def deny_moving():
a = nn.Linear(1, 1)
b = nn.Linear(1, 1)
model = nn.Sequential(a, b)
model = Pipe(model, [1, 1], style=Pipe.MultiProcess, worker_map=get_worker_map())
model.cuda()
model.cpu()
model.to(torch.device("cuda"))
model.to(0)
model.to("cuda")
model.to(device=0)
model.to(torch.rand(1))
model.to(tensor=torch.rand(1))
# Casting is allowed.
model.half()
model.to(torch.double)
model.to(dtype=torch.float)
def test_deny_moving():
a = nn.Linear(1, 1)
b = nn.Linear(1, 1)
model = nn.Sequential(a, b)
model = Pipe(model, [1, 1], devices=["cpu", "cpu"])
# Moving is denied.
with pytest.raises(TypeError):
model.cuda()
with pytest.raises(TypeError):
model.cpu()
with pytest.raises(TypeError):
model.to(torch.device("cuda"))
with pytest.raises(TypeError):
model.to(0)
with pytest.raises(TypeError):
model.to("cuda")
with pytest.raises(TypeError):
model.to(device=0)
with pytest.raises(TypeError):
model.to(torch.rand(1))
with pytest.raises(TypeError):
model.to(tensor=torch.rand(1))
# Casting is allowed.
model.half()
model.to(torch.double)
model.to(dtype=torch.float)
