masahi commented on issue #6268:
URL: https://github.com/apache/incubator-tvm/issues/6268#issuecomment-685480132
I don't know what to do about it, other than wait for PyTorch people to fix
dtype saving. For quantized models, I added a workaround, but I don't know if
we can come up with a similar workaround (piggy back on to Relay's type
inference).
For reference, here is Torchscript IR with or without save/load:
without save/load
```
graph(%x : Long(4:5, 5:1)):
%1 : Long() = prim::Constant[value={1}]() # test.py:8:0
%2 : int = prim::Constant[value=1]() # test.py:8:0
%3 : Long(4:5, 5:1) = aten::sub(%x, %1, %2) # test.py:8:0
%4 : int = prim::Constant[value=4]() # test.py:8:0
%5 : bool = prim::Constant[value=0]() # test.py:8:0
%6 : bool = prim::Constant[value=0]() # test.py:8:0
%7 : None = prim::Constant()
%y.1 : Long(4:5, 5:1) = aten::to(%3, %4, %5, %6, %7) # test.py:8:0
%9 : int = prim::Constant[value=6]() # test.py:9:0
%10 : bool = prim::Constant[value=0]() # test.py:9:0
%11 : bool = prim::Constant[value=0]() # test.py:9:0
%12 : None = prim::Constant()
%y : Float(4:5, 5:1) = aten::to(%y.1, %9, %10, %11, %12) # test.py:9:0
%14 : int = prim::Constant[value=0]() # test.py:10:0
%15 : int = prim::Constant[value=0]() # test.py:10:0
%16 : int = prim::Constant[value=9223372036854775807]() # test.py:10:0
%17 : int = prim::Constant[value=1]() # test.py:10:0
%18 : Float(4:5, 5:1) = aten::slice(%y, %14, %15, %16, %17) # test.py:10:0
%19 : int = prim::Constant[value=1]() # test.py:10:0
%20 : int = prim::Constant[value=0]() # test.py:10:0
%21 : Float(4:5) = aten::select(%18, %19, %20) # test.py:10:0
return (%21)
```
```
graph(%self : __torch__.PlaceholderModule,
%x.1 : Tensor):
%2 : None = prim::Constant() # :0:0
%3 : bool = prim::Constant[value=0]() # test.py:8:0
%4 : Tensor = prim::Constant[value={1}]() # test.py:8:0
%5 : int = prim::Constant[value=1]() # test.py:8:0
%6 : int = prim::Constant[value=4]() # test.py:8:0
%7 : int = prim::Constant[value=6]() # test.py:9:0
%8 : int = prim::Constant[value=0]() # test.py:10:0
%9 : int = prim::Constant[value=9223372036854775807]() # test.py:10:0
%10 : Tensor = aten::sub(%x.1, %4, %5) # test.py:8:0
%y.1 : Tensor = aten::to(%10, %6, %3, %3, %2) # test.py:8:0
%y0.1 : Tensor = aten::to(%y.1, %7, %3, %3, %2) # test.py:9:0
%13 : Tensor = aten::slice(%y0.1, %8, %8, %9, %5) # test.py:10:0
%14 : Tensor = aten::select(%13, %5, %8) # test.py:10:0
return (%14)
```
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