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


lowercase__          =   logging.get_logger(__name__)

lowercase__          =   {
    '''alibaba-damo/mgp-str-base''': '''https://huggingface.co/alibaba-damo/mgp-str-base/resolve/main/config.json''',
}



class 		UpperCamelCase__  (	A__   ):
   _SCREAMING_SNAKE_CASE				:							List[str]     	=				'mgp-str'
   def __init__(self			: Optional[int] ,    snake_case_			: Union[str, Any]=[3_2, 1_2_8] ,    snake_case_			: str=4 ,    snake_case_			: Tuple=3 ,    snake_case_			: Optional[int]=2_7 ,    snake_case_			: Optional[int]=3_8 ,    snake_case_			: str=5_0_2_5_7 ,    snake_case_			: List[str]=3_0_5_2_2 ,    snake_case_			: List[Any]=7_6_8 ,    snake_case_			: Union[str, Any]=1_2 ,    snake_case_			: List[Any]=1_2 ,    snake_case_			: Tuple=4.0 ,    snake_case_			: Any=True ,    snake_case_			: Union[str, Any]=False ,    snake_case_			: Optional[Any]=1E-5 ,    snake_case_			: Optional[int]=0.0 ,    snake_case_			: str=0.0 ,    snake_case_			: Tuple=0.0 ,    snake_case_			: Optional[Any]=False ,    snake_case_			: Optional[Any]=0.02 ,    **snake_case_			: Optional[Any] ,    ):
    super().__init__(**lowerCamelCase__       )

    __a			:  List[Any]		    =  image_size
    __a			:  Optional[Any]		    =  patch_size
    __a			:  Optional[int]		    =  num_channels
    __a			:  str		    =  max_token_length
    __a			:  Tuple		    =  num_character_labels
    __a			:  Optional[Any]		    =  num_bpe_labels
    __a			:  Any		    =  num_wordpiece_labels
    __a			:  List[str]		    =  hidden_size
    __a			:  List[str]		    =  num_hidden_layers
    __a			:  Any		    =  num_attention_heads
    __a			:  str		    =  mlp_ratio
    __a			:  List[str]		    =  distilled
    __a			:  List[Any]		    =  layer_norm_eps
    __a			:  Optional[Any]		    =  drop_rate
    __a			:  int		    =  qkv_bias
    __a			:  int		    =  attn_drop_rate
    __a			:  Optional[int]		    =  drop_path_rate
    __a			:  Dict		    =  output_aa_attentions
    __a			:  Optional[int]		    =  initializer_range


import os
import unittest

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

from ...test_tokenization_common import TokenizerTesterMixin



class 		UpperCamelCase__  (	__lowercase   ,unittest.TestCase   ):
   _SCREAMING_SNAKE_CASE				:							Union[str, Any]     	=				PhobertTokenizer
   _SCREAMING_SNAKE_CASE				:							int     	=				False
   def 				lowerCAmelCase      (self			: Optional[int]       ):
    super().setUp()

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

    __a			:  Any		    =  os.path.join(self.tmpdirname ,    VOCAB_FILES_NAMES['''vocab_file''']       )
    __a			:  List[Any]		    =  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			: Union[str, Any] ,    **snake_case_			: List[str]       ):
    kwargs.update(self.special_tokens_map       )
    return PhobertTokenizer.from_pretrained(self.tmpdirname ,    **snake_case_       )
   def 				lowerCAmelCase      (self			: Any ,    snake_case_			: Dict       ):
    __a			:  Union[str, Any]		    =  '''Tôi là VinAI Research'''
    __a			:  int		    =  '''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			: Optional[Any]       ):
    __a			:  Optional[int]		    =  PhobertTokenizer(self.vocab_file ,    self.merges_file ,    **self.special_tokens_map       )
    __a			:  Any		    =  '''Tôi là VinAI Research'''
    __a			:  Union[str, Any]		    =  '''T@@ ô@@ i l@@ à V@@ i@@ n@@ A@@ I R@@ e@@ s@@ e@@ a@@ r@@ c@@ h'''.split()
    __a			:  List[str]		    =  tokenizer.tokenize(snake_case_       )
    print(snake_case_       )
    self.assertListEqual(snake_case_ ,    snake_case_       )

    __a			:  str		    =  tokens + [tokenizer.unk_token]

    __a			:  str		    =  [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_       )
