from __future__ import annotations

from collections.abc import Callable
from typing import Generic, TypeVar

_snake_case			=						TypeVar('''T''')
_snake_case			=						TypeVar('''U''')




class 					_snake_case						(						Generic[T, U]				):
					def __init__(  self:				Tuple	,  __lowerCamelCase:				T | None	,  __lowerCamelCase:				U | None     )    ->				int:
												__UpperCAmelCase						:			Union[str, Any]         =   key
												__UpperCAmelCase						:			int         =   val
												__UpperCAmelCase						:			int         =   0
												__UpperCAmelCase						:			DoubleLinkedListNode[T, U] | None         =   None
												__UpperCAmelCase						:			DoubleLinkedListNode[T, U] | None         =   None





					def __repr__(  self:				List[str]     )    ->				str:
												return "Node: key: {}, val: {}, freq: {}, has next: {}, has prev: {}".format(
												    self.key	,  self.val	,  self.freq	,  self.next is not None	,  self.prev is not None     )




class 					_snake_case						(						Generic[T, U]				):
					def __init__(  self:				str     )    ->				None:
												__UpperCAmelCase						:			DoubleLinkedListNode[T, U]         =   DoubleLinkedListNode(__lowerCamelCase	,  __lowerCamelCase     )
												__UpperCAmelCase						:			DoubleLinkedListNode[T, U]         =   DoubleLinkedListNode(__lowerCamelCase	,  __lowerCamelCase     )
												__UpperCAmelCase    ,	__UpperCAmelCase						:			List[str]         =   self.rear, self.head
					def __repr__(  self:				Optional[int]     )    ->				str:
												__UpperCAmelCase						:			Optional[int]         =   ["DoubleLinkedList"]
												__UpperCAmelCase						:			List[str]         =   self.head
												while node.next is not None:
																			rep.append(str(__lowerCamelCase     )     )
																			__UpperCAmelCase						:			Any         =   node.next
												rep.append(str(self.rear     )     )
												return ",\n    ".join(__lowerCamelCase     )
					def    _lowerCamelCase (  self:				str	,  __lowerCamelCase:				DoubleLinkedListNode[T, U]     )    ->				None:
												__UpperCAmelCase						:			List[str]         =   self.rear.prev

												# All nodes other than self.head are guaranteed to have non-None previous
												assert previous is not None

												__UpperCAmelCase						:			Tuple         =   node
												__UpperCAmelCase						:			Dict         =   previous
												__UpperCAmelCase						:			Tuple         =   node
												__UpperCAmelCase						:			Any         =   self.rear
												node.freq += 1
												self._position_node(__lowerCamelCase     )
					def    _lowerCamelCase (  self:				Optional[Any]	,  __lowerCamelCase:				DoubleLinkedListNode[T, U]     )    ->				None:

												while node.prev is not None and node.prev.freq > node.freq:
																			# swap node with previous node
																			__UpperCAmelCase						:			List[Any]         =   node.prev

																			__UpperCAmelCase						:			List[str]         =   previous_node.prev
																			__UpperCAmelCase						:			str         =   node.prev
																			__UpperCAmelCase						:			Optional[Any]         =   previous_node
																			__UpperCAmelCase						:			Any         =   node





					def    _lowerCamelCase (  self:				int	,  __lowerCamelCase:				DoubleLinkedListNode[T, U]     )    ->				DoubleLinkedListNode[T, U] | None:

												if node.prev is None or node.next is None:
																			return None

												__UpperCAmelCase						:			List[str]         =   node.next
												__UpperCAmelCase						:			List[Any]         =   node.prev
												__UpperCAmelCase						:			Optional[int]         =   None
												__UpperCAmelCase						:			Any         =   None
												return node




class 					_snake_case						(						Generic[T, U]				):
					lowerCamelCase__:		dict[Callable[[T], U], LFUCache[T, U]]  =     {}
					def __init__(  self:				Any	,  __lowerCamelCase:				int     )    ->				Dict:
												__UpperCAmelCase						:			DoubleLinkedList[T, U]         =   DoubleLinkedList()
												__UpperCAmelCase						:			Union[str, Any]         =   capacity
												__UpperCAmelCase						:			List[Any]         =   0
												__UpperCAmelCase						:			Any         =   0
												__UpperCAmelCase						:			Optional[int]         =   0
												__UpperCAmelCase						:			dict[T, DoubleLinkedListNode[T, U]]         =   {}
					def __repr__(  self:				Union[str, Any]     )    ->				str:
												return (
												    f'''CacheInfo(hits={self.hits}, misses={self.miss}, '''
												    f'''capacity={self.capacity}, current_size={self.num_keys})'''
												)
					def __contains__(  self:				Optional[int]	,  __lowerCamelCase:				T     )    ->				bool:
												return key in self.cache
					def    _lowerCamelCase (  self:				Dict	,  __lowerCamelCase:				T     )    ->				U | None:

												if key in self.cache:
																			self.hits += 1
																			__UpperCAmelCase						:			DoubleLinkedListNode[T, U]         =   self.cache[key]
																			__UpperCAmelCase						:			Union[str, Any]         =   self.list.remove(self.cache[key]     )
																			assert node == value_node

																			# node is guaranteed not None because it is in self.cache
																			assert node is not None
																			self.list.add(__lowerCamelCase     )
																			return node.val
												self.miss += 1
												return None
					def    _lowerCamelCase (  self:				Union[str, Any]	,  __lowerCamelCase:				T	,  __lowerCamelCase:				U     )    ->				None:

												if key not in self.cache:
																			if self.num_keys >= self.capacity:
																										# delete first node when over capacity
																										__UpperCAmelCase						:			Optional[int]         =   self.list.head.next

																										# guaranteed to have a non-None first node when num_keys > 0
																										# explain to type checker via assertions
																										assert first_node is not None
																										assert first_node.key is not None
																										assert self.list.remove(__lowerCamelCase     ) is not None
																										# first_node guaranteed to be in list

																										del self.cache[first_node.key]
																										self.num_keys -= 1
																			__UpperCAmelCase						:			List[str]         =   DoubleLinkedListNode(__lowerCamelCase	,  __lowerCamelCase     )
																			self.list.add(self.cache[key]     )
																			self.num_keys += 1

												else:
																			__UpperCAmelCase						:			Union[str, Any]         =   self.list.remove(self.cache[key]     )
																			assert node is not None  # node guaranteed to be in list
																			__UpperCAmelCase						:			Tuple         =   value
																			self.list.add(__lowerCamelCase     )





					@classmethod
					def    _lowerCamelCase (  cls:				type[LFUCache[T, U]]	,  __lowerCamelCase:				int = 1_28     )    ->				Callable[[Callable[[T], U]], Callable[..., U]]:

												def cache_decorator_inner(__lowerCamelCase:				Callable[[T], U]     ) -> Callable[..., U]:
																			def cache_decorator_wrapper(*__lowerCamelCase:				T     ) -> U:
																										if func not in cls.decorator_function_to_instance_map:
																																	__UpperCAmelCase						:			Dict         =   LFUCache(__lowerCamelCase     )

																										__UpperCAmelCase						:			Tuple         =   cls.decorator_function_to_instance_map[func].get(args[0]     )
																										if result is None:
																																	__UpperCAmelCase						:			Any         =   func(*__lowerCamelCase     )
																																	cls.decorator_function_to_instance_map[func].put(args[0]	,  __lowerCamelCase     )
																										return result

																			def cache_info() -> LFUCache[T, U]:
																										return cls.decorator_function_to_instance_map[func]

																			setattr(__lowerCamelCase	,  "cache_info"	,  __lowerCamelCase     )  # noqa: B010

																			return cache_decorator_wrapper

												return cache_decorator_inner


if __name__ == "__main__":
	import doctest

	doctest.testmod()





import numpy as np
import requests




def   _UpperCamelCase   (			)						->   Tuple:
							__UpperCAmelCase						:			Tuple         =   requests.get(
							    "https://raw.githubusercontent.com/yashLadha/The_Math_of_Intelligence/"
							    "master/Week1/ADRvsRating.csv"							)
							__UpperCAmelCase						:			List[Any]         =   response.text.splitlines()
							__UpperCAmelCase						:			Any         =   []
							for item in lines:
														__UpperCAmelCase						:			Any         =   item.split(","							)
														data.append(snake_case__							)
							data.pop(0							)  # This is for removing the labels from the list
							__UpperCAmelCase						:			List[str]         =   np.matrix(snake_case__							)
							return dataset




def   _UpperCamelCase   (			snake_case__,    snake_case__,    snake_case__,    snake_case__,    snake_case__							)						->   Optional[Any]:
							__UpperCAmelCase						:			Tuple         =   len_data

							__UpperCAmelCase						:			int         =   np.dot(snake_case__,    data_x.transpose()							)
							prod -= data_y.transpose()
							__UpperCAmelCase						:			Optional[int]         =   np.dot(snake_case__,    snake_case__							)
							__UpperCAmelCase						:			List[Any]         =   theta - (alpha / n) * sum_grad
							return theta




def   _UpperCamelCase   (			snake_case__,    snake_case__,    snake_case__,    snake_case__							)						->   Optional[int]:
							__UpperCAmelCase						:			Any         =   np.dot(snake_case__,    data_x.transpose()							)
							prod -= data_y.transpose()
							__UpperCAmelCase						:			Optional[int]         =   np.sum(np.square(snake_case__							)							)
							__UpperCAmelCase						:			List[Any]         =   sum_elem / (2 * len_data)
							return error




def   _UpperCamelCase   (			snake_case__,    snake_case__							)						->   Tuple:
							__UpperCAmelCase						:			Any         =   10_0000
							__UpperCAmelCase						:			Dict         =   0.000_1550

							__UpperCAmelCase						:			str         =   data_x.shape[1]
							__UpperCAmelCase						:			Any         =   data_x.shape[0] - 1

							__UpperCAmelCase						:			List[str]         =   np.zeros((1, no_features)							)

							for i in range(0,    snake_case__							):
														__UpperCAmelCase						:			Union[str, Any]         =   run_steep_gradient_descent(snake_case__,    snake_case__,    snake_case__,    snake_case__,    snake_case__							)
														__UpperCAmelCase						:			Any         =   sum_of_square_error(snake_case__,    snake_case__,    snake_case__,    snake_case__							)
														print(f'''At Iteration {i + 1} - Error is {error:.5f}'''							)

							return theta




def   _UpperCamelCase   (			snake_case__,    snake_case__							)						->   Optional[int]:
							__UpperCAmelCase						:			str         =   sum(abs(y - predicted_y[i]							) for i, y in enumerate(snake_case__							)							)
							return total / len(snake_case__							)




def   _UpperCamelCase   (			)						->   List[str]:
							__UpperCAmelCase						:			str         =   collect_dataset()

							__UpperCAmelCase						:			List[Any]         =   data.shape[0]
							__UpperCAmelCase						:			Union[str, Any]         =   np.c_[np.ones(snake_case__							), data[:, :-1]].astype(snake_case__							)
							__UpperCAmelCase						:			int         =   data[:, -1].astype(snake_case__							)

							__UpperCAmelCase						:			List[Any]         =   run_linear_regression(snake_case__,    snake_case__							)
							__UpperCAmelCase						:			List[str]         =   theta.shape[1]
							print("Resultant Feature vector : "							)
							for i in range(0,    snake_case__							):
														print(f'''{theta[0, i]:.5f}'''							)


if __name__ == "__main__":
	main()




