def test_search(): bob = VirtualWorker(sy.torch.hook) x = (torch.tensor([1, 2, 3, 4, 5]).tag("#fun", "#mnist").describe( "The images in the MNIST training dataset.").send(bob)) y = (torch.tensor([1, 2, 3, 4, 5]).tag("#not_fun", "#cifar").describe( "The images in the MNIST training dataset.").send(bob)) z = (torch.tensor([1, 2, 3, 4, 5]).tag("#fun", "#boston_housing").describe( "The images in the MNIST training dataset.").send(bob)) a = (torch.tensor([1, 2, 3, 4, 5]).tag( "#not_fun", "#boston_housing").describe( "The images in the MNIST training dataset.").send(bob)) assert len(bob.search("#fun")) == 2 assert len(bob.search("#mnist")) == 1 assert len(bob.search("#cifar")) == 1 assert len(bob.search("#not_fun")) == 2 assert len(bob.search("#not_fun", "#boston_housing")) == 1
def test_search(): worker_id = sy.ID_PROVIDER.pop() bob = VirtualWorker(sy.torch.hook, id=f"bob{worker_id}") x = (torch.tensor([1, 2, 3, 4, 5]).tag("#fun", "#mnist").describe( "The images in the MNIST training dataset.").send(bob)) y = (torch.tensor([1, 2, 3, 4, 5]).tag("#not_fun", "#cifar").describe( "The images in the MNIST training dataset.").send(bob)) z = (torch.tensor([1, 2, 3, 4, 5]).tag("#fun", "#boston_housing").describe( "The images in the MNIST training dataset.").send(bob)) a = (torch.tensor([1, 2, 3, 4, 5]).tag( "#not_fun", "#boston_housing").describe( "The images in the MNIST training dataset.").send(bob)) assert len(bob.search("#fun")) == 2 assert len(bob.search("#mnist")) == 1 assert len(bob.search("#cifar")) == 1 assert len(bob.search("#not_fun")) == 2 assert len(bob.search(["#not_fun", "#boston_housing"])) == 1