




import numpy as np




def  a_		(							__snake_case     ,		__snake_case					)	->			List[Any]:

			'''simple docstring'''


			UpperCamelCase_     				= np.array(UpperCAmelCase_					)
			UpperCamelCase_     				= np.array(UpperCAmelCase_					)

			UpperCamelCase_     				= abs(predict - actual					)
			UpperCamelCase_     				= difference.mean()

			return score




def  a_		(							__snake_case     ,		__snake_case					)	->			int:

			'''simple docstring'''


			UpperCamelCase_     				= np.array(UpperCAmelCase_					)
			UpperCamelCase_     				= np.array(UpperCAmelCase_					)

			UpperCamelCase_     				= predict - actual
			UpperCamelCase_     				= np.square(UpperCAmelCase_					)

			UpperCamelCase_     				= square_diff.mean()
			return score




def  a_		(							__snake_case     ,		__snake_case					)	->			Tuple:

			'''simple docstring'''


			UpperCamelCase_     				= np.array(UpperCAmelCase_					)
			UpperCamelCase_     				= np.array(UpperCAmelCase_					)

			UpperCamelCase_     				= predict - actual
			UpperCamelCase_     				= np.square(UpperCAmelCase_					)
			UpperCamelCase_     				= square_diff.mean()
			UpperCamelCase_     				= np.sqrt(UpperCAmelCase_					)
			return score




def  a_		(							__snake_case     ,		__snake_case					)	->			List[str]:

			'''simple docstring'''


			UpperCamelCase_     				= np.array(UpperCAmelCase_					)
			UpperCamelCase_     				= np.array(UpperCAmelCase_					)

			UpperCamelCase_     				= np.log(predict + 1					)
			UpperCamelCase_     				= np.log(actual + 1					)

			UpperCamelCase_     				= log_predict - log_actual
			UpperCamelCase_     				= np.square(UpperCAmelCase_					)
			UpperCamelCase_     				= square_diff.mean()

			UpperCamelCase_     				= np.sqrt(UpperCAmelCase_					)

			return score




def  a_		(							__snake_case     ,		__snake_case					)	->			str:

			'''simple docstring'''


			UpperCamelCase_     				= np.array(UpperCAmelCase_					)
			UpperCamelCase_     				= np.array(UpperCAmelCase_					)

			UpperCamelCase_     				= predict - actual
			UpperCamelCase_     				= np.sum(UpperCAmelCase_					) / len(UpperCAmelCase_					)
			UpperCamelCase_     				= np.sum(UpperCAmelCase_					) / len(UpperCAmelCase_					)
			# print(numerator, denumerator)
			UpperCamelCase_     				= float(UpperCAmelCase_					) / denumerator * 1_0_0

			return score





def  a_		(							__snake_case     ,		__snake_case					)	->			Any:

			'''simple docstring'''


			return np.mean(np.array(UpperCAmelCase_					) == np.array(UpperCAmelCase_					)					)





'''simple docstring'''







def 			_lowerCAmelCase(      UpperCAmelCase_      :	str						) ->							str:
							lowerCAmelCase__  =   word.upper()
							lowerCAmelCase__  =   0
							lowerCAmelCase__  =   {}
							lowerCAmelCase__  =   []

							for letter in word:
														if letter not in letter_nums:
																					lowerCAmelCase__  =   str(UpperCAmelCase_						)
																					next_num += 1
														word_pattern.append(letter_nums[letter]						)
							return ".".join(UpperCAmelCase_						)


if __name__ == "__main__":
		import pprint
		import time

		_UpperCamelCase  						=			time.time()
		with open("""dictionary.txt""") as in_file:
				_UpperCamelCase  						=			in_file.read().splitlines()

		_UpperCamelCase  						=			{}
		for word in word_list:
				_UpperCamelCase  						=			get_word_pattern(word)
				if pattern in all_patterns:
						all_patterns[pattern].append(word)
				else:
						_UpperCamelCase  						=			[word]

		with open("""word_patterns.txt""", """w""") as out_file:
				out_file.write(pprint.pformat(all_patterns))

		_UpperCamelCase  						=			round(time.time() - start_time, 2)
		print(f'Done!  {len(all_patterns):,} word patterns found in {total_time} seconds.')
		# Done!  9,581 word patterns found in 0.58 seconds.





