




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						:							Optional[int]							=  get_tests_dir("""fixtures/test_sentencepiece.model""")


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

__A						:							List[Any]							=  1_2_8_0_2_2
__A						:							Union[str, Any]							=  1_2_8_0_2_8




@require_sentencepiece
class 			UpperCAmelCase_      (   A		,      unittest.TestCase       ):




							'''simple docstring'''



							a__						  =     MaMaaaTokenizer
							a__						  =     False
							a__						  =     False
							a__						  =     True





							def    _UpperCAmelCase     (					self       :	List[Any]			)			->					Dict:
										super().setUp()

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

										SCREAMING_SNAKE_CASE           =					MaMaaaTokenizer.from_pretrained(self.tmpdirname			)
										tokenizer.save_pretrained(self.tmpdirname			)





							def    _UpperCAmelCase     (					self       :	List[str]       ,     **a       :	Optional[int]			)			->					List[Any]:
										return MaMaaaTokenizer.from_pretrained(self.tmpdirname       ,     **a			)





							def    _UpperCAmelCase     (					self       :	Tuple       ,     a       :	Dict			)			->					Optional[Any]:
										return (
										    "This is a test",
										    "This is a test",
										)





							def    _UpperCAmelCase     (					self       :	List[str]			)			->					int:
										SCREAMING_SNAKE_CASE           =					"""</s>"""
										SCREAMING_SNAKE_CASE           =					0

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





							def    _UpperCAmelCase     (					self       :	List[Any]			)			->					int:
										SCREAMING_SNAKE_CASE           =					self.get_tokenizer()
										SCREAMING_SNAKE_CASE           =					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(a			)       ,     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]			)			->					int:
										pass





							def    _UpperCAmelCase     (					self       :	str			)			->					int:
										SCREAMING_SNAKE_CASE           =					self.get_tokenizer()

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

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

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

										SCREAMING_SNAKE_CASE           =					tokenizer.convert_tokens_to_string(a			)
										self.assertEqual(a       ,     """This is a test"""			)







							@slow
							def    _UpperCAmelCase     (					self       :	Optional[int]			)			->					Union[str, Any]:
										# fmt: off
										SCREAMING_SNAKE_CASE           =					{"""input_ids""": [[128_022, 110_108, 397, 11, 38_272, 2_247, 124_811, 285, 18_105, 1_586, 207, 7, 39_534, 4_428, 397, 1_019, 18_105, 1_586, 207, 7, 41_337, 16_786, 241, 7, 20_214, 17, 125_690, 10_398, 7, 44_378, 58_069, 68_342, 7_798, 7_343, 11, 299, 33_310, 4, 158, 37_350, 94_077, 4_569, 299, 33_310, 90, 4, 52_840, 290, 4, 31_270, 112, 299, 682, 4, 52_840, 39_953, 14_079, 193, 52_519, 90_894, 17_894, 120_697, 11, 40_445, 551, 17, 1_019, 52_519, 90_894, 17_756, 963, 11, 40_445, 480, 17, 9_792, 1_120, 5_173, 1_393, 6_240, 16_786, 241, 120_996, 28, 1_245, 1_393, 118_240, 11_123, 1_019, 93_612, 2_691, 10_618, 98_058, 120_409, 1_928, 279, 4, 40_683, 367, 178, 207, 1_019, 103, 103_121, 506, 65_296, 5, 2], [128_022, 21_217, 367, 117, 125_450, 128, 719, 7, 7_308, 40, 93_612, 12_669, 1_116, 16_704, 71, 17_785, 3_699, 15_592, 35, 144, 9_584, 241, 11_943, 713, 950, 799, 2_247, 88_427, 150, 149, 118_813, 120_706, 1_019, 106_906, 81_518, 28, 1_224, 22_799, 397, 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], [128_022, 1_658, 123_311, 5_155, 5_578, 4_722, 279, 14_947, 2_366, 1_120, 1_197, 14, 1_348, 9_232, 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=a       ,     model_name="""facebook/m2m100_418M"""       ,     revision="""c168bae485c864188cf9aa0e4108b0b6934dc91e"""       ,     )





@require_torch
@require_sentencepiece
@require_tokenizers
class 			UpperCAmelCase_      (   unittest.TestCase       ):




							'''simple docstring'''



							a__						  =     '''facebook/m2m100_418M'''
							a__						  =     [
							    '''In my opinion, there are two levels of response from the French government.''',
							    '''NSA Affair Emphasizes Complete Lack of Debate on Intelligence''',
							]
							a__						  =     [
							    '''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
							a__						  =     [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    _UpperCAmelCase     (					cls       :	List[Any]			)			->					str:
										SCREAMING_SNAKE_CASE           =					MaMaaaTokenizer.from_pretrained(
										    cls.checkpoint_name       ,     src_lang="""en"""       ,     tgt_lang="""fr"""			)
										SCREAMING_SNAKE_CASE           =					1
										return cls





							def    _UpperCAmelCase     (					self       :	Union[str, Any]			)			->					Optional[Any]:
										self.assertEqual(self.tokenizer.get_lang_id("""ar"""			)       ,     128_006			)
										self.assertEqual(self.tokenizer.get_lang_id("""en"""			)       ,     128_022			)
										self.assertEqual(self.tokenizer.get_lang_id("""ro"""			)       ,     128_076			)
										self.assertEqual(self.tokenizer.get_lang_id("""mr"""			)       ,     128_063			)





							def    _UpperCAmelCase     (					self       :	str			)			->					List[str]:
										SCREAMING_SNAKE_CASE           =					self.tokenizer.get_vocab()
										self.assertEqual(len(a			)       ,     self.tokenizer.vocab_size			)
										self.assertEqual(vocab["""<unk>"""]       ,     3			)
										self.assertIn(self.tokenizer.get_lang_token("""en"""			)       ,     a			)





							def    _UpperCAmelCase     (					self       :	Tuple			)			->					Dict:
										SCREAMING_SNAKE_CASE           =					"""en"""
										SCREAMING_SNAKE_CASE           =					self.tokenizer.batch_encode_plus(self.src_text			).input_ids[0]
										self.assertListEqual(self.expected_src_tokens       ,     a			)





							def    _UpperCAmelCase     (					self       :	Union[str, Any]			)			->					List[str]:
										self.assertIn(a       ,     self.tokenizer.all_special_ids			)
										# fmt: off
										SCREAMING_SNAKE_CASE           =					[FR_CODE, 5_364, 82, 8_642, 4, 294, 47, 8, 14_028, 136, 3_286, 9_706, 6, 90_797, 6, 144_012, 162, 88_128, 30_061, 5, 2]
										# fmt: on
										SCREAMING_SNAKE_CASE           =					self.tokenizer.decode(a       ,     skip_special_tokens=a			)
										SCREAMING_SNAKE_CASE           =					self.tokenizer.decode(generated_ids[1:]       ,     skip_special_tokens=a			)
										self.assertEqual(a       ,     a			)
										self.assertNotIn(self.tokenizer.eos_token       ,     a			)





							def    _UpperCAmelCase     (					self       :	Dict			)			->					Optional[int]:
										SCREAMING_SNAKE_CASE           =					tempfile.mkdtemp()
										SCREAMING_SNAKE_CASE           =					self.tokenizer.lang_token_to_id
										self.tokenizer.save_pretrained(a			)
										SCREAMING_SNAKE_CASE           =					MaMaaaTokenizer.from_pretrained(a			)
										self.assertDictEqual(new_tok.lang_token_to_id       ,     a			)





							@require_torch
							def    _UpperCAmelCase     (					self       :	Tuple			)			->					List[str]:
										SCREAMING_SNAKE_CASE           =					"""en"""
										SCREAMING_SNAKE_CASE           =					"""fr"""

										SCREAMING_SNAKE_CASE           =					self.tokenizer(self.src_text       ,     text_target=self.tgt_text       ,     padding=a       ,     return_tensors="""pt"""			)

										SCREAMING_SNAKE_CASE           =					shift_tokens_right(
										    batch["""labels"""]       ,     self.tokenizer.pad_token_id       ,     self.tokenizer.eos_token_id			)

										for k in batch:
													SCREAMING_SNAKE_CASE           =					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       :	Dict			)			->					Union[str, Any]:
										SCREAMING_SNAKE_CASE           =					"""mr"""
										self.assertListEqual(self.tokenizer.prefix_tokens       ,     [self.tokenizer.get_lang_id("""mr"""			)]			)
										self.assertListEqual(self.tokenizer.suffix_tokens       ,     [self.tokenizer.eos_token_id]			)

										SCREAMING_SNAKE_CASE           =					"""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       :	Any			)			->					Any:
										SCREAMING_SNAKE_CASE           =					"""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			)]			)

										SCREAMING_SNAKE_CASE           =					"""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       :	Union[str, Any]			)			->					Dict:
										SCREAMING_SNAKE_CASE           =					self.tokenizer._build_translation_inputs("""A test"""       ,     return_tensors="""pt"""       ,     src_lang="""en"""       ,     tgt_lang="""ar"""			)

										self.assertEqual(
										    nested_simplify(a			)       ,     {
										        # en_XX, A, test, EOS
										        """input_ids""": [[128_022, 58, 4_183, 2]],
										        """attention_mask""": [[1, 1, 1, 1]],
										        # ar_AR
										        """forced_bos_token_id""": 128_006,
										    }       ,     )












from __future__ import annotations
def 					lowerCamelCase_    (    SCREAMING_SNAKE_CASE   ):
			'''simple docstring'''
			create_state_space_tree(SCREAMING_SNAKE_CASE					,	[]					,	0					,	[0 for i in range(len(SCREAMING_SNAKE_CASE   )   )]   )
def 					lowerCamelCase_    (    SCREAMING_SNAKE_CASE					,	SCREAMING_SNAKE_CASE					,	SCREAMING_SNAKE_CASE					,	SCREAMING_SNAKE_CASE					,	):
			'''simple docstring'''

			if index == len(SCREAMING_SNAKE_CASE   ):
						print(SCREAMING_SNAKE_CASE   )
						return

			for i in range(len(SCREAMING_SNAKE_CASE   )   ):
						if not index_used[i]:
									current_sequence.append(sequence[i]   )
									SCREAMING_SNAKE_CASE           =					True
									create_state_space_tree(SCREAMING_SNAKE_CASE					,	SCREAMING_SNAKE_CASE					,	index + 1					,	SCREAMING_SNAKE_CASE   )
									current_sequence.pop()
									SCREAMING_SNAKE_CASE           =					False
__A						:							list[int | str]							=  [3, 1, 2, 4]
generate_all_permutations(sequence)

__A						:							list[int | str]							=  ["A", "B", "C"]




generate_all_permutations(sequence_a)






