


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


snake_case				:    List[str]       				=     get_tests_dir('''fixtures/test_sentencepiece.model''')







@require_sentencepiece
class 		_snake_case  (      _snake_case						,    unittest.TestCase							):
 SCREAMING_SNAKE_CASE__      =       XLMProphetNetTokenizer
 SCREAMING_SNAKE_CASE__      =       False
 SCREAMING_SNAKE_CASE__      =       True




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

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




 def        SCREAMING_SNAKE_CASE__				(		self    ):
       a						:Optional[int] 							=       '''[PAD]'''
       a						:Tuple 							=       0

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




 def        SCREAMING_SNAKE_CASE__				(		self    ):
       a						:Optional[Any] 							=       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(_lowerCamelCase    )					,  1012    )




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




 def        SCREAMING_SNAKE_CASE__				(		self    ):
       a						:Tuple 							=       XLMProphetNetTokenizer(_lowerCamelCase					,  keep_accents=_lowerCamelCase    )

       a						:List[str] 							=       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 [285, 46, 10, 170, 382]]					,  )

       a						:Optional[Any] 							=       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						:str 							=       tokenizer.convert_tokens_to_ids(_lowerCamelCase    )
       self.assertListEqual(
           _lowerCamelCase					,  [
               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						:List[Any] 							=       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]''',
               '''.''',
           ]					,  )




 @cached_property
 def        SCREAMING_SNAKE_CASE__				(		self    ):
       return XLMProphetNetTokenizer.from_pretrained('''microsoft/xprophetnet-large-wiki100-cased'''    )




 @slow
 def        SCREAMING_SNAKE_CASE__				(		self    ):
       a						:List[Any] 							=       '''Hello World!'''
       a						:str 							=       [3_5389, 6672, 49, 2]
       self.assertListEqual(_lowerCamelCase					,  self.big_tokenizer.encode(_lowerCamelCase    )    )




 @slow
 def        SCREAMING_SNAKE_CASE__				(		self    ):
       # fmt: off
       a						:List[str] 							=       {'''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=_lowerCamelCase					,  model_name='''microsoft/xprophetnet-large-wiki100-cased'''					,  revision='''1acad1643ddd54a44df6a1b797ada8373685d90e'''					,  )







"""simple docstring"""





from collections import OrderedDict
from typing import Mapping

from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig


_a		       =							{
    'albert-base-v1': 'https://huggingface.co/albert-base-v1/resolve/main/config.json',
    'albert-large-v1': 'https://huggingface.co/albert-large-v1/resolve/main/config.json',
    'albert-xlarge-v1': 'https://huggingface.co/albert-xlarge-v1/resolve/main/config.json',
    'albert-xxlarge-v1': 'https://huggingface.co/albert-xxlarge-v1/resolve/main/config.json',
    'albert-base-v2': 'https://huggingface.co/albert-base-v2/resolve/main/config.json',
    'albert-large-v2': 'https://huggingface.co/albert-large-v2/resolve/main/config.json',
    'albert-xlarge-v2': 'https://huggingface.co/albert-xlarge-v2/resolve/main/config.json',
    'albert-xxlarge-v2': 'https://huggingface.co/albert-xxlarge-v2/resolve/main/config.json',
}


class A_	(lowercase__      ):




  '''simple docstring'''
  SCREAMING_SNAKE_CASE__			:						Optional[Any]       =		"""albert"""







  def __init__(		self				,   lowercase_=3_0000				,   lowercase_=128				,   lowercase_=4096				,   lowercase_=12				,   lowercase_=1				,   lowercase_=64				,   lowercase_=1_6384				,   lowercase_=1				,   lowercase_="gelu_new"				,   lowercase_=0				,   lowercase_=0				,   lowercase_=512				,   lowercase_=2				,   lowercase_=0.02				,   lowercase_=1E-1_2				,   lowercase_=0.1				,   lowercase_="absolute"				,   lowercase_=0				,   lowercase_=2				,   lowercase_=3				,   **lowercase_				,   ):

     """simple docstring"""
     super().__init__(pad_token_id=lowercase_				,   bos_token_id=lowercase_				,   eos_token_id=lowercase_				,   **lowercase_  )

     UpperCAmelCase_					:					int			     =    vocab_size
     UpperCAmelCase_					:					Optional[int]			     =    embedding_size
     UpperCAmelCase_					:					List[str]			     =    hidden_size
     UpperCAmelCase_					:					Optional[int]			     =    num_hidden_layers
     UpperCAmelCase_					:					Union[str, Any]			     =    num_hidden_groups
     UpperCAmelCase_					:					Dict			     =    num_attention_heads
     UpperCAmelCase_					:					Any			     =    inner_group_num
     UpperCAmelCase_					:					Union[str, Any]			     =    hidden_act
     UpperCAmelCase_					:					Union[str, Any]			     =    intermediate_size
     UpperCAmelCase_					:					List[str]			     =    hidden_dropout_prob
     UpperCAmelCase_					:					Union[str, Any]			     =    attention_probs_dropout_prob
     UpperCAmelCase_					:					Optional[Any]			     =    max_position_embeddings
     UpperCAmelCase_					:					Any			     =    type_vocab_size
     UpperCAmelCase_					:					List[str]			     =    initializer_range
     UpperCAmelCase_					:					Optional[int]			     =    layer_norm_eps
     UpperCAmelCase_					:					List[Any]			     =    classifier_dropout_prob
     UpperCAmelCase_					:					Tuple			     =    position_embedding_type




class A_	(lowercase__      ):




  '''simple docstring'''







  @property
  def        UpperCamelCase__					(		self  ):

     """simple docstring"""
     if self.task == "multiple-choice":
        UpperCAmelCase_					:					int			     =    {0: "batch", 1: "choice", 2: "sequence"}
     else:
        UpperCAmelCase_					:					Optional[Any]			     =    {0: "batch", 1: "sequence"}
     return OrderedDict(
         [
             ("input_ids", dynamic_axis),
             ("attention_mask", dynamic_axis),
             ("token_type_ids", dynamic_axis),
         ]  )


