Add support for decorated pipeline steps (#1154)

examples/pipeline/decorated_pipeline_step_decorators.py

@@ -0,0 +1,24 @@
+from clearml import PipelineDecorator
+
+
+def our_decorator(func):
+    def function_wrapper(*args, **kwargs):
+        return func(*args, **kwargs) + 1
+    return function_wrapper
+
+
+@PipelineDecorator.component()
+@our_decorator
+def step():
+    return 1
+
+
+@PipelineDecorator.pipeline(name="test_decorated", project="test_decorated")
+def pipeline():
+    result = step()
+    assert result == 2
+
+
+if __name__ == "__main__":
+    PipelineDecorator.run_locally()
+    pipeline()

examples/pipeline/decorated_pipeline_step_functions.py

@@ -0,0 +1,27 @@
+from clearml import PipelineController
+
+
+def our_decorator(func):
+    def function_wrapper(*args, **kwargs):
+        return func(*args, **kwargs) + 1
+    return function_wrapper
+
+
+@our_decorator
+def step():
+    return 1
+
+
+def evaluate(step_return):
+    assert step_return == 2
+
+
+if __name__ == "__main__":
+    pipeline = PipelineController(name="test_decorated", project="test_decorated")
+    pipeline.add_function_step(name="step", function=step, function_return=["step_return"])
+    pipeline.add_function_step(
+        name="evaluate",
+        function=evaluate,
+        function_kwargs=dict(step_return='${step.step_return}')
+    )
+    pipeline.start_locally(run_pipeline_steps_locally=True)