remove_punctuation, str.title] def clean_strings(strings, ops): result = [] for valu...
fromsklearn.neural_networkimportMLPClassifier nn_model= MLPClassifier(activation ='logistic', max_iter = 10)#Sigmoid Activation Functionparam_grid = {'learning_rate_init': [0.001, 0.0015, 0.002, 0.0025]} grid_nn_model= HalvingGridSearchCV(nn_model, param_grid = param_grid, n_jobs = -1, ...
defmy_function(x,y,z=1.5):# 可以指定参数的默认值ifz>1:print(z*(x+y))else:print(z/(x+y))# 函数调用的几种方法my_function(5,6,z=0.7)my_function(3.14,7,3.5)my_function(z=3.14,x=7,y=3.5)# 可以通过等式指定参数顺序 这么做有助于代码可读性my_function(10,20)0.0636363636363636335.493...
defremove_punctuation(value):returnre.sub('[!#?]','', value) clean_ops= [str.strip, remove_punctuation, str.title]#函数列表defclean_strings(strings, ops): result=[]forvalueinstrings:forfunctioninops: value=function(value) result.append(value)returnresult clean_strings(states, clean_ops)#调...
defremove_punctuation(value): returnre.sub('[!#?]', '', value) clean_ops = [str.strip, remove_punctuation, str.title] defclean_strings(strings, ops): result = [] forvalueinstrings: forfunctioninops: value = function(value) result.append(value) ...
]', '', value) // 去除空格、移除标点符号、适当调整大小写 clean_ops = [str.strip, remove_punctuation, str.title] // 清洗字符串列表 def clean_strings(strings, ops): result = [] for value in strings: for function in ops: value = function(value) result.append(value) return result ...
text=("this sentence's content includes: characters, spaces, and "\"punctuation.")# Define helperfunctionto display pre-tokenized output defprint_pretokenized_str(pre_tokens):forpre_tokeninpre_tokens:print(f'"{pre_token[0]}", ',end='')# Instantiate pre-tokenizers ...
from tokenizers.pre_tokenizers import WhitespaceSplit, BertPreTokenizer# Text to normalizetext = ("this sentence's content includes: characters, spaces, and "\"punctuation.")#Definehelper function to display pre-tokenized outputdef print_pretokenized_str(pre_tokens):forpre_token in pre_tokens:pri...
As programs become more complicated, it becomes increasingly beneficial to modularize them in this way. Remove ads Namespace Separation A namespace is a region of a program in which identifiers have meaning. As you’ll see below, when a Python function is called, a new namespace is created ...
#Given an array nums, write a function to move all zeroes to the end of it while maintaining the relative order of #the non-zero elements. array1 = [0,1,0,3,12]array2 = [1,7,0,0,8,0,10,12,0,4] def solution(nums): for i in nums: if 0 in nums: nums.remove(0) nums...