fix failing test and add notes on change in outputs

Signed-off-by: Anh-Uong <[email protected]>

examples/text-sentiment/client.py

@@ -51,14 +51,10 @@
 
         # Run inference for two sample prompts
         for text in ["I am not feeling well today!", "Today is a nice sunny day"]:
-            # TODO: is this the recommended approach for setting up client and request?
             predict_class = DataBase.get_class_for_name(
                 "HuggingFaceSentimentTaskRequest"
             )
             request = predict_class(text_input=text).to_proto()
-            # request = inference_service.messages.HuggingFaceSentimentTaskRequest(
-            #     text_input=text
-            # )
             response = client_stub.HuggingFaceSentimentTaskPredict(
                 request, metadata=[("mm-model-id", model_id)], timeout=1
             )

tests/runtime/interceptors/test_caikit_runtime_server_wrapper.py

@@ -18,6 +18,7 @@
 import grpc
 
 # Local
+from caikit.core.data_model.base import DataBase
 from caikit.runtime.interceptors.caikit_runtime_server_wrapper import (
     CaikitRuntimeServerWrapper,
 )
@@ -47,9 +48,8 @@ def predict(request, context, caikit_rpc):
         client = sample_inference_service.stub_class(
             grpc.insecure_channel(f"localhost:{open_port}")
         )
-        _ = client.SampleTaskPredict(
-            sample_inference_service.messages.SampleTaskRequest(), timeout=3
-        )
+        predict_class = DataBase.get_class_for_name("SampleTaskRequest")
+        _ = client.SampleTaskPredict(predict_class().to_proto(), timeout=3)
         assert len(calls) == 1
         assert isinstance(calls[0], TaskPredictRPC)
         assert calls[0].name == "SampleTaskPredict"

tests/runtime/servicers/test_global_predict_servicer_impl.py

@@ -111,19 +111,11 @@ def test_global_predict_works_on_bidirectional_streaming_rpcs(
 ):
     """Simple test that our SampleModule's bidirectional stream inference fn is supported"""
 
-    def req_iterator() -> Iterator[
-        sample_inference_service.messages.BidiStreamingSampleTaskRequest
-    ]:
-        # TODO: can this be replaced?
-        # Guessing not since got error: caikit.runtime.types.caikit_runtime_exception.CaikitRuntimeException: Exception raised during inference. This may be a problem with your input: BidiStreamingSampleTaskRequest.__init__() got an unexpected keyword argument 'sample_input'
-        # predict_class = DataBase.get_class_for_name("BidiStreamingSampleTaskRequest")
-        # predict_class(
-        #         sample_input=HAPPY_PATH_INPUT_DM
-        #     ).to_proto()
+    predict_class = DataBase.get_class_for_name("BidiStreamingSampleTaskRequest")
+
+    def req_iterator() -> Iterator[predict_class]:
         for i in range(100):
-            yield sample_inference_service.messages.BidiStreamingSampleTaskRequest(
-                sample_inputs=HAPPY_PATH_INPUT
-            )
+            yield predict_class(sample_inputs=HAPPY_PATH_INPUT_DM).to_proto()
 
     response_stream = sample_predict_servicer.Predict(
         req_iterator(),
@@ -147,13 +139,11 @@ def test_global_predict_works_on_bidirectional_streaming_rpcs_with_multiple_stre
     mock_manager = MagicMock()
     mock_manager.retrieve_model.return_value = GeoStreamingModule()
 
-    def req_iterator() -> Iterator[
-        sample_inference_service.messages.BidiStreamingGeoSpatialTaskRequest
-    ]:
+    predict_class = DataBase.get_class_for_name("BidiStreamingGeoSpatialTaskRequest")
+
+    def req_iterator() -> Iterator[predict_class]:
         for i in range(100):
-            yield sample_inference_service.messages.BidiStreamingGeoSpatialTaskRequest(
-                lats=i, lons=100 - i, name="Gabe"
-            )
+            yield predict_class(lats=i, lons=100 - i, name="Gabe").to_proto()
 
     with patch.object(sample_predict_servicer, "_model_manager", mock_manager):
         response_stream = sample_predict_servicer.Predict(

tests/runtime/test_grpc_server.py

@@ -59,6 +59,7 @@
     process_pb2_grpc,
 )
 from caikit.runtime.service_factory import ServicePackage, ServicePackageFactory
+from caikit.runtime.utils.servicer_util import build_caikit_library_request_dict
 from sample_lib import InnerModule, SamplePrimitiveModule
 from sample_lib.data_model import (
     OtherOutputType,
@@ -206,34 +207,52 @@ def test_components_preinitialized(reset_globals, open_port):
         assert MODEL_MANAGER._initializers
 
 
-def test_predict_sample_module_proto_ok_response(
+def test_predict_sample_module_ok_response(
     sample_task_model_id, runtime_grpc_server, sample_inference_service
 ):
     """Test RPC CaikitRuntime.SampleTaskPredict successful response"""
     stub = sample_inference_service.stub_class(runtime_grpc_server.make_local_channel())
-    predict_request = sample_inference_service.messages.SampleTaskRequest(
-        sample_input=HAPPY_PATH_INPUT
-    )
+    predict_class = DataBase.get_class_for_name("SampleTaskRequest")
+    predict_request = predict_class(sample_input=HAPPY_PATH_INPUT_DM).to_proto()
+
     actual_response = stub.SampleTaskPredict(
         predict_request, metadata=[("mm-model-id", sample_task_model_id)]
     )
+
     assert actual_response == HAPPY_PATH_RESPONSE
 
 
-def test_predict_sample_module_ok_response(
-    sample_task_model_id, runtime_grpc_server, sample_inference_service
+def test_global_predict_build_caikit_library_request_dict_creates_caikit_core_run_kwargs(
+    sample_inference_service,
 ):
-    """Test RPC CaikitRuntime.SampleTaskPredict successful response"""
-    stub = sample_inference_service.stub_class(runtime_grpc_server.make_local_channel())
+    """Test using proto versus pythonic data model for inference requests to compare diffs"""
+    # Protobuf input
+    proto_request = sample_inference_service.messages.SampleTaskRequest(
+        sample_input=HAPPY_PATH_INPUT_DM.to_proto(),
+    )
+    proto_request_dict = build_caikit_library_request_dict(
+        proto_request,
+        sample_lib.modules.sample_task.SampleModule.RUN_SIGNATURE,
+    )
+
+    # unset fields not included
+    proto_expected_arguments = {"sample_input"}
+    assert proto_request.HasField("throw") is False
+    assert proto_expected_arguments == set(proto_request_dict.keys())
+
+    # Pythonic data model
     predict_class = DataBase.get_class_for_name("SampleTaskRequest")
-    # TODO: is this getting predict_class = SampleModule() ??
-    predict_request = predict_class(sample_input=HAPPY_PATH_INPUT_DM).to_proto()
+    python_request = predict_class(sample_input=HAPPY_PATH_INPUT_DM).to_proto()
 
-    actual_response = stub.SampleTaskPredict(
-        predict_request, metadata=[("mm-model-id", sample_task_model_id)]
+    python_sample_module_request_dict = build_caikit_library_request_dict(
+        python_request,
+        sample_lib.modules.sample_task.SampleModule.RUN_SIGNATURE,
     )
 
-    assert actual_response == HAPPY_PATH_RESPONSE
+    # unset fields are included if they have defaults set
+    python_expected_arguments = {"sample_input", "throw"}
+    assert python_request.HasField("throw") is True
+    assert python_expected_arguments == set(python_sample_module_request_dict.keys())
 
 
 def test_predict_streaming_module(

tests/runtime/test_service_factory.py

@@ -23,6 +23,7 @@
 
 # Local
 from caikit.core.data_model import render_dataobject_protos
+from caikit.core.data_model.base import DataBase
 from caikit.runtime.service_factory import ServicePackage, ServicePackageFactory
 from sample_lib import SampleModule
 from sample_lib.data_model import SampleInputType, SampleOutputType
@@ -359,7 +360,8 @@ def run(
     inference_service = ServicePackageFactory.get_service_package(
         ServicePackageFactory.ServiceType.INFERENCE
     )
-    sample_task_request = inference_service.messages.SampleTaskRequest
+    predict_class = DataBase.get_class_for_name("SampleTaskRequest")
+    sample_task_request = predict_class().to_proto()
 
     # Check that the new parameter defined in this backend module exists in the service
     assert "backend_param" in sample_task_request.DESCRIPTOR.fields_by_name.keys()