import os
import unittest

from transformers import LxmertTokenizer, LxmertTokenizerFast
from transformers.models.bert.tokenization_bert import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers

from ...test_tokenization_common import TokenizerTesterMixin



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







 """simple docstring"""






 lowerCamelCase	:str    			=		LxmertTokenizer
 lowerCamelCase	:Union[str, Any]    			=		LxmertTokenizerFast
 lowerCamelCase	:int    			=		True
 lowerCamelCase	:Optional[int]    			=		True



 def      UpperCAmelCase							(					self							)  ->					Optional[int]:
        super().setUp()

        _A        =  [
            """[UNK]""",
            """[CLS]""",
            """[SEP]""",
            """want""",
            """##want""",
            """##ed""",
            """wa""",
            """un""",
            """runn""",
            """##ing""",
            """,""",
            """low""",
            """lowest""",
        ]
        _A        =  os.path.join(self.tmpdirname		,				VOCAB_FILES_NAMES["""vocab_file"""]							)
        with open(self.vocab_file		,				"""w"""		,				encoding="""utf-8"""							) as vocab_writer:
               vocab_writer.write("""""".join([x + """\n""" for x in vocab_tokens]							)							)



 def      UpperCAmelCase							(					self		,				lowerCAmelCase_							)  ->					Tuple:
        _A        =  """UNwant\u00E9d,running"""
        _A        =  """unwanted, running"""
        return input_text, output_text



 def      UpperCAmelCase							(					self							)  ->					Optional[int]:
        _A        =  self.tokenizer_class(self.vocab_file							)

        _A        =  tokenizer.tokenize("""UNwant\u00E9d,running"""							)
        self.assertListEqual(lowerCAmelCase_		,				["""un""", """##want""", """##ed""", """,""", """runn""", """##ing"""]							)
        self.assertListEqual(tokenizer.convert_tokens_to_ids(lowerCAmelCase_							)		,				[7, 4, 5, 10, 8, 9]							)



 def      UpperCAmelCase							(					self							)  ->					str:
        if not self.test_rust_tokenizer:
               return

        _A        =  self.get_tokenizer()
        _A        =  self.get_rust_tokenizer()

        _A        =  """I was born in 92000, and this is falsé."""

        _A        =  tokenizer.tokenize(lowerCAmelCase_							)
        _A        =  rust_tokenizer.tokenize(lowerCAmelCase_							)
        self.assertListEqual(lowerCAmelCase_		,				lowerCAmelCase_							)

        _A        =  tokenizer.encode(lowerCAmelCase_		,				add_special_tokens=lowerCAmelCase_							)
        _A        =  rust_tokenizer.encode(lowerCAmelCase_		,				add_special_tokens=lowerCAmelCase_							)
        self.assertListEqual(lowerCAmelCase_		,				lowerCAmelCase_							)

        _A        =  self.get_rust_tokenizer()
        _A        =  tokenizer.encode(lowerCAmelCase_							)
        _A        =  rust_tokenizer.encode(lowerCAmelCase_							)
        self.assertListEqual(lowerCAmelCase_		,				lowerCAmelCase_							)





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


_SCREAMING_SNAKE_CASE										=						logging.get_logger(__name__)

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



class 				a							(			__lowerCAmelCase       ):







 """simple docstring"""






 lowerCamelCase	:Any    			=		'''biogpt'''



 def __init__(					self		,				lowerCAmelCase_=4_23_84		,				lowerCAmelCase_=10_24		,				lowerCAmelCase_=24		,				lowerCAmelCase_=16		,				lowerCAmelCase_=40_96		,				lowerCAmelCase_="gelu"		,				lowerCAmelCase_=0.1		,				lowerCAmelCase_=0.1		,				lowerCAmelCase_=10_24		,				lowerCAmelCase_=0.02		,				lowerCAmelCase_=1E-12		,				lowerCAmelCase_=True		,				lowerCAmelCase_=True		,				lowerCAmelCase_=0.0		,				lowerCAmelCase_=0.0		,				lowerCAmelCase_=1		,				lowerCAmelCase_=0		,				lowerCAmelCase_=2		,				**lowerCAmelCase_		,				)  ->					Tuple:
        _A        =  vocab_size
        _A        =  max_position_embeddings
        _A        =  hidden_size
        _A        =  num_hidden_layers
        _A        =  num_attention_heads
        _A        =  intermediate_size
        _A        =  hidden_act
        _A        =  hidden_dropout_prob
        _A        =  attention_probs_dropout_prob
        _A        =  initializer_range
        _A        =  layer_norm_eps
        _A        =  scale_embedding
        _A        =  use_cache
        _A        =  layerdrop
        _A        =  activation_dropout
        super().__init__(pad_token_id=lowerCAmelCase_		,				bos_token_id=lowerCAmelCase_		,				eos_token_id=lowerCAmelCase_		,				**lowerCAmelCase_							)




