Fix a bug caused by PyTorch instance_norm when the input shape is [1,1,1,2]

python/tvm/relay/frontend/pytorch.py

@@ -4424,7 +4424,7 @@ def _create_typed_const(data, dtype):
     dtype should be a TVM dtype"""
 
     if dtype == "float64":
-        typed_data = _expr.const(np.float64(data), dtype=dtype)
+        typed_data = _expr.const(np.asarray(data, dtype="float64"), dtype=dtype)
     elif dtype == "float32":
         typed_data = _expr.const(np.float32(data), dtype=dtype)
     elif dtype == "float16":

tests/python/frontend/pytorch/test_forward.py

@@ -3449,6 +3449,20 @@ def test_forward_adaptive_max_pool1d():
     verify_model(m.float().eval(), input_data=input_data)
 
 
+@tvm.testing.uses_gpu
+def test_forward_instance_norm():
+    """test_forward_instance_norm"""
+
+    class instance_norm(Module):
+        def forward(self, *args):
+            return torch.nn.functional.instance_norm(args[0], use_input_stats=True)
+
+    m = instance_norm().float().eval()
+    input_data = torch.randn([1, 1, 1, 2], dtype=torch.float64)
+
+    verify_model(m.float().eval(), input_data=input_data)
+
+
 @tvm.testing.uses_gpu
 def test_forward_full_like():
     """test_forward_full_like"""