'''simple docstring'''





import shutil
import tempfile
import unittest

from transformers import SPIECE_UNDERLINE, BatchEncoding, MBartTokenizer, MBartTokenizerFast, is_torch_available
from transformers.testing_utils import (
    get_tests_dir,
    nested_simplify,
    require_sentencepiece,
    require_tokenizers,
    require_torch,
)

from ...test_tokenization_common import TokenizerTesterMixin


lowerCAmelCase_	:		str			=     get_tests_dir("""fixtures/test_sentencepiece.model""")


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

lowerCAmelCase_	:		Optional[int]			=     25_0004
lowerCAmelCase_	:		List[Any]			=     25_0020




@require_sentencepiece
@require_tokenizers
class 		SCREAMING_SNAKE_CASE     (					SCREAMING_SNAKE_CASE   , unittest.TestCase	):







				'''simple docstring'''
				UpperCAmelCase__							=							MBartTokenizer
				UpperCAmelCase__							=							MBartTokenizerFast
				UpperCAmelCase__							=							True
				UpperCAmelCase__							=							True





				def  snake_case__				(						self					:						List[str]					)							->Dict:


										'''simple docstring'''




										super().setUp()

										# We have a SentencePiece fixture for testing
										_UpperCamelCase			:			Optional[Any]   			=						MBartTokenizer(lowercase__       ,		keep_accents=lowercase__					)
										tokenizer.save_pretrained(self.tmpdirname					)





				def  snake_case__				(						self					:						List[str]					)							->Union[str, Any]:


										'''simple docstring'''




										_UpperCamelCase			:			Tuple   			=						MBartTokenizer(lowercase__       ,		keep_accents=lowercase__					)

										_UpperCamelCase			:			Tuple   			=						tokenizer.tokenize("This is a test"					)
										self.assertListEqual(lowercase__       ,		["▁This", "▁is", "▁a", "▁t", "est"]					)

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

										_UpperCamelCase			:			Dict   			=						tokenizer.tokenize("I was born in 92000, and this is falsé."					)
										self.assertListEqual(
										    lowercase__       ,		[
										        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",
										        ".",
										    ]       ,		)
										_UpperCamelCase			:			Optional[Any]   			=						tokenizer.convert_tokens_to_ids(lowercase__					)
										self.assertListEqual(
										    lowercase__       ,		[
										        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]
										        #                                       ^ unk: 2 + 1 = 3                  unk: 2 + 1 = 3 ^
										    ]       ,		)

										_UpperCamelCase			:			Tuple   			=						tokenizer.convert_ids_to_tokens(lowercase__					)
										self.assertListEqual(
										    lowercase__       ,		[
										        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>",
										        ".",
										    ]       ,		)







				def  snake_case__				(						self					:						Dict					)							->Tuple:


										'''simple docstring'''




										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

										_UpperCamelCase			:			Dict   			=						(self.rust_tokenizer_class, "hf-internal-testing/tiny-random-mbart", {})
										for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
																with self.subTest(f'''{tokenizer.__class__.__name__} ({pretrained_name})'''					):
																						_UpperCamelCase			:			Optional[int]   			=						self.rust_tokenizer_class.from_pretrained(lowercase__       ,		**lowercase__					)
																						_UpperCamelCase			:			Optional[Any]   			=						self.tokenizer_class.from_pretrained(lowercase__       ,		**lowercase__					)

																						_UpperCamelCase			:			Any   			=						tempfile.mkdtemp()

																						_UpperCamelCase			:			Optional[Any]   			=						tokenizer_r.save_pretrained(lowercase__					)
																						_UpperCamelCase			:			int   			=						tokenizer_p.save_pretrained(lowercase__					)

																						# 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					)					)
																						_UpperCamelCase			:			Any   			=						tuple(f for f in tokenizer_r_files if "tokenizer.json" not in f					)
																						self.assertSequenceEqual(lowercase__       ,		lowercase__					)

																						# Checks everything loads correctly in the same way
																						_UpperCamelCase			:			str   			=						tokenizer_r.from_pretrained(lowercase__					)
																						_UpperCamelCase			:			Optional[Any]   			=						tokenizer_p.from_pretrained(lowercase__					)

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

																						shutil.rmtree(lowercase__					)

																						# Save tokenizer rust, legacy_format=True
																						_UpperCamelCase			:			Any   			=						tempfile.mkdtemp()

																						_UpperCamelCase			:			Tuple   			=						tokenizer_r.save_pretrained(lowercase__       ,		legacy_format=lowercase__					)
																						_UpperCamelCase			:			List[str]   			=						tokenizer_p.save_pretrained(lowercase__					)

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

																						# Checks everything loads correctly in the same way
																						_UpperCamelCase			:			Tuple   			=						tokenizer_r.from_pretrained(lowercase__					)
																						_UpperCamelCase			:			Union[str, Any]   			=						tokenizer_p.from_pretrained(lowercase__					)

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

																						shutil.rmtree(lowercase__					)

																						# Save tokenizer rust, legacy_format=False
																						_UpperCamelCase			:			Tuple   			=						tempfile.mkdtemp()

																						_UpperCamelCase			:			Optional[int]   			=						tokenizer_r.save_pretrained(lowercase__       ,		legacy_format=lowercase__					)
																						_UpperCamelCase			:			Tuple   			=						tokenizer_p.save_pretrained(lowercase__					)

																						# 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
																						_UpperCamelCase			:			int   			=						tokenizer_r.from_pretrained(lowercase__					)
																						_UpperCamelCase			:			Optional[int]   			=						tokenizer_p.from_pretrained(lowercase__					)

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

																						shutil.rmtree(lowercase__					)





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







				'''simple docstring'''
				UpperCAmelCase__							=							'''facebook/mbart-large-en-ro'''
				UpperCAmelCase__							=							[
				    ''' 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.''',
				]
				UpperCAmelCase__							=							[
				    '''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.''',
				]
				UpperCAmelCase__							=							[82_74, 12_78_73, 2_59_16, 7, 86_22, 20_71, 4_38, 6_74_85, 53, 18_78_95, 23, 5_17_12, 2, EN_CODE]





				@classmethod
				def  snake_case__				(						cls					:						str					)							->List[Any]:


										'''simple docstring'''




										_UpperCamelCase			:			MBartTokenizer   			=						MBartTokenizer.from_pretrained(
										    cls.checkpoint_name       ,		src_lang="en_XX"       ,		tgt_lang="ro_RO"					)
										_UpperCamelCase			:			List[str]   			=						1
										return cls





				def  snake_case__				(						self					:						str					)							->str:


										'''simple docstring'''




										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					)





				def  snake_case__				(						self					:						Optional[int]					)							->List[str]:


										'''simple docstring'''




										_UpperCamelCase			:			Dict   			=						self.tokenizer.batch_encode_plus(self.src_text					).input_ids[0]
										self.assertListEqual(self.expected_src_tokens       ,		lowercase__					)





				def  snake_case__				(						self					:						int					)							->Dict:


										'''simple docstring'''




										self.assertIn(lowercase__       ,		self.tokenizer.all_special_ids					)
										_UpperCamelCase			:			Union[str, Any]   			=						[RO_CODE, 884, 9_019, 96, 9, 916, 86_792, 36, 18_743, 15_596, 5, 2]
										_UpperCamelCase			:			Optional[Any]   			=						self.tokenizer.decode(lowercase__       ,		skip_special_tokens=lowercase__					)
										_UpperCamelCase			:			List[Any]   			=						self.tokenizer.decode(generated_ids[1:]       ,		skip_special_tokens=lowercase__					)
										self.assertEqual(lowercase__       ,		lowercase__					)
										self.assertNotIn(self.tokenizer.eos_token       ,		lowercase__					)





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


										'''simple docstring'''




										_UpperCamelCase			:			Dict   			=						["this is gunna be a long sentence " * 20]
										assert isinstance(src_text[0]       ,		lowercase__					)
										_UpperCamelCase			:			int   			=						10
										_UpperCamelCase			:			str   			=						self.tokenizer(lowercase__       ,		max_length=lowercase__       ,		truncation=lowercase__					).input_ids[0]
										self.assertEqual(ids[-2]       ,		2					)
										self.assertEqual(ids[-1]       ,		lowercase__					)
										self.assertEqual(len(lowercase__					)       ,		lowercase__					)





				def  snake_case__				(						self					:						Any					)							->int:


										'''simple docstring'''




										self.assertListEqual(self.tokenizer.convert_tokens_to_ids(["<mask>", "ar_AR"]					)       ,		[250_026, 250_001]					)





				def  snake_case__				(						self					:						Dict					)							->Dict:


										'''simple docstring'''




										_UpperCamelCase			:			Tuple   			=						tempfile.mkdtemp()
										_UpperCamelCase			:			List[Any]   			=						self.tokenizer.fairseq_tokens_to_ids
										self.tokenizer.save_pretrained(lowercase__					)
										_UpperCamelCase			:			Tuple   			=						MBartTokenizer.from_pretrained(lowercase__					)
										self.assertDictEqual(new_tok.fairseq_tokens_to_ids       ,		lowercase__					)





				@require_torch
				def  snake_case__				(						self					:						Optional[Any]					)							->List[Any]:


										'''simple docstring'''




										_UpperCamelCase			:			Optional[Any]   			=						self.tokenizer(self.src_text       ,		text_target=self.tgt_text       ,		padding=lowercase__       ,		return_tensors="pt"					)
										_UpperCamelCase			:			Dict   			=						shift_tokens_right(batch["labels"]       ,		self.tokenizer.pad_token_id					)

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





				@require_torch
				def  snake_case__				(						self					:						List[str]					)							->List[Any]:


										'''simple docstring'''




										_UpperCamelCase			:			Tuple   			=						self.tokenizer(
										    self.src_text       ,		text_target=self.tgt_text       ,		padding=lowercase__       ,		truncation=lowercase__       ,		max_length=len(self.expected_src_tokens					)       ,		return_tensors="pt"       ,		)

										_UpperCamelCase			:			int   			=						shift_tokens_right(batch["labels"]       ,		self.tokenizer.pad_token_id					)

										self.assertIsInstance(lowercase__       ,		lowercase__					)

										self.assertEqual((2, 14)       ,		batch.input_ids.shape					)
										self.assertEqual((2, 14)       ,		batch.attention_mask.shape					)
										_UpperCamelCase			:			Optional[int]   			=						batch.input_ids.tolist()[0]
										self.assertListEqual(self.expected_src_tokens       ,		lowercase__					)
										self.assertEqual(2       ,		batch.decoder_input_ids[0, -1]					)  # EOS
										# Test that special tokens are reset
										self.assertEqual(self.tokenizer.prefix_tokens       ,		[]					)
										self.assertEqual(self.tokenizer.suffix_tokens       ,		[self.tokenizer.eos_token_id, EN_CODE]					)





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


										'''simple docstring'''




										_UpperCamelCase			:			Union[str, Any]   			=						self.tokenizer(self.src_text       ,		padding=lowercase__       ,		truncation=lowercase__       ,		max_length=3       ,		return_tensors="pt"					)
										_UpperCamelCase			:			int   			=						self.tokenizer(
										    text_target=self.tgt_text       ,		padding=lowercase__       ,		truncation=lowercase__       ,		max_length=10       ,		return_tensors="pt"					)
										_UpperCamelCase			:			List[Any]   			=						targets["input_ids"]
										_UpperCamelCase			:			Optional[int]   			=						shift_tokens_right(lowercase__       ,		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  snake_case__				(						self					:						Optional[Any]					)							->Dict:


										'''simple docstring'''




										_UpperCamelCase			:			List[Any]   			=						self.tokenizer._build_translation_inputs(
										    "A test"       ,		return_tensors="pt"       ,		src_lang="en_XX"       ,		tgt_lang="ar_AR"					)

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



'''simple docstring'''





import re
from pathlib import Path
from unittest import TestCase

import pytest




@pytest.mark.integration
class 		SCREAMING_SNAKE_CASE     (					SCREAMING_SNAKE_CASE	):







				'''simple docstring'''





				def  snake_case__				(						self					:						Dict       ,		lowercase__					:						str					)							->Tuple:


										'''simple docstring'''




										with open(lowercase__       ,		encoding="utf-8"					) as input_file:
																_UpperCamelCase			:			Optional[int]   			=						re.compile(r"(?!.*\b(?:encoding|rb|w|wb|w+|wb+|ab|ab+)\b)(?<=\s)(open)\((.*)\)"					)
																_UpperCamelCase			:			Dict   			=						input_file.read()
																_UpperCamelCase			:			Dict   			=						regexp.search(lowercase__					)

										return match





				def  snake_case__				(						self					:						str       ,		lowercase__					:						str					)							->Tuple:


										'''simple docstring'''




										with open(lowercase__       ,		encoding="utf-8"					) as input_file:
																_UpperCamelCase			:			str   			=						re.compile(r"#[^\r\n]*print\(|\"[^\r\n]*print\(|\"\"\".*?print\(.*?\"\"\"|(print\()"       ,		re.DOTALL					)
																_UpperCamelCase			:			Optional[Any]   			=						input_file.read()
																# use `re.finditer` to handle the case where the ignored groups would be matched first by `re.search`
																_UpperCamelCase			:			List[str]   			=						regexp.finditer(lowercase__					)

										_UpperCamelCase			:			Any   			=						[match for match in matches if match is not None and match.group(1					) is not None]
										return matches[0] if matches else None





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


										'''simple docstring'''




										_UpperCamelCase			:			Any   			=						Path("./datasets"					)
										_UpperCamelCase			:			List[Any]   			=						list(dataset_paths.absolute().glob("**/*.py"					)					)

										for dataset in dataset_files:
																if self._no_encoding_on_file_open(str(lowercase__					)					):
																						raise AssertionError(f'''open(...) must use utf-8 encoding in {dataset}'''					)







				def  snake_case__				(						self					:						Optional[Any]					)							->Union[str, Any]:


										'''simple docstring'''




										_UpperCamelCase			:			Any   			=						Path("./datasets"					)
										_UpperCamelCase			:			Any   			=						list(dataset_paths.absolute().glob("**/*.py"					)					)

										for dataset in dataset_files:
																if self._no_print_statements(str(lowercase__					)					):
																						raise AssertionError(f'''print statement found in {dataset}. Use datasets.logger/logging instead.'''					)


