




"""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


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


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

A				=							250_004
A				=							250_020



@require_sentencepiece
@require_tokenizers
class   a__					(						__magic_name__				,     unittest.TestCase ):
			lowercase_		=						MBartTokenizer
			lowercase_		=						MBartTokenizerFast
			lowercase_		=						True
			lowercase_		=						True


			def    a_  (   self   :     str):


						"""simple docstring"""




						super().setUp()

						# We have a SentencePiece fixture for testing
						__UpperCAmelCase						:			Any												=       MBartTokenizer(UpperCamelCase_   ,	keep_accents=UpperCamelCase_)
						tokenizer.save_pretrained(self.tmpdirname)


			def    a_  (   self   :     int):


						"""simple docstring"""




						__UpperCAmelCase						:			Dict												=       MBartTokenizer(UpperCamelCase_   ,	keep_accents=UpperCamelCase_)

						__UpperCAmelCase						:			Optional[int]												=       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]]   ,	)

						__UpperCAmelCase						:			List[Any]												=       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",
						        ".",
						    ]   ,	)
						__UpperCAmelCase						:			Any												=       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]
						        #                                       ^ unk: 2 + 1 = 3                  unk: 2 + 1 = 3 ^
						    ]   ,	)

						__UpperCAmelCase						:			Union[str, Any]												=       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>",
						        ".",
						    ]   ,	)


			def    a_  (   self   :     Dict):


						"""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						:			List[str]												=       self.rust_tokenizer_class.from_pretrained(UpperCamelCase_   ,	**UpperCamelCase_)
												__UpperCAmelCase						:			int												=       self.tokenizer_class.from_pretrained(UpperCamelCase_   ,	**UpperCamelCase_)

												__UpperCAmelCase						:			int												=       tempfile.mkdtemp()

												__UpperCAmelCase						:			Optional[int]												=       tokenizer_r.save_pretrained(UpperCamelCase_)
												__UpperCAmelCase						:			Any												=       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))
												__UpperCAmelCase						:			Any												=       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
												__UpperCAmelCase						:			int												=       tokenizer_r.from_pretrained(UpperCamelCase_)
												__UpperCAmelCase						:			Tuple												=       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
												__UpperCAmelCase						:			Optional[int]												=       tempfile.mkdtemp()

												__UpperCAmelCase						:			Dict												=       tokenizer_r.save_pretrained(UpperCamelCase_   ,	legacy_format=UpperCamelCase_)
												__UpperCAmelCase						:			int												=       tokenizer_p.save_pretrained(UpperCamelCase_)

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

												# Checks everything loads correctly in the same way
												__UpperCAmelCase						:			int												=       tokenizer_r.from_pretrained(UpperCamelCase_)
												__UpperCAmelCase						:			Optional[Any]												=       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
												__UpperCAmelCase						:			Tuple												=       tempfile.mkdtemp()

												__UpperCAmelCase						:			int												=       tokenizer_r.save_pretrained(UpperCamelCase_   ,	legacy_format=UpperCamelCase_)
												__UpperCAmelCase						:			Optional[int]												=       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
												__UpperCAmelCase						:			Optional[Any]												=       tokenizer_r.from_pretrained(UpperCamelCase_)
												__UpperCAmelCase						:			str												=       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   a__					(						unittest.TestCase ):
			lowercase_		=						"facebook/mbart-large-en-ro"
			lowercase_		=						[
			    " 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.",
			]
			lowercase_		=						[
			    "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.",
			]
			lowercase_		=						[8_2_7_4, 1_2_7_8_7_3, 2_5_9_1_6, 7, 8_6_2_2, 2_0_7_1, 4_3_8, 6_7_4_8_5, 5_3, 1_8_7_8_9_5, 2_3, 5_1_7_1_2, 2, EN_CODE]


			@classmethod
			def    a_  (   cls   :     int):


						"""simple docstring"""




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


			def    a_  (   self   :     List[Any]):


						"""simple docstring"""




						self.assertEqual(self.tokenizer.fairseq_tokens_to_ids["ar_AR"]   ,	250001)
						self.assertEqual(self.tokenizer.fairseq_tokens_to_ids["en_EN"]   ,	250004)
						self.assertEqual(self.tokenizer.fairseq_tokens_to_ids["ro_RO"]   ,	250020)


			def    a_  (   self   :     List[str]):


						"""simple docstring"""




						__UpperCAmelCase						:			Optional[Any]												=       self.tokenizer.batch_encode_plus(self.src_text).input_ids[0]
						self.assertListEqual(self.expected_src_tokens   ,	UpperCamelCase_)


			def    a_  (   self   :     Optional[int]):


						"""simple docstring"""




						self.assertIn(UpperCamelCase_   ,	self.tokenizer.all_special_ids)
						__UpperCAmelCase						:			Union[str, Any]												=       [RO_CODE, 884, 9019, 96, 9, 916, 86792, 36, 18743, 15596, 5, 2]
						__UpperCAmelCase						:			Optional[Any]												=       self.tokenizer.decode(UpperCamelCase_   ,	skip_special_tokens=UpperCamelCase_)
						__UpperCAmelCase						:			int												=       self.tokenizer.decode(generated_ids[1:]   ,	skip_special_tokens=UpperCamelCase_)
						self.assertEqual(UpperCamelCase_   ,	UpperCamelCase_)
						self.assertNotIn(self.tokenizer.eos_token   ,	UpperCamelCase_)


			def    a_  (   self   :     int):


						"""simple docstring"""




						__UpperCAmelCase						:			Optional[Any]												=       ["this is gunna be a long sentence " * 20]
						assert isinstance(src_text[0]   ,	UpperCamelCase_)
						__UpperCAmelCase						:			Tuple												=       10
						__UpperCAmelCase						:			List[Any]												=       self.tokenizer(UpperCamelCase_   ,	max_length=UpperCamelCase_   ,	truncation=UpperCamelCase_).input_ids[0]
						self.assertEqual(ids[-2]   ,	2)
						self.assertEqual(ids[-1]   ,	UpperCamelCase_)
						self.assertEqual(len(UpperCamelCase_)   ,	UpperCamelCase_)


			def    a_  (   self   :     Any):


						"""simple docstring"""




						self.assertListEqual(self.tokenizer.convert_tokens_to_ids(["<mask>", "ar_AR"])   ,	[250026, 250001])


			def    a_  (   self   :     Optional[Any]):


						"""simple docstring"""




						__UpperCAmelCase						:			List[str]												=       tempfile.mkdtemp()
						__UpperCAmelCase						:			Union[str, Any]												=       self.tokenizer.fairseq_tokens_to_ids
						self.tokenizer.save_pretrained(UpperCamelCase_)
						__UpperCAmelCase						:			List[Any]												=       MBartTokenizer.from_pretrained(UpperCamelCase_)
						self.assertDictEqual(new_tok.fairseq_tokens_to_ids   ,	UpperCamelCase_)


			@require_torch
			def    a_  (   self   :     Optional[Any]):


						"""simple docstring"""




						__UpperCAmelCase						:			Union[str, Any]												=       self.tokenizer(self.src_text   ,	text_target=self.tgt_text   ,	padding=UpperCamelCase_   ,	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    a_  (   self   :     Optional[int]):


						"""simple docstring"""




						__UpperCAmelCase						:			Dict												=       self.tokenizer(
						    self.src_text   ,	text_target=self.tgt_text   ,	padding=UpperCamelCase_   ,	truncation=UpperCamelCase_   ,	max_length=len(self.expected_src_tokens)   ,	return_tensors="pt"   ,	)

						__UpperCAmelCase						:			Tuple												=       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)
						__UpperCAmelCase						:			List[str]												=       batch.input_ids.tolist()[0]
						self.assertListEqual(self.expected_src_tokens   ,	UpperCamelCase_)
						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    a_  (   self   :     Tuple):


						"""simple docstring"""




						__UpperCAmelCase						:			List[str]												=       self.tokenizer(self.src_text   ,	padding=UpperCamelCase_   ,	truncation=UpperCamelCase_   ,	max_length=3   ,	return_tensors="pt")
						__UpperCAmelCase						:			Any												=       self.tokenizer(
						    text_target=self.tgt_text   ,	padding=UpperCamelCase_   ,	truncation=UpperCamelCase_   ,	max_length=10   ,	return_tensors="pt")
						__UpperCAmelCase						:			int												=       targets["input_ids"]
						__UpperCAmelCase						:			Any												=       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   :     int):


						"""simple docstring"""




						__UpperCAmelCase						:			int												=       self.tokenizer._build_translation_inputs(
						    "A test"   ,	return_tensors="pt"   ,	src_lang="en_XX"   ,	tgt_lang="ar_AR")

						self.assertEqual(
						    nested_simplify(UpperCamelCase_)   ,	{
						        # A, test, EOS, en_XX
						        "input_ids": [[62, 3034, 2, 250004]],
						        "attention_mask": [[1, 1, 1, 1]],
						        # ar_AR
						        "forced_bos_token_id": 250001,
						    }   ,	)





"""simple docstring"""


import tempfile
import unittest

from transformers import SPIECE_UNDERLINE, BatchEncoding, PLBartTokenizer, 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.plbart.modeling_plbart import shift_tokens_right

UpperCAmelCase													=50_003
UpperCAmelCase													=50_002





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



    '''simple docstring'''




    _lowerCamelCase					=   PLBartTokenizer
    _lowerCamelCase					=   None
    _lowerCamelCase					=   False




    def UpperCamelCase__		( self    )    ->      Tuple:
          super().setUp()

          # We have a SentencePiece fixture for testing
          A				  =		PLBartTokenizer(lowerCamelCase_ ,language_codes="""base""" ,keep_accents=lowerCamelCase_    )
          tokenizer.save_pretrained(self.tmpdirname    )




    def UpperCamelCase__		( self    )    ->      int:
          A				  =		PLBartTokenizer(lowerCamelCase_ ,language_codes="""base""" ,keep_accents=lowerCamelCase_    )

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

          self.assertListEqual(
              tokenizer.convert_tokens_to_ids(lowerCamelCase_    ) ,[value + tokenizer.fairseq_offset for value in [2_8_5, 4_6, 1_0, 1_7_0, 3_8_2]] ,)

          A				  =		tokenizer.tokenize("""I was born in 92000, and this is falsé."""    )
          self.assertListEqual(
              lowerCamelCase_ ,[
                  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(lowerCamelCase_    )
          self.assertListEqual(
              lowerCamelCase_ ,[
                  value + tokenizer.fairseq_offset
                  for value in [8, 2_1, 8_4, 5_5, 2_4, 1_9, 7, 2, 6_0_2, 3_4_7, 3_4_7, 3_4_7, 3, 1_2, 6_6, 4_6, 7_2, 8_0, 6, 2, 4]
              ] ,)

          A				  =		tokenizer.convert_ids_to_tokens(lowerCamelCase_    )
          self.assertListEqual(
              lowerCamelCase_ ,[
                  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>""",
                  """.""",
              ] ,)

          A				  =		tokenizer.vocab_size
          A				  =		[tokenizer.convert_ids_to_tokens(lowerCamelCase_    ) for x in range(end - 4 ,lowerCamelCase_    )]

          self.assertListEqual(lowerCamelCase_ ,["""__java__""", """__python__""", """__en_XX__""", """<mask>"""]    )

          A				  =		"""java.lang.Exception, python.lang.Exception, javascript, php, ruby, go"""
          A				  =		tokenizer(lowerCamelCase_    ).input_ids
          self.assertEqual(
              tokenizer.decode(lowerCamelCase_ ,skip_special_tokens=lowerCamelCase_ ,clean_up_tokenization_spaces=lowerCamelCase_    ) ,lowerCamelCase_ ,)




    def UpperCamelCase__		( self    )    ->      Optional[Any]:
          A				  =		PLBartTokenizer(lowerCamelCase_ ,language_codes="""multi""" ,keep_accents=lowerCamelCase_    )

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

          self.assertListEqual(
              tokenizer.convert_tokens_to_ids(lowerCamelCase_    ) ,[value + tokenizer.fairseq_offset for value in [2_8_5, 4_6, 1_0, 1_7_0, 3_8_2]] ,)

          A				  =		tokenizer.tokenize("""I was born in 92000, and this is falsé."""    )
          self.assertListEqual(
              lowerCamelCase_ ,[
                  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(lowerCamelCase_    )
          self.assertListEqual(
              lowerCamelCase_ ,[
                  value + tokenizer.fairseq_offset
                  for value in [8, 2_1, 8_4, 5_5, 2_4, 1_9, 7, 2, 6_0_2, 3_4_7, 3_4_7, 3_4_7, 3, 1_2, 6_6, 4_6, 7_2, 8_0, 6, 2, 4]
              ] ,)

          A				  =		tokenizer.convert_ids_to_tokens(lowerCamelCase_    )
          self.assertListEqual(
              lowerCamelCase_ ,[
                  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>""",
                  """.""",
              ] ,)
          A				  =		tokenizer.vocab_size
          A				  =		[tokenizer.convert_ids_to_tokens(lowerCamelCase_    ) for x in range(end - 7 ,lowerCamelCase_    )]

          self.assertListEqual(
              lowerCamelCase_ ,["""__java__""", """__python__""", """__en_XX__""", """__javascript__""", """__php__""", """__ruby__""", """__go__"""]    )
          A				  =		"""java.lang.Exception, python.lang.Exception, javascript, php, ruby, go"""
          A				  =		tokenizer(lowerCamelCase_    ).input_ids
          self.assertEqual(
              tokenizer.decode(lowerCamelCase_ ,skip_special_tokens=lowerCamelCase_ ,clean_up_tokenization_spaces=lowerCamelCase_    ) ,lowerCamelCase_ ,)





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



    '''simple docstring'''




    _lowerCamelCase					=   '''uclanlp/plbart-python-en_XX'''
    _lowerCamelCase					=   [
        '''def maximum(a,b,c):NEW_LINE_INDENTreturn max([a,b,c])''',
        '''def sum(a,b,c):NEW_LINE_INDENTreturn sum([a,b,c])''',
    ]
    _lowerCamelCase					=   [
        '''Returns the maximum value of a b c.''',
        '''Sums the values of a b c.''',
    ]
    _lowerCamelCase					=   [
        134,
        5452,
        33460,
        33441,
        33463,
        33465,
        33463,
        33449,
        988,
        20,
        33456,
        19,
        33456,
        771,
        39,
        4258,
        889,
        3318,
        33441,
        33463,
        33465,
        33463,
        33449,
        2471,
        2,
        PYTHON_CODE,
    ]




    @classmethod
    def UpperCamelCase__		( cls    )    ->      List[str]:
          A				  =		PLBartTokenizer.from_pretrained(
              cls.checkpoint_name ,language_codes="""base""" ,src_lang="""python""" ,tgt_lang="""en_XX"""    )
          A				  =		1
          return cls




    def UpperCamelCase__		( self    )    ->      Optional[int]:
          self.assertEqual(self.tokenizer.fairseq_tokens_to_ids["""__java__"""] ,5_0_0_0_1    )
          self.assertEqual(self.tokenizer.fairseq_tokens_to_ids["""__python__"""] ,5_0_0_0_2    )
          self.assertEqual(self.tokenizer.fairseq_tokens_to_ids["""__en_XX__"""] ,5_0_0_0_3    )




    def UpperCamelCase__		( self    )    ->      Optional[int]:
          A				  =		self.tokenizer.batch_encode_plus(self.src_text    ).input_ids[0]
          self.assertListEqual(self.expected_src_tokens ,lowerCamelCase_    )




    def UpperCamelCase__		( self    )    ->      str:
          self.assertIn(lowerCamelCase_ ,self.tokenizer.all_special_ids    )
          A				  =		[EN_CODE, 9_0_3_7, 3_3_4_4_2, 5_7, 7_5_2, 1_5_3, 1_4, 5_6, 1_8, 9, 2]
          A				  =		self.tokenizer.decode(lowerCamelCase_ ,skip_special_tokens=lowerCamelCase_    )
          A				  =		self.tokenizer.decode(generated_ids[1:] ,skip_special_tokens=lowerCamelCase_    )
          self.assertEqual(lowerCamelCase_ ,lowerCamelCase_    )
          self.assertNotIn(self.tokenizer.eos_token ,lowerCamelCase_    )




    def UpperCamelCase__		( self    )    ->      List[str]:
          A				  =		["""def sum(a,b,c):NEW_LINE_INDENTreturn sum([a,b,c])""" * 2_0]
          self.assertIsInstance(src_text[0] ,lowerCamelCase_    )
          A				  =		1_0
          A				  =		self.tokenizer(lowerCamelCase_ ,max_length=lowerCamelCase_ ,truncation=lowerCamelCase_    ).input_ids[0]
          self.assertEqual(ids[-2] ,2    )
          self.assertEqual(ids[-1] ,lowerCamelCase_    )
          self.assertEqual(len(lowerCamelCase_    ) ,lowerCamelCase_    )




    def UpperCamelCase__		( self    )    ->      Any:
          self.assertListEqual(self.tokenizer.convert_tokens_to_ids(["""<mask>""", """__java__"""]    ) ,[5_0_0_0_4, 5_0_0_0_1]    )




    def UpperCamelCase__		( self    )    ->      Optional[int]:
          A				  =		tempfile.mkdtemp()
          A				  =		self.tokenizer.fairseq_tokens_to_ids
          self.tokenizer.save_pretrained(lowerCamelCase_    )
          A				  =		PLBartTokenizer.from_pretrained(lowerCamelCase_    )
          self.assertDictEqual(new_tok.fairseq_tokens_to_ids ,lowerCamelCase_    )




    @require_torch
    def UpperCamelCase__		( self    )    ->      Optional[int]:
          A				  =		self.tokenizer(self.src_text ,text_target=self.tgt_text ,padding=lowerCamelCase_ ,return_tensors="""pt"""    )
          A				  =		shift_tokens_right(batch["""labels"""] ,self.tokenizer.pad_token_id    )

          # fairseq batch: https://gist.github.com/sshleifer/cba08bc2109361a74ac3760a7e30e4f4
          self.assertEqual(batch.input_ids[1][-2:].tolist() ,[2, PYTHON_CODE]    )
          self.assertEqual(batch.decoder_input_ids[1][0] ,lowerCamelCase_    )
          self.assertEqual(batch.decoder_input_ids[1][-1] ,2    )
          self.assertEqual(batch.labels[1][-2:].tolist() ,[2, EN_CODE]    )




    @require_torch
    def UpperCamelCase__		( self    )    ->      str:
          A				  =		self.tokenizer(
              self.src_text ,text_target=self.tgt_text ,padding=lowerCamelCase_ ,truncation=lowerCamelCase_ ,max_length=len(self.expected_src_tokens    ) ,return_tensors="""pt""" ,)
          A				  =		shift_tokens_right(batch["""labels"""] ,self.tokenizer.pad_token_id    )

          self.assertIsInstance(lowerCamelCase_ ,lowerCamelCase_    )

          self.assertEqual((2, 2_6) ,batch.input_ids.shape    )
          self.assertEqual((2, 2_6) ,batch.attention_mask.shape    )
          A				  =		batch.input_ids.tolist()[0]
          self.assertListEqual(self.expected_src_tokens ,lowerCamelCase_    )
          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, PYTHON_CODE]    )




    def UpperCamelCase__		( self    )    ->      Tuple:
          A				  =		self.tokenizer(self.src_text ,padding=lowerCamelCase_ ,truncation=lowerCamelCase_ ,max_length=3 ,return_tensors="""pt"""    )
          A				  =		self.tokenizer(
              text_target=self.tgt_text ,padding=lowerCamelCase_ ,truncation=lowerCamelCase_ ,max_length=1_0 ,return_tensors="""pt"""    )
          A				  =		targets["""input_ids"""]
          A				  =		shift_tokens_right(lowerCamelCase_ ,self.tokenizer.pad_token_id    )

          self.assertEqual(batch.input_ids.shape[1] ,3    )
          self.assertEqual(batch.decoder_input_ids.shape[1] ,1_0    )




    @require_torch
    def UpperCamelCase__		( self    )    ->      List[Any]:
          A				  =		self.tokenizer._build_translation_inputs(
              """A test""" ,return_tensors="""pt""" ,src_lang="""en_XX""" ,tgt_lang="""java"""    )

          self.assertEqual(
              nested_simplify(lowerCamelCase_    ) ,{
                  # A, test, EOS, en_XX
                  """input_ids""": [[1_5_0, 2_4_2, 2, 5_0_0_0_3]],
                  """attention_mask""": [[1, 1, 1, 1]],
                  # java
                  """forced_bos_token_id""": 5_0_0_0_1,
              } ,)




