Review comment fix, testcase added

tests/python/frontend/pytorch/test_forward.py

@@ -381,28 +381,61 @@ def test_forward_arange():
     class Arange1(Module):
         def forward(self, *args):
             return torch.arange(5)
+
     class Arange2(Module):
         def forward(self, *args):
             return torch.arange(2.5)
+
     class Arange3(Module):
         def forward(self, *args):
             return torch.arange(1, 4)
+
     class Arange4(Module):
         def forward(self, *args):
             return torch.arange(1, 2.5, 0.5)
+
     class Arange5(Module):
         def forward(self, *args):
             return torch.arange(1, 2, 1, dtype=torch.int32)
+
     class Arange6(Module):
         def forward(self, *args):
             return torch.arange(start=1, end=6, step=2)
+
     class Arange7(Module):
         def forward(self, *args):
             return torch.arange(1, 4, dtype=torch.float32)
+
     class Arange8(Module):
         def forward(self, *args):
             return torch.arange(1, 2, 1, dtype=torch.int16)
 
+    class Arange9(Module):
+        def forward(self, *args):
+            end = torch.add(torch.tensor(4), 1)
+            return torch.arange(end) + torch.ones((5,), dtype=torch.int64)
+
+    class Arange10(Module):
+        def forward(self, *args):
+            end = torch.add(torch.tensor(4.0), torch.tensor(1.0))
+            return torch.arange(end) + torch.ones((5,), dtype=torch.float)
+
+    class Arange11(Module):
+        def forward(self, *args):
+            start = torch.add(torch.tensor(1), 1)
+            end = torch.add(torch.tensor(4), 1)
+            step = torch.add(torch.tensor(2), 1)
+            out = torch.arange(start, end, step)
+            return out + torch.ones((3,), dtype=torch.int64)
+
+    class Arange12(Module):
+        def forward(self, *args):
+            start = torch.add(torch.tensor(1), 1)
+            end = torch.add(torch.tensor(4), 1)
+            step = torch.add(torch.tensor(2.5), torch.tensor(4.1))
+            out = torch.arange(start, end, step)
+            return out + torch.ones((3,), dtype=torch.float)
+
     verify_model(Arange1().float().eval())
     verify_model(Arange2().float().eval())
     verify_model(Arange3().float().eval())
@@ -411,6 +444,11 @@ def forward(self, *args):
     verify_model(Arange6().float().eval())
     verify_model(Arange7().float().eval())
     verify_model(Arange8().float().eval())
+    verify_model(Arange9().float().eval())
+    verify_model(Arange10().float().eval())
+    verify_model(Arange11().float().eval())
+    verify_model(Arange12().float().eval())
+
 
 def test_forward_abs():
     torch.set_grad_enabled(False)
@@ -810,9 +848,15 @@ class View2(Module):
         def forward(self, *args):
             return args[0].view(args[0].shape[0], -1)
 
+    class View3(Module):
+        def forward(self, *args):
+            d1 = torch.tensor(3) * torch.tensor(10) * torch.tensor(10)
+            return args[0].view(args[0].shape[0], d1)
+
     input_data = torch.rand(input_shape).float()
     verify_model(View1().float().eval(), input_data=input_data)
     verify_model(View2().float().eval(), input_data=input_data)
+    verify_model(View3().float().eval(), input_data=input_data)
 
 def test_forward_select():
     torch.set_grad_enabled(False)
@@ -896,9 +940,17 @@ class Slice2(Module):
         def forward(self, *args):
             return args[0][0, :, :, :]
 
+    class Slice3(Module):
+        def forward(self, *args):
+            x0 = torch.tensor(2) - torch.tensor(1)
+            x1 = torch.tensor(3) + torch.tensor(1)
+            return args[0][:, x0:, :x1, :]
+
     input_data = torch.rand(input_shape).float()
     verify_model(Slice1().float().eval(), input_data=input_data)
     verify_model(Slice2().float().eval(), input_data=input_data)
+    verify_model(Slice3().float().eval(), input_data=input_data)
+
 
 def test_forward_mean():
     torch.set_grad_enabled(False)