self		)   ->					Optional[int]:
         self.assertListEqual(self.tokenizer.convert_tokens_to_ids(["<mask>", "ar_AR"]		)    ,						[250053, 250001]		)





      def 					_lowerCamelCase  (  self		)   ->					Optional[Any]:
         lowerCamelCase__						=			tempfile.mkdtemp()
         lowerCamelCase__						=			self.tokenizer.fairseq_tokens_to_ids
         self.tokenizer.save_pretrained(__lowerCamelCase		)
         lowerCamelCase__						=			MBartaaTokenizer.from_pretrained(__lowerCamelCase		)
         self.assertDictEqual(new_tok.fairseq_tokens_to_ids    ,						__lowerCamelCase		)





      @require_torch
      def 					_lowerCamelCase  (  self		)   ->					Any:
         lowerCamelCase__						=			self.tokenizer(self.src_text    ,						text_target=self.tgt_text    ,						padding=__lowerCamelCase    ,						return_tensors="pt"		)
         lowerCamelCase__						=			shift_tokens_right(batch["labels"]    ,						self.tokenizer.pad_token_id		)

         # fairseq batch: https://gist.github.com/sshleifer/cba08bc2109361a74ac3760a7e30e4f4
         assert batch.input_ids[1][0] == EN_CODE
         assert batch.input_ids[1][-1] == 2
         assert batch.labels[1][0] == RO_CODE
         assert batch.labels[1][-1] == 2
         assert batch.decoder_input_ids[1][:2].tolist() == [2, RO_CODE]





      @require_torch
      def 					_lowerCamelCase  (  self		)   ->					str:
         lowerCamelCase__						=			self.tokenizer(
             self.src_text    ,						text_target=self.tgt_text    ,						padding=__lowerCamelCase    ,						truncation=__lowerCamelCase    ,						max_length=len(self.expected_src_tokens		)    ,						return_tensors="pt"    ,						)
         lowerCamelCase__						=			shift_tokens_right(batch["labels"]    ,						self.tokenizer.pad_token_id		)

         self.assertIsInstance(__lowerCamelCase    ,						__lowerCamelCase		)

         self.assertEqual((2, 14)    ,						batch.input_ids.shape		)
         self.assertEqual((2, 14)    ,						batch.attention_mask.shape		)
         lowerCamelCase__						=			batch.input_ids.tolist()[0]
         self.assertListEqual(self.expected_src_tokens    ,						__lowerCamelCase		)
         self.assertEqual(2    ,						batch.decoder_input_ids[0, 0]		)  # decoder_start_token_id
         # Test that special tokens are reset
         self.assertEqual(self.tokenizer.prefix_tokens    ,						[EN_CODE]		)
         self.assertEqual(self.tokenizer.suffix_tokens    ,						[self.tokenizer.eos_token_id]		)





      def 					_lowerCamelCase  (  self		)   ->					List[Any]:
         lowerCamelCase__						=			self.tokenizer(self.src_text    ,						padding=__lowerCamelCase    ,						truncation=__lowerCamelCase    ,						max_length=3    ,						return_tensors="pt"		)
         lowerCamelCase__						=			self.tokenizer(
             text_target=self.tgt_text    ,						padding=__lowerCamelCase    ,						truncation=__lowerCamelCase    ,						max_length=10    ,						return_tensors="pt"		)
         lowerCamelCase__						=			targets["input_ids"]
         lowerCamelCase__						=			shift_tokens_right(__lowerCamelCase    ,						self.tokenizer.pad_token_id		)

         self.assertEqual(batch.input_ids.shape[1]    ,						3		)
         self.assertEqual(batch.decoder_input_ids.shape[1]    ,						10		)





      @require_torch
      def 					_lowerCamelCase  (  self		)   ->					List[str]:
         lowerCamelCase__						=			self.tokenizer._build_translation_inputs(
             "A test"    ,						return_tensors="pt"    ,						src_lang="en_XX"    ,						tgt_lang="ar_AR"		)

         self.assertEqual(
             nested_simplify(__lowerCamelCase		)    ,						{
                 # en_XX, A, test, EOS
                 "input_ids": [[250004, 62, 3034, 2]],
                 "attention_mask": [[1, 1, 1, 1]],
                 # ar_AR
                 "forced_bos_token_id": 250001,
             }    ,						)







"""simple docstring"""




from typing import TYPE_CHECKING

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


SCREAMING_SNAKE_CASE_     :			List[Any]	  =			{
    '''configuration_rag''': ['''RagConfig'''],
    '''retrieval_rag''': ['''RagRetriever'''],
    '''tokenization_rag''': ['''RagTokenizer'''],
}

try:
     if not is_torch_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     SCREAMING_SNAKE_CASE_     :			Union[str, Any]	  =			[
         '''RagModel''',
         '''RagPreTrainedModel''',
         '''RagSequenceForGeneration''',
         '''RagTokenForGeneration''',
     ]

try:
     if not is_tf_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     SCREAMING_SNAKE_CASE_     :			str	  =			[
         '''TFRagModel''',
         '''TFRagPreTrainedModel''',
         '''TFRagSequenceForGeneration''',
         '''TFRagTokenForGeneration''',
     ]


if TYPE_CHECKING:
     from .configuration_rag import RagConfig
     from .retrieval_rag import RagRetriever
     from .tokenization_rag import RagTokenizer

     try:
          if not is_torch_available():
               raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
          pass
     else:
          from .modeling_rag import RagModel, RagPreTrainedModel, RagSequenceForGeneration, RagTokenForGeneration

     try:
          if not is_tf_available():
               raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
          pass
     else:
          from .modeling_tf_rag import (
              TFRagModel,
              TFRagPreTrainedModel,
              TFRagSequenceForGeneration,
              TFRagTokenForGeneration,
          )

else:
     import sys

     SCREAMING_SNAKE_CASE_     :			List[str]	  =			_LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)




