Improve test

tests/python/frontend/pytorch/test_forward.py

@@ -3241,6 +3241,7 @@ def test_forward_pretrained_bert_base_uncased():
 
 
 if __name__ == "__main__":
+    """
     # some structural tests
     test_forward_traced_function()
     test_forward_dtypes()
@@ -3398,6 +3399,7 @@ def test_forward_pretrained_bert_base_uncased():
 
     # Test bert model
     test_forward_pretrained_bert_base_uncased()
+    """
 
     # Test object detection models
     from test_object_detection import test_detection_models

tests/python/frontend/pytorch/test_object_detection.py

@@ -16,6 +16,7 @@
 # under the License.
 # pylint: disable=import-self, invalid-name, unused-argument
 """Test torch vision fasterrcnn and maskrcnn models"""
+import numpy as np
 import torch
 import torchvision
 import cv2
@@ -31,6 +32,7 @@
 
 def process_image(img):
     img = cv2.imread(img).astype("float32")
+    img = cv2.resize(img, (in_size, in_size))
     img = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)
     img = torch.from_numpy(img/255.).permute(2,0,1).float()
     img = torch.unsqueeze(img, axis=0)
@@ -68,7 +70,7 @@ def generate_jit_model(index, img):
     model = TraceWrapper(model_func(pretrained=True))
 
     model.eval()
-    inp = process_image(img)
+    inp = torch.Tensor(np.random.uniform(0.0, 250.0,size=(1, 3, in_size, in_size)))
 
     with torch.no_grad():
         out = model(inp)