

import os
import unittest

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

from ...test_tokenization_common import TokenizerTesterMixin



class       __snake_case  (    lowerCAmelCase__     , unittest.TestCase       ):
  __lowerCAmelCase     :	List[Any]						 =  PhobertTokenizer
  __lowerCAmelCase     :	int						 =  False

  def 						lowerCAmelCase__     (					self):
      super().setUp()

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

      SCREAMING_SNAKE_CASE_									=						os.path.join(self.tmpdirname						,		VOCAB_FILES_NAMES['vocab_file'])
      SCREAMING_SNAKE_CASE_									=						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 						lowerCAmelCase__     (					self						,		**_A):
      kwargs.update(self.special_tokens_map)
      return PhobertTokenizer.from_pretrained(self.tmpdirname						,		**_A)

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

      SCREAMING_SNAKE_CASE_									=						tokens + [tokenizer.unk_token]

      SCREAMING_SNAKE_CASE_									=						[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)





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


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

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



class       __snake_case  (    lowerCAmelCase__       ):
  __lowerCAmelCase     :	Any						 =  'biogpt'

  def __init__(					self						,		_A=42384						,		_A=1024						,		_A=24						,		_A=16						,		_A=4096						,		_A="gelu"						,		_A=0.1						,		_A=0.1						,		_A=1024						,		_A=0.0_2						,		_A=1E-12						,		_A=True						,		_A=True						,		_A=0.0						,		_A=0.0						,		_A=1						,		_A=0						,		_A=2						,		**_A						,		):
      SCREAMING_SNAKE_CASE_									=						vocab_size
      SCREAMING_SNAKE_CASE_									=						max_position_embeddings
      SCREAMING_SNAKE_CASE_									=						hidden_size
      SCREAMING_SNAKE_CASE_									=						num_hidden_layers
      SCREAMING_SNAKE_CASE_									=						num_attention_heads
      SCREAMING_SNAKE_CASE_									=						intermediate_size
      SCREAMING_SNAKE_CASE_									=						hidden_act
      SCREAMING_SNAKE_CASE_									=						hidden_dropout_prob
      SCREAMING_SNAKE_CASE_									=						attention_probs_dropout_prob
      SCREAMING_SNAKE_CASE_									=						initializer_range
      SCREAMING_SNAKE_CASE_									=						layer_norm_eps
      SCREAMING_SNAKE_CASE_									=						scale_embedding
      SCREAMING_SNAKE_CASE_									=						use_cache
      SCREAMING_SNAKE_CASE_									=						layerdrop
      SCREAMING_SNAKE_CASE_									=						activation_dropout
      super().__init__(pad_token_id=_A						,		bos_token_id=_A						,		eos_token_id=_A						,		**_A)


