
"""simple docstring"""





import os
import unittest

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

from ...test_tokenization_common import TokenizerTesterMixin






class    _UpperCAmelCase(   lowerCamelCase				,					unittest.TestCase     ):
		lowercase__      =				PhobertTokenizer
		lowercase__      =				False



		def 						UpperCAmelCase							( self)	->	str:






							'''simple docstring'''
							super().setUp()

							# Adapted from Sennrich et al. 2015 and https://github.com/rsennrich/subword-nmt
							__UpperCamelCase										=  ['''T@@''', '''i''', '''I''', '''R@@''', '''r''', '''e@@''']
							__UpperCamelCase										=  dict(zip(__a    ,		range(len(__a))))
							__UpperCamelCase										=  ['''#version: 0.2''', '''l à</w>''']
							__UpperCamelCase										=  {'''unk_token''': '''<unk>'''}

							__UpperCamelCase										=  os.path.join(self.tmpdirname    ,		VOCAB_FILES_NAMES['''vocab_file'''])
							__UpperCamelCase										=  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(__a))



		def 						UpperCAmelCase							( self    ,		**__a)	->	Optional[int]:






							'''simple docstring'''
							kwargs.update(self.special_tokens_map)
							return PhobertTokenizer.from_pretrained(self.tmpdirname    ,		**__a)



		def 						UpperCAmelCase							( self    ,		__a)	->	Optional[Any]:






							'''simple docstring'''
							__UpperCamelCase										=  '''Tôi là VinAI Research'''
							__UpperCamelCase										=  '''T<unk> i <unk> <unk> <unk> <unk> <unk> <unk> I Re<unk> e<unk> <unk> <unk> <unk>'''
							return input_text, output_text




		def 						UpperCAmelCase							( self)	->	Union[str, Any]:






							'''simple docstring'''
							__UpperCamelCase										=  PhobertTokenizer(self.vocab_file    ,		self.merges_file    ,		**self.special_tokens_map)
							__UpperCamelCase										=  '''Tôi là VinAI Research'''
							__UpperCamelCase										=  '''T@@ ô@@ i l@@ à V@@ i@@ n@@ A@@ I R@@ e@@ s@@ e@@ a@@ r@@ c@@ h'''.split()
							__UpperCamelCase										=  tokenizer.tokenize(__a)
							print(__a)
							self.assertListEqual(__a    ,		__a)

							__UpperCamelCase										=  tokens + [tokenizer.unk_token]

							__UpperCamelCase										=  [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(__a)    ,		__a)








"""simple docstring"""





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


_a														=		logging.get_logger(__name__)

_a														=		{
    """microsoft/biogpt""": """https://huggingface.co/microsoft/biogpt/resolve/main/config.json""",
    # See all BioGPT models at https://huggingface.co/models?filter=biogpt
}






class    _UpperCAmelCase(   lowerCamelCase     ):
		lowercase__      =				'biogpt'



		def __init__( self    ,		__a=4_23_84    ,		__a=10_24    ,		__a=24    ,		__a=16    ,		__a=40_96    ,		__a="gelu"    ,		__a=0.1    ,		__a=0.1    ,		__a=10_24    ,		__a=0.02    ,		__a=1e-12    ,		__a=True    ,		__a=True    ,		__a=0.0    ,		__a=0.0    ,		__a=1    ,		__a=0    ,		__a=2    ,		**__a    ,		)	->	Dict:






							'''simple docstring'''
							_UpperCamelCase										=  vocab_size
							_UpperCamelCase										=  max_position_embeddings
							_UpperCamelCase										=  hidden_size
							_UpperCamelCase										=  num_hidden_layers
							_UpperCamelCase										=  num_attention_heads
							_UpperCamelCase										=  intermediate_size
							_UpperCamelCase										=  hidden_act
							_UpperCamelCase										=  hidden_dropout_prob
							_UpperCamelCase										=  attention_probs_dropout_prob
							_UpperCamelCase										=  initializer_range
							_UpperCamelCase										=  layer_norm_eps
							_UpperCamelCase										=  scale_embedding
							_UpperCamelCase										=  use_cache
							_UpperCamelCase										=  layerdrop
							_UpperCamelCase										=  activation_dropout
							super().__init__(pad_token_id=__a    ,		bos_token_id=__a    ,		eos_token_id=__a    ,		**__a)






