






'''simple docstring'''







from typing import Callable, Optional, Union

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


_A			:    Optional[int]					  =logging.get_logger(__name__)

_A			:    List[Any]					  ={
    '''microsoft/xprophetnet-large-wiki100-cased''': (
        '''https://huggingface.co/microsoft/xprophetnet-large-wiki100-cased/resolve/main/config.json'''
    ),
}

class _lowercase			(       _lowercase	):
							a          = """xlm-prophetnet"""
							a          = ["""past_key_values"""]
							a          = {
							    """num_attention_heads""": """num_encoder_attention_heads""",
							}




							def __init__(							self:       Union[str, Any]    ,							UpperCamelCase__:       Optional[float] = 0.1    ,							UpperCamelCase__:       Optional[Union[str, Callable]] = "gelu"    ,							UpperCamelCase__:       Optional[int] = 30_522    ,							UpperCamelCase__:       Optional[int] = 1_024    ,							UpperCamelCase__:       Optional[int] = 4_096    ,							UpperCamelCase__:       Optional[int] = 12    ,							UpperCamelCase__:       Optional[int] = 16    ,							UpperCamelCase__:       Optional[int] = 4_096    ,							UpperCamelCase__:       Optional[int] = 12    ,							UpperCamelCase__:       Optional[int] = 16    ,							UpperCamelCase__:       Optional[float] = 0.1    ,							UpperCamelCase__:       Optional[float] = 0.1    ,							UpperCamelCase__:       Optional[int] = 512    ,							UpperCamelCase__:       Optional[float] = 0.02    ,							UpperCamelCase__:       Optional[bool] = True    ,							UpperCamelCase__:       Optional[bool] = True    ,							UpperCamelCase__:       Optional[int] = 0    ,							UpperCamelCase__:       Optional[int] = 2    ,							UpperCamelCase__:       Optional[int] = 32    ,							UpperCamelCase__:       Optional[int] = 128    ,							UpperCamelCase__:       Optional[bool] = False    ,							UpperCamelCase__:       Optional[float] = 0.0    ,							UpperCamelCase__:       Optional[bool] = True    ,							UpperCamelCase__:       Optional[int] = 0    ,							UpperCamelCase__:       Optional[int] = 1    ,							UpperCamelCase__:       Optional[int] = 2    ,							**UpperCamelCase__:       Any    ,							):
														lowerCamelCase__      :			Union[str, Any] 						= vocab_size
														lowerCamelCase__      :			str 						= hidden_size
														lowerCamelCase__      :			List[Any] 						= encoder_ffn_dim
														lowerCamelCase__      :			Optional[int] 						= num_encoder_layers
														lowerCamelCase__      :			List[str] 						= num_encoder_attention_heads
														lowerCamelCase__      :			Dict 						= decoder_ffn_dim
														lowerCamelCase__      :			Optional[Any] 						= num_decoder_layers
														lowerCamelCase__      :			List[Any] 						= num_decoder_attention_heads
														lowerCamelCase__      :			str 						= max_position_embeddings
														lowerCamelCase__      :			Optional[int] 						= init_std  # Normal(0, this parameter)
														lowerCamelCase__      :			Dict 						= activation_function

														# parameters for xlmprophetnet
														lowerCamelCase__      :			Dict 						= ngram
														lowerCamelCase__      :			Any 						= num_buckets
														lowerCamelCase__      :			int 						= relative_max_distance
														lowerCamelCase__      :			Optional[int] 						= disable_ngram_loss
														lowerCamelCase__      :			int 						= eps

														# 3 Types of Dropout
														lowerCamelCase__      :			str 						= attention_dropout
														lowerCamelCase__      :			Dict 						= activation_dropout
														lowerCamelCase__      :			str 						= dropout

														lowerCamelCase__      :			List[Any] 						= use_cache

														super().__init__(
														    pad_token_id=UpperCamelCase__    ,							bos_token_id=UpperCamelCase__    ,							eos_token_id=UpperCamelCase__    ,							is_encoder_decoder=UpperCamelCase__    ,							add_cross_attention=UpperCamelCase__    ,							decoder_start_token_id=UpperCamelCase__    ,							**UpperCamelCase__    ,							)




							@property
							def 	lowerCamelCase_       (							self:       Union[str, Any]  ):
														return self.num_encoder_layers + self.num_decoder_layers




							@num_hidden_layers.setter
							def 	lowerCamelCase_       (							self:       Optional[Any]    ,							UpperCamelCase__:       Dict  ):
														raise NotImplementedError(
														    """This model does not support the setting of `num_hidden_layers`. Please set `num_encoder_layers` and"""
														    """ `num_decoder_layers`."""  )









'''simple docstring'''







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


_A			:    Optional[Any]					  =logging.get_logger(__name__)

_A			:    Dict					  ={'''vocab_file''': '''vocab.json''', '''merges_file''': '''merges.txt''', '''tokenizer_file''': '''tokenizer.json'''}

_A			:    Tuple					  ={
    '''tokenizer_file''': {
        '''EleutherAI/gpt-neox-20b''': '''https://huggingface.co/EleutherAI/gpt-neox-20b/resolve/main/tokenizer.json''',
    },
}

_A			:    List[Any]					  ={
    '''gpt-neox-20b''': 2_048,
}

class _lowercase			(       _lowercase	):
							a          = VOCAB_FILES_NAMES
							a          = PRETRAINED_VOCAB_FILES_MAP
							a          = PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
							a          = ["""input_ids""", """attention_mask"""]




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

														lowerCamelCase__      :			Dict 						= json.loads(self.backend_tokenizer.pre_tokenizer.__getstate__()  )
														if pre_tok_state.get("""add_prefix_space"""    ,							UpperCamelCase__  ) != add_prefix_space:
																					lowerCamelCase__      :			Any 						= getattr(UpperCamelCase__    ,							pre_tok_state.pop("""type"""  )  )
																					lowerCamelCase__      :			Dict 						= add_prefix_space
																					lowerCamelCase__      :			Optional[int] 						= pre_tok_class(**UpperCamelCase__  )

														lowerCamelCase__      :			Dict 						= add_prefix_space




							def 	lowerCamelCase_       (							self:       int    ,							UpperCamelCase__:       str    ,							UpperCamelCase__:       Optional[str] = None  ):
														lowerCamelCase__      :			Optional[Any] 						= self._tokenizer.model.save(UpperCamelCase__    ,							name=UpperCamelCase__  )
														return tuple(UpperCamelCase__  )




							def 	lowerCamelCase_       (							self:       Optional[int]    ,							UpperCamelCase__:       "Conversation"  ):
														lowerCamelCase__      :			str 						= []
														for is_user, text in conversation.iter_texts():
																					input_ids.extend(self.encode(UpperCamelCase__    ,							add_special_tokens=UpperCamelCase__  ) + [self.eos_token_id]  )

														if len(UpperCamelCase__  ) > self.model_max_length:
																					lowerCamelCase__      :			int 						= input_ids[-self.model_max_length :]
														return input_ids

