def test_get_conda_env_dir(tmp_path):
d = tmp_path / "tf1"
d.mkdir()
os.environ["CONDA_PREFIX"] = str(d)
with pytest.raises(ValueError):
# env does not exist
env_dir = get_conda_env_dir("tf2")
tf2_dir = tmp_path / "tf2"
tf2_dir.mkdir()
env_dir = get_conda_env_dir("tf2")
assert (env_dir == str(tmp_path / "tf2"))
os.environ["CONDA_PREFIX"] = ""
def create_backend(self,
backend_tag: str,
func_or_class: Union[Callable, Type[Callable]],
*actor_init_args: Any,
ray_actor_options: Optional[Dict] = None,
config: Optional[Union[BackendConfig,
Dict[str, Any]]] = None,
env: Optional[CondaEnv] = None) -> None:
"""Create a backend with the provided tag.
The backend will serve requests with func_or_class.
Args:
backend_tag (str): a unique tag assign to identify this backend.
func_or_class (callable, class): a function or a class implementing
__call__.
actor_init_args (optional): the arguments to pass to the class.
initialization method.
ray_actor_options (optional): options to be passed into the
@ray.remote decorator for the backend actor.
config (dict, serve.BackendConfig, optional): configuration options
for this backend. Either a BackendConfig, or a dictionary
mapping strings to values for the following supported options:
- "num_replicas": number of processes to start up that
will handle requests to this backend.
- "max_batch_size": the maximum number of requests that will
be processed in one batch by this backend.
- "batch_wait_timeout": time in seconds that backend replicas
will wait for a full batch of requests before processing a
partial batch.
- "max_concurrent_queries": the maximum number of queries that
will be sent to a replica of this backend without receiving a
response.
- "user_config" (experimental): Arguments to pass to the
reconfigure method of the backend. The reconfigure method is
called if "user_config" is not None.
env (serve.CondaEnv, optional): conda environment to run this
backend in. Requires the caller to be running in an activated
conda environment (not necessarily ``env``), and requires
``env`` to be an existing conda environment on all nodes. If
``env`` is not provided but conda is activated, the backend
will run in the conda environment of the caller.
"""
if backend_tag in self.list_backends().keys():
raise ValueError(
"Cannot create backend. "
"Backend '{}' is already registered.".format(backend_tag))
if config is None:
config = {}
if ray_actor_options is None:
ray_actor_options = {}
if env is None:
# If conda is activated, default to conda env of this process.
if os.environ.get("CONDA_PREFIX"):
if "override_environment_variables" not in ray_actor_options:
ray_actor_options["override_environment_variables"] = {}
ray_actor_options["override_environment_variables"].update(
{"PYTHONHOME": os.environ.get("CONDA_PREFIX")})
else:
conda_env_dir = get_conda_env_dir(env.name)
ray_actor_options.update(
override_environment_variables={"PYTHONHOME": conda_env_dir})
replica_config = ReplicaConfig(func_or_class,
*actor_init_args,
ray_actor_options=ray_actor_options)
metadata = BackendMetadata(
accepts_batches=replica_config.accepts_batches,
is_blocking=replica_config.is_blocking)
if isinstance(config, dict):
backend_config = BackendConfig.parse_obj({
**config, "internal_metadata":
metadata
})
elif isinstance(config, BackendConfig):
backend_config = config.copy(
update={"internal_metadata": metadata})
else:
raise TypeError("config must be a BackendConfig or a dictionary.")
backend_config._validate_complete()
ray.get(
self._controller.create_backend.remote(backend_tag, backend_config,
replica_config))
