


'''simple docstring'''




import os
from shutil import copyfile
from typing import List, Optional, Tuple

from ...tokenization_utils import AddedToken
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging


if is_sentencepiece_available():
				from .tokenization_big_bird import BigBirdTokenizer
else:
				_lowerCAmelCase  :		Union[str, Any]		     =	None

_lowerCAmelCase  :		Union[str, Any]		     =	logging.get_logger(__name__)
_lowerCAmelCase  :		Optional[Any]		     =	{'vocab_file': 'spiece.model', 'tokenizer_file': 'tokenizer.json'}

_lowerCAmelCase  :		int		     =	{
    'vocab_file': {
        'google/bigbird-roberta-base': 'https://huggingface.co/google/bigbird-roberta-base/resolve/main/spiece.model',
        'google/bigbird-roberta-large': (
            'https://huggingface.co/google/bigbird-roberta-large/resolve/main/spiece.model'
        ),
        'google/bigbird-base-trivia-itc': (
            'https://huggingface.co/google/bigbird-base-trivia-itc/resolve/main/spiece.model'
        ),
    },
    'tokenizer_file': {
        'google/bigbird-roberta-base': (
            'https://huggingface.co/google/bigbird-roberta-base/resolve/main/tokenizer.json'
        ),
        'google/bigbird-roberta-large': (
            'https://huggingface.co/google/bigbird-roberta-large/resolve/main/tokenizer.json'
        ),
        'google/bigbird-base-trivia-itc': (
            'https://huggingface.co/google/bigbird-base-trivia-itc/resolve/main/tokenizer.json'
        ),
    },
}

_lowerCAmelCase  :		Any		     =	{
    'google/bigbird-roberta-base': 4096,
    'google/bigbird-roberta-large': 4096,
    'google/bigbird-base-trivia-itc': 4096,
}


_lowerCAmelCase  :		Any		     =	'▁'



class  lowerCAmelCase				(				a							):
	_lowerCamelCase   :					Any			      = VOCAB_FILES_NAMES
	_lowerCamelCase   :					List[str]			      = PRETRAINED_VOCAB_FILES_MAP
	_lowerCamelCase   :					Dict			      = PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
	_lowerCamelCase   :					str			      = BigBirdTokenizer
	_lowerCamelCase   :					Dict			      = ["""input_ids""", """attention_mask"""]
	_lowerCamelCase   :					List[int]			      = []



	def __init__(					self ,					snake_case__=None ,					snake_case__=None ,					snake_case__="<unk>" ,					snake_case__="<s>" ,					snake_case__="</s>" ,					snake_case__="<pad>" ,					snake_case__="[SEP]" ,					snake_case__="[MASK]" ,					snake_case__="[CLS]" ,					**snake_case__ ,					):
		lowerCAmelCase					:    Tuple      							= AddedToken(snake_case__ ,					lstrip=snake_case__ ,					rstrip=snake_case__    ) if isinstance(snake_case__ ,					snake_case__    ) else bos_token
		lowerCAmelCase					:    List[str]      							= AddedToken(snake_case__ ,					lstrip=snake_case__ ,					rstrip=snake_case__    ) if isinstance(snake_case__ ,					snake_case__    ) else eos_token
		lowerCAmelCase					:    str      							= AddedToken(snake_case__ ,					lstrip=snake_case__ ,					rstrip=snake_case__    ) if isinstance(snake_case__ ,					snake_case__    ) else unk_token
		lowerCAmelCase					:    Optional[Any]      							= AddedToken(snake_case__ ,					lstrip=snake_case__ ,					rstrip=snake_case__    ) if isinstance(snake_case__ ,					snake_case__    ) else pad_token
		lowerCAmelCase					:    Tuple      							= AddedToken(snake_case__ ,					lstrip=snake_case__ ,					rstrip=snake_case__    ) if isinstance(snake_case__ ,					snake_case__    ) else cls_token
		lowerCAmelCase					:    Union[str, Any]      							= AddedToken(snake_case__ ,					lstrip=snake_case__ ,					rstrip=snake_case__    ) if isinstance(snake_case__ ,					snake_case__    ) else sep_token

		# Mask token behave like a normal word, i.e. include the space before it
		lowerCAmelCase					:    Optional[Any]      							= AddedToken(snake_case__ ,					lstrip=snake_case__ ,					rstrip=snake_case__    ) if isinstance(snake_case__ ,					snake_case__    ) else mask_token

		super().__init__(
		    snake_case__ ,					tokenizer_file=snake_case__ ,					bos_token=snake_case__ ,					eos_token=snake_case__ ,					unk_token=snake_case__ ,					sep_token=snake_case__ ,					pad_token=snake_case__ ,					cls_token=snake_case__ ,					mask_token=snake_case__ ,					**snake_case__ ,					)

		lowerCAmelCase					:    Optional[int]      							= vocab_file
		lowerCAmelCase					:    Union[str, Any]      							= False if not self.vocab_file else True



	def 				lowercase     (					self ,					snake_case__ ,					snake_case__ = None    ):
		lowerCAmelCase					:    Dict      							= [self.sep_token_id]
		lowerCAmelCase					:    Union[str, Any]      							= [self.cls_token_id]
		if token_ids_a is None:
			return cls + token_ids_a + sep
		return cls + token_ids_a + sep + token_ids_a + sep



	def 				lowercase     (					self ,					snake_case__ ,					snake_case__ = None ,					snake_case__ = False    ):

		if already_has_special_tokens:
			if token_ids_a is not None:
				raise ValueError(
				    'You should not supply a second sequence if the provided sequence of '
				    'ids is already formatted with special tokens for the model.'    )
			return [1 if x in [self.sep_token_id, self.cls_token_id] else 0 for x in token_ids_a]

		if token_ids_a is None:
			return [1] + ([0] * len(snake_case__    )) + [1]
		return [1] + ([0] * len(snake_case__    )) + [1] + ([0] * len(snake_case__    )) + [1]



	def 				lowercase     (					self ,					snake_case__ ,					snake_case__ = None    ):
		lowerCAmelCase					:    List[Any]      							= [self.sep_token_id]
		lowerCAmelCase					:    Tuple      							= [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 				lowercase     (					self ,					snake_case__ ,					snake_case__ = None    ):
		if not self.can_save_slow_tokenizer:
			raise ValueError(
			    'Your fast tokenizer does not have the necessary information to save the vocabulary for a slow '
			    'tokenizer.'    )

		if not os.path.isdir(snake_case__    ):
			logger.error(f"Vocabulary path ({save_directory}) should be a directory"    )
			return
		lowerCAmelCase					:    str      							= os.path.join(
		    snake_case__ ,					(filename_prefix + '-' if filename_prefix else '') + VOCAB_FILES_NAMES['vocab_file']    )

		if os.path.abspath(self.vocab_file    ) != os.path.abspath(snake_case__    ):
			copyfile(self.vocab_file ,					snake_case__    )

		return (out_vocab_file,)




'''simple docstring'''




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


_lowerCAmelCase  :		str		     =	logging.get_logger(__name__)

_lowerCAmelCase  :		Tuple		     =	{
    's-JoL/Open-Llama-V1': 'https://huggingface.co/s-JoL/Open-Llama-V1/blob/main/config.json',
}



class  lowerCAmelCase				(				a							):
	_lowerCamelCase   :					Union[str, Any]			      = """open-llama"""



	def __init__(					self ,					snake_case__=10_0000 ,					snake_case__=4096 ,					snake_case__=1_1008 ,					snake_case__=32 ,					snake_case__=32 ,					snake_case__="silu" ,					snake_case__=2048 ,					snake_case__=0.0_2 ,					snake_case__=1e-6 ,					snake_case__=True ,					snake_case__=0 ,					snake_case__=1 ,					snake_case__=2 ,					snake_case__=False ,					snake_case__=True ,					snake_case__=0.1 ,					snake_case__=0.1 ,					snake_case__=True ,					snake_case__=True ,					snake_case__=None ,					**snake_case__ ,					):
		lowerCAmelCase					:    Tuple      							= vocab_size
		lowerCAmelCase					:    Optional[Any]      							= max_position_embeddings
		lowerCAmelCase					:    List[Any]      							= hidden_size
		lowerCAmelCase					:    List[Any]      							= intermediate_size
		lowerCAmelCase					:    Tuple      							= num_hidden_layers
		lowerCAmelCase					:    List[Any]      							= num_attention_heads
		lowerCAmelCase					:    List[Any]      							= hidden_act
		lowerCAmelCase					:    Union[str, Any]      							= initializer_range
		lowerCAmelCase					:    str      							= rms_norm_eps
		lowerCAmelCase					:    Optional[int]      							= use_cache
		lowerCAmelCase					:    Dict      							= kwargs.pop(
		    'use_memorry_efficient_attention' ,					snake_case__    )
		lowerCAmelCase					:    Optional[int]      							= hidden_dropout_prob
		lowerCAmelCase					:    Optional[Any]      							= attention_dropout_prob
		lowerCAmelCase					:    Union[str, Any]      							= use_stable_embedding
		lowerCAmelCase					:    Tuple      							= shared_input_output_embedding
		lowerCAmelCase					:    Tuple      							= rope_scaling
		self._rope_scaling_validation()

		super().__init__(
		    pad_token_id=snake_case__ ,					bos_token_id=snake_case__ ,					eos_token_id=snake_case__ ,					tie_word_embeddings=snake_case__ ,					**snake_case__ ,					)



	def 				lowercase     (					self    ):
		if self.rope_scaling is None:
			return

		if not isinstance(self.rope_scaling ,					snake_case__    ) or len(self.rope_scaling    ) != 2:
			raise ValueError(
			    '`rope_scaling` must be a dictionary with with two fields, `name` and `factor`, '
			    f"got {self.rope_scaling}"    )
		lowerCAmelCase					:    List[Any]      							= self.rope_scaling.get('type' ,					snake_case__    )
		lowerCAmelCase					:    List[str]      							= self.rope_scaling.get('factor' ,					snake_case__    )
		if rope_scaling_type is None or rope_scaling_type not in ["linear", "dynamic"]:
			raise ValueError(
			    f"`rope_scaling`'s name field must be one of ['linear', 'dynamic'], got {rope_scaling_type}"    )
		if rope_scaling_factor is None or not isinstance(snake_case__ ,					snake_case__    ) or rope_scaling_factor <= 1.0:
			raise ValueError(f"`rope_scaling`'s factor field must be an float > 1, got {rope_scaling_factor}"    )
