


"""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


__snake_case         =					get_tests_dir("""fixtures/test_sentencepiece.model""")


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

__snake_case         =					250004
__snake_case         =					250020







@require_sentencepiece
@require_tokenizers
class _lowerCAmelCase       (   __lowercase					,							unittest.TestCase			):
			__UpperCAmelCase				: int													=						MBartTokenizer
			__UpperCAmelCase				: Optional[int]													=						MBartTokenizerFast
			__UpperCAmelCase				: Optional[int]													=						True
			__UpperCAmelCase				: str													=						True







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

							'''simple docstring'''




							super().setUp()

							# We have a SentencePiece fixture for testing
							snake_case					:   Optional[int]         =					MBartTokenizer(__a		,			keep_accents=__a		)
							tokenizer.save_pretrained(self.tmpdirname		)







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

							'''simple docstring'''




							snake_case					:   List[str]         =					MBartTokenizer(__a		,			keep_accents=__a		)

							snake_case					:   List[str]         =					tokenizer.tokenize("This is a test"		)
							self.assertListEqual(__a		,			["▁This", "▁is", "▁a", "▁t", "est"]		)

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

							snake_case					:   str         =					tokenizer.tokenize("I was born in 92000, and this is falsé."		)
							self.assertListEqual(
							    __a		,			[
							        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",
							        ".",
							    ]		,			)
							snake_case					:   int         =					tokenizer.convert_tokens_to_ids(__a		)
							self.assertListEqual(
							    __a		,			[
							        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 ^
							    ]		,			)

							snake_case					:   int         =					tokenizer.convert_ids_to_tokens(__a		)
							self.assertListEqual(
							    __a		,			[
							        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 				lowerCamelCase	(			self		)			->	Optional[int]:

							'''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

							snake_case					:   str         =					(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})'		):
															snake_case					:   List[Any]         =					self.rust_tokenizer_class.from_pretrained(__a		,			**__a		)
															snake_case					:   str         =					self.tokenizer_class.from_pretrained(__a		,			**__a		)

															snake_case					:   Optional[int]         =					tempfile.mkdtemp()

															snake_case					:   Tuple         =					tokenizer_r.save_pretrained(__a		)
															snake_case					:   Optional[Any]         =					tokenizer_p.save_pretrained(__a		)

															# 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		)		)
															snake_case					:   Optional[int]         =					tuple(f for f in tokenizer_r_files if "tokenizer.json" not in f		)
															self.assertSequenceEqual(__a		,			__a		)

															# Checks everything loads correctly in the same way
															snake_case					:   Optional[int]         =					tokenizer_r.from_pretrained(__a		)
															snake_case					:   Optional[int]         =					tokenizer_p.from_pretrained(__a		)

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

															shutil.rmtree(__a		)

															# Save tokenizer rust, legacy_format=True
															snake_case					:   int         =					tempfile.mkdtemp()

															snake_case					:   Union[str, Any]         =					tokenizer_r.save_pretrained(__a		,			legacy_format=__a		)
															snake_case					:   Any         =					tokenizer_p.save_pretrained(__a		)

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

															# Checks everything loads correctly in the same way
															snake_case					:   int         =					tokenizer_r.from_pretrained(__a		)
															snake_case					:   Optional[int]         =					tokenizer_p.from_pretrained(__a		)

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

															shutil.rmtree(__a		)

															# Save tokenizer rust, legacy_format=False
															snake_case					:   Dict         =					tempfile.mkdtemp()

															snake_case					:   Any         =					tokenizer_r.save_pretrained(__a		,			legacy_format=__a		)
															snake_case					:   List[str]         =					tokenizer_p.save_pretrained(__a		)

															# 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
															snake_case					:   Tuple         =					tokenizer_r.from_pretrained(__a		)
															snake_case					:   Dict         =					tokenizer_p.from_pretrained(__a		)

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

															shutil.rmtree(__a		)







@require_torch
@require_sentencepiece
@require_tokenizers
class _lowerCAmelCase       (   unittest.TestCase			):
			__UpperCAmelCase				: Dict													=						'''facebook/mbart-large-en-ro'''
			__UpperCAmelCase				: int													=						[
			    ''' 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				: Optional[int]													=						[
			    '''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				: Optional[int]													=						[8274, 127873, 25916, 7, 8622, 2071, 438, 67485, 53, 187895, 23, 51712, 2, EN_CODE]







			@classmethod
			def 				lowerCamelCase	(			cls		)			->	Union[str, Any]:

							'''simple docstring'''




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







			def 				lowerCamelCase	(			self		)			->	List[str]:

							'''simple docstring'''




							self.assertEqual(self.tokenizer.fairseq_tokens_to_ids["ar_AR"]		,			25_0001		)
							self.assertEqual(self.tokenizer.fairseq_tokens_to_ids["en_EN"]		,			25_0004		)
							self.assertEqual(self.tokenizer.fairseq_tokens_to_ids["ro_RO"]		,			25_0020		)







			def 				lowerCamelCase	(			self		)			->	Tuple:

							'''simple docstring'''




							snake_case					:   Any         =					self.tokenizer.batch_encode_plus(self.src_text		).input_ids[0]
							self.assertListEqual(self.expected_src_tokens		,			__a		)







			def 				lowerCamelCase	(			self		)			->	Optional[Any]:

							'''simple docstring'''




							self.assertIn(__a		,			self.tokenizer.all_special_ids		)
							snake_case					:   Union[str, Any]         =					[RO_CODE, 884, 9019, 96, 9, 916, 8_6792, 36, 1_8743, 1_5596, 5, 2]
							snake_case					:   Tuple         =					self.tokenizer.decode(__a		,			skip_special_tokens=__a		)
							snake_case					:   Tuple         =					self.tokenizer.decode(generated_ids[1:]		,			skip_special_tokens=__a		)
							self.assertEqual(__a		,			__a		)
							self.assertNotIn(self.tokenizer.eos_token		,			__a		)







			def 				lowerCamelCase	(			self		)			->	Any:

							'''simple docstring'''




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







			def 				lowerCamelCase	(			self		)			->	Any:

							'''simple docstring'''




							self.assertListEqual(self.tokenizer.convert_tokens_to_ids(["<mask>", "ar_AR"]		)		,			[25_0026, 25_0001]		)







			def 				lowerCamelCase	(			self		)			->	List[str]:

							'''simple docstring'''




							snake_case					:   str         =					tempfile.mkdtemp()
							snake_case					:   Tuple         =					self.tokenizer.fairseq_tokens_to_ids
							self.tokenizer.save_pretrained(__a		)
							snake_case					:   Optional[int]         =					MBartTokenizer.from_pretrained(__a		)
							self.assertDictEqual(new_tok.fairseq_tokens_to_ids		,			__a		)







			@require_torch
			def 				lowerCamelCase	(			self		)			->	int:

							'''simple docstring'''




							snake_case					:   int         =					self.tokenizer(self.src_text		,			text_target=self.tgt_text		,			padding=__a		,			return_tensors="pt"		)
							snake_case					:   Any         =					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 				lowerCamelCase	(			self		)			->	Dict:

							'''simple docstring'''




							snake_case					:   List[Any]         =					self.tokenizer(
							    self.src_text		,			text_target=self.tgt_text		,			padding=__a		,			truncation=__a		,			max_length=len(self.expected_src_tokens		)		,			return_tensors="pt"		,			)

							snake_case					:   Optional[Any]         =					shift_tokens_right(batch["labels"]		,			self.tokenizer.pad_token_id		)

							self.assertIsInstance(__a		,			__a		)

							self.assertEqual((2, 14)		,			batch.input_ids.shape		)
							self.assertEqual((2, 14)		,			batch.attention_mask.shape		)
							snake_case					:   Any         =					batch.input_ids.tolist()[0]
							self.assertListEqual(self.expected_src_tokens		,			__a		)
							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 				lowerCamelCase	(			self		)			->	Dict:

							'''simple docstring'''




							snake_case					:   Any         =					self.tokenizer(self.src_text		,			padding=__a		,			truncation=__a		,			max_length=3		,			return_tensors="pt"		)
							snake_case					:   int         =					self.tokenizer(
							    text_target=self.tgt_text		,			padding=__a		,			truncation=__a		,			max_length=10		,			return_tensors="pt"		)
							snake_case					:   Optional[int]         =					targets["""input_ids"""]
							snake_case					:   Optional[int]         =					shift_tokens_right(__a		,			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 				lowerCamelCase	(			self		)			->	List[Any]:

							'''simple docstring'''




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

							self.assertEqual(
							    nested_simplify(__a		)		,			{
							        # A, test, EOS, en_XX
							        "input_ids": [[62, 3034, 2, 25_0004]],
							        "attention_mask": [[1, 1, 1, 1]],
							        # ar_AR
							        "forced_bos_token_id": 25_0001,
							    }		,			)









"""simple docstring"""



# this script reports modified .py files under the desired list of top-level sub-dirs passed as a list of arguments, e.g.:
#   python ./utils/get_modified_files.py utils src tests examples
#
# it uses git to find the forking point and which files were modified - i.e. files not under git won't be considered
# since the output of this script is fed into Makefile commands it doesn't print a newline after the results

import re
import subprocess
import sys


__snake_case         =					subprocess.check_output("""git merge-base main HEAD""".split()).decode("""utf-8""")
__snake_case         =					(
    subprocess.check_output(F'''git diff --diff-filter=d --name-only {fork_point_sha}'''.split()).decode("""utf-8""").split()
)

__snake_case         =					"""|""".join(sys.argv[1:])
__snake_case         =					re.compile(RF'''^({joined_dirs}).*?\.py$''')

__snake_case         =					[x for x in modified_files if regex.match(x)]
print(""" """.join(relevant_modified_files), end="""""")





