

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


SCREAMING_SNAKE_CASE_						=					logging.get_logger(__name__)

SCREAMING_SNAKE_CASE_						=					{
    'facebook/opt-125m': 'https://huggingface.co/facebook/opt-125m/blob/main/config.json',
    'facebook/opt-350m': 'https://huggingface.co/facebook/opt-350m/blob/main/config.json',
    'facebook/opt-1.3b': 'https://huggingface.co/facebook/opt-1.3b/blob/main/config.json',
    'facebook/opt-2.7b': 'https://huggingface.co/facebook/opt-2.7b/blob/main/config.json',
    'facebook/opt-6.7b': 'https://huggingface.co/facebook/opt-6.7b/blob/main/config.json',
    'facebook/opt-13b': 'https://huggingface.co/facebook/opt-13b/blob/main/config.json',
}

class  a     (		UpperCAmelCase ):
						_lowercase			  =	"opt"
						_lowercase			  =	["past_key_values"]


						def __init__(				self  ,    A_=50272  ,    A_=768  ,    A_=12  ,    A_=3072  ,    A_=2048  ,    A_=True  ,    A_=False  ,    A_=None  ,    A_=0.1  ,    A_=0.0  ,    A_=12  ,    A_="relu"  ,    A_=0.0  ,    A_=0.02  ,    A_=True  ,    A_=1  ,    A_=2  ,    A_=2  ,    A_=True  ,    A_=True  ,    **A_  ,    ):







										'''simple docstring'''


										super().__init__(
										    pad_token_id=A_  ,    bos_token_id=A_  ,    eos_token_id=A_  ,    **A_  ,    )
										_UpperCAmelCase				:						Dict       						=			vocab_size
										_UpperCAmelCase				:						Optional[Any]       						=			max_position_embeddings
										_UpperCAmelCase				:						Union[str, Any]       						=			num_attention_heads
										_UpperCAmelCase				:						str       						=			word_embed_proj_dim if word_embed_proj_dim is not None else hidden_size
										_UpperCAmelCase				:						Union[str, Any]       						=			ffn_dim
										_UpperCAmelCase				:						Tuple       						=			hidden_size
										_UpperCAmelCase				:						Tuple       						=			num_hidden_layers
										_UpperCAmelCase				:						List[str]       						=			dropout
										_UpperCAmelCase				:						List[str]       						=			attention_dropout
										_UpperCAmelCase				:						int       						=			activation_function
										_UpperCAmelCase				:						Tuple       						=			init_std
										_UpperCAmelCase				:						List[Any]       						=			layerdrop
										_UpperCAmelCase				:						List[Any]       						=			use_cache
										_UpperCAmelCase				:						Tuple       						=			do_layer_norm_before
										# We keep these variables at `True` for backward compatibility.
										_UpperCAmelCase				:						Optional[int]       						=			enable_bias
										_UpperCAmelCase				:						Any       						=			layer_norm_elementwise_affine

										# Note that the only purpose of `_remove_final_layer_norm` is to keep backward compatibility
										# with checkpoints that have been fine-tuned before transformers v4.20.1
										# see https://github.com/facebookresearch/metaseq/pull/164
										_UpperCAmelCase				:						List[str]       						=			_remove_final_layer_norm





from __future__ import annotations

SCREAMING_SNAKE_CASE_						=					'Alexander Joslin'

def 							__SCREAMING_SNAKE_CASE							( lowerCAmelCase:     int       )      ->				int:

				if number <= 0:
								_UpperCAmelCase				:						Optional[Any]       						=			F'n must be greater than 0. Got n = {number}'
								raise ValueError(lowerCAmelCase       )

				_UpperCAmelCase				:						Dict       						=			[number + 1] * (number + 1)

				# starting position
				_UpperCAmelCase				:						Dict       						=			0
				for i in range(1     ,					lowerCAmelCase       ):
								_UpperCAmelCase				:						int       						=			min(table[i + 1]     ,					table[i] + 1       )
								# check if out of bounds
								if i * 2 <= number:
												_UpperCAmelCase				:						int       						=			min(table[i * 2]     ,					table[i] + 1       )
								# check if out of bounds
								if i * 3 <= number:
												_UpperCAmelCase				:						int       						=			min(table[i * 3]     ,					table[i] + 1       )
				return table[number]


if __name__ == "__main__":
					import doctest

					doctest.testmod()


