





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():
						UpperCamelCase_									=get_tests_dir("""fixtures/test_sentencepiece.model""")


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

UpperCamelCase_									=128_022
UpperCamelCase_									=128_028




@require_sentencepiece
class 			_a						(				UpperCAmelCase__     ,    unittest.TestCase    ):
				UpperCamelCase								=   MaMaaaTokenizer
				UpperCamelCase								=   False
				UpperCamelCase								=   False
				UpperCamelCase								=   True






				def     snake_case     (			self		:   Dict							)     ->				Union[str, Any]:




										'''simple docstring'''



										super().setUp()

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

										_UpperCamelCase      : Union[str, Any]         =   MaMaaaTokenizer.from_pretrained(self.tmpdirname							)
										tokenizer.save_pretrained(self.tmpdirname							)






				def     snake_case     (			self		:   Dict,			**lowerCAmelCase__		:   int							)     ->				Optional[int]:




										'''simple docstring'''



										return MaMaaaTokenizer.from_pretrained(self.tmpdirname,			**_SCREAMING_SNAKE_CASE							)






				def     snake_case     (			self		:   Dict,			lowerCAmelCase__		:   int							)     ->				int:




										'''simple docstring'''



										return (
										    "This is a test",
										    "This is a test",
										)






				def     snake_case     (			self		:   Union[str, Any]							)     ->				Tuple:




										'''simple docstring'''



										_UpperCamelCase      : Tuple         =   """</s>"""
										_UpperCamelCase      : Optional[Any]         =   0

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






				def     snake_case     (			self		:   int							)     ->				Optional[int]:




										'''simple docstring'''



										_UpperCamelCase      : int         =   self.get_tokenizer()
										_UpperCamelCase      : Dict         =   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(_SCREAMING_SNAKE_CASE							),			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		:   List[str]							)     ->				Tuple:




										'''simple docstring'''



										pass






				def     snake_case     (			self		:   List[str]							)     ->				Tuple:




										'''simple docstring'''



										_UpperCamelCase      : Optional[int]         =   self.get_tokenizer()

										_UpperCamelCase      : str         =   tokenizer.tokenize('''This is a test'''							)
										self.assertListEqual(_SCREAMING_SNAKE_CASE,			['''▁This''', '''▁is''', '''▁a''', '''▁t''', '''est''']							)

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

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

										_UpperCamelCase      : Dict         =   tokenizer.convert_tokens_to_string(_SCREAMING_SNAKE_CASE							)
										self.assertEqual(_SCREAMING_SNAKE_CASE,			'''This is a test'''							)






				@slow
				def     snake_case     (			self		:   List[str]							)     ->				Any:




										'''simple docstring'''



										_UpperCamelCase      : Any         =   {"""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=_SCREAMING_SNAKE_CASE,			model_name='''facebook/m2m100_418M''',			revision='''c168bae485c864188cf9aa0e4108b0b6934dc91e''',			)




@require_torch
@require_sentencepiece
@require_tokenizers
class 			_a						(				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, 593, 1949, 11_5781, 4, 7_1586, 4234, 6_0633, 12_6233, 432, 12_3808, 1_5592, 1197, 11_7132, 12_0618, 5, 2]






				@classmethod
				def     snake_case     (			cls		:   Dict							)     ->				Optional[int]:




										'''simple docstring'''



										_UpperCamelCase      : MaMaaaTokenizer         =   MaMaaaTokenizer.from_pretrained(
										    cls.checkpoint_name,			src_lang='''en''',			tgt_lang='''fr'''							)
										_UpperCamelCase      : Optional[int]         =   1
										return cls






				def     snake_case     (			self		:   Any							)     ->				List[Any]:




										'''simple docstring'''



										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     snake_case     (			self		:   Optional[int]							)     ->				Optional[Any]:




										'''simple docstring'''



										_UpperCamelCase      : str         =   self.tokenizer.get_vocab()
										self.assertEqual(len(_SCREAMING_SNAKE_CASE							),			self.tokenizer.vocab_size							)
										self.assertEqual(vocab['''<unk>'''],			3							)
										self.assertIn(self.tokenizer.get_lang_token('''en'''							),			_SCREAMING_SNAKE_CASE							)






				def     snake_case     (			self		:   Optional[Any]							)     ->				List[Any]:




										'''simple docstring'''



										_UpperCamelCase      : Any         =   """en"""
										_UpperCamelCase      : List[Any]         =   self.tokenizer.batch_encode_plus(self.src_text							).input_ids[0]
										self.assertListEqual(self.expected_src_tokens,			_SCREAMING_SNAKE_CASE							)






				def     snake_case     (			self		:   List[str]							)     ->				Tuple:




										'''simple docstring'''



										self.assertIn(_SCREAMING_SNAKE_CASE,			self.tokenizer.all_special_ids							)
										# fmt: off
										_UpperCamelCase      : List[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
										_UpperCamelCase      : List[str]         =   self.tokenizer.decode(_SCREAMING_SNAKE_CASE,			skip_special_tokens=_SCREAMING_SNAKE_CASE							)
										_UpperCamelCase      : Optional[int]         =   self.tokenizer.decode(generated_ids[1:],			skip_special_tokens=_SCREAMING_SNAKE_CASE							)
										self.assertEqual(_SCREAMING_SNAKE_CASE,			_SCREAMING_SNAKE_CASE							)
										self.assertNotIn(self.tokenizer.eos_token,			_SCREAMING_SNAKE_CASE							)






				def     snake_case     (			self		:   str							)     ->				List[Any]:




										'''simple docstring'''



										_UpperCamelCase      : str         =   tempfile.mkdtemp()
										_UpperCamelCase      : Union[str, Any]         =   self.tokenizer.lang_token_to_id
										self.tokenizer.save_pretrained(_SCREAMING_SNAKE_CASE							)
										_UpperCamelCase      : str         =   MaMaaaTokenizer.from_pretrained(_SCREAMING_SNAKE_CASE							)
										self.assertDictEqual(new_tok.lang_token_to_id,			_SCREAMING_SNAKE_CASE							)






				@require_torch
				def     snake_case     (			self		:   Union[str, Any]							)     ->				List[str]:




										'''simple docstring'''



										_UpperCamelCase      : List[Any]         =   """en"""
										_UpperCamelCase      : Dict         =   """fr"""

										_UpperCamelCase      : Optional[int]         =   self.tokenizer(self.src_text,			text_target=self.tgt_text,			padding=_SCREAMING_SNAKE_CASE,			return_tensors='''pt'''							)

										_UpperCamelCase      : Tuple         =   shift_tokens_right(
										    batch['''labels'''],			self.tokenizer.pad_token_id,			self.tokenizer.eos_token_id							)

										for k in batch:
																_UpperCamelCase      : 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		:   Optional[Any]							)     ->				Optional[Any]:




										'''simple docstring'''



										_UpperCamelCase      : Optional[Any]         =   """mr"""
										self.assertListEqual(self.tokenizer.prefix_tokens,			[self.tokenizer.get_lang_id('''mr'''							)]							)
										self.assertListEqual(self.tokenizer.suffix_tokens,			[self.tokenizer.eos_token_id]							)

										_UpperCamelCase      : 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		:   Union[str, Any]							)     ->				Dict:




										'''simple docstring'''



										_UpperCamelCase      : Optional[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							)]							)

										_UpperCamelCase      : Union[str, Any]         =   """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		:   str							)     ->				Dict:




										'''simple docstring'''



										_UpperCamelCase      : Dict         =   self.tokenizer._build_translation_inputs('''A test''',			return_tensors='''pt''',			src_lang='''en''',			tgt_lang='''ar'''							)

										self.assertEqual(
										    nested_simplify(_SCREAMING_SNAKE_CASE							),			{
										        # 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 warnings

from diffusers import StableDiffusionInpaintPipeline as StableDiffusionInpaintPipeline  # noqa F401


warnings.warn(
    """The `inpainting.py` script is outdated. Please use directly `from diffusers import"""
    """ StableDiffusionInpaintPipeline` instead."""
)



