A Node context is used to indicate that all Tasks instantiated within will
run on the given node name. (Only the name of the node actually counts.)
Example:
with TaskGroup() as tg:
with Node('node1'):
s1 = execution_step(...)
Task(step=s1)
with Node('node2'):
s2 = execution_step(...)
with Node('node1'):
s3 = execution_step(...)
In this example, all three execution steps will run in parallel.
Moreover, s1 and s3 will run on the same node, and can see each
others blobs.
Additionally, a Node can be passed implementation-specific kwargs,
in order to specify properties of the node. When using AML Flow,
we currently support:
resource_requirements: a fblearner.flow.api.ResourceRequirements
specifying requirements for this Node.
flow_returns: a fblearner.flow.api.types.Schema object specifying
the output schema of the Flow operator where the
Node will run.
Definition at line 56 of file task.py.