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


SCREAMING_SNAKE_CASE							:Optional[int]										=    logging.get_logger(__name__)

SCREAMING_SNAKE_CASE							:Any										=    {
    'facebook/nllb-moe-54B': 'https://huggingface.co/facebook/nllb-moe-54b/resolve/main/config.json',
}





class 							UpperCAmelCase				(  __SCREAMING_SNAKE_CASE  ):




	'''simple docstring'''





	snake_case_    =					"nllb-moe"
	snake_case_    =					["past_key_values"]
	snake_case_    =					{"num_attention_heads": "encoder_attention_heads", "hidden_size": "d_model"}






	def __init__(	self :			Union[str, Any]							,A :			List[str]=12_81_12							,A :			Dict=10_24							,A :			Optional[int]=12							,A :			str=40_96							,A :			Optional[int]=16							,A :			Tuple=12							,A :			Union[str, Any]=40_96							,A :			List[Any]=16							,A :			Optional[int]=0.05							,A :			List[Any]=0.05							,A :			List[Any]=True							,A :			Union[str, Any]=True							,A :			Tuple="relu"							,A :			Optional[int]=10_24							,A :			List[Any]=0.1							,A :			Union[str, Any]=0.1							,A :			Tuple=0.0							,A :			int=0.02							,A :			Union[str, Any]=2							,A :			Dict=True							,A :			Optional[int]=False							,A :			Dict="float32"							,A :			Dict=False							,A :			List[Any]=1_28							,A :			Optional[Any]=64							,A :			List[Any]=4							,A :			Dict=4							,A :			Union[str, Any]=0.0_01							,A :			Dict=0.0_01							,A :			Union[str, Any]="all"							,A :			Optional[Any]=False							,A :			Union[str, Any]=False							,A :			Dict=1.0							,A :			int=0.2							,A :			Dict=1							,A :			Dict=0							,A :			Any=2							,A :			int=False							,**A :			List[Any]							,):
					__A             =			vocab_size
					__A             =			max_position_embeddings
					__A             =			d_model
					__A             =			encoder_ffn_dim
					__A             =			encoder_layers
					__A             =			encoder_attention_heads
					__A             =			decoder_ffn_dim
					__A             =			decoder_layers
					__A             =			decoder_attention_heads
					__A             =			dropout
					__A             =			attention_dropout
					__A             =			activation_dropout
					__A             =			activation_function
					__A             =			init_std
					__A             =			encoder_layerdrop
					__A             =			decoder_layerdrop
					__A             =			use_cache
					__A             =			encoder_layers
					__A             =			scale_embedding  # scale factor will be sqrt(d_model) if True
					__A             =			router_z_loss_coef
					__A             =			router_aux_loss_coef
					__A             =			decoder_sparse_step
					__A             =			encoder_sparse_step
					__A             =			num_experts
					__A             =			expert_capacity
					__A             =			router_bias
					if router_dtype not in ["float32", "float16", "bfloat16"]:
									raise ValueError(f'''`router_dtype` must be one of \'float32\', \'float16\' or \'bfloat16\', got {router_dtype}'''			)
					__A             =			router_dtype

					__A             =			router_ignore_padding_tokens
					__A             =			batch_prioritized_routing
					__A             =			second_expert_policy
					__A             =			normalize_router_prob_before_dropping
					__A             =			moe_eval_capacity_token_fraction
					__A             =			moe_token_dropout
					__A             =			output_router_logits
					super().__init__(
					    pad_token_id=A							,bos_token_id=A							,eos_token_id=A							,is_encoder_decoder=A							,decoder_start_token_id=A							,**A							,)


from __future__ import annotations

import math
from collections import Counter
from string import ascii_lowercase


def 						UpperCAmelCase      (     a_						)		->     None:







				"""simple docstring"""



				__A      ,							__A             =			analyze_text(a_						)
				__A             =			list(" " + ascii_lowercase						)
				# what is our total sum of probabilities.
				__A             =			sum(single_char_strings.values()						)

				# one length string
				__A             =			0
				# for each alpha we go in our dict and if it is in it we calculate entropy
				for ch in my_alphas:
								if ch in single_char_strings:
												__A             =			single_char_strings[ch]
												__A             =			my_str / all_sum
												my_fir_sum += prob * math.loga(a_						)  # entropy formula.

    # print entropy
				print(F'''{round(-1 * my_fir_sum						):.1f}'''						)

				# two len string
				__A             =			sum(two_char_strings.values()						)
				__A             =			0
				# for each alpha (two in size) calculate entropy.
				for cha in my_alphas:
								for cha in my_alphas:
												__A             =			cha + cha
												if sequence in two_char_strings:
																__A             =			two_char_strings[sequence]
																__A             =			int(a_						) / all_sum
																my_sec_sum += prob * math.loga(a_						)

    # print second entropy
				print(F'''{round(-1 * my_sec_sum						):.1f}'''						)

				# print the difference between them
				print(F'''{round((-1 * my_sec_sum) - (-1 * my_fir_sum)						):.1f}'''						)


def 						UpperCAmelCase      (     a_						)		->     tuple[dict, dict]:







				"""simple docstring"""



				__A             =			Counter()  # type: ignore
				__A             =			Counter()  # type: ignore
				single_char_strings[text[-1]] += 1

				# first case when we have space at start.
				two_char_strings[" " + text[0]] += 1
				for i in range(0		,       len(a_						) - 1						):
								single_char_strings[text[i]] += 1
								two_char_strings[text[i : i + 2]] += 1
				return single_char_strings, two_char_strings


def 						UpperCAmelCase      (     )		->     Optional[Any]:







				"""simple docstring"""



				import doctest

				doctest.testmod()
				# text = (
				#     "Had repulsive dashwoods suspicion sincerity but advantage now him. Remark "
				#     "easily garret nor nay. Civil those mrs enjoy shy fat merry. You greatest "
				#     "jointure saw horrible. He private he on be imagine suppose. Fertile "
				#     "beloved evident through no service elderly is. Blind there if every no so "
				#     "at. Own neglected you preferred way sincerity delivered his attempted. To "
				#     "of message cottage windows do besides against uncivil.  Delightful "
				#     "unreserved impossible few estimating men favourable see entreaties. She "
				#     "propriety immediate was improving. He or entrance humoured likewise "
				#     "moderate. Much nor game son say feel. Fat make met can must form into "
				#     "gate. Me we offending prevailed discovery. "
				# )

				# calculate_prob(text)


if __name__ == "__main__":
					main()
