






"""simple docstring"""
import unittest

from transformers.models.xlm_prophetnet.tokenization_xlm_prophetnet import SPIECE_UNDERLINE, XLMProphetNetTokenizer
from transformers.testing_utils import get_tests_dir, require_sentencepiece, slow
from transformers.utils import cached_property

from ...test_tokenization_common import TokenizerTesterMixin


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







@require_sentencepiece
class      UpperCamelCase_			(__A							,		unittest.TestCase	):
	__magic_name__       =							XLMProphetNetTokenizer
	__magic_name__       =							False
	__magic_name__       =							True





	def 	_SCREAMING_SNAKE_CASE ( self   :					Optional[int]		)		->     List[str]:
				super().setUp()

				# We have a SentencePiece fixture for testing
				UpperCAmelCase_	:					int     	=   XLMProphetNetTokenizer(SCREAMING_SNAKE_CASE_      ,      keep_accents=SCREAMING_SNAKE_CASE_		)
				tokenizer.save_pretrained(self.tmpdirname		)





	def 	_SCREAMING_SNAKE_CASE ( self   :					Any		)		->     Optional[Any]:
				UpperCAmelCase_	:					List[Any]     	=   "[PAD]"
				UpperCAmelCase_	:					Tuple     	=   0

				self.assertEqual(self.get_tokenizer()._convert_token_to_id(SCREAMING_SNAKE_CASE_		)      ,      SCREAMING_SNAKE_CASE_		)
				self.assertEqual(self.get_tokenizer()._convert_id_to_token(SCREAMING_SNAKE_CASE_		)      ,      SCREAMING_SNAKE_CASE_		)





	def 	_SCREAMING_SNAKE_CASE ( self   :					Optional[Any]		)		->     int:
				UpperCAmelCase_	:					Optional[int]     	=   list(self.get_tokenizer().get_vocab().keys()		)

				self.assertEqual(vocab_keys[0]      ,      "[PAD]"		)
				self.assertEqual(vocab_keys[1]      ,      "[CLS]"		)
				self.assertEqual(vocab_keys[-1]      ,      "j"		)
				self.assertEqual(len(SCREAMING_SNAKE_CASE_		)      ,      1_012		)





	def 	_SCREAMING_SNAKE_CASE ( self   :					int		)		->     int:
				self.assertEqual(self.get_tokenizer().vocab_size      ,      1_012		)





	def 	_SCREAMING_SNAKE_CASE ( self   :					Union[str, Any]		)		->     Union[str, Any]:
				UpperCAmelCase_	:					List[str]     	=   XLMProphetNetTokenizer(SCREAMING_SNAKE_CASE_      ,      keep_accents=SCREAMING_SNAKE_CASE_		)

				UpperCAmelCase_	:					Dict     	=   tokenizer.tokenize("This is a test"		)
				self.assertListEqual(SCREAMING_SNAKE_CASE_      ,      ["▁This", "▁is", "▁a", "▁t", "est"]		)

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

				UpperCAmelCase_	:					str     	=   tokenizer.tokenize("I was born in 92000, and this is falsé."		)
				self.assertListEqual(
				    SCREAMING_SNAKE_CASE_      ,      [
				        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_	:					Tuple     	=   tokenizer.convert_tokens_to_ids(SCREAMING_SNAKE_CASE_		)
				self.assertListEqual(
				    SCREAMING_SNAKE_CASE_      ,      [
				        value + tokenizer.fairseq_offset
				        for value in [8, 21, 84, 55, 24, 19, 7, -9, 602, 347, 347, 347, 3, 12, 66, 46, 72, 80, 6, -9, 4]
				    ]      ,      )

				UpperCAmelCase_	:					Dict     	=   tokenizer.convert_ids_to_tokens(SCREAMING_SNAKE_CASE_		)
				self.assertListEqual(
				    SCREAMING_SNAKE_CASE_      ,      [
				        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]",
				        ".",
				    ]      ,      )





	@cached_property
	def 	_SCREAMING_SNAKE_CASE ( self   :					Tuple		)		->     List[Any]:
				return XLMProphetNetTokenizer.from_pretrained("microsoft/xprophetnet-large-wiki100-cased"		)





	@slow
	def 	_SCREAMING_SNAKE_CASE ( self   :					Optional[int]		)		->     Union[str, Any]:
				UpperCAmelCase_	:					Any     	=   "Hello World!"
				UpperCAmelCase_	:					Dict     	=   [35_389, 6_672, 49, 2]
				self.assertListEqual(SCREAMING_SNAKE_CASE_      ,      self.big_tokenizer.encode(SCREAMING_SNAKE_CASE_		)		)





	@slow
	def 	_SCREAMING_SNAKE_CASE ( self   :					Any		)		->     List[Any]:
				# fmt: off
				UpperCAmelCase_	:					Tuple     	=   {"input_ids": [[11_073, 82_783, 18, 26, 82_783, 549, 51_540, 248, 17_209, 1_301, 217, 20, 215_186, 1_325, 147, 17_209, 1_301, 217, 20, 56_370, 53, 122_020, 20, 16_477, 27, 87_355, 4_548, 20, 4_728, 78_392, 17, 159_969, 18, 26, 24_491, 629, 15, 538, 22_704, 5_439, 15, 2_788, 24_491, 9_885, 15, 43_534, 605, 15, 814, 18_403, 33_200, 29, 15, 43_534, 24_458, 12_410, 111, 24_966, 83_669, 9_637, 144_068, 26, 850, 22_346, 27, 147, 24_966, 83_669, 83_490, 26, 39_113, 735, 27, 689, 656, 2_800, 1_339, 4_600, 53, 122_020, 115_785, 34, 816, 1_339, 46_887, 18, 147, 53_905, 1_951, 42_238, 41_170, 17_732, 834, 436, 15, 27_523, 98_733, 217, 147, 5_542, 4_981, 930, 17_347, 16, 2], [20_091, 629, 94, 82_786, 58, 490, 20, 1_528, 84, 53_905, 344, 80_592, 110_128, 18_822, 5_267, 1_306, 62, 152_537, 308, 7_997, 401, 124_427, 549, 35_442, 225, 109, 15_055, 25_748, 147, 7_119, 43_712, 34, 767, 135_366, 18, 16, 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], [592, 63_784, 119_466, 17, 147_808, 88_214, 18, 656, 81, 32, 3_296, 10_280, 16, 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, 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, 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, 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, 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, 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=SCREAMING_SNAKE_CASE_      ,      model_name="microsoft/xprophetnet-large-wiki100-cased"      ,      revision="1acad1643ddd54a44df6a1b797ada8373685d90e"      ,      )





import copy

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


__a         =   logging.get_logger(__name__)
class 					lowercase__(							UpperCAmelCase				):



	"""simple docstring"""




	a     :List[str]       	=      'encoder-decoder'
	a     :Any       	=      True
	def __init__(			self    :     List[Any]			,				**SCREAMING_SNAKE_CASE_    :     List[Any]			)			->	Optional[int]:
					super().__init__(**SCREAMING_SNAKE_CASE_			)
					assert (
					    "encoder" in kwargs and "decoder" in kwargs
					), "Config has to be initialized with encoder and decoder config"
					lowercase_	    =   kwargs.pop('''encoder'''			)
					lowercase_	    =   encoder_config.pop('''model_type'''			)
					lowercase_	    =   kwargs.pop('''decoder'''			)
					lowercase_	    =   decoder_config.pop('''model_type'''			)

					from ..auto.configuration_auto import AutoConfig

					lowercase_	    =   AutoConfig.for_model(SCREAMING_SNAKE_CASE_			,				**SCREAMING_SNAKE_CASE_			)
					lowercase_	    =   AutoConfig.for_model(SCREAMING_SNAKE_CASE_			,				**SCREAMING_SNAKE_CASE_			)
					lowercase_	    =   True
	@classmethod
	def 		_lowercase    (			cls    :     Optional[int]			,				SCREAMING_SNAKE_CASE_    :     PretrainedConfig			,				SCREAMING_SNAKE_CASE_    :     PretrainedConfig			,				**SCREAMING_SNAKE_CASE_    :     Optional[int]			)			->	PretrainedConfig:
					logger.info('''Set `config.is_decoder=True` and `config.add_cross_attention=True` for decoder_config'''			)
					lowercase_	    =   True
					lowercase_	    =   True

					return cls(encoder=encoder_config.to_dict()			,				decoder=decoder_config.to_dict()			,				**SCREAMING_SNAKE_CASE_			)




	def 		_lowercase    (			self    :     Tuple			)			->	List[Any]:
					lowercase_	    =   copy.deepcopy(self.__dict__			)
					lowercase_	    =   self.encoder.to_dict()
					lowercase_	    =   self.decoder.to_dict()
					lowercase_	    =   self.__class__.model_type
					return output




