Fix the logic of passing default values of pipeline parameters. (#2098)

* Fix the logic of passing default values.

* Modify unit test

* Solve.

sdk/python/kfp/compiler/compiler.py

@@ -718,7 +718,7 @@ class Compiler(object):
       pipeline_func: Callable,
       pipeline_name: Text=None,
       pipeline_description: Text=None,
-      params_list: List[dsl.PipelineParam]=()) -> Dict[Text, Any]:
+      params_list: List[dsl.PipelineParam]=None) -> Dict[Text, Any]:
     """ Create workflow spec from pipeline function and specified pipeline
     params/metadata. Currently, the pipeline params are either specified in
     the signature of the pipeline function or by passing a list of
@@ -730,6 +730,7 @@ class Compiler(object):
     :param params_list: list of pipeline params to append to the pipeline.
     :return: workflow dict.
     """
+    params_list = params_list or []
     argspec = inspect.getfullargspec(pipeline_func)
 
     # Create the arg list with no default values and call pipeline function.
@@ -739,6 +740,13 @@ class Compiler(object):
     pipeline_meta.description = pipeline_description or pipeline_meta.description
     pipeline_name = K8sHelper.sanitize_k8s_name(pipeline_meta.name)
 
+    # Need to first clear the default value of dsl.PipelineParams. Otherwise, it
+    # will be resolved immediately in place when being to each component.
+    default_param_values = {}
+    for param in params_list:
+      default_param_values[param.name] = param.value
+      param.value = None
+
     # Currently only allow specifying pipeline params at one place.
     if params_list and pipeline_meta.inputs:
       raise ValueError('Either specify pipeline params in the pipeline function, or in "params_list", but not both.')
@@ -767,6 +775,9 @@ class Compiler(object):
           arg.value = default.value if isinstance(default, dsl.PipelineParam) else default
     else:
       # Or, if args are provided by params_list, fill in pipeline_meta.
+      for param in params_list:
+        param.value = default_param_values[param.name]
+
       args_list_with_defaults = params_list
       pipeline_meta.inputs = [
         ParameterMeta(
@@ -790,7 +801,7 @@ class Compiler(object):
 
   def _compile(self, pipeline_func):
     """Compile the given pipeline function into workflow."""
-    return self.create_workflow(pipeline_func, [])
+    return self.create_workflow(pipeline_func=pipeline_func)
 
   def compile(self, pipeline_func, package_path, type_check=True):
     """Compile the given pipeline function into workflow yaml.

sdk/python/tests/compiler/testdata/basic_no_decorator.py

@@ -18,7 +18,7 @@ import kfp.gcp as gcp
 
 
 message_param = dsl.PipelineParam(name='message')
-output_path_param = dsl.PipelineParam(name='outputpath')
+output_path_param = dsl.PipelineParam(name='outputpath', value='default_output')
 
 class GetFrequentWordOp(dsl.ContainerOp):
   """A get frequent word class representing a component in ML Pipelines.

sdk/python/tests/compiler/testdata/basic_no_decorator.yaml

@@ -15,13 +15,14 @@ apiVersion: argoproj.io/v1alpha1
 kind: Workflow
 metadata:
   annotations:
-    pipelines.kubeflow.org/pipeline_spec: '{"description": "Get Most Frequent Word and Save to GCS", "inputs": [{"name": "message"}, {"name": "outputpath"}], "name": "Save Most Frequent"}'
+    pipelines.kubeflow.org/pipeline_spec: '{"description": "Get Most Frequent Word and Save to GCS", "inputs": [{"name": "message"}, {"default": "default_output", "name": "outputpath"}], "name": "Save Most Frequent"}'
   generateName: save-most-frequent-
 spec:
   arguments:
     parameters:
       - name: message
       - name: outputpath
+        value: default_output
   entrypoint: save-most-frequent
   serviceAccountName: pipeline-runner
   onExit: exiting