





import json
import os
import unittest

from transformers.models.biogpt.tokenization_biogpt import VOCAB_FILES_NAMES, BioGptTokenizer
from transformers.testing_utils import slow

from ...test_tokenization_common import TokenizerTesterMixin



class        _SCREAMING_SNAKE_CASE						(     __SCREAMING_SNAKE_CASE   ,							unittest.TestCase   ):







 '''simple docstring'''
 lowercase_		=      BioGptTokenizer
 lowercase_		=      False

 def 							SCREAMING_SNAKE_CASE_ (self    :       Optional[Any])	->str:



   '''simple docstring'''



   super().setUp()

   # Adapted from Sennrich et al. 2015 and https://github.com/rsennrich/subword-nmt
   lowerCamelCase__:				str        =[
       "l",
       "o",
       "w",
       "e",
       "r",
       "s",
       "t",
       "i",
       "d",
       "n",
       "w</w>",
       "r</w>",
       "t</w>",
       "lo",
       "low",
       "er</w>",
       "low</w>",
       "lowest</w>",
       "newer</w>",
       "wider</w>",
       "<unk>",
   ]
   lowerCamelCase__:				Optional[Any]        =dict(zip(UpperCAmelCase_	,			range(len(UpperCAmelCase_))))
   lowerCamelCase__:				Optional[Any]        =["l o 123", "lo w 1456", "e r</w> 1789", ""]

   lowerCamelCase__:				List[Any]        =os.path.join(self.tmpdirname	,			VOCAB_FILES_NAMES["vocab_file"])
   lowerCamelCase__:				Any        =os.path.join(self.tmpdirname	,			VOCAB_FILES_NAMES["merges_file"])
   with open(self.vocab_file	,			"w") as fp:
     fp.write(json.dumps(UpperCAmelCase_))
   with open(self.merges_file	,			"w") as fp:
     fp.write("\n".join(UpperCAmelCase_))

 def 							SCREAMING_SNAKE_CASE_ (self    :       Optional[Any]	,			UpperCAmelCase_    :       Union[str, Any])	->int:



   '''simple docstring'''



   lowerCamelCase__:				List[str]        ="lower newer"
   lowerCamelCase__:				Optional[int]        ="lower newer"
   return input_text, output_text

 def 							SCREAMING_SNAKE_CASE_ (self    :       Tuple)	->int:



   '''simple docstring'''



   lowerCamelCase__:				str        =BioGptTokenizer(self.vocab_file	,			self.merges_file)

   lowerCamelCase__:				Union[str, Any]        ="lower"
   lowerCamelCase__:				Optional[Any]        =["low", "er</w>"]
   lowerCamelCase__:				Optional[Any]        =tokenizer.tokenize(UpperCAmelCase_)
   self.assertListEqual(UpperCAmelCase_	,			UpperCAmelCase_)

   lowerCamelCase__:				str        =tokens + ["<unk>"]
   lowerCamelCase__:				Any        =[14, 15, 20]
   self.assertListEqual(tokenizer.convert_tokens_to_ids(UpperCAmelCase_)	,			UpperCAmelCase_)







 @slow
 def 							SCREAMING_SNAKE_CASE_ (self    :       int)	->Any:



   '''simple docstring'''



   lowerCamelCase__:				Optional[int]        =BioGptTokenizer.from_pretrained("microsoft/biogpt")

   lowerCamelCase__:				str        =tokenizer.encode("sequence builders"	,			add_special_tokens=UpperCAmelCase_)
   lowerCamelCase__:				Tuple        =tokenizer.encode("multi-sequence build"	,			add_special_tokens=UpperCAmelCase_)

   lowerCamelCase__:				int        =tokenizer.build_inputs_with_special_tokens(UpperCAmelCase_)
   lowerCamelCase__:				Any        =tokenizer.build_inputs_with_special_tokens(UpperCAmelCase_	,			UpperCAmelCase_)

   self.assertTrue(encoded_sentence == [2] + text)
   self.assertTrue(encoded_pair == [2] + text + [2] + text_a)








from collections import OrderedDict
from typing import Mapping

from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging


__A     =    logging.get_logger(__name__)

__A     =    {
    "distilbert-base-uncased": "https://huggingface.co/distilbert-base-uncased/resolve/main/config.json",
    "distilbert-base-uncased-distilled-squad": (
        "https://huggingface.co/distilbert-base-uncased-distilled-squad/resolve/main/config.json"
    ),
    "distilbert-base-cased": "https://huggingface.co/distilbert-base-cased/resolve/main/config.json",
    "distilbert-base-cased-distilled-squad": (
        "https://huggingface.co/distilbert-base-cased-distilled-squad/resolve/main/config.json"
    ),
    "distilbert-base-german-cased": "https://huggingface.co/distilbert-base-german-cased/resolve/main/config.json",
    "distilbert-base-multilingual-cased": (
        "https://huggingface.co/distilbert-base-multilingual-cased/resolve/main/config.json"
    ),
    "distilbert-base-uncased-finetuned-sst-2-english": (
        "https://huggingface.co/distilbert-base-uncased-finetuned-sst-2-english/resolve/main/config.json"
    ),
}



class        _SCREAMING_SNAKE_CASE						(     __SCREAMING_SNAKE_CASE   ):







 '''simple docstring'''
 lowercase_		=      "distilbert"
 lowercase_		=      {
     "hidden_size": "dim",
     "num_attention_heads": "n_heads",
     "num_hidden_layers": "n_layers",
 }

 def __init__(self    :       Any	,			UpperCAmelCase_    :       str=30_522	,			UpperCAmelCase_    :       Union[str, Any]=512	,			UpperCAmelCase_    :       int=False	,			UpperCAmelCase_    :       Optional[Any]=6	,			UpperCAmelCase_    :       Optional[Any]=12	,			UpperCAmelCase_    :       Any=768	,			UpperCAmelCase_    :       List[Any]=4 * 768	,			UpperCAmelCase_    :       Tuple=0.1	,			UpperCAmelCase_    :       List[Any]=0.1	,			UpperCAmelCase_    :       Any="gelu"	,			UpperCAmelCase_    :       int=0.02	,			UpperCAmelCase_    :       Optional[Any]=0.1	,			UpperCAmelCase_    :       Optional[int]=0.2	,			UpperCAmelCase_    :       int=0	,			**UpperCAmelCase_    :       List[Any]	,			)	->Any:



   '''simple docstring'''



   lowerCamelCase__:				int        =vocab_size
   lowerCamelCase__:				Any        =max_position_embeddings
   lowerCamelCase__:				Optional[int]        =sinusoidal_pos_embds
   lowerCamelCase__:				str        =n_layers
   lowerCamelCase__:				str        =n_heads
   lowerCamelCase__:				str        =dim
   lowerCamelCase__:				Optional[Any]        =hidden_dim
   lowerCamelCase__:				Dict        =dropout
   lowerCamelCase__:				Optional[Any]        =attention_dropout
   lowerCamelCase__:				int        =activation
   lowerCamelCase__:				Dict        =initializer_range
   lowerCamelCase__:				Optional[Any]        =qa_dropout
   lowerCamelCase__:				int        =seq_classif_dropout
   super().__init__(**UpperCAmelCase_	,			pad_token_id=UpperCAmelCase_)



class        _SCREAMING_SNAKE_CASE						(     __SCREAMING_SNAKE_CASE   ):







 '''simple docstring'''

 @property
 def 							SCREAMING_SNAKE_CASE_ (self    :       List[str])	->Mapping[str, Mapping[int, str]]:



   '''simple docstring'''



   if self.task == "multiple-choice":
     lowerCamelCase__:				Dict        ={0: "batch", 1: "choice", 2: "sequence"}
   else:
     lowerCamelCase__:				Optional[int]        ={0: "batch", 1: "sequence"}
   return OrderedDict(
       [
           ("input_ids", dynamic_axis),
           ("attention_mask", dynamic_axis),
       ])

