



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


UpperCAmelCase_							:      Any      =  get_tests_dir("fixtures/test_sentencepiece.model")

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

UpperCAmelCase_							:      List[str]      =  250_004
UpperCAmelCase_							:      Optional[Any]      =  250_020






@require_sentencepiece
@require_tokenizers
class      UpperCamelCase    (						_UpperCAmelCase       ,    unittest.TestCase     ):
	lowerCAmelCase	:   int				=	MBartaaTokenizer
	lowerCAmelCase	:   List[Any]				=	MBartaaTokenizerFast
	lowerCAmelCase	:   Any				=	True
	lowerCAmelCase	:   List[Any]				=	True



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

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



	def 			__A							(       self		):
							A__							=       "<s>"
							A__							=       0

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



	def 			__A							(       self		):
							A__							=       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(UpperCAmelCase__		)			,	1_054		)



	def 			__A							(       self		):
							self.assertEqual(self.get_tokenizer().vocab_size			,	1_054		)



	def 			__A							(       self		):
							A__							=       MBartaaTokenizer(UpperCAmelCase__			,	src_lang="en_XX"			,	tgt_lang="ro_RO"			,	keep_accents=UpperCAmelCase__		)

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

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

							A__							=       tokenizer.tokenize("I was born in 92000, and this is falsé."		)
							self.assertListEqual(
							    UpperCAmelCase__			,	[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", "."]			,	)
							A__							=       tokenizer.convert_tokens_to_ids(UpperCAmelCase__		)
							self.assertListEqual(
							    UpperCAmelCase__			,	[
							        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]
							    ]			,	)

							A__							=       tokenizer.convert_ids_to_tokens(UpperCAmelCase__		)
							self.assertListEqual(
							    UpperCAmelCase__			,	[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 			__A							(       self		):
							# fmt: off
							A__							=       {"input_ids": [[250_004, 11_062, 82_772, 7, 15, 82_772, 538, 51_529, 237, 17_198, 1_290, 206, 9, 215_175, 1_314, 136, 17_198, 1_290, 206, 9, 56_359, 42, 122_009, 9, 16_466, 16, 87_344, 4_537, 9, 4_717, 78_381, 6, 159_958, 7, 15, 24_480, 618, 4, 527, 22_693, 5_428, 4, 2_777, 24_480, 9_874, 4, 43_523, 594, 4, 803, 18_392, 33_189, 18, 4, 43_523, 24_447, 12_399, 100, 24_955, 83_658, 9_626, 144_057, 15, 839, 22_335, 16, 136, 24_955, 83_658, 83_479, 15, 39_102, 724, 16, 678, 645, 2_789, 1_328, 4_589, 42, 122_009, 115_774, 23, 805, 1_328, 46_876, 7, 136, 53_894, 1_940, 42_227, 41_159, 17_721, 823, 425, 4, 27_512, 98_722, 206, 136, 5_531, 4_970, 919, 17_336, 5, 2], [250_004, 20_080, 618, 83, 82_775, 47, 479, 9, 1_517, 73, 53_894, 333, 80_581, 110_117, 18_811, 5_256, 1_295, 51, 152_526, 297, 7_986, 390, 124_416, 538, 35_431, 214, 98, 15_044, 25_737, 136, 7_108, 43_701, 23, 756, 135_355, 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], [250_004, 581, 63_773, 119_455, 6, 147_797, 88_203, 7, 645, 70, 21, 3_285, 10_269, 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=UpperCAmelCase__			,	model_name="facebook/mbart-large-50"			,	revision="d3913889c59cd5c9e456b269c376325eabad57e2"			,	)



	def 			__A							(       self		):
							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

							A__							=       (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})"""		):
																			A__							=       self.rust_tokenizer_class.from_pretrained(UpperCAmelCase__			,	**UpperCAmelCase__		)
																			A__							=       self.tokenizer_class.from_pretrained(UpperCAmelCase__			,	**UpperCAmelCase__		)

																			A__							=       tempfile.mkdtemp()

																			A__							=       tokenizer_r.save_pretrained(UpperCAmelCase__		)
																			A__							=       tokenizer_p.save_pretrained(UpperCAmelCase__		)

																			# 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		)		)
																			A__							=       tuple(f for f in tokenizer_r_files if "tokenizer.json" not in f		)
																			self.assertSequenceEqual(UpperCAmelCase__			,	UpperCAmelCase__		)

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

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

																			shutil.rmtree(UpperCAmelCase__		)

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

																			A__							=       tokenizer_r.save_pretrained(UpperCAmelCase__			,	legacy_format=UpperCAmelCase__		)
																			A__							=       tokenizer_p.save_pretrained(UpperCAmelCase__		)

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

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

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

																			shutil.rmtree(UpperCAmelCase__		)

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

																			A__							=       tokenizer_r.save_pretrained(UpperCAmelCase__			,	legacy_format=UpperCAmelCase__		)
																			A__							=       tokenizer_p.save_pretrained(UpperCAmelCase__		)

																			# 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
																			A__							=       tokenizer_r.from_pretrained(UpperCAmelCase__		)
																			A__							=       tokenizer_p.from_pretrained(UpperCAmelCase__		)

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

																			shutil.rmtree(UpperCAmelCase__		)






@require_torch
@require_sentencepiece
@require_tokenizers
class      UpperCamelCase    (						unittest.TestCase     ):
	lowerCAmelCase	:   Tuple				=	"""facebook/mbart-large-50-one-to-many-mmt"""
	lowerCAmelCase	:   Union[str, Any]				=	[
	    """ 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.""",
	]
	lowerCAmelCase	:   str				=	[
	    """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.""",
	]
	lowerCAmelCase	:   List[str]				=	[EN_CODE, 8_274, 127_873, 25_916, 7, 8_622, 2_071, 438, 67_485, 53, 187_895, 23, 51_712, 2]



	@classmethod
	def 			__A							(       cls		):
							A__							=       MBartaaTokenizer.from_pretrained(
							    cls.checkpoint_name			,	src_lang="en_XX"			,	tgt_lang="ro_RO"		)
							A__							=       1
							return cls



	def 			__A							(       self		):
							self.assertEqual(self.tokenizer.fairseq_tokens_to_ids["ar_AR"]			,	250_001		)
							self.assertEqual(self.tokenizer.fairseq_tokens_to_ids["en_EN"]			,	250_004		)
							self.assertEqual(self.tokenizer.fairseq_tokens_to_ids["ro_RO"]			,	250_020		)
							self.assertEqual(self.tokenizer.fairseq_tokens_to_ids["mr_IN"]			,	250_038		)



	def 			__A							(       self		):
							A__							=       self.tokenizer.batch_encode_plus(self.src_text		).input_ids[0]
							self.assertListEqual(self.expected_src_tokens			,	UpperCAmelCase__		)



	def 			__A							(       self		):
							self.assertIn(UpperCAmelCase__			,	self.tokenizer.all_special_ids		)
							A__							=       [RO_CODE, 884, 9_019, 96, 9, 916, 86_792, 36, 18_743, 15_596, 5, 2]
							A__							=       self.tokenizer.decode(UpperCAmelCase__			,	skip_special_tokens=UpperCAmelCase__		)
							A__							=       self.tokenizer.decode(generated_ids[1:]			,	skip_special_tokens=UpperCAmelCase__		)
							self.assertEqual(UpperCAmelCase__			,	UpperCAmelCase__		)
							self.assertNotIn(self.tokenizer.eos_token			,	UpperCAmelCase__		)



	def 			__A							(       self		):
							A__							=       ["this is gunna be a long sentence " * 20]
							assert isinstance(src_text[0]			,	UpperCAmelCase__		)
							A__							=       10
							A__							=       self.tokenizer(UpperCAmelCase__			,	max_length=UpperCAmelCase__			,	truncation=UpperCAmelCase__		).input_ids[0]
							self.assertEqual(ids[0]			,	UpperCAmelCase__		)
							self.assertEqual(ids[-1]			,	2		)
							self.assertEqual(len(UpperCAmelCase__		)			,	UpperCAmelCase__		)



	def 			__A							(       self		):
							self.assertListEqual(self.tokenizer.convert_tokens_to_ids(["<mask>", "ar_AR"]		)			,	[250_053, 250_001]		)



	def 			__A							(       self		):
							A__							=       tempfile.mkdtemp()
							A__							=       self.tokenizer.fairseq_tokens_to_ids
							self.tokenizer.save_pretrained(UpperCAmelCase__		)
							A__							=       MBartaaTokenizer.from_pretrained(UpperCAmelCase__		)
							self.assertDictEqual(new_tok.fairseq_tokens_to_ids			,	UpperCAmelCase__		)



	@require_torch
	def 			__A							(       self		):
							A__							=       self.tokenizer(self.src_text			,	text_target=self.tgt_text			,	padding=UpperCAmelCase__			,	return_tensors="pt"		)
							A__							=       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 			__A							(       self		):
							A__							=       self.tokenizer(
							    self.src_text			,	text_target=self.tgt_text			,	padding=UpperCAmelCase__			,	truncation=UpperCAmelCase__			,	max_length=len(self.expected_src_tokens		)			,	return_tensors="pt"			,	)
							A__							=       shift_tokens_right(batch["labels"]			,	self.tokenizer.pad_token_id		)

							self.assertIsInstance(UpperCAmelCase__			,	UpperCAmelCase__		)

							self.assertEqual((2, 14)			,	batch.input_ids.shape		)
							self.assertEqual((2, 14)			,	batch.attention_mask.shape		)
							A__							=       batch.input_ids.tolist()[0]
							self.assertListEqual(self.expected_src_tokens			,	UpperCAmelCase__		)
							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 			__A							(       self		):
							A__							=       self.tokenizer(self.src_text			,	padding=UpperCAmelCase__			,	truncation=UpperCAmelCase__			,	max_length=3			,	return_tensors="pt"		)
							A__							=       self.tokenizer(
							    text_target=self.tgt_text			,	padding=UpperCAmelCase__			,	truncation=UpperCAmelCase__			,	max_length=10			,	return_tensors="pt"		)
							A__							=       targets["input_ids"]
							A__							=       shift_tokens_right(UpperCAmelCase__			,	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 			__A							(       self		):
							A__							=       self.tokenizer._build_translation_inputs(
							    "A test"			,	return_tensors="pt"			,	src_lang="en_XX"			,	tgt_lang="ar_AR"		)

							self.assertEqual(
							    nested_simplify(UpperCAmelCase__		)			,	{
							        # en_XX, A, test, EOS
							        "input_ids": [[250_004, 62, 3_034, 2]],
							        "attention_mask": [[1, 1, 1, 1]],
							        # ar_AR
							        "forced_bos_token_id": 250_001,
							    }			,	)










import os
import time

import pytest

from datasets.utils.filelock import FileLock, Timeout
def  UpperCamelCase						(       _A			:				Optional[int]    )->       List[Any]:





						"""simple docstring"""





						A__							=       FileLock(str(tmpdir / "foo.lock"    )    )
						A__							=       FileLock(str(tmpdir / "foo.lock"    )    )
						A__							=       0.01
						with locka.acquire():
												with pytest.raises(_A    ):
																		A__							=       time.time()
																		locka.acquire(_A    )
																		assert time.time() - _start > timeout
def  UpperCamelCase						(       _A			:				str    )->       List[Any]:





						"""simple docstring"""





						A__							=       "a" * 1000 + ".lock"
						A__							=       FileLock(str(tmpdir / filename    )    )
						assert locka._lock_file.endswith(".lock"    )
						assert not locka._lock_file.endswith(_A    )
						assert len(os.path.basename(locka._lock_file    )    ) <= 255
						A__							=       FileLock(tmpdir / filename    )
						with locka.acquire():
												with pytest.raises(_A    ):
																		locka.acquire(0    )





