import order cause core dump

[allenling]

pytorch1.3.0, onnx1.6.0, onnxsim0.2.0

a simple test case

import torch
import onnx     # type: ignore
import onnxsim


def main():
    class TestNet(torch.nn.Module):
        def __init__(self):
            super(TestNet, self).__init__()
            self.conv = torch.nn.Conv1d(2, 3, kernel_size=(1,))
            return
        def forward(self, x):
            res = self.conv(x)
            return res
    net = TestNet()
    it = torch.randn(1, 2, 3)
    torch.onnx.export(net, it, "test_sim.onnx", export_params=True, verbose=True, input_names=["data"])
    model_opt = onnxsim.simplify(
        "test_sim.onnx"
        )
    print("export done")

    onnx.save(model_opt, "test_sim_simple.onnx")
    print("Ok!")


if __name__ == '__main__':
    main()

outputs

graph(%data : Float(1, 2, 3),
      %conv.weight : Float(3, 2, 1),
      %conv.bias : Float(3)):
  %3 : Float(1, 3, 3) = onnx::Conv[dilations=[1], group=1, kernel_shape=[1], pads=[0, 0], strides=[1]](%data, %conv.weight, %conv.bias), scope: TestNet/Conv1d[conv] # /usr/local/lib/python3.5/dist-packages/torch/nn/modules/conv.py:202:0
  return (%3)

Segmentation fault (core dumped)

but it works after i import torch after onnx

import torch
import onnx     # type: ignore
import onnxsim

change to

import onnx     # type: ignore
# import torch after onnx
import torch
import onnxsim

[daquexian]

Thanks for your report! I think it might be related to torch and onnx themselves, but not to onnxsim. Could you please check if it occurs due to the import of onnxsim? Allen Ling <notifications@github.com> 于 2019年11月16日周六 上午11:47写道：

…

pytorch1.3.0, onnx1.6.0, onnxsim0.2.0 a simple test case import torch import onnx # type: ignore import onnxsim def main(): class TestNet(torch.nn.Module): def __init__(self): super(TestNet, self).__init__() self.conv = torch.nn.Conv1d(2, 3, kernel_size=(1,)) return def forward(self, x): res = self.conv(x) return res net = TestNet() it = torch.randn(1, 2, 3) torch.onnx.export(net, it, "test_sim.onnx", export_params=True, verbose=True, input_names=["data"]) model_opt = onnxsim.simplify( "test_sim.onnx" ) print("export done") onnx.save(model_opt, "test_sim_simple.onnx") print("Ok!") if __name__ == '__main__': main() outputs graph(%data : Float(1, 2, 3), %conv.weight : Float(3, 2, 1), %conv.bias : Float(3)): %3 : Float(1, 3, 3) = onnx::Conv[dilations=[1], group=1, kernel_shape=[1], pads=[0, 0], strides=[1]](%data, %conv.weight, %conv.bias), scope: TestNet/Conv1d[conv] # /usr/local/lib/python3.5/dist-packages/torch/nn/modules/conv.py:202:0 return (%3) Segmentation fault (core dumped) but it works after i import torch after onnx import torch import onnx # type: ignore import onnxsim change to import onnx # type: ignore # import torch after onnx import torch import onnxsim — You are receiving this because you are subscribed to this thread. Reply to this email directly, view it on GitHub <#32?email_source=notifications&email_token=ACYRZH6LESJ3V6ESM5772GLQT5UNXA5CNFSM4JODIVC2YY3PNVWWK3TUL52HS4DFUVEXG43VMWVGG33NNVSW45C7NFSM4HZYKMRA>, or unsubscribe <https://github.com/notifications/unsubscribe-auth/ACYRZHZ7KPJXVFHT3HLFRT3QT5UNXANCNFSM4JODIVCQ> .

[allenling]

onnx.checker.check_model fail

def simplify(model_ori: Union[str, onnx.ModelProto], check_n: int = 0, perform_optimization: bool = True,
             input_shapes: TensorShapes = {}) \
        -> onnx.ModelProto:
    if type(model_ori) == str:
        model_ori = onnx.load(model_ori)
    # ===========>core dump here
    onnx.checker.check_model(model_ori)

guess it is a bug in torch/onnx, onnxsim is clean...

import torch
import onnx 


def main():
    class TestNet(torch.nn.Module):
        def __init__(self):
            super(TestNet, self).__init__()
            self.conv = torch.nn.Conv1d(2, 3, kernel_size=(1,))
            return
        def forward(self, x):
            res = self.conv(x)
            return res
    net = TestNet()
    it = torch.randn(1, 2, 3)
    torch.onnx.export(net, it, "test_sim.onnx", export_params=True, verbose=True, input_names=["data"])
    print("export done")
    model_ori = onnx.load("test_sim.onnx")
    onnx.checker.check_model(model_ori)
    print("Ok!")


if __name__ == '__main__':
    main()

core dump without onnxsim

[allenling]

issue in onnx onnx/onnx#2431

[daquexian]

issue in onnx onnx/onnx#2431

Thanks!