"""simple docstring"""


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    a__    (   _a					,					unittest.TestCase	):
   snake_case_							=      None
   snake_case_							=      BloomTokenizerFast
   snake_case_							=      BloomTokenizerFast
   snake_case_							=      True
   snake_case_							=      False
   snake_case_							=      "tokenizer_file"
   snake_case_							=      {"bos_token": "<s>", "eos_token": "</s>", "unk_token": "<unk>", "pad_token": "<pad>"}


   def 	snake_case__	(     self  ):
        '''simple docstring'''



        super().setUp()
        lowercase__				 =							BloomTokenizerFast.from_pretrained("bigscience/tokenizer"  )
        tokenizer.save_pretrained(self.tmpdirname  )


   def 	snake_case__	(     self,				**_UpperCAmelCase  ):
        '''simple docstring'''



        kwargs.update(self.special_tokens_map  )
        return BloomTokenizerFast.from_pretrained(self.tmpdirname,				**_UpperCAmelCase  )


   def 	snake_case__	(     self  ):
        '''simple docstring'''



        lowercase__				 =							self.get_rust_tokenizer()

        lowercase__				 =							["The quick brown fox</s>", "jumps over the lazy dog</s>"]
        lowercase__				 =							[[2175, 2_3714, 7_3173, 14_4252, 2], [77, 13_2619, 3478, 368, 10_9586, 3_5433, 2]]

        lowercase__				 =							tokenizer.batch_encode_plus(_UpperCAmelCase  )["input_ids"]
        self.assertListEqual(_UpperCAmelCase,				_UpperCAmelCase  )

        lowercase__				 =							tokenizer.batch_decode(_UpperCAmelCase  )
        self.assertListEqual(_UpperCAmelCase,				_UpperCAmelCase  )


   def 	snake_case__	(     self,				_UpperCAmelCase=6  ):
        '''simple docstring'''



        for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
             with self.subTest(F'''{tokenizer.__class__.__name__} ({pretrained_name})'''  ):
                  lowercase__				 =							self.rust_tokenizer_class.from_pretrained(_UpperCAmelCase,				**_UpperCAmelCase  )
                  # tokenizer_r.pad_token = None # Hotfixing padding = None
                  # Simple input
                  lowercase__				 =							"This is a simple input"
                  lowercase__				 =							["This is a simple input 1", "This is a simple input 2"]
                  lowercase__				 =							("This is a simple input", "This is a pair")
                  lowercase__				 =							[
                      ("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(_UpperCAmelCase,				max_length=_UpperCAmelCase  )
                       tokenizer_r.encode_plus(_UpperCAmelCase,				max_length=_UpperCAmelCase  )

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

                  lowercase__				 =							None  # Hotfixing padding = None
                  self.assertRaises(_UpperCAmelCase,				tokenizer_r.encode,				_UpperCAmelCase,				max_length=_UpperCAmelCase,				padding="max_length"  )

                  # Simple input
                  self.assertRaises(_UpperCAmelCase,				tokenizer_r.encode_plus,				_UpperCAmelCase,				max_length=_UpperCAmelCase,				padding="max_length"  )

                  # Simple input
                  self.assertRaises(
                      _UpperCAmelCase,				tokenizer_r.batch_encode_plus,				_UpperCAmelCase,				max_length=_UpperCAmelCase,				padding="max_length",				)

                  # Pair input
                  self.assertRaises(_UpperCAmelCase,				tokenizer_r.encode,				_UpperCAmelCase,				max_length=_UpperCAmelCase,				padding="max_length"  )

                  # Pair input
                  self.assertRaises(_UpperCAmelCase,				tokenizer_r.encode_plus,				_UpperCAmelCase,				max_length=_UpperCAmelCase,				padding="max_length"  )

                  # Pair input
                  self.assertRaises(
                      _UpperCAmelCase,				tokenizer_r.batch_encode_plus,				_UpperCAmelCase,				max_length=_UpperCAmelCase,				padding="max_length",				)


   def 	snake_case__	(     self  ):
        '''simple docstring'''



        lowercase__				 =							self.get_rust_tokenizer()
        lowercase__				 =							load_dataset("xnli",				"all_languages",				split="test",				streaming=_UpperCAmelCase  )

        lowercase__				 =							next(iter(_UpperCAmelCase  )  )["premise"]  # pick up one data
        lowercase__				 =							list(sample_data.values()  )

        lowercase__				 =							list(map(tokenizer.encode,				_UpperCAmelCase  )  )
        lowercase__				 =							[tokenizer.decode(_UpperCAmelCase,				clean_up_tokenization_spaces=_UpperCAmelCase  ) for x in output_tokens]
        self.assertListEqual(_UpperCAmelCase,				_UpperCAmelCase  )


   def 	snake_case__	(     self  ):
        '''simple docstring'''



        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  )





"""simple docstring"""


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


lowerCAmelCase_:					List[Any]     =					logging.get_logger(__name__)

lowerCAmelCase_:					int     =					{
    "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    a__    (   _a	):
   snake_case_							=      "markuplm"


   def __init__(     self,				_UpperCAmelCase=3_0522,				_UpperCAmelCase=768,				_UpperCAmelCase=12,				_UpperCAmelCase=12,				_UpperCAmelCase=3072,				_UpperCAmelCase="gelu",				_UpperCAmelCase=0.1,				_UpperCAmelCase=0.1,				_UpperCAmelCase=512,				_UpperCAmelCase=2,				_UpperCAmelCase=0.02,				_UpperCAmelCase=1E-12,				_UpperCAmelCase=0,				_UpperCAmelCase=0,				_UpperCAmelCase=2,				_UpperCAmelCase=256,				_UpperCAmelCase=1024,				_UpperCAmelCase=216,				_UpperCAmelCase=1001,				_UpperCAmelCase=32,				_UpperCAmelCase=50,				_UpperCAmelCase="absolute",				_UpperCAmelCase=True,				_UpperCAmelCase=None,				**_UpperCAmelCase,				):
        '''simple docstring'''



        super().__init__(
            pad_token_id=_UpperCAmelCase,				bos_token_id=_UpperCAmelCase,				eos_token_id=_UpperCAmelCase,				**_UpperCAmelCase,				)
        lowercase__				 =							vocab_size
        lowercase__				 =							hidden_size
        lowercase__				 =							num_hidden_layers
        lowercase__				 =							num_attention_heads
        lowercase__				 =							hidden_act
        lowercase__				 =							intermediate_size
        lowercase__				 =							hidden_dropout_prob
        lowercase__				 =							attention_probs_dropout_prob
        lowercase__				 =							max_position_embeddings
        lowercase__				 =							type_vocab_size
        lowercase__				 =							initializer_range
        lowercase__				 =							layer_norm_eps
        lowercase__				 =							position_embedding_type
        lowercase__				 =							use_cache
        lowercase__				 =							classifier_dropout
        # additional properties
        lowercase__				 =							max_depth
        lowercase__				 =							max_xpath_tag_unit_embeddings
        lowercase__				 =							max_xpath_subs_unit_embeddings
        lowercase__				 =							tag_pad_id
        lowercase__				 =							subs_pad_id
        lowercase__				 =							xpath_unit_hidden_size




