Hi,
I’m trying to trace FasterRCNN to use in Pytorch Mobile on iOS.
I simply trace as shown below:
model = torchvision.models.detection.fasterrcnn_resnet50_fpn(pretrained=True)
model.eval()
input_tensor = torch.rand(1,3,224,224)
script_model = torch.jit.trace(model, input_tensor)
script_model.save("models/fRCNN_resnet50.pt")
I receive a “Only tensors or tuples of tensors can be output from traced functions (getOutput at …/torch/csrc/jit/tracer.cpp:209)” error as shown below
RuntimeError: Only tensors or tuples of tensors can be output from traced functions (getOutput at ../torch/csrc/jit/tracer.cpp:209)
frame #0: c10::Error::Error(c10::SourceLocation, std::__1::basic_string<char, std::__1::char_traits<char>, std::__1::allocator<char> > const&) + 135 (0x128cc29e7 in libc10.dylib)
frame #1: torch::jit::tracer::TracingState::getOutput(c10::IValue const&) + 1785 (0x120164069 in libtorch.dylib)
frame #2: torch::jit::tracer::exit(std::__1::vector<c10::IValue, std::__1::allocator<c10::IValue> > const&) + 232 (0x120167108 in libtorch.dylib)
frame #3: torch::jit::tracer::createGraphByTracing(pybind11::function const&, torch::jit::tracer::TypedStack, pybind11::function const&, bool, torch::jit::script::Module*) + 916 (0x11c957914 in libtorch_python.dylib)
frame #4: void pybind11::cpp_function::initialize<torch::jit::script::initJitScriptBindings(_object*)::$_16, void, torch::jit::script::Module&, std::__1::basic_string<char, std::__1::char_traits<char>, std::__1::allocator<char> > const&, pybind11::function, pybind11::tuple, pybind11::function, bool, pybind11::name, pybind11::is_method, pybind11::sibling>(torch::jit::script::initJitScriptBindings(_object*)::$_16&&, void (*)(torch::jit::script::Module&, std::__1::basic_string<char, std::__1::char_traits<char>, std::__1::allocator<char> > const&, pybind11::function, pybind11::tuple, pybind11::function, bool), pybind11::name const&, pybind11::is_method const&, pybind11::sibling const&)::'lambda'(pybind11::detail::function_call&)::__invoke(pybind11::detail::function_call&) + 197 (0x11c993185 in libtorch_python.dylib)
frame #5: pybind11::cpp_function::dispatcher(_object*, _object*, _object*) + 3324 (0x11c4cd92c in libtorch_python.dylib)
frame #6: _PyCFunction_FastCallDict + 183 (0x10e3d0167 in Python)
frame #7: call_function + 184 (0x10e452d28 in Python)
frame #8: _PyEval_EvalFrameDefault + 27511 (0x10e44f597 in Python)
frame #9: _PyEval_EvalCodeWithName + 2447 (0x10e45388f in Python)
frame #10: fast_function + 545 (0x10e454141 in Python)
frame #11: call_function + 401 (0x10e452e01 in Python)
frame #12: _PyEval_EvalFrameDefault + 27511 (0x10e44f597 in Python)
frame #13: _PyEval_EvalCodeWithName + 2447 (0x10e45388f in Python)
frame #14: fast_function + 545 (0x10e454141 in Python)
frame #15: call_function + 401 (0x10e452e01 in Python)
frame #16: _PyEval_EvalFrameDefault + 27511 (0x10e44f597 in Python)
frame #17: _PyEval_EvalCodeWithName + 2447 (0x10e45388f in Python)
frame #18: PyEval_EvalCode + 100 (0x10e448954 in Python)
frame #19: builtin_exec + 548 (0x10e445fe4 in Python)
frame #20: _PyCFunction_FastCallDict + 491 (0x10e3d029b in Python)
frame #21: call_function + 439 (0x10e452e27 in Python)
frame #22: _PyEval_EvalFrameDefault + 27511 (0x10e44f597 in Python)
frame #23: gen_send_ex + 183 (0x10e3a7fe7 in Python)
frame #24: _PyEval_EvalFrameDefault + 11552 (0x10e44b740 in Python)
frame #25: gen_send_ex + 183 (0x10e3a7fe7 in Python)
frame #26: _PyEval_EvalFrameDefault + 11552 (0x10e44b740 in Python)
frame #27: gen_send_ex + 183 (0x10e3a7fe7 in Python)
frame #28: _PyCFunction_FastCallDict + 560 (0x10e3d02e0 in Python)
frame #29: call_function + 439 (0x10e452e27 in Python)
frame #30: _PyEval_EvalFrameDefault + 27511 (0x10e44f597 in Python)
frame #31: fast_function + 381 (0x10e45409d in Python)
frame #32: call_function + 401 (0x10e452e01 in Python)
frame #33: _PyEval_EvalFrameDefault + 27511 (0x10e44f597 in Python)
frame #34: fast_function + 381 (0x10e45409d in Python)
frame #35: call_function + 401 (0x10e452e01 in Python)
frame #36: _PyEval_EvalFrameDefault + 27511 (0x10e44f597 in Python)
frame #37: _PyEval_EvalCodeWithName + 2447 (0x10e45388f in Python)
frame #38: _PyFunction_FastCallDict + 763 (0x10e45445b in Python)
frame #39: _PyObject_FastCallDict + 247 (0x10e3873e7 in Python)
frame #40: _PyObject_Call_Prepend + 149 (0x10e387505 in Python)
frame #41: PyObject_Call + 96 (0x10e387220 in Python)
frame #42: _PyEval_EvalFrameDefault + 28250 (0x10e44f87a in Python)
frame #43: _PyEval_EvalCodeWithName + 2447 (0x10e45388f in Python)
frame #44: fast_function + 545 (0x10e454141 in Python)
frame #45: call_function + 401 (0x10e452e01 in Python)
frame #46: _PyEval_EvalFrameDefault + 27670 (0x10e44f636 in Python)
frame #47: gen_send_ex + 183 (0x10e3a7fe7 in Python)
frame #48: builtin_next + 92 (0x10e446bcc in Python)
frame #49: _PyCFunction_FastCallDict + 491 (0x10e3d029b in Python)
frame #50: call_function + 439 (0x10e452e27 in Python)
frame #51: _PyEval_EvalFrameDefault + 27511 (0x10e44f597 in Python)
frame #52: _PyEval_EvalCodeWithName + 2447 (0x10e45388f in Python)
frame #53: fast_function + 545 (0x10e454141 in Python)
frame #54: call_function + 401 (0x10e452e01 in Python)
frame #55: _PyEval_EvalFrameDefault + 27511 (0x10e44f597 in Python)
frame #56: gen_send_ex + 183 (0x10e3a7fe7 in Python)
frame #57: builtin_next + 92 (0x10e446bcc in Python)
frame #58: _PyCFunction_FastCallDict + 491 (0x10e3d029b in Python)
frame #59: call_function + 439 (0x10e452e27 in Python)
frame #60: _PyEval_EvalFrameDefault + 27511 (0x10e44f597 in Python)
frame #61: _PyEval_EvalCodeWithName + 2447 (0x10e45388f in Python)
frame #62: fast_function + 545 (0x10e454141 in Python)
frame #63: call_function + 401 (0x10e452e01 in Python)
Could someone explain to me how to properly trace or script a pretrained object detection model such as this one? I don’t know which steps I might be missing if any!