[Relay][Frontend[Onnx] Add testing for output datatypes and fix relat…

…ed bugs. (apache#7364)

* Add testing for datatypes and fix related bugs.

* Fix lint issue in onnx.

python/tvm/relay/frontend/onnx.py

@@ -1451,7 +1451,7 @@ def _impl_v1(cls, inputs, attr, params):
         axis = attr.get("axis", 0)
         keepdims = attr.get("keepdims", True)
         attr = {"axis": axis, "keepdims": keepdims}
-        return AttrCvt("argmax")(inputs, attr)
+        return _op.cast(AttrCvt("argmax")(inputs, attr), "int64")
 
 
 class ArgMin(OnnxOpConverter):
@@ -1462,7 +1462,7 @@ def _impl_v1(cls, inputs, attr, params):
         axis = attr.get("axis", 0)
         keepdims = attr.get("keepdims", True)
         attr = {"axis": axis, "keepdims": keepdims}
-        return AttrCvt("argmin")(inputs, attr)
+        return _op.cast(AttrCvt("argmin")(inputs, attr), "int64")
 
 
 class Softmax(OnnxOpConverter):
@@ -2000,7 +2000,7 @@ def _impl_v1(cls, inputs, attr, params):
         if largest == 0:
             raise ValueError("TVM only supports finding TopK largest elements")
 
-        return _op.topk(inputs[0], inputs[1], axis=axis)
+        return _op.topk(inputs[0], inputs[1], axis=axis, dtype="int64")
 
 
 class Range(OnnxOpConverter):

tests/python/frontend/onnx/test_forward.py

@@ -163,6 +163,7 @@ def verify_with_ort_with_inputs(
                 ort_val = scipy.special.softmax(ort_val)
                 tvm_val = scipy.special.softmax(tvm_val)
             tvm.testing.assert_allclose(ort_val, tvm_val, rtol=rtol, atol=atol)
+            assert ort_val.dtype == tvm_val.dtype
 
 
 def verify_with_ort(