



'''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


UpperCAmelCase     		=   get_tests_dir('fixtures/test_sentencepiece.model')


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

UpperCAmelCase     		=   25_0004
UpperCAmelCase     		=   25_0020

@require_sentencepiece
@require_tokenizers
class __snake_case(				_lowerCAmelCase		,							unittest.TestCase ):


						'''simple docstring'''



						UpperCAmelCase							:   Tuple									=		MBartTokenizer
						UpperCAmelCase							:   Optional[int]									=		MBartTokenizerFast
						UpperCAmelCase							:   Optional[int]									=		True
						UpperCAmelCase							:   str									=		True


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

							# We have a SentencePiece fixture for testing
							lowerCAmelCase   =     MBartTokenizer(A_     ,	keep_accents=A_				)
							tokenizer.save_pretrained(self.tmpdirname				)


						def     __snake_case   ( self				)     ->     Any:
							lowerCAmelCase   =     MBartTokenizer(A_     ,	keep_accents=A_				)

							lowerCAmelCase   =     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]]     ,	)

							lowerCAmelCase   =     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""",
							        """.""",
							    ]     ,	)
							lowerCAmelCase   =     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 ^
							    ]     ,	)

							lowerCAmelCase   =     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     __snake_case   ( self				)     ->     int:
							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

							lowerCAmelCase   =     (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})'				):
									lowerCAmelCase   =     self.rust_tokenizer_class.from_pretrained(A_     ,	**A_				)
									lowerCAmelCase   =     self.tokenizer_class.from_pretrained(A_     ,	**A_				)

									lowerCAmelCase   =     tempfile.mkdtemp()

									lowerCAmelCase   =     tokenizer_r.save_pretrained(A_				)
									lowerCAmelCase   =     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				)				)
									lowerCAmelCase   =     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
									lowerCAmelCase   =     tokenizer_r.from_pretrained(A_				)
									lowerCAmelCase   =     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
									lowerCAmelCase   =     tempfile.mkdtemp()

									lowerCAmelCase   =     tokenizer_r.save_pretrained(A_     ,	legacy_format=A_				)
									lowerCAmelCase   =     tokenizer_p.save_pretrained(A_				)

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

									# Checks everything loads correctly in the same way
									lowerCAmelCase   =     tokenizer_r.from_pretrained(A_				)
									lowerCAmelCase   =     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
									lowerCAmelCase   =     tempfile.mkdtemp()

									lowerCAmelCase   =     tokenizer_r.save_pretrained(A_     ,	legacy_format=A_				)
									lowerCAmelCase   =     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
									lowerCAmelCase   =     tokenizer_r.from_pretrained(A_				)
									lowerCAmelCase   =     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 __snake_case(				unittest.TestCase ):


						'''simple docstring'''



						UpperCAmelCase							:   str									=		"facebook/mbart-large-en-ro"
						UpperCAmelCase							:   Dict									=		[
						    " 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							:   Tuple									=		[
						    "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							:   str									=		[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				)     ->     int:
							lowerCAmelCase   =     MBartTokenizer.from_pretrained(
							    cls.checkpoint_name     ,	src_lang="""en_XX"""     ,	tgt_lang="""ro_RO"""				)
							lowerCAmelCase   =     1
							return cls


						def     __snake_case   ( self				)     ->     List[Any]:
							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     __snake_case   ( self				)     ->     List[str]:
							lowerCAmelCase   =     self.tokenizer.batch_encode_plus(self.src_text				).input_ids[0]
							self.assertListEqual(self.expected_src_tokens     ,	A_				)


						def     __snake_case   ( self				)     ->     List[str]:
							self.assertIn(A_     ,	self.tokenizer.all_special_ids				)
							lowerCAmelCase   =     [RO_CODE, 884, 9019, 96, 9, 916, 8_6792, 36, 1_8743, 1_5596, 5, 2]
							lowerCAmelCase   =     self.tokenizer.decode(A_     ,	skip_special_tokens=A_				)
							lowerCAmelCase   =     self.tokenizer.decode(generated_ids[1:]     ,	skip_special_tokens=A_				)
							self.assertEqual(A_     ,	A_				)
							self.assertNotIn(self.tokenizer.eos_token     ,	A_				)


						def     __snake_case   ( self				)     ->     Optional[Any]:
							lowerCAmelCase   =     ["""this is gunna be a long sentence """ * 20]
							assert isinstance(src_text[0]     ,	A_				)
							lowerCAmelCase   =     10
							lowerCAmelCase   =     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     __snake_case   ( self				)     ->     List[Any]:
							self.assertListEqual(self.tokenizer.convert_tokens_to_ids(["""<mask>""", """ar_AR"""]				)     ,	[25_0026, 25_0001]				)


						def     __snake_case   ( self				)     ->     str:
							lowerCAmelCase   =     tempfile.mkdtemp()
							lowerCAmelCase   =     self.tokenizer.fairseq_tokens_to_ids
							self.tokenizer.save_pretrained(A_				)
							lowerCAmelCase   =     MBartTokenizer.from_pretrained(A_				)
							self.assertDictEqual(new_tok.fairseq_tokens_to_ids     ,	A_				)


						@require_torch
						def     __snake_case   ( self				)     ->     Dict:
							lowerCAmelCase   =     self.tokenizer(self.src_text     ,	text_target=self.tgt_text     ,	padding=A_     ,	return_tensors="""pt"""				)
							lowerCAmelCase   =     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				)     ->     Tuple:
							lowerCAmelCase   =     self.tokenizer(
							    self.src_text     ,	text_target=self.tgt_text     ,	padding=A_     ,	truncation=A_     ,	max_length=len(self.expected_src_tokens				)     ,	return_tensors="""pt"""     ,	)

							lowerCAmelCase   =     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				)
							lowerCAmelCase   =     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     __snake_case   ( self				)     ->     Union[str, Any]:
							lowerCAmelCase   =     self.tokenizer(self.src_text     ,	padding=A_     ,	truncation=A_     ,	max_length=3     ,	return_tensors="""pt"""				)
							lowerCAmelCase   =     self.tokenizer(
							    text_target=self.tgt_text     ,	padding=A_     ,	truncation=A_     ,	max_length=10     ,	return_tensors="""pt"""				)
							lowerCAmelCase   =     targets["""input_ids"""]
							lowerCAmelCase   =     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     __snake_case   ( self				)     ->     Any:
							lowerCAmelCase   =     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'''

from ...configuration_utils import PretrainedConfig
from ...utils import logging


UpperCAmelCase     		=   logging.get_logger(__name__)

class __snake_case(				_lowerCAmelCase ):


						'''simple docstring'''



						UpperCAmelCase							:   Optional[int]									=		"timm_backbone"


						def __init__( self     ,	A_=None     ,	A_=3     ,	A_=True     ,	A_=True     ,	A_=None     ,	**A_     ,	)     ->     int:
							super().__init__(**A_				)
							lowerCAmelCase   =     backbone
							lowerCAmelCase   =     num_channels
							lowerCAmelCase   =     features_only
							lowerCAmelCase   =     use_pretrained_backbone
							lowerCAmelCase   =     True
							lowerCAmelCase   =     out_indices if out_indices is not None else (-1,)