WIP: Need to fix tests to work in C++ mode

tests/examples/log_parsing/conftest.py

@@ -16,8 +16,8 @@
 import pytest
 
 
-@pytest.fixture
-def config(config):  # pylint: disable=redefined-outer-name
+@pytest.fixture(name="config")
+def config_fixture(config):
     """
     The log_parsing pipelie requires NLP mode. Set this here so all the tests don't need to set it themselves.
     """

tests/examples/log_parsing/test_inference.py

@@ -35,12 +35,6 @@
 from morpheus.utils.type_aliases import DataFrameType
 
 
-@pytest.fixture(name="config")
-def config_fixture(config: Config):
-    config.mode = PipelineModes.NLP
-    yield config
-
-
 def build_response_mem(log_test_data_dir: str) -> TensorMemory:
     # we have tensor data for the first five rows
     count = 5
@@ -113,11 +107,9 @@ def _check_worker(inference_mod: types.ModuleType, worker: TritonInferenceWorker
     assert worker._inout_mapping == expected_mapping
 
 
-@pytest.mark.use_python
 @pytest.mark.import_mod([os.path.join(TEST_DIRS.examples_dir, 'log_parsing', 'inference.py')])
 def test_log_parsing_triton_inference_log_parsing_constructor(config: Config,
                                                               import_mod: typing.List[types.ModuleType]):
-    config.mode = PipelineModes.NLP
     inference_mod = import_mod[0]
     worker = inference_mod.TritonInferenceLogParsing(inf_queue=ProducerConsumerQueue(),
                                                      c=config,
@@ -131,7 +123,6 @@ def test_log_parsing_triton_inference_log_parsing_constructor(config: Config,
     _check_worker(inference_mod, worker, {'test': 'this'})
 
 
-@pytest.mark.use_python
 @pytest.mark.import_mod([os.path.join(TEST_DIRS.examples_dir, 'log_parsing', 'inference.py')])
 @pytest.mark.parametrize("mess_offset,mess_count,offset,count", [(0, 20, 0, 20), (5, 10, 5, 10)])
 def test_log_parsing_triton_inference_log_parsing_build_output_message(config: Config,
@@ -173,7 +164,6 @@ def test_log_parsing_triton_inference_log_parsing_build_output_message(config: C
     assert msg.seq_ids.shape == (count, 3)
 
 
-@pytest.mark.use_python
 @pytest.mark.import_mod([os.path.join(TEST_DIRS.examples_dir, 'log_parsing', 'inference.py')])
 def test_log_parsing_inference_stage_constructor(config: Config, import_mod: typing.List[types.ModuleType]):
     inference_mod = import_mod[0]
@@ -205,7 +195,6 @@ def test_log_parsing_inference_stage_constructor(config: Config, import_mod: typ
     assert stage._kwargs == expected_kwargs
 
 
-@pytest.mark.use_python
 @pytest.mark.import_mod([os.path.join(TEST_DIRS.examples_dir, 'log_parsing', 'inference.py')])
 def test_log_parsing_inference_stage_get_inference_worker(config: Config, import_mod: typing.List[types.ModuleType]):
     inference_mod = import_mod[0]
@@ -225,7 +214,6 @@ def test_log_parsing_inference_stage_get_inference_worker(config: Config, import
     _check_worker(inference_mod, worker, expected_mapping)
 
 
-@pytest.mark.use_python
 @pytest.mark.usefixtures("manual_seed", "config")
 @pytest.mark.import_mod(os.path.join(TEST_DIRS.examples_dir, 'log_parsing', 'inference.py'))
 @pytest.mark.parametrize("mess_offset,mess_count,offset,count", [(0, 5, 0, 5), (5, 5, 0, 5)])
@@ -237,8 +225,6 @@ def test_log_parsing_inference_stage_convert_one_response(import_mod: typing.Lis
                                                           count):
     inference_mod = import_mod
 
-    ttl_count = len(filter_probs_df)
-
     input_res = build_response_mem(os.path.join(TEST_DIRS.tests_data_dir, 'examples/log_parsing'))
 
     # confidences, labels & input_ids all have the same shape

tests/examples/log_parsing/test_log_parsing_pipe.py

@@ -126,7 +126,6 @@ def _run_mocked_pipeline(config: Config, dataset_cudf: DatasetManager, import_mo
 
 
 @pytest.mark.slow
-@pytest.mark.use_python
 @pytest.mark.import_mod([
     os.path.join(TEST_DIRS.examples_dir, 'log_parsing', 'inference.py'),
     os.path.join(TEST_DIRS.examples_dir, 'log_parsing', 'postprocessing.py')