


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():
 lowerCamelCase					:		str            =						get_tests_dir('fixtures/test_sentencepiece.model')


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

lowerCamelCase					:		Tuple            =						1_2_8_0_2_2
lowerCamelCase					:		List[Any]            =						1_2_8_0_2_8


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




       def     UpperCAmelCase__    ( self				:    str			):
              super().setUp()

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

              snake_case__ :       str	   =							MaMaaaTokenizer.from_pretrained(self.tmpdirname			)
              tokenizer.save_pretrained(self.tmpdirname			)




       def     UpperCAmelCase__    ( self				:    Optional[int]    ,				**_lowerCamelCase				:    Union[str, Any]			):
              return MaMaaaTokenizer.from_pretrained(self.tmpdirname    ,				**__lowerCamelCase			)




       def     UpperCAmelCase__    ( self				:    List[Any]    ,				_lowerCamelCase				:    Optional[Any]			):
              return (
                  "This is a test",
                  "This is a test",
              )




       def     UpperCAmelCase__    ( self				:    int			):
              snake_case__ :       Any	   =							'</s>'
              snake_case__ :       List[str]	   =							0

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




       def     UpperCAmelCase__    ( self				:    List[str]			):
              snake_case__ :       Dict	   =							self.get_tokenizer()
              snake_case__ :       str	   =							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(__lowerCamelCase			)    ,				tokenizer.vocab_size + len(tokenizer.get_added_vocab()			)			)




       @unittest.skip('Skip this test while all models are still to be uploaded.'			)
       def     UpperCAmelCase__    ( self				:    List[Any]			):
              pass




       def     UpperCAmelCase__    ( self				:    Any			):
              snake_case__ :       int	   =							self.get_tokenizer()

              snake_case__ :       Optional[Any]	   =							tokenizer.tokenize('This is a test'			)
              self.assertListEqual(__lowerCamelCase    ,				['▁This', '▁is', '▁a', '▁t', 'est']			)

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

              snake_case__ :       Optional[int]	   =							tokenizer.convert_ids_to_tokens([2, 3, 4, 5, 6]			)
              self.assertListEqual(__lowerCamelCase    ,				['▁This', '▁is', '▁a', '▁t', 'est']			)

              snake_case__ :       str	   =							tokenizer.convert_tokens_to_string(__lowerCamelCase			)
              self.assertEqual(__lowerCamelCase    ,				'This is a test'			)




       @slow
       def     UpperCAmelCase__    ( self				:    Tuple			):
              snake_case__ :       int	   =							{'input_ids': [[1_2_8_0_2_2, 1_1_0_1_0_8, 3_9_7, 1_1, 3_8_2_7_2, 2_2_4_7, 1_2_4_8_1_1, 2_8_5, 1_8_1_0_5, 1_5_8_6, 2_0_7, 7, 3_9_5_3_4, 4_4_2_8, 3_9_7, 1_0_1_9, 1_8_1_0_5, 1_5_8_6, 2_0_7, 7, 4_1_3_3_7, 1_6_7_8_6, 2_4_1, 7, 2_0_2_1_4, 1_7, 1_2_5_6_9_0, 1_0_3_9_8, 7, 4_4_3_7_8, 5_8_0_6_9, 6_8_3_4_2, 7_7_9_8, 7_3_4_3, 1_1, 2_9_9, 3_3_3_1_0, 4, 1_5_8, 3_7_3_5_0, 9_4_0_7_7, 4_5_6_9, 2_9_9, 3_3_3_1_0, 9_0, 4, 5_2_8_4_0, 2_9_0, 4, 3_1_2_7_0, 1_1_2, 2_9_9, 6_8_2, 4, 5_2_8_4_0, 3_9_9_5_3, 1_4_0_7_9, 1_9_3, 5_2_5_1_9, 9_0_8_9_4, 1_7_8_9_4, 1_2_0_6_9_7, 1_1, 4_0_4_4_5, 5_5_1, 1_7, 1_0_1_9, 5_2_5_1_9, 9_0_8_9_4, 1_7_7_5_6, 9_6_3, 1_1, 4_0_4_4_5, 4_8_0, 1_7, 9_7_9_2, 1_1_2_0, 5_1_7_3, 1_3_9_3, 6_2_4_0, 1_6_7_8_6, 2_4_1, 1_2_0_9_9_6, 2_8, 1_2_4_5, 1_3_9_3, 1_1_8_2_4_0, 1_1_1_2_3, 1_0_1_9, 9_3_6_1_2, 2_6_9_1, 1_0_6_1_8, 9_8_0_5_8, 1_2_0_4_0_9, 1_9_2_8, 2_7_9, 4, 4_0_6_8_3, 3_6_7, 1_7_8, 2_0_7, 1_0_1_9, 1_0_3, 1_0_3_1_2_1, 5_0_6, 6_5_2_9_6, 5, 2], [1_2_8_0_2_2, 2_1_2_1_7, 3_6_7, 1_1_7, 1_2_5_4_5_0, 1_2_8, 7_1_9, 7, 7_3_0_8, 4_0, 9_3_6_1_2, 1_2_6_6_9, 1_1_1_6, 1_6_7_0_4, 7_1, 1_7_7_8_5, 3_6_9_9, 1_5_5_9_2, 3_5, 1_4_4, 9_5_8_4, 2_4_1, 1_1_9_4_3, 7_1_3, 9_5_0, 7_9_9, 2_2_4_7, 8_8_4_2_7, 1_5_0, 1_4_9, 1_1_8_8_1_3, 1_2_0_7_0_6, 1_0_1_9, 1_0_6_9_0_6, 8_1_5_1_8, 2_8, 1_2_2_4, 2_2_7_9_9, 3_9_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_2_8_0_2_2, 1_6_5_8, 1_2_3_3_1_1, 5_1_5_5, 5_5_7_8, 4_7_2_2, 2_7_9, 1_4_9_4_7, 2_3_6_6, 1_1_2_0, 1_1_9_7, 1_4, 1_3_4_8, 9_2_3_2, 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=__lowerCamelCase    ,				model_name='facebook/m2m100_418M'    ,				revision='c168bae485c864188cf9aa0e4108b0b6934dc91e'    ,				)


@require_torch
@require_sentencepiece
@require_tokenizers
class snake_case__			(    unittest.TestCase					):
       _lowerCAmelCase   ='''facebook/m2m100_418M'''
       _lowerCAmelCase   =[
           '''In my opinion, there are two levels of response from the French government.''',
           '''NSA Affair Emphasizes Complete Lack of Debate on Intelligence''',
       ]
       _lowerCAmelCase   =[
           '''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
       _lowerCAmelCase   =[EN_CODE, 593, 1949, 115781, 4, 71586, 4234, 60633, 126233, 432, 123808, 15592, 1197, 117132, 120618, 5, 2]




       @classmethod
       def     UpperCAmelCase__    ( cls				:    Optional[int]			):
              snake_case__ :       List[str]	   =							MaMaaaTokenizer.from_pretrained(
                  cls.checkpoint_name    ,				src_lang='en'    ,				tgt_lang='fr'			)
              snake_case__ :       Union[str, Any]	   =							1
              return cls




       def     UpperCAmelCase__    ( self				:    str			):
              self.assertEqual(self.tokenizer.get_lang_id('ar'			)    ,				1_2_8_0_0_6			)
              self.assertEqual(self.tokenizer.get_lang_id('en'			)    ,				1_2_8_0_2_2			)
              self.assertEqual(self.tokenizer.get_lang_id('ro'			)    ,				1_2_8_0_7_6			)
              self.assertEqual(self.tokenizer.get_lang_id('mr'			)    ,				1_2_8_0_6_3			)




       def     UpperCAmelCase__    ( self				:    List[Any]			):
              snake_case__ :       Optional[Any]	   =							self.tokenizer.get_vocab()
              self.assertEqual(len(__lowerCamelCase			)    ,				self.tokenizer.vocab_size			)
              self.assertEqual(vocab['<unk>']    ,				3			)
              self.assertIn(self.tokenizer.get_lang_token('en'			)    ,				__lowerCamelCase			)




       def     UpperCAmelCase__    ( self				:    Dict			):
              snake_case__ :       Dict	   =							'en'
              snake_case__ :       Dict	   =							self.tokenizer.batch_encode_plus(self.src_text			).input_ids[0]
              self.assertListEqual(self.expected_src_tokens    ,				__lowerCamelCase			)




       def     UpperCAmelCase__    ( self				:    Union[str, Any]			):
              self.assertIn(__lowerCamelCase    ,				self.tokenizer.all_special_ids			)
              # fmt: off
              snake_case__ :       Optional[Any]	   =							[FR_CODE, 5_3_6_4, 8_2, 8_6_4_2, 4, 2_9_4, 4_7, 8, 1_4_0_2_8, 1_3_6, 3_2_8_6, 9_7_0_6, 6, 9_0_7_9_7, 6, 1_4_4_0_1_2, 1_6_2, 8_8_1_2_8, 3_0_0_6_1, 5, 2]
              # fmt: on
              snake_case__ :       Union[str, Any]	   =							self.tokenizer.decode(__lowerCamelCase    ,				skip_special_tokens=__lowerCamelCase			)
              snake_case__ :       Optional[int]	   =							self.tokenizer.decode(generated_ids[1:]    ,				skip_special_tokens=__lowerCamelCase			)
              self.assertEqual(__lowerCamelCase    ,				__lowerCamelCase			)
              self.assertNotIn(self.tokenizer.eos_token    ,				__lowerCamelCase			)




       def     UpperCAmelCase__    ( self				:    str			):
              snake_case__ :       Tuple	   =							tempfile.mkdtemp()
              snake_case__ :       int	   =							self.tokenizer.lang_token_to_id
              self.tokenizer.save_pretrained(__lowerCamelCase			)
              snake_case__ :       Union[str, Any]	   =							MaMaaaTokenizer.from_pretrained(__lowerCamelCase			)
              self.assertDictEqual(new_tok.lang_token_to_id    ,				__lowerCamelCase			)




       @require_torch
       def     UpperCAmelCase__    ( self				:    Union[str, Any]			):
              snake_case__ :       List[Any]	   =							'en'
              snake_case__ :       Optional[int]	   =							'fr'

              snake_case__ :       int	   =							self.tokenizer(self.src_text    ,				text_target=self.tgt_text    ,				padding=__lowerCamelCase    ,				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__ :       Tuple	   =							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     UpperCAmelCase__    ( self				:    int			):
              snake_case__ :       Dict	   =							'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__ :       Optional[Any]	   =							'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     UpperCAmelCase__    ( self				:    Dict			):
              snake_case__ :       List[Any]	   =							'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     UpperCAmelCase__    ( self				:    int			):
              snake_case__ :       Any	   =							self.tokenizer._build_translation_inputs('A test'    ,				return_tensors='pt'    ,				src_lang='en'    ,				tgt_lang='ar'			)

              self.assertEqual(
                  nested_simplify(__lowerCamelCase			)    ,				{
                      # en_XX, A, test, EOS
                      'input_ids': [[1_2_8_0_2_2, 5_8, 4_1_8_3, 2]],
                      'attention_mask': [[1, 1, 1, 1]],
                      # ar_AR
                      'forced_bos_token_id': 1_2_8_0_0_6,
                  }    ,				)










"""simple docstring"""






import os
from pathlib import Path




def 			snake_case		(		)						->				Tuple:
  from torch.utils.cpp_extension import load

  _snake_case   	=      Path(lowerCAmelCase_	).resolve().parent.parent.parent / '''kernels''' / '''deformable_detr'''
  _snake_case   	=      [
      root / filename
      for filename in [
          '''vision.cpp''',
          os.path.join('''cpu'''  ,						'''ms_deform_attn_cpu.cpp'''	),
          os.path.join('''cuda'''  ,						'''ms_deform_attn_cuda.cu'''	),
      ]
  ]

  load(
      '''MultiScaleDeformableAttention'''  ,						lowerCAmelCase_  ,						with_cuda=lowerCAmelCase_  ,						extra_include_paths=[str(lowerCAmelCase_	)]  ,						extra_cflags=['''-DWITH_CUDA=1''']  ,						extra_cuda_cflags=[
          '''-DCUDA_HAS_FP16=1''',
          '''-D__CUDA_NO_HALF_OPERATORS__''',
          '''-D__CUDA_NO_HALF_CONVERSIONS__''',
          '''-D__CUDA_NO_HALF2_OPERATORS__''',
      ]  ,						)

  import MultiScaleDeformableAttention as MSDA

  return MSDA





