remove kubeflow training to favor tfx components

test/sample-test/run_sample_test.py

@@ -96,15 +96,6 @@ def main():
         'steps':
           '5'
     }
-  elif args.testname == 'kubeflow_training_classification':
-    params = {
-        'output': args.output,
-        'project': 'ml-pipeline-test',
-        'evaluation': 'gs://ml-pipeline-dataset/sample-test/flower/eval15.csv',
-        'train': 'gs://ml-pipeline-dataset/sample-test/flower/train30.csv',
-        'hidden-layer-size': '10,5',
-        'steps': '5'
-    }
   elif args.testname == 'xgboost_training_cm':
     params = {
         'output': args.output,
@@ -150,22 +141,7 @@ def main():
 
   ###### Validate the results for specific test cases ######
   #TODO: Add result check for tfx-cab-classification after launch.
-  if args.testname == 'kubeflow_training_classification':
-    cm_tar_path = './confusion_matrix.tar.gz'
-    utils.get_artifact_in_minio(workflow_json, 'confusion-matrix', cm_tar_path,
-                                'mlpipeline-ui-metadata')
-    with tarfile.open(cm_tar_path) as tar_handle:
-      file_handles = tar_handle.getmembers()
-      assert len(file_handles) == 1
-
-      with tar_handle.extractfile(file_handles[0]) as f:
-        cm_data = json.load(io.TextIOWrapper(f))
-        utils.add_junit_test(
-            test_cases, 'confusion matrix format',
-            (len(cm_data['outputs'][0]['schema']) == 3),
-            'the column number of the confusion matrix output is not equal to three'
-        )
-  elif args.testname == 'xgboost_training_cm':
+  if args.testname == 'xgboost_training_cm':
     cm_tar_path = './confusion_matrix.tar.gz'
     utils.get_artifact_in_minio(workflow_json, 'confusion-matrix', cm_tar_path,
                                 'mlpipeline-ui-metadata')

test/sample-test/run_test.sh

@@ -203,17 +203,6 @@ xgboost_training_cm_injection() {
   sed -i "s|gcr.io/ml-pipeline/ml-pipeline-local-roc:\([a-zA-Z0-9_.-]\)\+|${LOCAL_ROC_IMAGE}|g" ${TEST_NAME}.yaml
 }
 
-################################################################################
-# Utility function to inject correct images to python files for
-# kubeflow_training_classification test.
-################################################################################
-kubeflow_training_classification_injection() {
-  sed -i "s|gcr.io/ml-pipeline/ml-pipeline-dataflow-tft:\([a-zA-Z0-9_.-]\)\+|${DATAFLOW_TFT_IMAGE}|g" ${TEST_NAME}.py
-  sed -i "s|gcr.io/ml-pipeline/ml-pipeline-kubeflow-tf-trainer:\([a-zA-Z0-9_.-]\)\+|${KUBEFLOW_DNNTRAINER_IMAGE}|g" ${TEST_NAME}.py
-  sed -i "s|gcr.io/ml-pipeline/ml-pipeline-dataflow-tf-predict:\([a-zA-Z0-9_.-]\)\+|${DATAFLOW_PREDICT_IMAGE}|g" ${TEST_NAME}.py
-  sed -i "s|gcr.io/ml-pipeline/ml-pipeline-local-confusion-matrix:\([a-zA-Z0-9_.-]\)\+|${LOCAL_CONFUSIONMATRIX_IMAGE}|g" ${TEST_NAME}.py
-}
-
 if [[ -z "$RESULTS_GCS_DIR" ]]; then
   usage
   exit 1
@@ -231,17 +220,7 @@ echo "Run the sample tests..."
 # Run the tests
 preparation ${TEST_NAME}
 
-if [[ "${TEST_NAME}" == "kubeflow_training_classification" ]]; then
-  #TODO(numerology): convert the sed commands to sed -e
-  # 's|gcr.io/ml-pipeline/|gcr.io/ml-pipeline-test/' and tag replacement. Also
-  # let the postsubmit tests refer to yaml files.
-  if [ -n "${DATAFLOW_TFT_IMAGE}" ];then
-    kubeflow_training_classification_injection
-  fi
-
-  dsl-compile --py "${TEST_NAME}.py" --output "${TEST_NAME}.yaml"
-  check_result ${TEST_NAME}
-elif [[ "${TEST_NAME}" == "tfx_cab_classification" ]]; then
+if [[ "${TEST_NAME}" == "tfx_cab_classification" ]]; then
   dsl-compile --py "${TEST_NAME}.py" --output "${TEST_NAME}.yaml"
   if [[ -n "${DATAFLOW_TFT_IMAGE}" ]]; then
     tfx_cab_classification_injection

test/sample_test.yaml

@@ -65,7 +65,6 @@ spec:
                 - name: test-name
                   value: "{{item}}"
             withItems:
-              - kubeflow_training_classification
               - tfx_cab_classification
               - xgboost_training_cm
               - kubeflow_pipeline_using_TFX_OSS_components