def test_cuda_extension(self): import torch_test_cpp_extension.cuda as cuda_extension x = torch.FloatTensor(100).zero_().cuda() y = torch.FloatTensor(100).zero_().cuda() z = cuda_extension.sigmoid_add(x, y).cpu() # 2 * sigmoid(0) = 2 * 0.5 = 1 self.assertEqual(z, torch.ones_like(z))
def test_cuda_extension(self): import torch_test_cpp_extension.cuda as cuda_extension x = torch.zeros(100, device="cuda", dtype=torch.float32) y = torch.zeros(100, device="cuda", dtype=torch.float32) z = cuda_extension.sigmoid_add(x, y).cpu() # 2 * sigmoid(0) = 2 * 0.5 = 1 self.assertEqual(z, torch.ones_like(z))
def test_cuda_extension(self): import torch_test_cpp_extension.cuda as cuda_extension x = torch.zeros(100, device='cuda', dtype=torch.float32) y = torch.zeros(100, device='cuda', dtype=torch.float32) z = cuda_extension.sigmoid_add(x, y).cpu() # 2 * sigmoid(0) = 2 * 0.5 = 1 self.assertEqual(z, torch.ones_like(z))