onnx model.py fix (nod-ai#254)

 For nod-ai/SHARK-ModelDev#683
 RAFT model test failed due to accessing`E2ESHARK_CHECK` with "inputs" instead of "input".
 Fixed other tests failing in the same way (found in model's `inference.log` file).

e2eshark/onnx/models/DeepLabV3_resnet50_vaiq_int8/model.py

@@ -33,9 +33,9 @@
 
 
 model_output = session.run(
-    [outputs[0].name],
+    [outputs[0].name, outputs[1].name],
     {inputs[0].name: model_input_X},
-)[0]
+)
 E2ESHARK_CHECK["input"] = [torch.from_numpy(model_input_X)]
 E2ESHARK_CHECK["output"] = [torch.from_numpy(arr) for arr in model_output]
 

e2eshark/onnx/models/FCN_vaiq_int8/model.py

@@ -35,7 +35,7 @@
 model_output = session.run(
     [outputs[0].name, outputs[1].name],
     {inputs[0].name: model_input_X},
-)[0]
+)
 E2ESHARK_CHECK["input"] = [torch.from_numpy(model_input_X)]
 E2ESHARK_CHECK["output"] = [torch.from_numpy(arr) for arr in model_output]
 

e2eshark/onnx/models/RAFT_vaiq_int8/model.py

@@ -48,12 +48,12 @@
         inputs[0].name: model_input_X,
         inputs[1].name: model_input_Y
     },
-)[0]
-E2ESHARK_CHECK["inputs"] = [torch.from_numpy(model_input_X), torch.from_numpy(model_input_Y)]
-E2ESHARK_CHECK["outputs"] = [torch.from_numpy(arr) for arr in model_output]
+)
+E2ESHARK_CHECK["input"] = [torch.from_numpy(model_input_X), torch.from_numpy(model_input_Y)]
+E2ESHARK_CHECK["output"] = [torch.from_numpy(arr) for arr in model_output]
 
-print("Input:", E2ESHARK_CHECK["inputs"])
-print("Output:", E2ESHARK_CHECK["outputs"])
+print("Input:", E2ESHARK_CHECK["input"])
+print("Output:", E2ESHARK_CHECK["output"])
 
 # Post process output to do:
 # sort(topk(torch.nn.functional.softmax(output, 0), 2)[1])[0]

e2eshark/onnx/models/U-2-Net_vaiq_int8/model.py

@@ -40,7 +40,7 @@
         outputs[6].name,
     ],
     {inputs[0].name: model_input_X},
-)[0]
+)
 E2ESHARK_CHECK["input"] = [torch.from_numpy(model_input_X)]
 E2ESHARK_CHECK["output"] = [torch.from_numpy(arr) for arr in model_output]
 

e2eshark/onnx/models/YoloNetV3_vaiq_int8/model.py

@@ -32,7 +32,7 @@
 model_output = session.run(
     [outputs[0].name],
     {inputs[0].name: model_input_X},
-)[0]
+)
 E2ESHARK_CHECK["input"] = [torch.from_numpy(model_input_X)]
 E2ESHARK_CHECK["output"] = [torch.from_numpy(arr) for arr in model_output]
 

e2eshark/onnx/models/u-net_brain_mri_vaiq_int8/model.py

@@ -32,7 +32,7 @@
 model_output = session.run(
     [outputs[0].name],
     {inputs[0].name: model_input_X},
-)[0]
+)
 E2ESHARK_CHECK["input"] = [torch.from_numpy(model_input_X)]
 E2ESHARK_CHECK["output"] = [torch.from_numpy(arr) for arr in model_output]
 

e2eshark/onnx/models/yolov8n_vaiq_int8/model.py

@@ -32,7 +32,7 @@
 model_output = session.run(
     [outputs[0].name, outputs[1].name, outputs[2].name, outputs[3].name],
     {inputs[0].name: model_input_X},
-)[0]
+)
 E2ESHARK_CHECK["input"] = [torch.from_numpy(model_input_X)]
 E2ESHARK_CHECK["output"] = [torch.from_numpy(arr) for arr in model_output]