masahi commented on issue #4497: [WIP] [Relay] Add a PyTorch to Relay Parser URL: https://github.com/apache/incubator-tvm/pull/4497#issuecomment-574076780 @alexwong I tried your PR locally. With pytorch v1.3 it works, but they introduced big change in [#28408](https://github.com/pytorch/pytorch/pull/28408) and [#28409](https://github.com/pytorch/pytorch/pull/28409), and it broke your PR (I may be wrong about which PR broke it). Below is how their IR looks like for resnet18 now. My pytorch version is '1.5.0a0+0dbd5c0' (the output of torch.__version__). ``` graph(%self.1 : __torch__.torch.nn.modules.module.___torch_mangle_66.Module, %input.1 : Float(1, 3, 224, 224)): %1452 : __torch__.torch.nn.modules.module.___torch_mangle_65.Module = prim::GetAttr[name="fc"](%self.1) %1449 : __torch__.torch.nn.modules.module.___torch_mangle_64.Module = prim::GetAttr[name="avgpool"](%self.1) %1448 : __torch__.torch.nn.modules.module.___torch_mangle_63.Module = prim::GetAttr[name="layer4"](%self.1) %1402 : __torch__.torch.nn.modules.module.___torch_mangle_47.Module = prim::GetAttr[name="layer3"](%self.1) %1356 : __torch__.torch.nn.modules.module.___torch_mangle_31.Module = prim::GetAttr[name="layer2"](%self.1) %1310 : __torch__.torch.nn.modules.module.___torch_mangle_15.Module = prim::GetAttr[name="layer1"](%self.1) %1273 : __torch__.torch.nn.modules.module.___torch_mangle_2.Module = prim::GetAttr[name="maxpool"](%self.1) %1272 : __torch__.torch.nn.modules.module.___torch_mangle_1.Module = prim::GetAttr[name="relu"](%self.1) %1271 : __torch__.torch.nn.modules.module.___torch_mangle_0.Module = prim::GetAttr[name="bn1"](%self.1) %1265 : __torch__.torch.nn.modules.module.Module = prim::GetAttr[name="conv1"](%self.1) %1528 : Tensor = prim::CallMethod[name="forward"](%1265, %input.1) %1529 : Tensor = prim::CallMethod[name="forward"](%1271, %1528) %1530 : Tensor = prim::CallMethod[name="forward"](%1272, %1529) %1531 : Tensor = prim::CallMethod[name="forward"](%1273, %1530) %1532 : Tensor = prim::CallMethod[name="forward"](%1310, %1531) %1533 : Tensor = prim::CallMethod[name="forward"](%1356, %1532) %1534 : Tensor = prim::CallMethod[name="forward"](%1402, %1533) %1535 : Tensor = prim::CallMethod[name="forward"](%1448, %1534) %1536 : Tensor = prim::CallMethod[name="forward"](%1449, %1535) %1182 : int = prim::Constant[value=1]() # /home/masa/anaconda3/lib/python3.7/site-packages/torchvision-0.5.0a0+07cbb46-py3.7-linux-x86_64.egg/torchvision/models/resnet.py:210:0 %1183 : int = prim::Constant[value=-1]() # /home/masa/anaconda3/lib/python3.7/site-packages/torchvision-0.5.0a0+07cbb46-py3.7-linux-x86_64.egg/torchvision/models/resnet.py:210:0 %input : Float(1, 512) = aten::flatten(%1536, %1182, %1183) # /home/masa/anaconda3/lib/python3.7/site-packages/torchvision-0.5.0a0+07cbb46-py3.7-linux-x86_64.egg/torchvision/models/resnet.py:210:0 %1537 : Tensor = prim::CallMethod[name="forward"](%1452, %input) return (%1537) ```
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