


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


a					  =     logging.get_logger(__name__)

a					  =     {
    'RWKV/rwkv-4-169m-pile': 'https://huggingface.co/RWKV/rwkv-4-169m-pile/resolve/main/config.json',
    'RWKV/rwkv-4-430m-pile': 'https://huggingface.co/RWKV/rwkv-4-430m-pile/resolve/main/config.json',
    'RWKV/rwkv-4-1b5-pile': 'https://huggingface.co/RWKV/rwkv-4-1b5-pile/resolve/main/config.json',
    'RWKV/rwkv-4-3b-pile': 'https://huggingface.co/RWKV/rwkv-4-3b-pile/resolve/main/config.json',
    'RWKV/rwkv-4-7b-pile': 'https://huggingface.co/RWKV/rwkv-4-7b-pile/resolve/main/config.json',
    'RWKV/rwkv-4-14b-pile': 'https://huggingface.co/RWKV/rwkv-4-14b-pile/resolve/main/config.json',
    'RWKV/rwkv-raven-1b5': 'https://huggingface.co/RWKV/rwkv-raven-1b5/resolve/main/config.json',
    'RWKV/rwkv-raven-3b': 'https://huggingface.co/RWKV/rwkv-raven-3b/resolve/main/config.json',
    'RWKV/rwkv-raven-7b': 'https://huggingface.co/RWKV/rwkv-raven-7b/resolve/main/config.json',
    'RWKV/rwkv-raven-14b': 'https://huggingface.co/RWKV/rwkv-raven-14b/resolve/main/config.json',
}







class        UpperCamelCase__   (	__magic_name__   ):
					__SCREAMING_SNAKE_CASE       :  Any						=   'rwkv'
					__SCREAMING_SNAKE_CASE       :  Optional[Any]						=   {'max_position_embeddings': 'context_length'}

					def __init__(     self       :   List[Any]							,					UpperCamelCase__       :   List[str]=50_277							,					UpperCamelCase__       :   Optional[Any]=1_024							,					UpperCamelCase__       :   int=4_096							,					UpperCamelCase__       :   Optional[Any]=32							,					UpperCamelCase__       :   Any=None							,					UpperCamelCase__       :   Tuple=None							,					UpperCamelCase__       :   Tuple=1e-5							,					UpperCamelCase__       :   Union[str, Any]=0							,					UpperCamelCase__       :   Tuple=0							,					UpperCamelCase__       :   Union[str, Any]=6							,					UpperCamelCase__       :   Dict=False							,					UpperCamelCase__       :   str=True							,					**UpperCamelCase__       :   Union[str, Any]							,					):






										'''simple docstring'''






										lowercase_  							=			vocab_size
										lowercase_  							=			context_length
										lowercase_  							=			hidden_size
										lowercase_  							=			num_hidden_layers
										lowercase_  							=			attention_hidden_size if attention_hidden_size is not None else hidden_size
										lowercase_  							=			intermediate_size if intermediate_size is not None else 4 * hidden_size
										lowercase_  							=			layer_norm_epsilon
										lowercase_  							=			rescale_every
										lowercase_  							=			use_cache

										lowercase_  							=			bos_token_id
										lowercase_  							=			eos_token_id

										super().__init__(
										    tie_word_embeddings=UpperCamelCase__							,					bos_token_id=UpperCamelCase__							,					eos_token_id=UpperCamelCase__							,					**UpperCamelCase__       )






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

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


if is_sentencepiece_available():
							from .tokenization_ta import TaTokenizer
else:
							a					  =     None


a					  =     logging.get_logger(__name__)

a					  =     {'vocab_file': 'spiece.model', 'tokenizer_file': 'tokenizer.json'}

a					  =     {
    'vocab_file': {
        't5-small': 'https://huggingface.co/t5-small/resolve/main/spiece.model',
        't5-base': 'https://huggingface.co/t5-base/resolve/main/spiece.model',
        't5-large': 'https://huggingface.co/t5-large/resolve/main/spiece.model',
        't5-3b': 'https://huggingface.co/t5-3b/resolve/main/spiece.model',
        't5-11b': 'https://huggingface.co/t5-11b/resolve/main/spiece.model',
    },
    'tokenizer_file': {
        't5-small': 'https://huggingface.co/t5-small/resolve/main/tokenizer.json',
        't5-base': 'https://huggingface.co/t5-base/resolve/main/tokenizer.json',
        't5-large': 'https://huggingface.co/t5-large/resolve/main/tokenizer.json',
        't5-3b': 'https://huggingface.co/t5-3b/resolve/main/tokenizer.json',
        't5-11b': 'https://huggingface.co/t5-11b/resolve/main/tokenizer.json',
    },
}


# TODO(PVP) - this should be removed in Transformers v5
a					  =     {
    't5-small': 5_1_2,
    't5-base': 5_1_2,
    't5-large': 5_1_2,
    't5-3b': 5_1_2,
    't5-11b': 5_1_2,
}







class        UpperCamelCase__   (	__magic_name__   ):
					__SCREAMING_SNAKE_CASE       :  Union[str, Any]						=   VOCAB_FILES_NAMES
					__SCREAMING_SNAKE_CASE       :  int						=   PRETRAINED_VOCAB_FILES_MAP
					__SCREAMING_SNAKE_CASE       :  Any						=   PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
					__SCREAMING_SNAKE_CASE       :  str						=   ['input_ids', 'attention_mask']
					__SCREAMING_SNAKE_CASE       :  Dict						=   TaTokenizer

					__SCREAMING_SNAKE_CASE       :  List[int]						=   []

					def __init__(     self       :   int							,					UpperCamelCase__       :   Union[str, Any]=None							,					UpperCamelCase__       :   Any=None							,					UpperCamelCase__       :   Dict="</s>"							,					UpperCamelCase__       :   Tuple="<unk>"							,					UpperCamelCase__       :   Optional[Any]="<pad>"							,					UpperCamelCase__       :   Union[str, Any]=100							,					UpperCamelCase__       :   Optional[Any]=None							,					**UpperCamelCase__       :   List[str]							,					):






										'''simple docstring'''






										if extra_ids > 0 and additional_special_tokens is None:
															lowercase_  							=			[F'''<extra_id_{i}>''' for i in range(UpperCamelCase__       )]
										elif extra_ids > 0 and additional_special_tokens is not None:
															# Check that we have the right number of extra special tokens
															lowercase_  							=			len(set(filter(lambda UpperCamelCase__       : bool("""extra_id_""" in str(UpperCamelCase__       )       )							,					UpperCamelCase__       )       )       )
															if extra_tokens != extra_ids:
																				raise ValueError(
																				    F'''Both extra_ids ({extra_ids}) and additional_special_tokens ({additional_special_tokens}) are'''
																				    """ provided to T5Tokenizer. In this case the additional_special_tokens must include the extra_ids"""
																				    """ tokens"""       )

										super().__init__(
										    UpperCamelCase__							,					tokenizer_file=UpperCamelCase__							,					eos_token=UpperCamelCase__							,					unk_token=UpperCamelCase__							,					pad_token=UpperCamelCase__							,					extra_ids=UpperCamelCase__							,					additional_special_tokens=UpperCamelCase__							,					**UpperCamelCase__							,					)

										lowercase_  							=			vocab_file
										lowercase_  							=			False if not self.vocab_file else True
										lowercase_  							=			extra_ids

					@staticmethod
					def   UpperCAmelCase__       (     UpperCamelCase__       :   Tuple							,					UpperCamelCase__       :   str							,					UpperCamelCase__       :   int       ):






										'''simple docstring'''






										if pretrained_model_name_or_path in TaTokenizerFast.max_model_input_sizes:
															lowercase_  							=			TaTokenizerFast.max_model_input_sizes[pretrained_model_name_or_path]
															if init_max_model_length is not None and init_max_model_length != max_model_length:
																				return init_max_model_length
															elif init_max_model_length is None:
																				warnings.warn(
																				    """This tokenizer was incorrectly instantiated with a model max length of"""
																				    F''' {deprecated_max_model_length} which will be corrected in Transformers v5.\nFor now, this'''
																				    """ behavior is kept to avoid breaking backwards compatibility when padding/encoding with"""
																				    """ `truncation is True`.\n- Be aware that you SHOULD NOT rely on"""
																				    F''' {pretrained_model_name_or_path} automatically truncating your input to'''
																				    F''' {deprecated_max_model_length} when padding/encoding.\n- If you want to encode/pad to sequences'''
																				    F''' longer than {deprecated_max_model_length} you can either instantiate this tokenizer with'''
																				    """ `model_max_length` or pass `max_length` when encoding/padding.\n- To avoid this warning, please"""
																				    """ instantiate this tokenizer with `model_max_length` set to your preferred value."""							,					UpperCamelCase__							,					)

										return max_model_length

					def   UpperCAmelCase__       (     self       :   int							,					UpperCamelCase__       :   str							,					UpperCamelCase__       :   Optional[str] = None       ):






										'''simple docstring'''






										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(UpperCamelCase__       ):
															logger.error(F'''Vocabulary path ({save_directory}) should be a directory'''       )
															return
										lowercase_  							=			os.path.join(
										    UpperCamelCase__							,					(filename_prefix + """-""" if filename_prefix else """""") + VOCAB_FILES_NAMES["""vocab_file"""]       )

										if os.path.abspath(self.vocab_file       ) != os.path.abspath(UpperCamelCase__       ):
															copyfile(self.vocab_file							,					UpperCamelCase__       )
															logger.info(F'''Copy vocab file to {out_vocab_file}'''       )

										return (out_vocab_file,)

					def   UpperCAmelCase__       (     self       :   int							,					UpperCamelCase__       :   List[int]							,					UpperCamelCase__       :   Optional[List[int]] = None       ):






										'''simple docstring'''






										lowercase_  							=			token_ids_a + [self.eos_token_id]
										if token_ids_a is None:
															return self.prefix_tokens + token_ids_a
										else:
															lowercase_  							=			token_ids_a + [self.eos_token_id]
															return self.prefix_tokens + token_ids_a + token_ids_a

					def   UpperCAmelCase__       (     self       :   str							,					UpperCamelCase__       :   List[int]							,					UpperCamelCase__       :   Optional[List[int]] = None       ):






										'''simple docstring'''






										lowercase_  							=			[self.eos_token_id]

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

					def   UpperCAmelCase__       (     self       :   Dict       ):






										'''simple docstring'''






										return list(
										    set(filter(lambda UpperCamelCase__       : bool(re.search(R"""<extra_id_\d+>"""							,					UpperCamelCase__       )       ) is not None							,					self.additional_special_tokens       )       )       )







					def   UpperCAmelCase__       (     self       :   str       ):






										'''simple docstring'''






										return [self.convert_tokens_to_ids(UpperCamelCase__       ) for token in self.get_sentinel_tokens()]


