


"""simple docstring"""



import os
import unittest

from transformers.models.phobert.tokenization_phobert import VOCAB_FILES_NAMES, PhobertTokenizer

from ...test_tokenization_common import TokenizerTesterMixin







class _lowerCAmelCase       (   SCREAMING_SNAKE_CASE__					,							unittest.TestCase			):
   __UpperCAmelCase				: Optional[int]													=						PhobertTokenizer
   __UpperCAmelCase				: int													=						False







   def 				lowerCamelCase	(			self		)			->	Any:

       '''simple docstring'''




       super().setUp()

       # Adapted from Sennrich et al. 2015 and https://github.com/rsennrich/subword-nmt
       snake_case					:   Optional[Any]         =					["T@@", "i", "I", "R@@", "r", "e@@"]
       snake_case					:   Dict         =					dict(zip(snake_case__		,			range(len(snake_case__		)		)		)		)
       snake_case					:   Tuple         =					["#version: 0.2", "l à</w>"]
       snake_case					:   Union[str, Any]         =					{"unk_token": "<unk>"}

       snake_case					:   Optional[Any]         =					os.path.join(self.tmpdirname		,			VOCAB_FILES_NAMES["vocab_file"]		)
       snake_case					:   str         =					os.path.join(self.tmpdirname		,			VOCAB_FILES_NAMES["merges_file"]		)

       with open(self.vocab_file		,			"w"		,			encoding="utf-8"		) as fp:
           for token in vocab_tokens:
               fp.write(F'{token} {vocab_tokens[token]}\n'		)
       with open(self.merges_file		,			"w"		,			encoding="utf-8"		) as fp:
           fp.write("\n".join(snake_case__		)		)







   def 				lowerCamelCase	(			self		,			**UpperCamelCase__		)			->	int:

       '''simple docstring'''




       kwargs.update(self.special_tokens_map		)
       return PhobertTokenizer.from_pretrained(self.tmpdirname		,			**snake_case__		)







   def 				lowerCamelCase	(			self		,			UpperCamelCase__		)			->	Any:

       '''simple docstring'''




       snake_case					:   Optional[Any]         =					"Tôi là VinAI Research"
       snake_case					:   Union[str, Any]         =					"T<unk> i <unk> <unk> <unk> <unk> <unk> <unk> I Re<unk> e<unk> <unk> <unk> <unk>"
       return input_text, output_text







   def 				lowerCamelCase	(			self		)			->	Any:

       '''simple docstring'''




       snake_case					:   List[Any]         =					PhobertTokenizer(self.vocab_file		,			self.merges_file		,			**self.special_tokens_map		)
       snake_case					:   Dict         =					"Tôi là VinAI Research"
       snake_case					:   Optional[int]         =					"T@@ ô@@ i l@@ à V@@ i@@ n@@ A@@ I R@@ e@@ s@@ e@@ a@@ r@@ c@@ h".split()
       snake_case					:   Dict         =					tokenizer.tokenize(snake_case__		)
       print(snake_case__		)
       self.assertListEqual(snake_case__		,			snake_case__		)

       snake_case					:   Union[str, Any]         =					tokens + [tokenizer.unk_token]

       snake_case					:   Tuple         =					[4, 3, 5, 3, 3, 3, 3, 3, 3, 6, 7, 9, 3, 9, 3, 3, 3, 3, 3]
       self.assertListEqual(tokenizer.convert_tokens_to_ids(snake_case__		)		,			snake_case__		)









"""simple docstring"""



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


__snake_case         =					logging.get_logger(__name__)

__snake_case         =					{
    """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       (   snake_case_			):
   __UpperCAmelCase				: Tuple													=						'''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__		,			)			->	Any:

       '''simple docstring'''




       super().__init__(
           pad_token_id=UpperCamelCase__		,			bos_token_id=UpperCamelCase__		,			eos_token_id=UpperCamelCase__		,			**UpperCamelCase__		,			)
       snake_case					:   List[str]         =					vocab_size
       snake_case					:   Optional[int]         =					hidden_size
       snake_case					:   List[str]         =					num_hidden_layers
       snake_case					:   Union[str, Any]         =					num_attention_heads
       snake_case					:   Dict         =					hidden_act
       snake_case					:   Tuple         =					intermediate_size
       snake_case					:   int         =					hidden_dropout_prob
       snake_case					:   Tuple         =					attention_probs_dropout_prob
       snake_case					:   Dict         =					max_position_embeddings
       snake_case					:   Optional[Any]         =					type_vocab_size
       snake_case					:   Any         =					initializer_range
       snake_case					:   Union[str, Any]         =					layer_norm_eps
       snake_case					:   List[str]         =					position_embedding_type
       snake_case					:   Optional[Any]         =					use_cache
       snake_case					:   str         =					classifier_dropout
       # additional properties
       snake_case					:   Optional[int]         =					max_depth
       snake_case					:   Optional[int]         =					max_xpath_tag_unit_embeddings
       snake_case					:   str         =					max_xpath_subs_unit_embeddings
       snake_case					:   int         =					tag_pad_id
       snake_case					:   Dict         =					subs_pad_id
       snake_case					:   List[str]         =					xpath_unit_hidden_size





