
import operator as op


__lowerCamelCase							=       """scaler.pt"""
__lowerCamelCase							=       """pytorch_model"""
__lowerCamelCase							=       """random_states"""
__lowerCamelCase							=       """optimizer"""
__lowerCamelCase							=       """scheduler"""
__lowerCamelCase							=       """pytorch_model.bin"""
__lowerCamelCase							=       """pytorch_model.bin.index.json"""
__lowerCamelCase							=       """model.safetensors"""
__lowerCamelCase							=       """model.safetensors.index.json"""
__lowerCamelCase							=       """1.10.2"""
__lowerCamelCase							=       """py38"""
__lowerCamelCase							=       """4.17.0"""
__lowerCamelCase							=       ["""ml.p3.16xlarge""", """ml.p3dn.24xlarge""", """ml.p4dn.24xlarge"""]
__lowerCamelCase							=       ["""FULL_SHARD""", """SHARD_GRAD_OP""", """NO_SHARD""", """HYBRID_SHARD""", """HYBRID_SHARD_ZERO2"""]
__lowerCamelCase							=       ["""TRANSFORMER_BASED_WRAP""", """SIZE_BASED_WRAP""", """NO_WRAP"""]
__lowerCamelCase							=       ["""BACKWARD_PRE""", """BACKWARD_POST""", """NO_PREFETCH"""]
__lowerCamelCase							=       ["""FULL_STATE_DICT""", """LOCAL_STATE_DICT""", """SHARDED_STATE_DICT"""]
__lowerCamelCase							=       """2.0.1"""
__lowerCamelCase							=       ["""pdsh""", """standard""", """openmpi""", """mvapich"""]
__lowerCamelCase							=       ["""default""", """reduce-overhead""", """max-autotune"""]

__lowerCamelCase							=       {""">""": op.gt, """>=""": op.ge, """==""": op.eq, """!=""": op.ne, """<=""": op.le, """<""": op.lt}

# These are the args for `torch.distributed.launch` for pytorch < 1.9
__lowerCamelCase							=       [
    """nnodes""",
    """nproc_per_node""",
    """rdzv_backend""",
    """rdzv_endpoint""",
    """rdzv_id""",
    """rdzv_conf""",
    """standalone""",
    """max_restarts""",
    """monitor_interval""",
    """start_method""",
    """role""",
    """module""",
    """m""",
    """no_python""",
    """run_path""",
    """log_dir""",
    """r""",
    """redirects""",
    """t""",
    """tee""",
    """node_rank""",
    """master_addr""",
    """master_port""",
]

__lowerCamelCase							=       ["""DEEPSPEED""", """MULTI_GPU""", """FSDP""", """MEGATRON_LM"""]
__lowerCamelCase							=       ["""DEEPSPEED""", """MULTI_XPU""", """FSDP"""]







import json
from typing import List, Optional, Tuple

from tokenizers import normalizers

from ...tokenization_utils_fast import PreTrainedTokenizerFast
from .tokenization_lxmert import LxmertTokenizer


__lowerCamelCase							=       {"""vocab_file""": """vocab.txt""", """tokenizer_file""": """tokenizer.json"""}

__lowerCamelCase							=       {
    """vocab_file""": {
        """unc-nlp/lxmert-base-uncased""": """https://huggingface.co/unc-nlp/lxmert-base-uncased/resolve/main/vocab.txt""",
    },
    """tokenizer_file""": {
        """unc-nlp/lxmert-base-uncased""": (
            """https://huggingface.co/unc-nlp/lxmert-base-uncased/resolve/main/tokenizer.json"""
        ),
    },
}

__lowerCamelCase							=       {
    """unc-nlp/lxmert-base-uncased""": 5_12,
}

__lowerCamelCase							=       {
    """unc-nlp/lxmert-base-uncased""": {"""do_lower_case""": True},
}






class   UpperCAmelCase		(						A_ ):
   A__					:		Any						     =     VOCAB_FILES_NAMES
   A__					:		Optional[int]						     =     PRETRAINED_VOCAB_FILES_MAP
   A__					:		Tuple						     =     PRETRAINED_INIT_CONFIGURATION
   A__					:		Tuple						     =     PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
   A__					:		List[Any]						     =     LxmertTokenizer



   def __init__(self		:					Dict    ,						snake_case__		:					Tuple=None    ,						snake_case__		:					Optional[Any]=None    ,						snake_case__		:					Optional[Any]=True    ,						snake_case__		:					Tuple="[UNK]"    ,						snake_case__		:					Optional[Any]="[SEP]"    ,						snake_case__		:					Optional[Any]="[PAD]"    ,						snake_case__		:					List[Any]="[CLS]"    ,						snake_case__		:					Tuple="[MASK]"    ,						snake_case__		:					Dict=True    ,						snake_case__		:					Union[str, Any]=None    ,						**snake_case__		:					Dict    ,						)		->	Optional[int]:


          '''simple docstring'''


          super().__init__(
              snake_case__    ,						tokenizer_file=snake_case__    ,						do_lower_case=snake_case__    ,						unk_token=snake_case__    ,						sep_token=snake_case__    ,						pad_token=snake_case__    ,						cls_token=snake_case__    ,						mask_token=snake_case__    ,						tokenize_chinese_chars=snake_case__    ,						strip_accents=snake_case__    ,						**snake_case__    ,						)

          snake_case       :   int							=      json.loads(self.backend_tokenizer.normalizer.__getstate__() )
          if (
              normalizer_state.get("lowercase"    ,						snake_case__ ) != do_lower_case
              or normalizer_state.get("strip_accents"    ,						snake_case__ ) != strip_accents
              or normalizer_state.get("handle_chinese_chars"    ,						snake_case__ ) != tokenize_chinese_chars
          ):
                 snake_case       :   Union[str, Any]							=      getattr(snake_case__    ,						normalizer_state.pop("type" ) )
                 snake_case       :   str							=      do_lower_case
                 snake_case       :   List[Any]							=      strip_accents
                 snake_case       :   Optional[int]							=      tokenize_chinese_chars
                 snake_case       :   int							=      normalizer_class(**snake_case__ )

          snake_case       :   Optional[Any]							=      do_lower_case



   def 				_SCREAMING_SNAKE_CASE   (self		:					Union[str, Any]    ,						snake_case__		:					Optional[Any]    ,						snake_case__		:					Dict=None )		->	Any:


          '''simple docstring'''


          snake_case       :   Optional[int]							=      [self.cls_token_id] + token_ids_a + [self.sep_token_id]

          if token_ids_a:
                 output += token_ids_a + [self.sep_token_id]

          return output



   def 				_SCREAMING_SNAKE_CASE   (self		:					Optional[int]    ,						snake_case__		:					List[int]    ,						snake_case__		:					Optional[List[int]] = None )		->	List[int]:


          '''simple docstring'''


          snake_case       :   Optional[Any]							=      [self.sep_token_id]
          snake_case       :   Optional[Any]							=      [self.cls_token_id]
          if token_ids_a is None:
                 return len(cls + token_ids_a + sep ) * [0]
          return len(cls + token_ids_a + sep ) * [0] + len(token_ids_a + sep ) * [1]



   def 				_SCREAMING_SNAKE_CASE   (self		:					Any    ,						snake_case__		:					str    ,						snake_case__		:					Optional[str] = None )		->	Tuple[str]:


          '''simple docstring'''


          snake_case       :   List[Any]							=      self._tokenizer.model.save(snake_case__    ,						name=snake_case__ )
          return tuple(snake_case__ )





