




"""simple docstring"""


from ...configuration_utils import PretrainedConfig






class 					lowercase(     __a ):







 '''simple docstring'''





 lowercase__ 					=					"bert-generation"


 def __init__(				self:		str,      a_:		str=50_358,      a_:		List[Any]=1_024,      a_:		Union[str, Any]=24,      a_:		int=16,      a_:		Union[str, Any]=4_096,      a_:		Union[str, Any]="gelu",      a_:		Tuple=0.1,      a_:		Any=0.1,      a_:		Union[str, Any]=512,      a_:		List[str]=0.02,      a_:		List[str]=1E-12,      a_:		Union[str, Any]=0,      a_:		Union[str, Any]=2,      a_:		List[Any]=1,      a_:		int="absolute",      a_:		Dict=True,      **a_:		List[Any],      ):




   '''simple docstring'''



   super().__init__(pad_token_id=a_,      bos_token_id=a_,      eos_token_id=a_,      **a_		)

   _snake_case							:		Optional[int]								=  vocab_size
   _snake_case							:		List[Any]								=  hidden_size
   _snake_case							:		str								=  num_hidden_layers
   _snake_case							:		Tuple								=  num_attention_heads
   _snake_case							:		Union[str, Any]								=  hidden_act
   _snake_case							:		Optional[Any]								=  intermediate_size
   _snake_case							:		Tuple								=  hidden_dropout_prob
   _snake_case							:		int								=  attention_probs_dropout_prob
   _snake_case							:		Any								=  max_position_embeddings
   _snake_case							:		List[str]								=  initializer_range
   _snake_case							:		Optional[Any]								=  layer_norm_eps
   _snake_case							:		List[Any]								=  position_embedding_type
   _snake_case							:		Tuple								=  use_cache








"""simple docstring"""




from math import ceil



def     a__ (				snake_case__       , snake_case__				)						->					Optional[int]:
			lowerCamelCase			      =					list(range(0       , snake_case__				)				)

			lowerCamelCase			      =					[item for sublist in list(device_map.values()				) for item in sublist]

			# Duplicate check
			lowerCamelCase			      =					[]
			for i in device_map_blocks:
						if device_map_blocks.count(snake_case__				) > 1 and i not in duplicate_blocks:
									duplicate_blocks.append(snake_case__				)
    # Missing blocks
			lowerCamelCase			      =					[i for i in blocks if i not in device_map_blocks]
			lowerCamelCase			      =					[i for i in device_map_blocks if i not in blocks]

			if len(snake_case__				) != 0:
						raise ValueError(
						    """Duplicate attention blocks specified in device_map. Attention blocks must be specified to one device."""
						    """ These attention blocks were specified more than once: """ + str(snake_case__				)				)
			if len(snake_case__				) != 0:
						raise ValueError(
						    """There are attention blocks for this model that are not specified in the device_map. Add these attention """
						    """blocks to a device on the device_map: """ + str(snake_case__				)				)
			if len(snake_case__				) != 0:
						raise ValueError(
						    """The device_map contains more attention blocks than this model has. Remove these from the device_map:"""
						    + str(snake_case__				)				)



def     a__ (				snake_case__       , snake_case__				)						->					List[Any]:
			lowerCamelCase			      =					list(range(snake_case__				)				)
			lowerCamelCase			      =					int(ceil(n_layers / len(snake_case__				)				)				)
			lowerCamelCase			      =					[layers[i : i + n_blocks] for i in range(0       , snake_case__       , snake_case__				)]

			return dict(zip(snake_case__       , snake_case__				)				)



