






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


lowercase  							=					logging.get_logger(__name__)

lowercase  							=					{
    '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_      (			snake_case_				):



	'''simple docstring'''




	lowerCAmelCase													= '''rwkv'''
	lowerCAmelCase													= {'''max_position_embeddings''': '''context_length'''}




	def __init__(       self       ,			a=5_02_77       ,			a=10_24       ,			a=40_96       ,			a=32       ,			a=None       ,			a=None       ,			a=1E-5       ,			a=0       ,			a=0       ,			a=6       ,			a=False       ,			a=True       ,			**a       ,			)       ->    List[str]:
								snake_case_				=							vocab_size
								snake_case_				=							context_length
								snake_case_				=							hidden_size
								snake_case_				=							num_hidden_layers
								snake_case_				=							attention_hidden_size if attention_hidden_size is not None else hidden_size
								snake_case_				=							intermediate_size if intermediate_size is not None else 4 * hidden_size
								snake_case_				=							layer_norm_epsilon
								snake_case_				=							rescale_every
								snake_case_				=							use_cache

								snake_case_				=							bos_token_id
								snake_case_				=							eos_token_id

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







from dataclasses import dataclass, field
from typing import ClassVar, Dict

from ..features import Features, Value
from .base import TaskTemplate







@dataclass(frozen=a			)
class 			__A( a			):
				snake_case_						   =    field(default='''language-modeling'''  ,   metadata={'''include_in_asdict_even_if_is_default''': True}			)

				snake_case_						   =    Features({'''text''': Value('''string'''			)}			)
				snake_case_						   =    Features({}			)
				snake_case_						   =    "text"




				@property
				def 				SCREAMING_SNAKE_CASE_		(     self				)    ->      Dict[str, str]:


								'''simple docstring'''




								return {self.text_column: "text"}