[workflows/client] Cannot get Workflows / Client to work!

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What happened + What you expected to happen

I started two containers with rayproject/ray:1df67e-py36-cpu.

docker run -it -p 10001:10001 rayproject/ray:1df67e-py36-cpu bash
 > ray start --head
 
 docker run -it --net=host rayproject/ray:1df67e-py36-cpu bash
# second container

In the second container, I ran:

from ray import workflow
ray.init("ray://127.0.0.1:10001")
workflow.init()

In [14]: @ray.remote
    ...: def hello():
    ...:     return "hello"
    ...:
    ...: @workflow.step
    ...: def words() -> List[ray.ObjectRef]:
    ...:     return [hello.remote(), ray.put("world")]
    ...:
    ...: @workflow.step
    ...: def concat(words: List[ray.ObjectRef]) -> str:
    ...:     return " ".join([ray.get(w) for w in words])

 my_workflow = concat.step(words.step())
 my_workflow.run()

And I get an exception:

---------------------------------------------------------------------------
AttributeError                            Traceback (most recent call last)
<ipython-input-11-6ce323455dc3> in <module>
----> 1 my_workflow.run()

~/anaconda3/lib/python3.6/site-packages/ray/workflow/common.py in run(self, workflow_id, metadata)
   444             The running result.
   445         """
--> 446         return ray.get(self.run_async(workflow_id, metadata))
   447
   448     @PublicAPI(stability="beta")

~/anaconda3/lib/python3.6/site-packages/ray/workflow/common.py in run_async(self, workflow_id, metadata)
   486         from ray.workflow.execution import run
   487         self._step_id = None
--> 488         return run(self, workflow_id, metadata)
   489
   490

~/anaconda3/lib/python3.6/site-packages/ray/workflow/execution.py in run(entry_workflow, workflow_id, metadata)
    45         # Workflow ID format: {Entry workflow UUID}.{Unix time to nanoseconds}
    46         workflow_id = f"{str(uuid.uuid4())}.{time.time():.9f}"
---> 47     step_type = entry_workflow.data.step_options.step_type
    48
    49     logger.info(f"Workflow job created. [id=\"{workflow_id}\", storage_url="

~/anaconda3/lib/python3.6/site-packages/ray/workflow/common.py in data(self)
   370         """Get the workflow data."""
   371         if self._data.inputs is None:
--> 372             self._data.inputs = self._prepare_inputs()
   373             del self._prepare_inputs
   374         return self._data

~/anaconda3/lib/python3.6/site-packages/ray/workflow/step_function.py in prepare_inputs()
    48                 ensure_ray_initialized()
    49                 return serialization_context.make_workflow_inputs(
---> 50                     flattened_args)
    51
    52             workflow_data = WorkflowData(

~/anaconda3/lib/python3.6/site-packages/ray/workflow/serialization_context.py in make_workflow_inputs(args_list)
   157     workflows: List[Workflow] = []
   158     workflow_refs: List[WorkflowRef] = []
--> 159     with workflow_args_serialization_context(workflows, workflow_refs):
   160         # NOTE: When calling 'ray.put', we trigger python object
   161         # serialization. Under our serialization context,

~/anaconda3/lib/python3.6/contextlib.py in __enter__(self)
    79     def __enter__(self):
    80         try:
---> 81             return next(self.gen)
    82         except StopIteration:
    83             raise RuntimeError("generator didn't yield") from None

~/anaconda3/lib/python3.6/site-packages/ray/workflow/serialization_context.py in workflow_args_serialization_context(workflows, workflow_refs)
    61         Workflow,
    62         serializer=workflow_serializer,
---> 63         deserializer=_resolve_workflow_outputs)
    64
    65     def workflow_ref_serializer(workflow_ref):

~/anaconda3/lib/python3.6/site-packages/ray/util/serialization.py in register_serializer(cls, serializer, deserializer)
    16             This function itself must be serializable.
    17     """
---> 18     context = ray.worker.global_worker.get_serialization_context()
    19     context._register_cloudpickle_serializer(cls, serializer, deserializer)
    20

~/anaconda3/lib/python3.6/site-packages/ray/worker.py in get_serialization_context(self, job_id)
   216         if job_id is None:
   217             job_id = self.current_job_id
--> 218         with self.lock:
   219             if job_id not in self.serialization_context_map:
   220                 self.serialization_context_map[

AttributeError: 'Worker' object has no attribute 'lock'

Versions / Dependencies

rayproject/ray:1df67e-py36-cpu.

MacOS computer

Reproduction script

See above

Anything else

No response

Are you willing to submit a PR?

• Yes I am willing to submit a PR!

[richardliaw]

Workaround:

In [9]: @ray.remote
   ...: def execute():
   ...:     workflow.init()
   ...:     my_workflow = concat.step(words.step())
   ...:     return my_workflow.run()
   ...:
   ...:

In [10]: ray.get(execute.remote())
Out[10]: 'hello world'

(execute pid=611) 2022-01-14 00:19:19,008	INFO api.py:52 -- Using storage: file:///tmp/ray/workflow_data
(execute pid=611) 2022-01-14 00:19:19,008	WARNING api.py:65 -- Calling 'workflow.init()' again with the same storage.
(execute pid=611) 2022-01-14 00:19:19,012	INFO execution.py:49 -- Workflow job created. [id="804c66aa-0af7-4bb4-831c-ac64e8ee39b9.1642148359.010978460", storage_url="file:///tmp/ray/workflow_data"]. Type: FUNCTION.

[vsergeyev]

@iycheng we may confirm, prototype is fixing issue on our side. We use Ray to run scientific quantum computing workflows, and this fix helps us a lot.