
import unittest

from transformers import DebertaVaTokenizer, DebertaVaTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow

from ...test_tokenization_common import TokenizerTesterMixin


lowercase__          =get_tests_dir('fixtures/spiece.model')



@require_sentencepiece
@require_tokenizers
class 		UpperCamelCase__  (	_a   ,unittest.TestCase   ):
			_SCREAMING_SNAKE_CASE				:							List[Any]     	=				DebertaVaTokenizer
			_SCREAMING_SNAKE_CASE				:							Any     	=				DebertaVaTokenizerFast
			_SCREAMING_SNAKE_CASE				:							Union[str, Any]     	=				True
			_SCREAMING_SNAKE_CASE				:							Tuple     	=				True
			def 				lowerCAmelCase      (self			: Union[str, Any]       ):
				super().setUp()

				# We have a SentencePiece fixture for testing
				__a			:  Tuple		    =  DebertaVaTokenizer(__lowerCamelCase ,    unk_token='''<unk>'''       )
				tokenizer.save_pretrained(self.tmpdirname       )
			def 				lowerCAmelCase      (self			: int ,    snake_case_			: Union[str, Any]       ):
				__a			:  str		    =  """this is a test"""
				__a			:  Dict		    =  """this is a test"""
				return input_text, output_text
			def 				lowerCAmelCase      (self			: Tuple       ):
				__a			:  Optional[Any]		    =  """<pad>"""
				__a			:  Optional[int]		    =  0

				self.assertEqual(self.get_tokenizer()._convert_token_to_id(__lowerCamelCase       ) ,    __lowerCamelCase       )
				self.assertEqual(self.get_tokenizer()._convert_id_to_token(__lowerCamelCase       ) ,    __lowerCamelCase       )
			def 				lowerCAmelCase      (self			: int       ):
				__a			:  Any		    =  list(self.get_tokenizer().get_vocab().keys()       )
				self.assertEqual(vocab_keys[0] ,    '''<pad>'''       )
				self.assertEqual(vocab_keys[1] ,    '''<unk>'''       )
				self.assertEqual(vocab_keys[-1] ,    '''[PAD]'''       )
				self.assertEqual(len(__lowerCamelCase       ) ,    3_0_0_0_1       )
			def 				lowerCAmelCase      (self			: Optional[int]       ):
				self.assertEqual(self.get_tokenizer().vocab_size ,    3_0_0_0_0       )
			def 				lowerCAmelCase      (self			: str       ):
				# fmt: off
				__a			:  Optional[int]		    =  """ \tHeLLo!how  \n Are yoU?  """
				__a			:  Any		    =  ["""▁hello""", """!""", """how""", """▁are""", """▁you""", """?"""]
				# fmt: on

				__a			:  Optional[Any]		    =  DebertaVaTokenizer(__lowerCamelCase ,    do_lower_case=__lowerCamelCase       )
				__a			:  Optional[int]		    =  tokenizer.convert_ids_to_tokens(tokenizer.encode(__lowerCamelCase ,    add_special_tokens=__lowerCamelCase       )       )

				self.assertListEqual(__lowerCamelCase ,    __lowerCamelCase       )

				__a			:  Any		    =  DebertaVaTokenizerFast(__lowerCamelCase ,    do_lower_case=__lowerCamelCase       )
				__a			:  List[Any]		    =  rust_tokenizer.convert_ids_to_tokens(rust_tokenizer.encode(__lowerCamelCase ,    add_special_tokens=__lowerCamelCase       )       )

				self.assertListEqual(__lowerCamelCase ,    __lowerCamelCase       )
			@unittest.skip('''There is an inconsistency between slow and fast tokenizer due to a bug in the fast one.'''       )
			def 				lowerCAmelCase      (self			: Dict       ):
				pass
			@unittest.skip('''There is an inconsistency between slow and fast tokenizer due to a bug in the fast one.'''       )
			def 				lowerCAmelCase      (self			: Optional[Any]       ):
				pass
			def 				lowerCAmelCase      (self			: Optional[int]       ):
				# fmt: off
				__a			:  Union[str, Any]		    =  """I was born in 92000, and this is falsé."""
				__a			:  int		    =  ["""▁""", """<unk>""", """▁was""", """▁born""", """▁in""", """▁9""", """2000""", """▁""", """,""", """▁and""", """▁this""", """▁is""", """▁fal""", """s""", """<unk>""", """▁""", """.""", ]
				# fmt: on

				__a			:  int		    =  DebertaVaTokenizer(__lowerCamelCase ,    split_by_punct=__lowerCamelCase       )
				__a			:  int		    =  tokenizer.convert_ids_to_tokens(tokenizer.encode(__lowerCamelCase ,    add_special_tokens=__lowerCamelCase       )       )

				self.assertListEqual(__lowerCamelCase ,    __lowerCamelCase       )

				__a			:  Optional[int]		    =  DebertaVaTokenizerFast(__lowerCamelCase ,    split_by_punct=__lowerCamelCase       )
				__a			:  Any		    =  rust_tokenizer.convert_ids_to_tokens(rust_tokenizer.encode(__lowerCamelCase ,    add_special_tokens=__lowerCamelCase       )       )

				self.assertListEqual(__lowerCamelCase ,    __lowerCamelCase       )
			def 				lowerCAmelCase      (self			: int       ):
				# fmt: off
				__a			:  Union[str, Any]		    =  """I was born in 92000, and this is falsé."""
				__a			:  Any		    =  ["""▁i""", """▁was""", """▁born""", """▁in""", """▁9""", """2000""", """▁""", """,""", """▁and""", """▁this""", """▁is""", """▁fal""", """s""", """<unk>""", """▁""", """.""", ]
				# fmt: on

				__a			:  Tuple		    =  DebertaVaTokenizer(__lowerCamelCase ,    do_lower_case=__lowerCamelCase ,    split_by_punct=__lowerCamelCase       )
				__a			:  Any		    =  tokenizer.convert_ids_to_tokens(tokenizer.encode(__lowerCamelCase ,    add_special_tokens=__lowerCamelCase       )       )
				self.assertListEqual(__lowerCamelCase ,    __lowerCamelCase       )

				__a			:  Union[str, Any]		    =  DebertaVaTokenizerFast(__lowerCamelCase ,    do_lower_case=__lowerCamelCase ,    split_by_punct=__lowerCamelCase       )
				__a			:  int		    =  rust_tokenizer.convert_ids_to_tokens(rust_tokenizer.encode(__lowerCamelCase ,    add_special_tokens=__lowerCamelCase       )       )
				self.assertListEqual(__lowerCamelCase ,    __lowerCamelCase       )
			def 				lowerCAmelCase      (self			: Any       ):
				# fmt: off
				__a			:  Union[str, Any]		    =  """I was born in 92000, and this is falsé."""
				__a			:  List[Any]		    =  ["""▁i""", """▁was""", """▁born""", """▁in""", """▁9""", """2000""", """,""", """▁and""", """▁this""", """▁is""", """▁fal""", """s""", """<unk>""", """.""", ]
				# fmt: on

				__a			:  Tuple		    =  DebertaVaTokenizer(__lowerCamelCase ,    do_lower_case=__lowerCamelCase ,    split_by_punct=__lowerCamelCase       )
				__a			:  Any		    =  tokenizer.convert_ids_to_tokens(tokenizer.encode(__lowerCamelCase ,    add_special_tokens=__lowerCamelCase       )       )

				self.assertListEqual(__lowerCamelCase ,    __lowerCamelCase       )

				__a			:  Union[str, Any]		    =  DebertaVaTokenizerFast(__lowerCamelCase ,    do_lower_case=__lowerCamelCase ,    split_by_punct=__lowerCamelCase       )
				__a			:  Dict		    =  rust_tokenizer.convert_ids_to_tokens(rust_tokenizer.encode(__lowerCamelCase ,    add_special_tokens=__lowerCamelCase       )       )

				self.assertListEqual(__lowerCamelCase ,    __lowerCamelCase       )
			def 				lowerCAmelCase      (self			: str       ):
				# fmt: off
				__a			:  List[str]		    =  """I was born in 92000, and this is falsé."""
				__a			:  int		    =  ["""▁""", """<unk>""", """▁was""", """▁born""", """▁in""", """▁9""", """2000""", """▁""", """,""", """▁and""", """▁this""", """▁is""", """▁fal""", """s""", """<unk>""", """▁""", """.""", ]
				# fmt: on

				__a			:  List[str]		    =  DebertaVaTokenizer(__lowerCamelCase ,    do_lower_case=__lowerCamelCase ,    split_by_punct=__lowerCamelCase       )
				__a			:  Tuple		    =  tokenizer.convert_ids_to_tokens(tokenizer.encode(__lowerCamelCase ,    add_special_tokens=__lowerCamelCase       )       )

				self.assertListEqual(__lowerCamelCase ,    __lowerCamelCase       )

				__a			:  List[str]		    =  DebertaVaTokenizerFast(__lowerCamelCase ,    do_lower_case=__lowerCamelCase ,    split_by_punct=__lowerCamelCase       )
				__a			:  Optional[int]		    =  rust_tokenizer.convert_ids_to_tokens(rust_tokenizer.encode(__lowerCamelCase ,    add_special_tokens=__lowerCamelCase       )       )

				self.assertListEqual(__lowerCamelCase ,    __lowerCamelCase       )
			def 				lowerCAmelCase      (self			: Optional[Any]       ):
				# fmt: off
				__a			:  Optional[Any]		    =  """ \tHeLLo!how  \n Are yoU?  """
				__a			:  Dict		    =  ["""▁""", """<unk>""", """e""", """<unk>""", """o""", """!""", """how""", """▁""", """<unk>""", """re""", """▁yo""", """<unk>""", """?"""]
				# fmt: on

				__a			:  int		    =  DebertaVaTokenizer(__lowerCamelCase ,    do_lower_case=__lowerCamelCase ,    split_by_punct=__lowerCamelCase       )
				__a			:  Optional[Any]		    =  tokenizer.convert_ids_to_tokens(tokenizer.encode(__lowerCamelCase ,    add_special_tokens=__lowerCamelCase       )       )

				self.assertListEqual(__lowerCamelCase ,    __lowerCamelCase       )

				__a			:  Any		    =  DebertaVaTokenizerFast(__lowerCamelCase ,    do_lower_case=__lowerCamelCase ,    split_by_punct=__lowerCamelCase       )
				__a			:  Tuple		    =  rust_tokenizer.convert_ids_to_tokens(rust_tokenizer.encode(__lowerCamelCase ,    add_special_tokens=__lowerCamelCase       )       )

				self.assertListEqual(__lowerCamelCase ,    __lowerCamelCase       )
			def 				lowerCAmelCase      (self			: int       ):
				__a			:  int		    =  self.get_tokenizer()
				__a			:  str		    =  self.get_rust_tokenizer()

				__a			:  Dict		    =  """I was born in 92000, and this is falsé."""

				__a			:  List[str]		    =  tokenizer.convert_ids_to_tokens(tokenizer.encode(__lowerCamelCase ,    add_special_tokens=__lowerCamelCase       )       )
				__a			:  Optional[int]		    =  rust_tokenizer.convert_ids_to_tokens(rust_tokenizer.encode(__lowerCamelCase ,    add_special_tokens=__lowerCamelCase       )       )
				self.assertListEqual(__lowerCamelCase ,    __lowerCamelCase       )

				__a			:  List[str]		    =  tokenizer.encode(__lowerCamelCase ,    add_special_tokens=__lowerCamelCase       )
				__a			:  Optional[int]		    =  rust_tokenizer.encode(__lowerCamelCase ,    add_special_tokens=__lowerCamelCase       )
				self.assertListEqual(__lowerCamelCase ,    __lowerCamelCase       )

				__a			:  int		    =  self.get_rust_tokenizer()
				__a			:  Tuple		    =  tokenizer.encode(__lowerCamelCase       )
				__a			:  Dict		    =  rust_tokenizer.encode(__lowerCamelCase       )
				self.assertListEqual(__lowerCamelCase ,    __lowerCamelCase       )
			def 				lowerCAmelCase      (self			: Dict       ):
				__a			:  Optional[int]		    =  """This is a test"""
				__a			:  str		    =  [1_3, 1, 4_3_9_8, 2_5, 2_1, 1_2_8_9]
				__a			:  int		    =  ["""▁""", """T""", """his""", """▁is""", """▁a""", """▁test"""]
				__a			:  Any		    =  ["""▁""", """<unk>""", """his""", """▁is""", """▁a""", """▁test"""]

				__a			:  str		    =  DebertaVaTokenizer(__lowerCamelCase ,    keep_accents=__lowerCamelCase       )
				__a			:  Union[str, Any]		    =  DebertaVaTokenizerFast(__lowerCamelCase ,    keep_accents=__lowerCamelCase       )

				__a			:  Optional[Any]		    =  tokenizer.encode(__lowerCamelCase ,    add_special_tokens=__lowerCamelCase       )
				self.assertListEqual(__lowerCamelCase ,    __lowerCamelCase       )
				__a			:  Union[str, Any]		    =  tokenizer.tokenize(__lowerCamelCase       )
				self.assertListEqual(__lowerCamelCase ,    __lowerCamelCase       )
				__a			:  Any		    =  tokenizer.convert_ids_to_tokens(__lowerCamelCase       )
				self.assertListEqual(__lowerCamelCase ,    __lowerCamelCase       )

				__a			:  List[Any]		    =  rust_tokenizer.encode(__lowerCamelCase ,    add_special_tokens=__lowerCamelCase       )
				self.assertListEqual(__lowerCamelCase ,    __lowerCamelCase       )
				__a			:  Optional[Any]		    =  rust_tokenizer.tokenize(__lowerCamelCase       )
				self.assertListEqual(__lowerCamelCase ,    __lowerCamelCase       )
				__a			:  int		    =  rust_tokenizer.convert_ids_to_tokens(__lowerCamelCase       )
				self.assertListEqual(__lowerCamelCase ,    __lowerCamelCase       )

				# fmt: off
				__a			:  Optional[Any]		    =  """I was born in 92000, and this is falsé."""
				__a			:  Any		    =  [1_3, 1, 2_3, 3_8_6, 1_9, 5_6_1, 3_0_5_0, 1_5, 1_7, 4_8, 2_5, 8_2_5_6, 1_8, 1, 9]
				__a			:  Union[str, Any]		    =  ["""▁""", """I""", """▁was""", """▁born""", """▁in""", """▁9""", """2000""", """,""", """▁and""", """▁this""", """▁is""", """▁fal""", """s""", """é""", """.""", ]
				__a			:  Optional[Any]		    =  ["""▁""", """<unk>""", """▁was""", """▁born""", """▁in""", """▁9""", """2000""", """,""", """▁and""", """▁this""", """▁is""", """▁fal""", """s""", """<unk>""", """.""", ]
				# fmt: on

				__a			:  str		    =  tokenizer.encode(__lowerCamelCase ,    add_special_tokens=__lowerCamelCase       )
				self.assertListEqual(__lowerCamelCase ,    __lowerCamelCase       )
				__a			:  Any		    =  tokenizer.tokenize(__lowerCamelCase       )
				self.assertListEqual(__lowerCamelCase ,    __lowerCamelCase       )
				__a			:  Union[str, Any]		    =  tokenizer.convert_ids_to_tokens(__lowerCamelCase       )
				self.assertListEqual(__lowerCamelCase ,    __lowerCamelCase       )

				__a			:  List[Any]		    =  rust_tokenizer.encode(__lowerCamelCase ,    add_special_tokens=__lowerCamelCase       )
				self.assertListEqual(__lowerCamelCase ,    __lowerCamelCase       )
				__a			:  int		    =  rust_tokenizer.tokenize(__lowerCamelCase       )
				self.assertListEqual(__lowerCamelCase ,    __lowerCamelCase       )
				__a			:  Dict		    =  rust_tokenizer.convert_ids_to_tokens(__lowerCamelCase       )
				self.assertListEqual(__lowerCamelCase ,    __lowerCamelCase       )
			def 				lowerCAmelCase      (self			: Optional[int]       ):
				__a			:  str		    =  DebertaVaTokenizer(__lowerCamelCase       )

				__a			:  Union[str, Any]		    =  tokenizer.encode('''sequence builders'''       )
				__a			:  Any		    =  tokenizer.encode('''multi-sequence build'''       )

				__a			:  Optional[int]		    =  tokenizer.build_inputs_with_special_tokens(__lowerCamelCase       )
				__a			:  str		    =  tokenizer.build_inputs_with_special_tokens(__lowerCamelCase ,    __lowerCamelCase       )

				self.assertEqual([tokenizer.cls_token_id] + text + [tokenizer.sep_token_id] ,    __lowerCamelCase       )
				self.assertEqual(
				    [tokenizer.cls_token_id] + text + [tokenizer.sep_token_id] + text_a + [tokenizer.sep_token_id] ,    __lowerCamelCase ,    )







			@slow
			def 				lowerCAmelCase      (self			: List[Any]       ):
				# fmt: off
				__a			:  Union[str, Any]		    =  {"""input_ids""": [[1, 3_9_8_6_7, 3_6, 1_9_3_9_0, 4_8_6, 2_7, 3_5_0_5_2, 8_1_4_3_6, 1_8, 6_0_6_8_5, 1_2_2_5, 7, 3_5_0_5_2, 8_1_4_3_6, 1_8, 9_3_6_7, 1_6_8_9_9, 1_8, 1_5_9_3_7, 5_3, 5_9_4, 7_7_3, 1_8, 1_6_2_8_7, 3_0_4_6_5, 3_6, 1_5_9_3_7, 6, 4_1_1_3_9, 3_8, 3_6_9_7_9, 6_0_7_6_3, 1_9_1, 6, 3_4_1_3_2, 9_9, 6, 5_0_5_3_8, 3_9_0, 4_3_2_3_0, 6, 3_4_1_3_2, 2_7_7_9, 2_0_8_5_0, 1_4, 6_9_9, 1_0_7_2, 1_1_9_4, 3_6, 3_8_2, 1_0_9_0_1, 5_3, 7, 6_9_9, 1_0_7_2, 2_0_8_4, 3_6, 2_0_4_2_2, 6_3_0, 5_3, 1_9, 1_0_5, 3_0_4_9, 1_8_9_6, 1_0_5_3, 1_6_8_9_9, 1_5_0_6, 1_1, 3_7_9_7_8, 4_2_4_3, 7, 1_2_3_7, 3_1_8_6_9, 2_0_0, 1_6_5_6_6, 6_5_4, 6, 3_5_0_5_2, 8_1_4_3_6, 7, 5_5_6_3_0, 1_3_5_9_3, 4, 2], [1, 2_6, 1_5_0_1_1, 1_3, 6_6_7, 8, 1_0_5_3, 1_8, 2_3_6_1_1, 1_2_3_7, 7_2_3_5_6, 1_2_8_2_0, 3_4, 1_0_4_1_3_4, 1_2_0_9, 3_5, 1_3_3_1_3, 6_6_2_7, 2_1, 2_0_2, 3_4_7, 7, 1_6_4, 2_3_9_9, 1_1, 4_6, 4_4_8_5, 4, 2, 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, 5, 1_2_3_2, 2_8_6_4, 1_5_7_8_5, 1_4_9_5_1, 1_0_5, 5, 8_5_8_1, 1_2_5_0, 4, 2, 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]], """token_type_ids""": [[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, 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, 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]], """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, 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, 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=__lowerCamelCase ,    model_name='''microsoft/deberta-v2-xlarge''' ,    revision='''ad6e42c1532ddf3a15c39246b63f5559d558b670''' ,    )


import os
from pathlib import Path

import numpy as np
import pytest
from pack_dataset import pack_data_dir
from parameterized import parameterized
from save_len_file import save_len_file
from torch.utils.data import DataLoader

from transformers import AutoTokenizer
from transformers.models.mbart.modeling_mbart import shift_tokens_right
from transformers.testing_utils import TestCasePlus, slow
from utils import FAIRSEQ_AVAILABLE, DistributedSortishSampler, LegacySeqaSeqDataset, SeqaSeqDataset


lowercase__          ='bert-base-cased'
lowercase__          ='google/pegasus-xsum'
lowercase__          =[' Sam ate lunch today.', 'Sams lunch ingredients.']
lowercase__          =['A very interesting story about what I ate for lunch.', 'Avocado, celery, turkey, coffee']
lowercase__          ='patrickvonplaten/t5-tiny-random'
lowercase__          ='sshleifer/bart-tiny-random'
lowercase__          ='sshleifer/tiny-mbart'
lowercase__          ='sshleifer/tiny-marian-en-de'




def        __UpperCamelCase					(    lowerCAmelCase__							:    Path  ,       lowerCAmelCase__							:    list  ):
 __a			:  List[Any]		    =  '''\n'''.join(lowerCAmelCase__  )
 Path(lowerCAmelCase__  ).open('''w'''  ).writelines(lowerCAmelCase__  )




def        __UpperCamelCase					(    lowerCAmelCase__							:    int  ):
 for split in ["train", "val", "test"]:
  _dump_articles(os.path.join(lowerCAmelCase__  ,       f"{split}.source"  )  ,       lowerCAmelCase__  )
  _dump_articles(os.path.join(lowerCAmelCase__  ,       f"{split}.target"  )  ,       lowerCAmelCase__  )
 return tmp_dir



class 		UpperCamelCase__  (	__lowercase   ):
   @parameterized.expand(
       [
           MBART_TINY,
           MARIAN_TINY,
           T5_TINY,
           BART_TINY,
           PEGASUS_XSUM,
       ] ,    )
   @slow
   def 				lowerCAmelCase      (self			: int ,    snake_case_			: int       ):
    __a			:  Optional[Any]		    =  AutoTokenizer.from_pretrained(snake_case_       )
    __a			:  Optional[Any]		    =  make_test_data_dir(tmp_dir=self.get_auto_remove_tmp_dir()       )
    __a			:  Union[str, Any]		    =  max(len(tokenizer.encode(snake_case_       )       ) for a in ARTICLES       )
    __a			:  str		    =  max(len(tokenizer.encode(snake_case_       )       ) for a in SUMMARIES       )
    __a			:  str		    =  4
    __a			:  Dict		    =  8
    assert max_len_target > max_src_len  # Will be truncated
    assert max_len_source > max_src_len  # Will be truncated
    __a    ,	__a			:  Any		    =  '''ro_RO''', '''de_DE'''  # ignored for all but mbart, but never causes error.
    __a			:  List[Any]		    =  SeqaSeqDataset(
        snake_case_ ,    data_dir=snake_case_ ,    type_path='''train''' ,    max_source_length=snake_case_ ,    max_target_length=snake_case_ ,    src_lang=snake_case_ ,    tgt_lang=snake_case_ ,    )
    __a			:  Dict		    =  DataLoader(snake_case_ ,    batch_size=2 ,    collate_fn=train_dataset.collate_fn       )
    for batch in dataloader:
     assert isinstance(snake_case_ ,    snake_case_       )
     assert batch["attention_mask"].shape == batch["input_ids"].shape
     # show that articles were trimmed.
     assert batch["input_ids"].shape[1] == max_src_len
     # show that targets are the same len
     assert batch["labels"].shape[1] == max_tgt_len
     if tok_name != MBART_TINY:
      continue
     # check language codes in correct place
     __a			:  Dict		    =  shift_tokens_right(batch['''labels'''] ,    tokenizer.pad_token_id       )
     assert batch["decoder_input_ids"][0, 0].item() == tokenizer.lang_code_to_id[tgt_lang]
     assert batch["decoder_input_ids"][0, -1].item() == tokenizer.eos_token_id
     assert batch["input_ids"][0, -2].item() == tokenizer.eos_token_id
     assert batch["input_ids"][0, -1].item() == tokenizer.lang_code_to_id[src_lang]

     break  # No need to test every batch
   @parameterized.expand([BART_TINY, BERT_BASE_CASED]       )
   def 				lowerCAmelCase      (self			: Optional[Any] ,    snake_case_			: str       ):
    __a			:  Union[str, Any]		    =  AutoTokenizer.from_pretrained(snake_case_       )
    __a			:  str		    =  make_test_data_dir(tmp_dir=self.get_auto_remove_tmp_dir()       )
    __a			:  Any		    =  max(len(tokenizer.encode(snake_case_       )       ) for a in ARTICLES       )
    __a			:  Any		    =  max(len(tokenizer.encode(snake_case_       )       ) for a in SUMMARIES       )
    __a			:  Dict		    =  4
    __a			:  Optional[int]		    =  LegacySeqaSeqDataset(
        snake_case_ ,    data_dir=snake_case_ ,    type_path='''train''' ,    max_source_length=2_0 ,    max_target_length=snake_case_ ,    )
    __a			:  Optional[Any]		    =  DataLoader(snake_case_ ,    batch_size=2 ,    collate_fn=train_dataset.collate_fn       )
    for batch in dataloader:
     assert batch["attention_mask"].shape == batch["input_ids"].shape
     # show that articles were trimmed.
     assert batch["input_ids"].shape[1] == max_len_source
     assert 2_0 >= batch["input_ids"].shape[1]  # trimmed significantly
     # show that targets were truncated
     assert batch["labels"].shape[1] == trunc_target  # Truncated
     assert max_len_target > trunc_target  # Truncated
     break  # No need to test every batch
   def 				lowerCAmelCase      (self			: List[str]       ):
    __a			:  int		    =  AutoTokenizer.from_pretrained('''facebook/mbart-large-cc25'''       )

    __a			:  Any		    =  Path(make_test_data_dir(tmp_dir=self.get_auto_remove_tmp_dir()       )       )
    __a			:  Optional[int]		    =  tmp_dir.joinpath('''train.source'''       ).open().readlines()
    __a			:  List[Any]		    =  Path(make_test_data_dir(tmp_dir=self.get_auto_remove_tmp_dir()       )       )
    pack_data_dir(snake_case_ ,    snake_case_ ,    1_2_8 ,    snake_case_       )
    __a			:  Optional[Any]		    =  {x.name for x in tmp_dir.iterdir()}
    __a			:  Union[str, Any]		    =  {x.name for x in save_dir.iterdir()}
    __a			:  str		    =  save_dir.joinpath('''train.source'''       ).open().readlines()
    # orig: [' Sam ate lunch today.\n', 'Sams lunch ingredients.']
    # desired_packed: [' Sam ate lunch today.\n Sams lunch ingredients.']
    assert len(snake_case_       ) < len(snake_case_       )
    assert len(snake_case_       ) == 1
    assert len(packed_examples[0]       ) == sum(len(snake_case_       ) for x in orig_examples       )
    assert orig_paths == new_paths
   @pytest.mark.skipif(not FAIRSEQ_AVAILABLE ,    reason='''This test requires fairseq'''       )
   def 				lowerCAmelCase      (self			: Any       ):
    if not FAIRSEQ_AVAILABLE:
     return
    __a    ,	__a    ,	__a			:  Any		    =  self._get_dataset(max_len=6_4       )
    __a			:  int		    =  6_4
    __a			:  List[str]		    =  ds.make_dynamic_sampler(snake_case_ ,    required_batch_size_multiple=snake_case_       )
    __a			:  List[str]		    =  [len(snake_case_       ) for x in batch_sampler]
    assert len(set(snake_case_       )       ) > 1  # it's not dynamic batch size if every batch is the same length
    assert sum(snake_case_       ) == len(snake_case_       )  # no dropped or added examples
    __a			:  Union[str, Any]		    =  DataLoader(snake_case_ ,    batch_sampler=snake_case_ ,    collate_fn=ds.collate_fn ,    num_workers=2       )
    __a			:  Tuple		    =  []
    __a			:  Union[str, Any]		    =  []
    for batch in data_loader:
     __a			:  Any		    =  batch['''input_ids'''].shape
     __a			:  str		    =  src_shape[0]
     assert bs % required_batch_size_multiple == 0 or bs < required_batch_size_multiple
     __a			:  Optional[Any]		    =  np.product(batch['''input_ids'''].shape       )
     num_src_per_batch.append(snake_case_       )
     if num_src_tokens > (max_tokens * 1.1):
      failures.append(snake_case_       )
    assert num_src_per_batch[0] == max(snake_case_       )
    if failures:
     raise AssertionError(f"too many tokens in {len(snake_case_       )} batches"       )
   def 				lowerCAmelCase      (self			: int       ):
    __a    ,	__a    ,	__a			:  Optional[int]		    =  self._get_dataset(max_len=5_1_2       )
    __a			:  Union[str, Any]		    =  2
    __a			:  str		    =  ds.make_sortish_sampler(snake_case_ ,    shuffle=snake_case_       )

    __a			:  Tuple		    =  DataLoader(snake_case_ ,    batch_size=snake_case_ ,    collate_fn=ds.collate_fn ,    num_workers=2       )
    __a			:  Tuple		    =  DataLoader(snake_case_ ,    batch_size=snake_case_ ,    collate_fn=ds.collate_fn ,    num_workers=2 ,    sampler=snake_case_       )

    __a			:  Optional[int]		    =  tokenizer.pad_token_id

    def count_pad_tokens(snake_case_			: Union[str, Any] ,    snake_case_			: List[str]="input_ids"       ):
     return [batch[k].eq(snake_case_       ).sum().item() for batch in data_loader]

    assert sum(count_pad_tokens(snake_case_ ,    k='''labels'''       )       ) < sum(count_pad_tokens(snake_case_ ,    k='''labels'''       )       )
    assert sum(count_pad_tokens(snake_case_       )       ) < sum(count_pad_tokens(snake_case_       )       )
    assert len(snake_case_       ) == len(snake_case_       )
   def 				lowerCAmelCase      (self			: int ,    snake_case_			: int=1_0_0_0 ,    snake_case_			: Optional[Any]=1_2_8       ):
    if os.getenv('''USE_REAL_DATA''' ,    snake_case_       ):
     __a			:  Optional[int]		    =  '''examples/seq2seq/wmt_en_ro'''
     __a			:  List[Any]		    =  max_len * 2 * 6_4
     if not Path(snake_case_       ).joinpath('''train.len'''       ).exists():
      save_len_file(snake_case_ ,    snake_case_       )
    else:
     __a			:  int		    =  '''examples/seq2seq/test_data/wmt_en_ro'''
     __a			:  List[str]		    =  max_len * 4
     save_len_file(snake_case_ ,    snake_case_       )

    __a			:  str		    =  AutoTokenizer.from_pretrained(snake_case_       )
    __a			:  Optional[int]		    =  SeqaSeqDataset(
        snake_case_ ,    data_dir=snake_case_ ,    type_path='''train''' ,    max_source_length=snake_case_ ,    max_target_length=snake_case_ ,    n_obs=snake_case_ ,    )
    return ds, max_tokens, tokenizer
   def 				lowerCAmelCase      (self			: List[str]       ):
    __a    ,	__a    ,	__a			:  str		    =  self._get_dataset()
    __a			:  Optional[Any]		    =  set(DistributedSortishSampler(snake_case_ ,    2_5_6 ,    num_replicas=2 ,    rank=0 ,    add_extra_examples=snake_case_       )       )
    __a			:  Tuple		    =  set(DistributedSortishSampler(snake_case_ ,    2_5_6 ,    num_replicas=2 ,    rank=1 ,    add_extra_examples=snake_case_       )       )
    assert idsa.intersection(snake_case_       ) == set()







   @parameterized.expand(
       [
           MBART_TINY,
           MARIAN_TINY,
           T5_TINY,
           BART_TINY,
           PEGASUS_XSUM,
       ] ,    )
   def 				lowerCAmelCase      (self			: str ,    snake_case_			: Union[str, Any]       ):
    __a			:  Union[str, Any]		    =  AutoTokenizer.from_pretrained(snake_case_ ,    use_fast=snake_case_       )
    if tok_name == MBART_TINY:
     __a			:  Any		    =  SeqaSeqDataset(
         snake_case_ ,    data_dir=make_test_data_dir(tmp_dir=self.get_auto_remove_tmp_dir()       ) ,    type_path='''train''' ,    max_source_length=4 ,    max_target_length=8 ,    src_lang='''EN''' ,    tgt_lang='''FR''' ,    )
     __a			:  Tuple		    =  train_dataset.dataset_kwargs
     assert "src_lang" in kwargs and "tgt_lang" in kwargs
    else:
     __a			:  Optional[Any]		    =  SeqaSeqDataset(
         snake_case_ ,    data_dir=make_test_data_dir(tmp_dir=self.get_auto_remove_tmp_dir()       ) ,    type_path='''train''' ,    max_source_length=4 ,    max_target_length=8 ,    )
     __a			:  List[Any]		    =  train_dataset.dataset_kwargs
     assert "add_prefix_space" not in kwargs if tok_name != BART_TINY else "add_prefix_space" in kwargs
     assert len(snake_case_       ) == 1 if tok_name == BART_TINY else len(snake_case_       ) == 0
