print(np.sign(arr))#sign计算各个元素的正负号,1为正数,-1为负数,0 1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 11. 12. 13. 14. 15. 二元数组 mod 元素级的取模% dot 点积 矩阵积 greater greater_equal less less_equal equal not_equal 元素级的比较运算,最终返回一个布尔型数组 logical_and lo...
b): return a / b def showTrue(flag): return flag class TestSomeFunc(unittest.TestCase): # 自定义测试类 继承unittest.TestCase def testrun(self): # 自定义测试方法 self.assertEqual('MC', showMsg('MC')) self.assertNotEqual('OK', showMsg('NO')) self.assertTrue(do_divdie(1, ...
TheassertItemsEqual/assertCountEqualfunction takes different code paths depending on whether or not the items in each list are hashable. And according to thedocs: If a class does not define a__cmp__()or__eq__()method it should not define a__hash__()operation either; if it defines__cm...
print data #[1,2,3] print type(arr) #<type 'numpy.ndarray'> print arr.dtype #int32 z = np.zeros((8,8),dtype=int) arr=np.random.randn(8,4) arr.ndim #维度 arr.dtype.name #类型名 a.size 元素总数 arr.astype(np.float) #astype做了复制,并转换数据类型,数组本身不变,使用astype将f...
fmod(x, y) is exactly (mathematically; to infinite precision) equal to x - n*y for some integer n such that the result has the same sign as x and magnitude less than abs(y). x % y returns a result with the sign of y instead, and may not be exactly computable for float ...
if not o or not isinstance(o, User): return False ... return self.name == o.name >>> s = set() >>> s.add(User("tom")) >>> s.add(User("tom")) >>> s set([<__main__.User object at 0x10a48d150>]) 数据结构很重要,这⼏几个内置类型并不⾜足以完成全部⼯工作.像 C...
must be a list of strings with the names of the long options which should be supported. The leading '--' characters should not be included in the option name. Long options which require an argument should be followed by an equal sign ('='). Optional arguments are not supported. To acce...
assertEqual(a, b) assertTrue(x) assertFalse(x) assertIs(a, b) assertIsNone(x) assertIn(a, b) assertNotIn(a, b) 报告生成展示 在命令行执行命令:pytest运行用例后,会得到一个测试报告的原始文件,但这个时候还不能打开成HTML的报告,还需要在项目根目录下,执行命令启动allure服务。下图是个结果测试结...
if layer.bias is not None: torch.nn.init.constant_(layer.bias, val=0.0) elif isinstance(layer, torch.nn.BatchNorm2d): torch.nn.init.constant_(layer.weight, val=1.0) torch.nn.init.constant_(layer.bias, val=0.0) elif isinstance(layer, torch.nn.Linear): ...
The great thing about einsum however, is that it does not build a temporary array of products first; it just sums the products as it goes. This can lead to big savings in memory use. A slightly bigger example To explain the dot product, here are two new arrays: A = array([[1, 1...