[Fix] Fix onnx unit tests (#2155)

tests/test_ops/test_onnx.py

@@ -67,7 +67,8 @@ def process_grid_sample(func, input, grid, ort_custom_op_path=''):
     input_initializer = [node.name for node in onnx_model.graph.initializer]
     net_feed_input = list(set(input_all) - set(input_initializer))
     assert (len(net_feed_input) == 2)
-    sess = rt.InferenceSession(onnx_file, session_options)
+    sess = rt.InferenceSession(
+        onnx_file, session_options, providers=['CPUExecutionProvider'])
     ort_result = sess.run(None, {
         'input': input.detach().numpy(),
         'grid': grid.detach().numpy()
@@ -160,7 +161,8 @@ def test_nms():
     input_initializer = [node.name for node in onnx_model.graph.initializer]
     net_feed_input = list(set(input_all) - set(input_initializer))
     assert (len(net_feed_input) == 2)
-    sess = rt.InferenceSession(onnx_file, session_options)
+    sess = rt.InferenceSession(
+        onnx_file, session_options, providers=['CPUExecutionProvider'])
     onnx_dets, _ = sess.run(None, {
         'scores': scores.detach().numpy(),
         'boxes': boxes.detach().numpy()
@@ -234,7 +236,8 @@ def test_softnms():
         ]
         net_feed_input = list(set(input_all) - set(input_initializer))
         assert (len(net_feed_input) == 2)
-        sess = rt.InferenceSession(onnx_file, session_options)
+        sess = rt.InferenceSession(
+            onnx_file, session_options, providers=['CPUExecutionProvider'])
         onnx_dets, onnx_inds = sess.run(None, {
             'scores': scores.detach().numpy(),
             'boxes': boxes.detach().numpy()
@@ -302,7 +305,8 @@ def test_roialign():
         ]
         net_feed_input = list(set(input_all) - set(input_initializer))
         assert (len(net_feed_input) == 2)
-        sess = rt.InferenceSession(onnx_file, session_options)
+        sess = rt.InferenceSession(
+            onnx_file, session_options, providers=['CPUExecutionProvider'])
         onnx_output = sess.run(None, {
             'input': input.detach().numpy(),
             'rois': rois.detach().numpy()
@@ -378,7 +382,8 @@ def test_roialign_rotated():
         ]
         net_feed_input = list(set(input_all) - set(input_initializer))
         assert (len(net_feed_input) == 2)
-        sess = rt.InferenceSession(onnx_file, session_options)
+        sess = rt.InferenceSession(
+            onnx_file, session_options, providers=['CPUExecutionProvider'])
         onnx_output = sess.run(None, {
             'features': input.detach().numpy(),
             'rois': rois.detach().numpy()
@@ -440,7 +445,8 @@ def test_roipool():
         ]
         net_feed_input = list(set(input_all) - set(input_initializer))
         assert (len(net_feed_input) == 2)
-        sess = rt.InferenceSession(onnx_file)
+        sess = rt.InferenceSession(
+            onnx_file, providers=['CPUExecutionProvider'])
         onnx_output = sess.run(
             None, {
                 'input': input.detach().cpu().numpy(),
@@ -470,7 +476,7 @@ def test_interpolate():
         onnx_file,
         input_names=['input'],
         opset_version=opset_version)
-    sess = rt.InferenceSession(onnx_file)
+    sess = rt.InferenceSession(onnx_file, providers=['CPUExecutionProvider'])
     onnx_result = sess.run(None, {'input': dummy_input.detach().numpy()})
     pytorch_result = func(dummy_input).detach().numpy()
 
@@ -581,7 +587,8 @@ def test_rotated_feature_align():
     input_initializer = [node.name for node in onnx_model.graph.initializer]
     net_feed_input = list(set(input_all) - set(input_initializer))
     assert (len(net_feed_input) == 2)
-    sess = rt.InferenceSession(onnx_file, session_options)
+    sess = rt.InferenceSession(
+        onnx_file, session_options, providers=['CPUExecutionProvider'])
     onnx_output = sess.run(None, {
         'feature': feature.detach().numpy(),
         'bbox': bbox.detach().numpy()
@@ -629,7 +636,8 @@ def test_corner_pool(mode, opset=11):
 
     session_options = rt.SessionOptions()
     session_options.register_custom_ops_library(ort_custom_op_path)
-    sess = rt.InferenceSession(onnx_file, session_options)
+    sess = rt.InferenceSession(
+        onnx_file, session_options, providers=['CPUExecutionProvider'])
     ort_result = sess.run(None, {'input': input.detach().numpy()})
     pytorch_results = wrapped_model(input.clone())
 
@@ -698,7 +706,8 @@ def test_cummax_cummin(key, opset=11):
 
             session_options = rt.SessionOptions()
             session_options.register_custom_ops_library(ort_custom_op_path)
-            sess = rt.InferenceSession(onnx_file, session_options)
+            sess = rt.InferenceSession(
+                onnx_file, session_options, providers=['CPUExecutionProvider'])
             ort_output, ort_inds = sess.run(None,
                                             {'input': input.detach().numpy()})
             pytorch_output, pytorch_inds = wrapped_model(input.clone())
@@ -737,7 +746,7 @@ def test_roll(shifts_dims_pair):
     net_feed_input = list(set(input_all) - set(input_initializer))
     assert (len(net_feed_input) == 1)
 
-    sess = rt.InferenceSession(onnx_file)
+    sess = rt.InferenceSession(onnx_file, providers=['CPUExecutionProvider'])
     ort_output = sess.run(None, {'input': input.detach().numpy()})[0]
 
     with torch.no_grad():
@@ -822,7 +831,8 @@ def test_modulated_deform_conv2d():
             session_options.register_custom_ops_library(ort_custom_op_path)
 
         # compute onnx_output
-        sess = rt.InferenceSession(onnx_file, session_options)
+        sess = rt.InferenceSession(
+            onnx_file, session_options, providers=['CPUExecutionProvider'])
         onnx_output = sess.run(
             None, {
                 'input': input.cpu().detach().numpy(),
@@ -902,7 +912,8 @@ def test_deform_conv2d(threshold=1e-3):
         session_options.register_custom_ops_library(ort_custom_op_path)
 
     # compute onnx_output
-    sess = rt.InferenceSession(onnx_file, session_options)
+    sess = rt.InferenceSession(
+        onnx_file, session_options, providers=['CPUExecutionProvider'])
     onnx_output = sess.run(
         None, {
             'input': x.cpu().detach().numpy(),