

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


A_			:					Optional[Any]    			=     get_tests_dir('fixtures/test_sentencepiece.model')



@require_sentencepiece
class        _a		(_SCREAMING_SNAKE_CASE						,  unittest.TestCase							):


					'''simple docstring'''






					UpperCAmelCase__:  List[str]    				=			XLMProphetNetTokenizer
					UpperCAmelCase__:  str    				=			False
					UpperCAmelCase__:  List[Any]    				=			True






					def     __A     (					self     ):
						super().setUp()

						# We have a SentencePiece fixture for testing
						A__				:       Dict	  =						XLMProphetNetTokenizer(_lowercase       ,			keep_accents=_lowercase     )
						tokenizer.save_pretrained(self.tmpdirname     )






					def     __A     (					self     ):
						A__				:       Optional[int]	  =						"""[PAD]"""
						A__				:       List[str]	  =						0

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






					def     __A     (					self     ):
						A__				:       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(_lowercase     )       ,			1012     )






					def     __A     (					self     ):
						self.assertEqual(self.get_tokenizer().vocab_size       ,			1012     )






					def     __A     (					self     ):
						A__				:       Any	  =						XLMProphetNetTokenizer(_lowercase       ,			keep_accents=_lowercase     )

						A__				:       Optional[int]	  =						tokenizer.tokenize("""This is a test"""     )
						self.assertListEqual(_lowercase       ,			["""▁This""", """▁is""", """▁a""", """▁t""", """est"""]     )

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

						A__				:       Optional[int]	  =						tokenizer.tokenize("""I was born in 92000, and this is falsé."""     )
						self.assertListEqual(
						    _lowercase       ,			[
						        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__				:       List[str]	  =						tokenizer.convert_tokens_to_ids(_lowercase     )
						self.assertListEqual(
						    _lowercase       ,			[
						        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]
						    ]       ,			)

						A__				:       Union[str, Any]	  =						tokenizer.convert_ids_to_tokens(_lowercase     )
						self.assertListEqual(
						    _lowercase       ,			[
						        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     __A     (					self     ):
						return XLMProphetNetTokenizer.from_pretrained("""microsoft/xprophetnet-large-wiki100-cased"""     )






					@slow
					def     __A     (					self     ):
						A__				:       List[str]	  =						"""Hello World!"""
						A__				:       Union[str, Any]	  =						[3_5389, 6672, 49, 2]
						self.assertListEqual(_lowercase       ,			self.big_tokenizer.encode(_lowercase     )     )






					@slow
					def     __A     (					self     ):
						A__				:       Dict	  =						{"""input_ids""": [[1_1073, 8_2783, 18, 26, 8_2783, 549, 5_1540, 248, 1_7209, 1301, 217, 20, 21_5186, 1325, 147, 1_7209, 1301, 217, 20, 5_6370, 53, 12_2020, 20, 1_6477, 27, 8_7355, 4548, 20, 4728, 7_8392, 17, 15_9969, 18, 26, 2_4491, 629, 15, 538, 2_2704, 5439, 15, 2788, 2_4491, 9885, 15, 4_3534, 605, 15, 814, 1_8403, 3_3200, 29, 15, 4_3534, 2_4458, 1_2410, 111, 2_4966, 8_3669, 9637, 14_4068, 26, 850, 2_2346, 27, 147, 2_4966, 8_3669, 8_3490, 26, 3_9113, 735, 27, 689, 656, 2800, 1339, 4600, 53, 12_2020, 11_5785, 34, 816, 1339, 4_6887, 18, 147, 5_3905, 1951, 4_2238, 4_1170, 1_7732, 834, 436, 15, 2_7523, 9_8733, 217, 147, 5542, 4981, 930, 1_7347, 16, 2], [2_0091, 629, 94, 8_2786, 58, 490, 20, 1528, 84, 5_3905, 344, 8_0592, 11_0128, 1_8822, 5267, 1306, 62, 15_2537, 308, 7997, 401, 12_4427, 549, 3_5442, 225, 109, 1_5055, 2_5748, 147, 7119, 4_3712, 34, 767, 13_5366, 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, 6_3784, 11_9466, 17, 14_7808, 8_8214, 18, 656, 81, 32, 3296, 1_0280, 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=_lowercase       ,			model_name="""microsoft/xprophetnet-large-wiki100-cased"""       ,			revision="""1acad1643ddd54a44df6a1b797ada8373685d90e"""       ,			)





'''simple docstring'''



from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_flax_available,
    is_tf_available,
    is_torch_available,
)


_lowercase          =						{"""configuration_vit_mae""": ["""VIT_MAE_PRETRAINED_CONFIG_ARCHIVE_MAP""", """ViTMAEConfig"""]}

try:
						if not is_torch_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						_lowercase          =						[
						    """VIT_MAE_PRETRAINED_MODEL_ARCHIVE_LIST""",
						    """ViTMAEForPreTraining""",
						    """ViTMAELayer""",
						    """ViTMAEModel""",
						    """ViTMAEPreTrainedModel""",
						]

try:
						if not is_tf_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						_lowercase          =						[
						    """TFViTMAEForPreTraining""",
						    """TFViTMAEModel""",
						    """TFViTMAEPreTrainedModel""",
						]

if TYPE_CHECKING:
						from .configuration_vit_mae import VIT_MAE_PRETRAINED_CONFIG_ARCHIVE_MAP, ViTMAEConfig

						try:
												if not is_torch_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .modeling_vit_mae import (
												    VIT_MAE_PRETRAINED_MODEL_ARCHIVE_LIST,
												    ViTMAEForPreTraining,
												    ViTMAELayer,
												    ViTMAEModel,
												    ViTMAEPreTrainedModel,
												)

						try:
												if not is_tf_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .modeling_tf_vit_mae import TFViTMAEForPreTraining, TFViTMAEModel, TFViTMAEPreTrainedModel


else:
						import sys

						_lowercase          =						_LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)
