frame #37: __libc_start_main + 0xd5 (0x7f6b88f11565 in /lib/x86_64-linux-gnu/libc.so.6)
 (function ComputeConstantFolding)
[W shape_type_inference.cpp:419] Warning: Constant folding in symbolic shape inference fails: expected scalar type Long but found Float
Exception raised from data_ptr<long int> at aten/src/ATen/core/TensorMethods.cpp:5759 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x42 (0x7f6acc30aa22 in /home/jintian/anaconda3/lib/python3.8/site-packages/torch/lib/libc10.so)
frame #1: c10::detail::torchCheckFail(char const*, char const*, unsigned int, std::string const&) + 0x5b (0x7f6acc3073db in /home/jintian/anaconda3/lib/python3.8/site-packages/torch/lib/libc10.so)
frame #2: long* at::Tensor::data_ptr<long>() const + 0xde (0x7f6ace4511fe in /home/jintian/anaconda3/lib/python3.8/site-packages/torch/lib/libtorch_cpu.so)
frame #3: torch::jit::onnx_constant_fold::runTorchSlice_opset10(torch::jit::Node const*, std::vector<at::Tensor, std::allocator<at::Tensor> >&) + 0x42e (0x7f6b7118d63e in /home/jintian/anaconda3/lib/python3.8/site-packages/torch/lib/libtorch_python.so)
frame #4: torch::jit::onnx_constant_fold::runTorchBackendForOnnx(torch::jit::Node const*, std::vector<at::Tensor, std::allocator<at::Tensor> >&, int) + 0x1c5 (0x7f6b7118e985 in /home/jintian/anaconda3/lib/python3.8/site-packages/torch/lib/libtorch_python.so)
frame #5: <unknown function> + 0xaed38e (0x7f6b711cd38e in /home/jintian/anaconda3/lib/python3.8/site-packages/torch/lib/libtorch_python.so)
frame #6: torch::jit::ONNXShapeTypeInference(torch::jit::Node*, std::map<std::string, c10::IValue, std::less<std::string>, std::allocator<std::pair<std::string const, c10::IValue> > > const&, int) + 0x906 (0x7f6b711d2146 in /home/jintian/anaconda3/lib/python3.8/site-packages/torch/lib/libtorch_python.so)
frame #7: <unknown function> + 0xaf4df4 (0x7f6b711d4df4 in /home/jintian/anaconda3/lib/python3.8/site-packages/torch/lib/libtorch_python.so)
frame #8: <unknown function> + 0xa71010 (0x7f6b71151010 in /home/jintian/anaconda3/lib/python3.8/site-packages/torch/lib/libtorch_python.so)
frame #9: <unknown function> + 0x5015fe (0x7f6b70be15fe in /home/jintian/anaconda3/lib/python3.8/site-packages/torch/lib/libtorch_python.so)
<omitting python frames>
frame #37: __libc_start_main + 0xd5 (0x7f6b88f11565 in /lib/x86_64-linux-gnu/libc.so.6)
 (function ComputeConstantFolding)
Traceback (most recent call last):
  File "export_onnx.py", line 261, in <module>
    torch.onnx.export(model, inp, onnx_f, output_names={
  File "/home/jintian/anaconda3/lib/python3.8/site-packages/torch/onnx/__init__.py", line 275, in export
    return utils.export(model, args, f, export_params, verbose, training,
  File "/home/jintian/anaconda3/lib/python3.8/site-packages/torch/onnx/utils.py", line 88, in export
    _export(model, args, f, export_params, verbose, training, input_names, output_names,
  File "/home/jintian/anaconda3/lib/python3.8/site-packages/torch/onnx/utils.py", line 689, in _export
    _model_to_graph(model, args, verbose, input_names,
  File "/home/jintian/anaconda3/lib/python3.8/site-packages/torch/onnx/utils.py", line 501, in _model_to_graph
    params_dict = torch._C._jit_pass_onnx_constant_fold(graph, params_dict,
RuntimeError: expected scalar type Long but found Float