def __init__(self, language, function, function_descriptor, num_cpus,
num_gpus, memory, object_store_memory, resources,
accelerator_type, num_returns, max_calls, max_retries,
retry_exceptions, runtime_env, placement_group):
if inspect.iscoroutinefunction(function):
raise ValueError("'async def' should not be used for remote "
"tasks. You can wrap the async function with "
"`asyncio.get_event_loop.run_until(f())`. "
"See more at docs.ray.io/async_api.html")
self._language = language
self._function = _inject_tracing_into_function(function)
self._function_name = (function.__module__ + "." + function.__name__)
self._function_descriptor = function_descriptor
self._is_cross_language = language != Language.PYTHON
self._num_cpus = (DEFAULT_REMOTE_FUNCTION_CPUS
if num_cpus is None else num_cpus)
self._num_gpus = num_gpus
self._memory = memory
if object_store_memory is not None:
raise NotImplementedError(
"setting object_store_memory is not implemented for tasks")
self._object_store_memory = None
self._resources = resources
self._accelerator_type = accelerator_type
self._num_returns = (DEFAULT_REMOTE_FUNCTION_NUM_RETURN_VALS
if num_returns is None else num_returns)
self._max_calls = (DEFAULT_REMOTE_FUNCTION_MAX_CALLS
if max_calls is None else max_calls)
self._max_retries = (DEFAULT_REMOTE_FUNCTION_NUM_TASK_RETRIES
if max_retries is None else max_retries)
self._retry_exceptions = (DEFAULT_REMOTE_FUNCTION_RETRY_EXCEPTIONS
if retry_exceptions is None else
retry_exceptions)
# Parse local pip/conda config files here. If we instead did it in
# .remote(), it would get run in the Ray Client server, which runs on
# a remote node where the files aren't available.
if runtime_env:
if isinstance(runtime_env, str):
self._runtime_env = runtime_env
else:
self._runtime_env = ParsedRuntimeEnv(runtime_env
or {}).serialize()
else:
self._runtime_env = None
self._placement_group = placement_group
self._decorator = getattr(function, "__ray_invocation_decorator__",
None)
self._function_signature = ray._private.signature.extract_signature(
self._function)
self._last_export_session_and_job = None
self._uuid = uuid.uuid4()
# Override task.remote's signature and docstring
@wraps(function)
def _remote_proxy(*args, **kwargs):
return self._remote(args=args, kwargs=kwargs)
self.remote = _remote_proxy
def __init__(
self,
language,
function,
function_descriptor,
task_options,
):
if inspect.iscoroutinefunction(function):
raise ValueError(
"'async def' should not be used for remote tasks. You can wrap the "
"async function with `asyncio.get_event_loop.run_until(f())`. "
"See more at https://docs.ray.io/en/latest/ray-core/async_api.html#asyncio-for-remote-tasks" # noqa
)
self._default_options = task_options
# TODO(suquark): This is a workaround for class attributes of options.
# They are being used in some other places, mostly tests. Need cleanup later.
# E.g., actors uses "__ray_metadata__" to collect options, we can so something
# similar for remote functions.
for k, v in ray_option_utils.task_options.items():
setattr(self, "_" + k, task_options.get(k, v.default_value))
self._runtime_env = parse_runtime_env(self._runtime_env)
if "runtime_env" in self._default_options:
self._default_options["runtime_env"] = self._runtime_env
self._language = language
self._function = _inject_tracing_into_function(function)
self._function_name = function.__module__ + "." + function.__name__
self._function_descriptor = function_descriptor
self._is_cross_language = language != Language.PYTHON
self._decorator = getattr(function, "__ray_invocation_decorator__",
None)
self._function_signature = ray._private.signature.extract_signature(
self._function)
self._last_export_session_and_job = None
self._uuid = uuid.uuid4()
# Override task.remote's signature and docstring
@wraps(function)
def _remote_proxy(*args, **kwargs):
return self._remote(args=args,
kwargs=kwargs,
**self._default_options)
self.remote = _remote_proxy
def __init__(self, language, function, function_descriptor, num_cpus,
num_gpus, memory, object_store_memory, resources,
accelerator_type, num_returns, max_calls, max_retries,
runtime_env):
if inspect.iscoroutinefunction(function):
raise ValueError("'async def' should not be used for remote "
"tasks. You can wrap the async function with "
"`asyncio.get_event_loop.run_until(f())`. "
"See more at docs.ray.io/async_api.html")
self._language = language
self._function = _inject_tracing_into_function(function)
self._function_name = (function.__module__ + "." + function.__name__)
self._function_descriptor = function_descriptor
self._is_cross_language = language != Language.PYTHON
self._num_cpus = (DEFAULT_REMOTE_FUNCTION_CPUS
if num_cpus is None else num_cpus)
self._num_gpus = num_gpus
self._memory = memory
if object_store_memory is not None:
raise NotImplementedError(
"setting object_store_memory is not implemented for tasks")
self._object_store_memory = None
self._resources = resources
self._accelerator_type = accelerator_type
self._num_returns = (DEFAULT_REMOTE_FUNCTION_NUM_RETURN_VALS
if num_returns is None else num_returns)
self._max_calls = (DEFAULT_REMOTE_FUNCTION_MAX_CALLS
if max_calls is None else max_calls)
self._max_retries = (DEFAULT_REMOTE_FUNCTION_NUM_TASK_RETRIES
if max_retries is None else max_retries)
self._runtime_env = runtime_env
self._decorator = getattr(function, "__ray_invocation_decorator__",
None)
self._function_signature = ray._private.signature.extract_signature(
self._function)
self._last_export_session_and_job = None
# Override task.remote's signature and docstring
@wraps(function)
def _remote_proxy(*args, **kwargs):
return self._remote(args=args, kwargs=kwargs)
self.remote = _remote_proxy
def __init__(
self,
language,
function,
function_descriptor,
num_cpus,
num_gpus,
memory,
object_store_memory,
resources,
accelerator_type,
num_returns,
max_calls,
max_retries,
retry_exceptions,
runtime_env,
placement_group,
scheduling_strategy: SchedulingStrategyT,
):
if inspect.iscoroutinefunction(function):
raise ValueError(
"'async def' should not be used for remote tasks. You can wrap the "
"async function with `asyncio.get_event_loop.run_until(f())`. "
"See more at https://docs.ray.io/en/latest/ray-core/async_api.html#asyncio-for-remote-tasks" # noqa
)
self._language = language
self._function = _inject_tracing_into_function(function)
self._function_name = function.__module__ + "." + function.__name__
self._function_descriptor = function_descriptor
self._is_cross_language = language != Language.PYTHON
self._num_cpus = DEFAULT_REMOTE_FUNCTION_CPUS if num_cpus is None else num_cpus
self._num_gpus = num_gpus
self._memory = memory
if object_store_memory is not None:
raise NotImplementedError(
"setting object_store_memory is not implemented for tasks"
)
self._object_store_memory = None
self._resources = resources
self._accelerator_type = accelerator_type
self._num_returns = (
DEFAULT_REMOTE_FUNCTION_NUM_RETURN_VALS
if num_returns is None
else num_returns
)
self._max_calls = (
DEFAULT_REMOTE_FUNCTION_MAX_CALLS if max_calls is None else max_calls
)
self._max_retries = (
DEFAULT_REMOTE_FUNCTION_NUM_TASK_RETRIES
if max_retries is None
else max_retries
)
self._retry_exceptions = (
DEFAULT_REMOTE_FUNCTION_RETRY_EXCEPTIONS
if retry_exceptions is None
else retry_exceptions
)
self._runtime_env = parse_runtime_env(runtime_env)
self._placement_group = placement_group
self._decorator = getattr(function, "__ray_invocation_decorator__", None)
self._function_signature = ray._private.signature.extract_signature(
self._function
)
self._scheduling_strategy = scheduling_strategy
self._last_export_session_and_job = None
self._uuid = uuid.uuid4()
# Override task.remote's signature and docstring
@wraps(function)
def _remote_proxy(*args, **kwargs):
return self._remote(args=args, kwargs=kwargs)
self.remote = _remote_proxy
