defflip_boolean(value):return1ifnotvalueelse0# 测试print(flip_boolean(1))# 输出: 0print(flip_boolean(0))# 输出: 1 1. 2. 3. 4. 5. 6. 在这个示例中,我们定义了一个flip_boolean函数,该函数接收一个布尔值,并返回它的相反值。 使用XOR 运算 除了使用not运算符,我们也可以用异或运算(XOR)来实...
例如,如果我们使用红色箭头在 3D 视口中平移立方体,我们会得到命令日志中清单 1-1 所示的输出。 bpy.ops.transform.translate(value=(3.05332,0,0), constraint_axis=(True,False,False), constraint_orientation='GLOBAL', mirror=False, proportional='DISABLED', proportional_edit_falloff='SMOOTH', proportional_...
9 boolean bitsChanged = false; 10 /** 遍历每个哈希函数 */ 11 for (int i = 1; i <= numHashFunctions; i++) { 12 int combinedHash = hash1 + (i * hash2); 13 // Flip all the bits if it's negative (guaranteed positive number) 14 if (combinedHash < 0) { 15 combinedHash =...
sys.modules: 已经加载的模块信息字典,key为模块名称,value为模块对象,在使用__import__导入模块时,可以先判断下是否有同名模块已经在sys.modules中加载了,如果已经存在了,可以先删除或者不再导入了。 以字典类型返回系统导入的模块。 sys.getsizeof(object): 获取一个对象的内存占用字节数大小。 sys.getdefaultenco...
1. The first point. 2. The second point. 3. The third point. 4. The fourth point. 5. The fifth point.The code imports the random module and assigns a Boolean value to 'a', generated randomly using the randint function from the random module. The value of 'a' is then printed. ...
import numpy as np arr = np.array([-1, 2, 0, -4, 5]) boolean_arr = arr > 0 print(boolean_arr) [False True False False True] 练习7: 将一维数组中的所有偶数替换为其负数。 import numpy as np arr = np.arange(1, 10) arr[arr % 2 == 0] *= -1 print(arr) ...
Here’s our current function, which returns a boolean value (i.e., one thing): It’s a trivial edit to have the function return multiple values (in one set) as opposed to a boolean. All we need to do is drop the call tobool: ...
Note that nan is a special value which is never equal to anything else, including itself! That’s why you’re seeing a solitary False in the output above. In addition to these, cmath provides two complex counterparts for NaN (not a number) and infinity, with both having zero real parts...
def flip[T0, T1](pair: tuple[T0, T1]) -> tuple[T1, T0]: first, second = pair return (second, first) Here, T0 and T1 are two independent type variables. They can take on different types, but they may also be the same. For example, maybe you pass in a pair of Booleans....
torch.eq(input, other, *, out=None) 1 Parameters(参数): input :必须是一个Tensor,该张量用于比较 other :可以是一个张量Tensor,也可以是一个值value return(返回值):返回一个Boolean类型的张量,对两个张量Tensor进行逐元素的比较,若相同位置的两个元素相同,则返回True;若不同,返回False。 神经网络 网络...