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


__lowerCAmelCase					:			Tuple			      =		logging.get_logger(__name__)

__lowerCAmelCase					:			Tuple			      =		{
    "microsoft/markuplm-base": "https://huggingface.co/microsoft/markuplm-base/resolve/main/config.json",
    "microsoft/markuplm-large": "https://huggingface.co/microsoft/markuplm-large/resolve/main/config.json",
}


class 						__lowerCAmelCase	(	lowerCAmelCase_      ):



      """simple docstring"""







      A__	:			List[Any]        =    '''markuplm'''




      def __init__(      self		:       Optional[int]				,       _snake_case		:       Optional[int]=3_0522				,       _snake_case		:       List[str]=768				,       _snake_case		:       Optional[int]=12				,       _snake_case		:       Tuple=12				,       _snake_case		:       str=3072				,       _snake_case		:       Union[str, Any]="gelu"				,       _snake_case		:       Any=0.1				,       _snake_case		:       Optional[Any]=0.1				,       _snake_case		:       Optional[Any]=512				,       _snake_case		:       str=2				,       _snake_case		:       List[str]=0.02				,       _snake_case		:       str=1E-1_2				,       _snake_case		:       Optional[Any]=0				,       _snake_case		:       Tuple=0				,       _snake_case		:       List[str]=2				,       _snake_case		:       Tuple=256				,       _snake_case		:       Optional[int]=1024				,       _snake_case		:       Optional[Any]=216				,       _snake_case		:       str=1001				,       _snake_case		:       int=32				,       _snake_case		:       int=50				,       _snake_case		:       Optional[Any]="absolute"				,       _snake_case		:       List[Any]=True				,       _snake_case		:       Dict=None				,       **_snake_case		:       List[Any]				,       ):
          super().__init__(
              pad_token_id=_snake_case				,       bos_token_id=_snake_case				,       eos_token_id=_snake_case				,       **_snake_case				,       )
          __lowercase		:			Any	    =       vocab_size
          __lowercase		:			List[str]	    =       hidden_size
          __lowercase		:			Union[str, Any]	    =       num_hidden_layers
          __lowercase		:			List[str]	    =       num_attention_heads
          __lowercase		:			Optional[Any]	    =       hidden_act
          __lowercase		:			Dict	    =       intermediate_size
          __lowercase		:			int	    =       hidden_dropout_prob
          __lowercase		:			Dict	    =       attention_probs_dropout_prob
          __lowercase		:			str	    =       max_position_embeddings
          __lowercase		:			List[Any]	    =       type_vocab_size
          __lowercase		:			int	    =       initializer_range
          __lowercase		:			List[Any]	    =       layer_norm_eps
          __lowercase		:			List[Any]	    =       position_embedding_type
          __lowercase		:			Optional[Any]	    =       use_cache
          __lowercase		:			Optional[Any]	    =       classifier_dropout
          # additional properties
          __lowercase		:			int	    =       max_depth
          __lowercase		:			Any	    =       max_xpath_tag_unit_embeddings
          __lowercase		:			str	    =       max_xpath_subs_unit_embeddings
          __lowercase		:			List[str]	    =       tag_pad_id
          __lowercase		:			Union[str, Any]	    =       subs_pad_id
          __lowercase		:			List[Any]	    =       xpath_unit_hidden_size


import unittest

from datasets import load_dataset

from transformers import BloomTokenizerFast
from transformers.testing_utils import require_tokenizers

from ...test_tokenization_common import TokenizerTesterMixin


@require_tokenizers
class 						__lowerCAmelCase	(	lowerCAmelCase_ , unittest.TestCase      ):



      """simple docstring"""







      A__	:			Dict        =    None
      A__	:			Any        =    BloomTokenizerFast
      A__	:			Optional[Any]        =    BloomTokenizerFast
      A__	:			List[Any]        =    True
      A__	:			int        =    False
      A__	:			Any        =    '''tokenizer_file'''
      A__	:			Optional[int]        =    {'''bos_token''': '''<s>''', '''eos_token''': '''</s>''', '''unk_token''': '''<unk>''', '''pad_token''': '''<pad>'''}




      def 		snake_case_			(      self		:       Any				):
          super().setUp()
          __lowercase		:			int	    =       BloomTokenizerFast.from_pretrained('''bigscience/tokenizer'''				)
          tokenizer.save_pretrained(self.tmpdirname				)




      def 		snake_case_			(      self		:       Dict				,       **_snake_case		:       Any				):
          kwargs.update(self.special_tokens_map				)
          return BloomTokenizerFast.from_pretrained(self.tmpdirname				,       **_snake_case				)




      def 		snake_case_			(      self		:       Any				):
          __lowercase		:			Dict	    =       self.get_rust_tokenizer()

          __lowercase		:			Optional[int]	    =       ['''The quick brown fox</s>''', '''jumps over the lazy dog</s>''']
          __lowercase		:			Union[str, Any]	    =       [[2175, 2_3714, 7_3173, 14_4252, 2], [77, 13_2619, 3478, 368, 10_9586, 3_5433, 2]]

          __lowercase		:			Optional[int]	    =       tokenizer.batch_encode_plus(_snake_case				)['''input_ids''']
          self.assertListEqual(_snake_case				,       _snake_case				)

          __lowercase		:			List[Any]	    =       tokenizer.batch_decode(_snake_case				)
          self.assertListEqual(_snake_case				,       _snake_case				)




      def 		snake_case_			(      self		:       str				,       _snake_case		:       int=6				):
          for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
              with self.subTest(F'{tokenizer.__class__.__name__} ({pretrained_name})'				):
                  __lowercase		:			Dict	    =       self.rust_tokenizer_class.from_pretrained(_snake_case				,       **_snake_case				)
                  # tokenizer_r.pad_token = None # Hotfixing padding = None
                  # Simple input
                  __lowercase		:			List[Any]	    =       '''This is a simple input'''
                  __lowercase		:			List[str]	    =       ['''This is a simple input 1''', '''This is a simple input 2''']
                  __lowercase		:			Optional[Any]	    =       ('''This is a simple input''', '''This is a pair''')
                  __lowercase		:			Any	    =       [
                      ('''This is a simple input 1''', '''This is a simple input 2'''),
                      ('''This is a simple pair 1''', '''This is a simple pair 2'''),
                  ]

                  # Simple input tests
                  try:
                      tokenizer_r.encode(_snake_case				,       max_length=_snake_case				)
                      tokenizer_r.encode_plus(_snake_case				,       max_length=_snake_case				)

                      tokenizer_r.batch_encode_plus(_snake_case				,       max_length=_snake_case				)
                      tokenizer_r.encode(_snake_case				,       max_length=_snake_case				)
                      tokenizer_r.batch_encode_plus(_snake_case				,       max_length=_snake_case				)
                  except ValueError:
                      self.fail('''Bloom Tokenizer should be able to deal with padding'''				)

                  __lowercase		:			Dict	    =       None  # Hotfixing padding = None
                  self.assertRaises(_snake_case				,       tokenizer_r.encode				,       _snake_case				,       max_length=_snake_case				,       padding='''max_length'''				)

                  # Simple input
                  self.assertRaises(_snake_case				,       tokenizer_r.encode_plus				,       _snake_case				,       max_length=_snake_case				,       padding='''max_length'''				)

                  # Simple input
                  self.assertRaises(
                      _snake_case				,       tokenizer_r.batch_encode_plus				,       _snake_case				,       max_length=_snake_case				,       padding='''max_length'''				,       )

                  # Pair input
                  self.assertRaises(_snake_case				,       tokenizer_r.encode				,       _snake_case				,       max_length=_snake_case				,       padding='''max_length'''				)

                  # Pair input
                  self.assertRaises(_snake_case				,       tokenizer_r.encode_plus				,       _snake_case				,       max_length=_snake_case				,       padding='''max_length'''				)

                  # Pair input
                  self.assertRaises(
                      _snake_case				,       tokenizer_r.batch_encode_plus				,       _snake_case				,       max_length=_snake_case				,       padding='''max_length'''				,       )




      def 		snake_case_			(      self		:       Optional[int]				):
          __lowercase		:			List[Any]	    =       self.get_rust_tokenizer()
          __lowercase		:			int	    =       load_dataset('''xnli'''				,       '''all_languages'''				,       split='''test'''				,       streaming=_snake_case				)

          __lowercase		:			Optional[Any]	    =       next(iter(_snake_case				)				)['''premise''']  # pick up one data
          __lowercase		:			List[str]	    =       list(sample_data.values()				)

          __lowercase		:			List[str]	    =       list(map(tokenizer.encode				,       _snake_case				)				)
          __lowercase		:			Tuple	    =       [tokenizer.decode(_snake_case				,       clean_up_tokenization_spaces=_snake_case				) for x in output_tokens]
          self.assertListEqual(_snake_case				,       _snake_case				)




      def 		snake_case_			(      self		:       List[Any]				):
          # The test has to be overriden because BLOOM uses ALiBi positional embeddings that does not have
          # any sequence length constraints. This test of the parent class will fail since it relies on the
          # maximum sequence length of the positoonal embeddings.
          self.assertGreaterEqual(len(self.tokenizer_class.pretrained_vocab_files_map				)				,       1				)
          self.assertGreaterEqual(len(list(self.tokenizer_class.pretrained_vocab_files_map.values()				)[0]				)				,       1				)


