
import json
from typing import TYPE_CHECKING, List, Optional, Tuple

from tokenizers import pre_tokenizers

from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging


if TYPE_CHECKING:
							from transformers.pipelines.conversational import Conversation


lowerCamelCase_  :	List[str] 				=					logging.get_logger(__name__)

lowerCamelCase_  :	int 				=					{"""vocab_file""": """vocab.json""", """merges_file""": """merges.txt""", """tokenizer_file""": """tokenizer.json"""}

lowerCamelCase_  :	Dict 				=					{
    """tokenizer_file""": {
        """EleutherAI/gpt-neox-20b""": """https://huggingface.co/EleutherAI/gpt-neox-20b/resolve/main/tokenizer.json""",
    },
}

lowerCamelCase_  :	Any 				=					{
    """gpt-neox-20b""": 20_48,
}

class     _UpperCamelCase			(   _A					):






			'''simple docstring'''

			__UpperCamelCase :  int    =	VOCAB_FILES_NAMES
			__UpperCamelCase :  str    =	PRETRAINED_VOCAB_FILES_MAP
			__UpperCamelCase :  str    =	PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
			__UpperCamelCase :  Tuple    =	["""input_ids""", """attention_mask"""]

			def __init__(    self	:    Tuple  ,		snake_case_	:    Dict=None  ,		snake_case_	:    List[Any]=None  ,		snake_case_	:    Tuple=None  ,		snake_case_	:    Optional[int]="<|endoftext|>"  ,		snake_case_	:    str="<|endoftext|>"  ,		snake_case_	:    Union[str, Any]="<|endoftext|>"  ,		snake_case_	:    List[str]=False  ,		**snake_case_	:    Union[str, Any]  ,		):
							super().__init__(
							    snake_case_  ,		snake_case_  ,		tokenizer_file=snake_case_  ,		unk_token=snake_case_  ,		bos_token=snake_case_  ,		eos_token=snake_case_  ,		add_prefix_space=snake_case_  ,		**snake_case_  ,		)

							UpperCamelCase_:							List[str]		=  json.loads(self.backend_tokenizer.pre_tokenizer.__getstate__() )
							if pre_tok_state.get("""add_prefix_space"""  ,		snake_case_ ) != add_prefix_space:
											UpperCamelCase_:							Union[str, Any]		=  getattr(snake_case_  ,		pre_tok_state.pop("""type""" ) )
											UpperCamelCase_:							Tuple		=  add_prefix_space
											UpperCamelCase_:							Union[str, Any]		=  pre_tok_class(**snake_case_ )

							UpperCamelCase_:							str		=  add_prefix_space

			def  lowerCAmelCase__		(    self	:    Union[str, Any]  ,		snake_case_	:    str  ,		snake_case_	:    Optional[str] = None ):
							UpperCamelCase_:							List[str]		=  self._tokenizer.model.save(snake_case_  ,		name=snake_case_ )
							return tuple(snake_case_ )




			def  lowerCAmelCase__		(    self	:    Any  ,		snake_case_	:    "Conversation" ):
							UpperCamelCase_:							List[Any]		=  []
							for is_user, text in conversation.iter_texts():
											input_ids.extend(self.encode(snake_case_  ,		add_special_tokens=snake_case_ ) + [self.eos_token_id] )

							if len(snake_case_ ) > self.model_max_length:
											UpperCamelCase_:							Dict		=  input_ids[-self.model_max_length :]
							return input_ids








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


lowerCamelCase_  :	Tuple 				=					logging.get_logger(__name__)

lowerCamelCase_  :	str 				=					{
    """unc-nlp/lxmert-base-uncased""": """https://huggingface.co/unc-nlp/lxmert-base-uncased/resolve/main/config.json""",
}

class     _UpperCamelCase			(   _A					):






			'''simple docstring'''

			__UpperCamelCase :  Any    =	"""lxmert"""
			__UpperCamelCase :  Optional[Any]    =	{}

			def __init__(    self	:    Dict  ,		snake_case_	:    List[str]=3_0522  ,		snake_case_	:    int=768  ,		snake_case_	:    str=12  ,		snake_case_	:    Tuple=9500  ,		snake_case_	:    Optional[Any]=1600  ,		snake_case_	:    str=400  ,		snake_case_	:    List[str]=3072  ,		snake_case_	:    Dict="gelu"  ,		snake_case_	:    Optional[Any]=0.1  ,		snake_case_	:    int=0.1  ,		snake_case_	:    Optional[int]=512  ,		snake_case_	:    Tuple=2  ,		snake_case_	:    Optional[int]=0.02  ,		snake_case_	:    Union[str, Any]=1e-12  ,		snake_case_	:    Tuple=9  ,		snake_case_	:    Tuple=5  ,		snake_case_	:    Union[str, Any]=5  ,		snake_case_	:    List[str]=2048  ,		snake_case_	:    Any=4  ,		snake_case_	:    int=6.67  ,		snake_case_	:    Dict=True  ,		snake_case_	:    Tuple=True  ,		snake_case_	:    int=True  ,		snake_case_	:    str=True  ,		snake_case_	:    List[Any]=True  ,		snake_case_	:    List[Any]=True  ,		snake_case_	:    List[str]=True  ,		**snake_case_	:    Optional[int]  ,		):
							UpperCamelCase_:							int		=  vocab_size
							UpperCamelCase_:							Tuple		=  hidden_size
							UpperCamelCase_:							Optional[Any]		=  num_attention_heads
							UpperCamelCase_:							List[str]		=  hidden_act
							UpperCamelCase_:							int		=  intermediate_size
							UpperCamelCase_:							Any		=  hidden_dropout_prob
							UpperCamelCase_:							List[Any]		=  attention_probs_dropout_prob
							UpperCamelCase_:							List[str]		=  max_position_embeddings
							UpperCamelCase_:							Optional[Any]		=  type_vocab_size
							UpperCamelCase_:							Optional[Any]		=  initializer_range
							UpperCamelCase_:							str		=  layer_norm_eps
							UpperCamelCase_:							List[str]		=  num_qa_labels
							UpperCamelCase_:							List[str]		=  num_object_labels
							UpperCamelCase_:							Tuple		=  num_attr_labels
							UpperCamelCase_:							List[Any]		=  l_layers
							UpperCamelCase_:							List[Any]		=  x_layers
							UpperCamelCase_:							Any		=  r_layers
							UpperCamelCase_:							str		=  visual_feat_dim
							UpperCamelCase_:							Union[str, Any]		=  visual_pos_dim
							UpperCamelCase_:							str		=  visual_loss_normalizer
							UpperCamelCase_:							Dict		=  task_matched
							UpperCamelCase_:							Tuple		=  task_mask_lm
							UpperCamelCase_:							List[str]		=  task_obj_predict
							UpperCamelCase_:							Any		=  task_qa
							UpperCamelCase_:							Dict		=  visual_obj_loss
							UpperCamelCase_:							Optional[Any]		=  visual_attr_loss
							UpperCamelCase_:							List[Any]		=  visual_feat_loss
							UpperCamelCase_:							Tuple		=  {"""vision""": r_layers, """cross_encoder""": x_layers, """language""": l_layers}
							super().__init__(**snake_case_ )






