Python torch 模块，lerp() 实例源码

我们从Python开源项目中，提取了以下5个代码示例，用于说明如何使用torch.lerp()。

项目：pytorch-dist 作者：apaszke | 项目源码 | 文件源码

def test_lerp(self):
        def TH_lerp(a, b, weight):
            return a + weight * (b-a);

        size = (100, 100)
        a = torch.rand(*size)
        b = torch.rand(*size)
        w = random.random()
        result = torch.lerp(a, b, w)
        expected = a.clone()
        expected.map2_(a, b, lambda _, a, b: TH_lerp(a, b, w))
        self.assertEqual(result, expected)

项目：pytorch 作者：tylergenter | 项目源码 | 文件源码

def test_lerp(self):
        def TH_lerp(a, b, weight):
            return a + weight * (b - a)

        size = (100, 100)
        a = torch.rand(*size)
        b = torch.rand(*size)
        w = random.random()
        result = torch.lerp(a, b, w)
        expected = a.clone()
        expected.map2_(a, b, lambda _, a, b: TH_lerp(a, b, w))
        self.assertEqual(result, expected)

项目：pytorch-coriander 作者：hughperkins | 项目源码 | 文件源码

def test_lerp(self):
        def TH_lerp(a, b, weight):
            return a + weight * (b - a)

        size = (100, 100)
        a = torch.rand(*size)
        b = torch.rand(*size)
        w = random.random()
        result = torch.lerp(a, b, w)
        expected = a.clone()
        expected.map2_(a, b, lambda _, a, b: TH_lerp(a, b, w))
        self.assertEqual(result, expected)

项目：pytorch 作者：ezyang | 项目源码 | 文件源码

def test_lerp(self):
        def TH_lerp(a, b, weight):
            return a + weight * (b - a)

        size = (100, 100)
        a = torch.rand(*size)
        b = torch.rand(*size)
        w = random.random()
        result = torch.lerp(a, b, w)
        expected = a.clone()
        expected.map2_(a, b, lambda _, a, b: TH_lerp(a, b, w))
        self.assertEqual(result, expected)

项目：pytorch 作者：pytorch | 项目源码 | 文件源码

def test_lerp(self):
        def TH_lerp(a, b, weight):
            return a + weight * (b - a)

        size = (100, 100)
        a = torch.rand(*size)
        b = torch.rand(*size)
        w = random.random()
        result = torch.lerp(a, b, w)
        expected = a.clone()
        expected.map2_(a, b, lambda _, a, b: TH_lerp(a, b, w))
        self.assertEqual(result, expected)