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
