def deploy_service_registry_and_set_urls(
    private_keys, web3, contract_manager, service_registry_address
) -> Tuple[ServiceRegistry, List[str]]:
    urls = ["http://foo", "http://boo", "http://coo"]
    c1_client = JSONRPCClient(web3, private_keys[0])
    c1_service_proxy = ServiceRegistry(
        jsonrpc_client=c1_client,
        service_registry_address=service_registry_address,
        contract_manager=contract_manager,
    )
    c2_client = JSONRPCClient(web3, private_keys[1])
    c2_service_proxy = ServiceRegistry(
        jsonrpc_client=c2_client,
        service_registry_address=service_registry_address,
        contract_manager=contract_manager,
    )
    c3_client = JSONRPCClient(web3, private_keys[2])
    c3_service_proxy = ServiceRegistry(
        jsonrpc_client=c3_client,
        service_registry_address=service_registry_address,
        contract_manager=contract_manager,
    )

    # Test that getting a random service for an empty registry returns None
    pfs_address = get_random_service(c1_service_proxy, "latest")
    assert pfs_address is None

    # Test that setting the urls works
    c1_service_proxy.set_url(urls[0])
    c2_service_proxy.set_url(urls[1])
    c3_service_proxy.set_url(urls[2])

    return c1_service_proxy, urls
def nonlinear_1d(module, grad_input, grad_output):
    delta_out = module.y[: int(module.y.shape[0] / 2)] - module.y[int(module.y.shape[0] / 2):]

    delta_in = module.x[: int(module.x.shape[0] / 2)] - module.x[int(module.x.shape[0] / 2):]
    dup0 = [2] + [1 for i in delta_in.shape[1:]]
    # handles numerical instabilities where delta_in is very small by
    # just taking the gradient in those cases
    grads = [None for _ in grad_input]
    grads[0] = torch.where(torch.abs(delta_in.repeat(dup0)) < 1e-6, grad_input[0],
                           grad_output[0] * (delta_out / delta_in).repeat(dup0))
    return tuple(grads)