






"""simple docstring"""
from typing import List, Optional, Union

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


lowerCamelCase_							      = logging.get_logger(__name__)

lowerCamelCase_							      = {
    '''huggingface/informer-tourism-monthly''': (
        '''https://huggingface.co/huggingface/informer-tourism-monthly/resolve/main/config.json'''
    ),
    # See all Informer models at https://huggingface.co/models?filter=informer
}







class      UpperCamelCase_			(__A	):
	__magic_name__       =							'''informer'''
	__magic_name__       =							{
	    '''hidden_size''': '''d_model''',
	    '''num_attention_heads''': '''encoder_attention_heads''',
	    '''num_hidden_layers''': '''encoder_layers''',
	}





	def __init__( self   :					Optional[Any]      ,      lowerCAmelCase_   :					Optional[int] = None      ,      lowerCAmelCase_   :					Optional[int] = None      ,      lowerCAmelCase_   :					str = "student_t"      ,      lowerCAmelCase_   :					str = "nll"      ,      lowerCAmelCase_   :					int = 1      ,      lowerCAmelCase_   :					List[int] = None      ,      lowerCAmelCase_   :					Optional[Union[str, bool]] = "mean"      ,      lowerCAmelCase_   :					int = 0      ,      lowerCAmelCase_   :					int = 0      ,      lowerCAmelCase_   :					int = 0      ,      lowerCAmelCase_   :					int = 0      ,      lowerCAmelCase_   :					Optional[List[int]] = None      ,      lowerCAmelCase_   :					Optional[List[int]] = None      ,      lowerCAmelCase_   :					int = 64      ,      lowerCAmelCase_   :					int = 32      ,      lowerCAmelCase_   :					int = 32      ,      lowerCAmelCase_   :					int = 2      ,      lowerCAmelCase_   :					int = 2      ,      lowerCAmelCase_   :					int = 2      ,      lowerCAmelCase_   :					int = 2      ,      lowerCAmelCase_   :					bool = True      ,      lowerCAmelCase_   :					str = "gelu"      ,      lowerCAmelCase_   :					float = 0.0_5      ,      lowerCAmelCase_   :					float = 0.1      ,      lowerCAmelCase_   :					float = 0.1      ,      lowerCAmelCase_   :					float = 0.1      ,      lowerCAmelCase_   :					float = 0.1      ,      lowerCAmelCase_   :					int = 100      ,      lowerCAmelCase_   :					float = 0.0_2      ,      lowerCAmelCase_   :					List[Any]=True      ,      lowerCAmelCase_   :					str = "prob"      ,      lowerCAmelCase_   :					int = 5      ,      lowerCAmelCase_   :					bool = True      ,      **lowerCAmelCase_   :					Tuple      ,      )		->     Tuple:
				# time series specific configuration
				UpperCAmelCase_	:					str     	=   prediction_length
				UpperCAmelCase_	:					Tuple     	=   context_length or prediction_length
				UpperCAmelCase_	:					Any     	=   distribution_output
				UpperCAmelCase_	:					Union[str, Any]     	=   loss
				UpperCAmelCase_	:					Any     	=   input_size
				UpperCAmelCase_	:					int     	=   num_time_features
				UpperCAmelCase_	:					Union[str, Any]     	=   lags_sequence if lags_sequence is not None else [1, 2, 3, 4, 5, 6, 7]
				UpperCAmelCase_	:					List[Any]     	=   scaling
				UpperCAmelCase_	:					List[str]     	=   num_dynamic_real_features
				UpperCAmelCase_	:					int     	=   num_static_real_features
				UpperCAmelCase_	:					Any     	=   num_static_categorical_features

				# set cardinality
				if cardinality and num_static_categorical_features > 0:
							if len(lowerCAmelCase_		) != num_static_categorical_features:
										raise ValueError(
										    "The cardinality should be a list of the same length as `num_static_categorical_features`"		)
							UpperCAmelCase_	:					Optional[Any]     	=   cardinality
				else:
							UpperCAmelCase_	:					Optional[int]     	=   [0]

				# set embedding_dimension
				if embedding_dimension and num_static_categorical_features > 0:
							if len(lowerCAmelCase_		) != num_static_categorical_features:
										raise ValueError(
										    "The embedding dimension should be a list of the same length as `num_static_categorical_features`"		)
							UpperCAmelCase_	:					Any     	=   embedding_dimension
				else:
							UpperCAmelCase_	:					Optional[Any]     	=   [min(50      ,      (cat + 1) // 2		) for cat in self.cardinality]

				UpperCAmelCase_	:					Dict     	=   num_parallel_samples

				# Transformer architecture configuration
				UpperCAmelCase_	:					Optional[Any]     	=   input_size * len(self.lags_sequence		) + self._number_of_features
				UpperCAmelCase_	:					List[Any]     	=   d_model
				UpperCAmelCase_	:					List[str]     	=   encoder_attention_heads
				UpperCAmelCase_	:					List[str]     	=   decoder_attention_heads
				UpperCAmelCase_	:					Union[str, Any]     	=   encoder_ffn_dim
				UpperCAmelCase_	:					Union[str, Any]     	=   decoder_ffn_dim
				UpperCAmelCase_	:					Tuple     	=   encoder_layers
				UpperCAmelCase_	:					List[Any]     	=   decoder_layers

				UpperCAmelCase_	:					List[str]     	=   dropout
				UpperCAmelCase_	:					Optional[Any]     	=   attention_dropout
				UpperCAmelCase_	:					Any     	=   activation_dropout
				UpperCAmelCase_	:					Union[str, Any]     	=   encoder_layerdrop
				UpperCAmelCase_	:					Optional[int]     	=   decoder_layerdrop

				UpperCAmelCase_	:					Union[str, Any]     	=   activation_function
				UpperCAmelCase_	:					int     	=   init_std

				UpperCAmelCase_	:					Optional[Any]     	=   use_cache

				# Informer
				UpperCAmelCase_	:					int     	=   attention_type
				UpperCAmelCase_	:					List[str]     	=   sampling_factor
				UpperCAmelCase_	:					Union[str, Any]     	=   distil

				super().__init__(is_encoder_decoder=lowerCAmelCase_      ,      **lowerCAmelCase_		)





	@property
	def 	_SCREAMING_SNAKE_CASE ( self   :					List[Any]		)		->     int:
				return (
				    sum(self.embedding_dimension		)
				    + self.num_dynamic_real_features
				    + self.num_time_features
				    + self.num_static_real_features
				    + self.input_size * 2  # the log1p(abs(loc)) and log(scale) features
				)











"""simple docstring"""
from __future__ import annotations

from fractions import Fraction
from math import gcd, sqrt

def 							snake_case (  A__		):
			UpperCAmelCase_	:					int     	=   int(number**0.5		)
			return number == sq * sq

def 							snake_case (  A__      ,A__      ,A__      ,A__      ,A__      ,A__		):
			UpperCAmelCase_	:					int     	=   x_num * y_den * z_den + y_num * x_den * z_den + z_num * x_den * y_den
			UpperCAmelCase_	:					int     	=   x_den * y_den * z_den
			UpperCAmelCase_	:					int     	=   gcd(A__      ,A__		)
			top //= hcf
			bottom //= hcf
			return top, bottom

def 							snake_case (  A__ = 35		):
			UpperCAmelCase_	:					set     	=   set()
			UpperCAmelCase_	:					int
			UpperCAmelCase_	:					Fraction     	=   Fraction(0		)
			UpperCAmelCase_	:					tuple[int, int]

			for x_num in range(1      ,order + 1		):
						for x_den in range(x_num + 1      ,order + 1		):
									for y_num in range(1      ,order + 1		):
												for y_den in range(y_num + 1      ,order + 1		):
															# n=1
															UpperCAmelCase_	:					Optional[int]     	=   x_num * y_den + x_den * y_num
															UpperCAmelCase_	:					List[Any]     	=   x_den * y_den
															UpperCAmelCase_	:					Tuple     	=   gcd(A__      ,A__		)
															z_num //= hcf
															z_den //= hcf
															if 0 < z_num < z_den <= order:
																		UpperCAmelCase_	:					int     	=   add_three(
																		    A__      ,A__      ,A__      ,A__      ,A__      ,A__		)
																		unique_s.add(A__		)

															# n=2
															UpperCAmelCase_	:					Optional[Any]     	=   (
															    x_num * x_num * y_den * y_den + x_den * x_den * y_num * y_num
															)
															UpperCAmelCase_	:					Dict     	=   x_den * x_den * y_den * y_den
															if is_sq(A__		) and is_sq(A__		):
																		UpperCAmelCase_	:					int     	=   int(sqrt(A__		)		)
																		UpperCAmelCase_	:					Any     	=   int(sqrt(A__		)		)
																		UpperCAmelCase_	:					str     	=   gcd(A__      ,A__		)
																		z_num //= hcf
																		z_den //= hcf
																		if 0 < z_num < z_den <= order:
																					UpperCAmelCase_	:					Tuple     	=   add_three(
																					    A__      ,A__      ,A__      ,A__      ,A__      ,A__		)
																					unique_s.add(A__		)

                    # n=-1
															UpperCAmelCase_	:					Optional[int]     	=   x_num * y_num
															UpperCAmelCase_	:					Dict     	=   x_den * y_num + x_num * y_den
															UpperCAmelCase_	:					Union[str, Any]     	=   gcd(A__      ,A__		)
															z_num //= hcf
															z_den //= hcf
															if 0 < z_num < z_den <= order:
																		UpperCAmelCase_	:					List[Any]     	=   add_three(
																		    A__      ,A__      ,A__      ,A__      ,A__      ,A__		)
																		unique_s.add(A__		)

															# n=2
															UpperCAmelCase_	:					Optional[Any]     	=   x_num * x_num * y_num * y_num
															UpperCAmelCase_	:					Dict     	=   (
															    x_den * x_den * y_num * y_num + x_num * x_num * y_den * y_den
															)
															if is_sq(A__		) and is_sq(A__		):
																		UpperCAmelCase_	:					str     	=   int(sqrt(A__		)		)
																		UpperCAmelCase_	:					int     	=   int(sqrt(A__		)		)
																		UpperCAmelCase_	:					Optional[Any]     	=   gcd(A__      ,A__		)
																		z_num //= hcf
																		z_den //= hcf
																		if 0 < z_num < z_den <= order:
																					UpperCAmelCase_	:					Optional[int]     	=   add_three(
																					    A__      ,A__      ,A__      ,A__      ,A__      ,A__		)
																					unique_s.add(A__		)

			for num, den in unique_s:
						total += Fraction(A__      ,A__		)

			return total.denominator + total.numerator


if __name__ == "__main__":
			print(f'{solution() = }')



