debuging integration test for tf

.github/workflows/integration-test.yml

@@ -32,7 +32,7 @@ jobs:
 
     - name: Install dependencies
       run: |
-        pip install tensorflow==1.15.0
+        pip install tensorflow==2.6.0
         pip install onnx==1.9.0
         pip install torch==1.9.0
         pip install torchvision==0.10.0

tests/integration_test/test_latency_predictor.py

@@ -79,13 +79,13 @@ def integration_test(model_type, url, ppath, output_name = "tests/integration_te
     
     # start testing
     for pred_name, pred_version in get_predictors():
-        try:
+        # try:
         since = time.time()
         # print(f'nn-meter --{model_type} {ppath} --predictor {pred_name} --predictor-version {pred_version}')
         result = subprocess.check_output(['nn-meter', 'predict', f'--{model_type}', f'{ppath}', '--predictor', f'{pred_name}', '--predictor-version', f'{pred_version}'])
         runtime = time.time() - since
-        except NotImplementedError:
-            logging.error(f"Meets ERROR when checking --{model_type} {ppath} --predictor {pred_name} --predictor-version {pred_version}")
+        # except NotImplementedError:
+        #     logging.error(f"Meets ERROR when checking --{model_type} {ppath} --predictor {pred_name} --predictor-version {pred_version}")
 
         latency_list = parse_latency_info(result.decode('utf-8'))
         for model, latency in latency_list: