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


SCREAMING_SNAKE_CASE							:str										=    logging.get_logger(__name__)

SCREAMING_SNAKE_CASE							:Optional[Any]										=    {
    '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				(  __SCREAMING_SNAKE_CASE  ):




	'''simple docstring'''





	snake_case_    =					"rwkv"
	snake_case_    =					{"max_position_embeddings": "context_length"}






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

					__A             =			bos_token_id
					__A             =			eos_token_id

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


from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available


SCREAMING_SNAKE_CASE							:Any										=    {
    'configuration_rag': ['RagConfig'],
    'retrieval_rag': ['RagRetriever'],
    'tokenization_rag': ['RagTokenizer'],
}

try:
					if not is_torch_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					SCREAMING_SNAKE_CASE							:List[Any]										=    [
					    'RagModel',
					    'RagPreTrainedModel',
					    'RagSequenceForGeneration',
					    'RagTokenForGeneration',
					]

try:
					if not is_tf_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					SCREAMING_SNAKE_CASE							:Any										=    [
					    'TFRagModel',
					    'TFRagPreTrainedModel',
					    'TFRagSequenceForGeneration',
					    'TFRagTokenForGeneration',
					]


if TYPE_CHECKING:
					from .configuration_rag import RagConfig
					from .retrieval_rag import RagRetriever
					from .tokenization_rag import RagTokenizer

					try:
										if not is_torch_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .modeling_rag import RagModel, RagPreTrainedModel, RagSequenceForGeneration, RagTokenForGeneration

					try:
										if not is_tf_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .modeling_tf_rag import (
										    TFRagModel,
										    TFRagPreTrainedModel,
										    TFRagSequenceForGeneration,
										    TFRagTokenForGeneration,
										)

else:
					import sys

					SCREAMING_SNAKE_CASE							:int										=    _LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)
