def chain_func(*args, **kw_argv):
# Get the first function as a start
wf_step = workflow.step(fs[0]).step(*args, **kw_argv)
for i in range(1, len(fs)):
# Convert each function inside steps into workflow step
# function and then use the previous output as the input
# for them.
wf_step = workflow.step(fs[i]).step(wf_step)
return wf_step
def test_partial(workflow_start_regular_shared):
ys = [1, 2, 3]
def add(x, y):
return x + y
from functools import partial
f1 = workflow.step(partial(add, 10)).step(10)
assert "__anonymous_func__" in f1._name
assert f1.run() == 20
fs = [partial(add, y=y) for y in ys]
@ray.remote
def chain_func(*args, **kw_argv):
# Get the first function as a start
wf_step = workflow.step(fs[0]).step(*args, **kw_argv)
for i in range(1, len(fs)):
# Convert each function inside steps into workflow step
# function and then use the previous output as the input
# for them.
wf_step = workflow.step(fs[i]).step(wf_step)
return wf_step
assert workflow.run(chain_func.bind(1)) == 7
def _node_visitor(node: Any) -> Any:
if isinstance(node, FunctionNode):
# "_resolve_like_object_ref_in_args" indicates we should resolve the
# workflow like an ObjectRef, when included in the arguments of
# another workflow.
workflow_step = workflow.step(
node._body).options(**node._bound_options,
_resolve_like_object_ref_in_args=True)
wf = workflow_step.step(*node._bound_args, **node._bound_kwargs)
return wf
if isinstance(node, InputAtrributeNode):
return node._execute_impl() # get data from input node
if isinstance(node, InputNode):
return input_context # replace input node with input data
if not isinstance(node, DAGNode):
return node # return normal objects
raise TypeError(f"Unsupported DAG node: {node}")
