mmdeploy
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20 hours ago •
open-mmlab
open-mmlab
[Bug] SystemError: Exception escaped from default exception translator! when ONNX Inference
Checklist
- [X] I have searched related issues but cannot get the expected help.
- [X] 2. I have read the FAQ documentation but cannot get the expected help.
- [X] 3. The bug has not been fixed in the latest version.
Describe the bug
I have downloaded RTMPose-S static ONNX model from https://platform.openmmlab.com/deploee
I'm trying to do inference with that model with the code shown in the tutorial. With the same model shown in the tutorial (td-hm_hrnet-w32_8xb64-210e_coco-256x192) my code works, but with RTMPose-S it doesn't work.
The tutorial I'm talking about is this one: https://github.com/open-mmlab/mmdeploy/blob/main/docs/en/04-supported-codebases/mmpose.md
Reproduction
This is my code in Python:
deploy_cfg = 'mmdeploy/configs/mmpose/pose-detection_onnxruntime_static.py' model_cfg = 'mmpose/configs/body_2d_keypoint/rtmpose/coco/rtmpose-s_8xb256-420e_coco-256x192.py' device = 'cpu' backend_model = ['onnx-models/rtmpose-s-static.onnx'] image = 'image.jpg'
def get_image_prediction(deploy_cfg, model_cfg, device, backend_model, image, output_path):
# read deploy_cfg and model_cfg
deploy_cfg, model_cfg = load_config(deploy_cfg, model_cfg)
# build task and backend model
task_processor = build_task_processor(model_cfg, deploy_cfg, device)
model = task_processor.build_backend_model(backend_model)
# process input image
input_shape = get_input_shape(deploy_cfg)
model_inputs, _ = task_processor.create_input(image, input_shape)
# do model inference
with torch.no_grad():
result = model.test_step(model_inputs)
# visualize results
task_processor.visualize(
image=image,
model=model,
result=result[0],
window_name='visualize',
output_file=output_path)
get_image_prediction(deploy_cfg, model_cfg, device, backend_model, image, 'predictions/output-rtmpose-s-onnx.png')
Environment
03/01 09:42:44 - mmengine - INFO - TorchVision: 0.15.2
03/01 09:42:44 - mmengine - INFO - OpenCV: 4.9.0
03/01 09:42:44 - mmengine - INFO - MMEngine: 0.10.3
03/01 09:42:44 - mmengine - INFO - MMCV: 2.1.0
03/01 09:42:44 - mmengine - INFO - MMCV Compiler: MSVC 192930148
03/01 09:42:44 - mmengine - INFO - MMCV CUDA Compiler: 11.8
03/01 09:42:44 - mmengine - INFO - MMDeploy: 1.3.1+c9389c9
03/01 09:42:44 - mmengine - INFO -
03/01 09:42:44 - mmengine - INFO - **********Backend information**********
03/01 09:42:44 - mmengine - INFO - tensorrt: None
03/01 09:42:44 - mmengine - INFO - ONNXRuntime: 1.8.1
03/01 09:42:44 - mmengine - INFO - ONNXRuntime-gpu: None
03/01 09:42:44 - mmengine - INFO - ONNXRuntime custom ops: NotAvailable
03/01 09:42:44 - mmengine - INFO - pplnn: None
03/01 09:42:45 - mmengine - INFO - ncnn: None
03/01 09:42:45 - mmengine - INFO - snpe: None
03/01 09:42:45 - mmengine - INFO - openvino: None
03/01 09:42:45 - mmengine - INFO - torchscript: 2.2.1+cu118
03/01 09:42:45 - mmengine - INFO - torchscript custom ops: NotAvailable
03/01 09:42:45 - mmengine - INFO - rknn-toolkit: None
03/01 09:42:45 - mmengine - INFO - rknn-toolkit2: None
03/01 09:42:45 - mmengine - INFO - ascend: None
03/01 09:42:45 - mmengine - INFO - coreml: None
03/01 09:42:45 - mmengine - INFO - tvm: None
03/01 09:42:45 - mmengine - INFO - vacc: None
03/01 09:42:45 - mmengine - INFO -
03/01 09:42:45 - mmengine - INFO - **********Codebase information**********
03/01 09:42:45 - mmengine - INFO - mmdet: 3.2.0
03/01 09:42:45 - mmengine - INFO - mmseg: None
03/01 09:42:45 - mmengine - INFO - mmpretrain: None
03/01 09:42:45 - mmengine - INFO - mmocr: None
03/01 09:42:45 - mmengine - INFO - mmagic: None
03/01 09:42:45 - mmengine - INFO - mmdet3d: None
03/01 09:42:45 - mmengine - INFO - mmpose: 1.3.1
03/01 09:42:45 - mmengine - INFO - mmrotate: None
03/01 09:42:45 - mmengine - INFO - mmaction: None
03/01 09:42:45 - mmengine - INFO - mmrazor: None
03/01 09:42:45 - mmengine - INFO - mmyolo: None
Error traceback
SystemError Traceback (most recent call last)
Cell In[12], [line 1](vscode-notebook-cell:?execution_count=12&line=1)
----> [1](vscode-notebook-cell:?execution_count=12&line=1) get_image_prediction(deploy_cfg, model_cfg, device, backend_model, image, 'predicciones/output-rtmpose-m-onnx.png')
Cell In[11], [line 15](vscode-notebook-cell:?execution_count=11&line=15)
[13](vscode-notebook-cell:?execution_count=11&line=13) # do model inference
[14](vscode-notebook-cell:?execution_count=11&line=14) with torch.no_grad():
---> [15](vscode-notebook-cell:?execution_count=11&line=15) result = model.test_step(model_inputs)
[17](vscode-notebook-cell:?execution_count=11&line=17) # visualize results
[18](vscode-notebook-cell:?execution_count=11&line=18) task_processor.visualize(
[19](vscode-notebook-cell:?execution_count=11&line=19) image=image,
[20](vscode-notebook-cell:?execution_count=11&line=20) model=model,
[21](vscode-notebook-cell:?execution_count=11&line=21) result=result[0],
[22](vscode-notebook-cell:?execution_count=11&line=22) window_name='visualize',
[23](vscode-notebook-cell:?execution_count=11&line=23) output_file=output_path)
File [c:\Users\E2K6\anaconda3\envs\mmpose-env\lib\site-packages\mmengine\model\base_model\base_model.py:145](file:///C:/Users/E2K6/anaconda3/envs/mmpose-env/lib/site-packages/mmengine/model/base_model/base_model.py:145), in BaseModel.test_step(self, data)
[136](file:///C:/Users/E2K6/anaconda3/envs/mmpose-env/lib/site-packages/mmengine/model/base_model/base_model.py:136) """``BaseModel`` implements ``test_step`` the same as ``val_step``.
[137](file:///C:/Users/E2K6/anaconda3/envs/mmpose-env/lib/site-packages/mmengine/model/base_model/base_model.py:137)
[138](file:///C:/Users/E2K6/anaconda3/envs/mmpose-env/lib/site-packages/mmengine/model/base_model/base_model.py:138) Args:
(...)
[142](file:///C:/Users/E2K6/anaconda3/envs/mmpose-env/lib/site-packages/mmengine/model/base_model/base_model.py:142) list: The predictions of given data.
[143](file:///C:/Users/E2K6/anaconda3/envs/mmpose-env/lib/site-packages/mmengine/model/base_model/base_model.py:143) """
[144](file:///C:/Users/E2K6/anaconda3/envs/mmpose-env/lib/site-packages/mmengine/model/base_model/base_model.py:144) data = self.data_preprocessor(data, False)
--> [145](file:///C:/Users/E2K6/anaconda3/envs/mmpose-env/lib/site-packages/mmengine/model/base_model/base_model.py:145) return self._run_forward(data, mode='predict')
File [c:\Users\E2K6\anaconda3\envs\mmpose-env\lib\site-packages\mmengine\model\base_model\base_model.py:361](file:///C:/Users/E2K6/anaconda3/envs/mmpose-env/lib/site-packages/mmengine/model/base_model/base_model.py:361), in BaseModel._run_forward(self, data, mode)
[351](file:///C:/Users/E2K6/anaconda3/envs/mmpose-env/lib/site-packages/mmengine/model/base_model/base_model.py:351) """Unpacks data for :meth:`forward`
[352](file:///C:/Users/E2K6/anaconda3/envs/mmpose-env/lib/site-packages/mmengine/model/base_model/base_model.py:352)
[353](file:///C:/Users/E2K6/anaconda3/envs/mmpose-env/lib/site-packages/mmengine/model/base_model/base_model.py:353) Args:
(...)
[358](file:///C:/Users/E2K6/anaconda3/envs/mmpose-env/lib/site-packages/mmengine/model/base_model/base_model.py:358) dict or list: Results of training or testing mode.
[359](file:///C:/Users/E2K6/anaconda3/envs/mmpose-env/lib/site-packages/mmengine/model/base_model/base_model.py:359) """
[360](file:///C:/Users/E2K6/anaconda3/envs/mmpose-env/lib/site-packages/mmengine/model/base_model/base_model.py:360) if isinstance(data, dict):
--> [361](file:///C:/Users/E2K6/anaconda3/envs/mmpose-env/lib/site-packages/mmengine/model/base_model/base_model.py:361) results = self(**data, mode=mode)
[362](file:///C:/Users/E2K6/anaconda3/envs/mmpose-env/lib/site-packages/mmengine/model/base_model/base_model.py:362) elif isinstance(data, (list, tuple)):
[363](file:///C:/Users/E2K6/anaconda3/envs/mmpose-env/lib/site-packages/mmengine/model/base_model/base_model.py:363) results = self(*data, mode=mode)
File [c:\Users\E2K6\anaconda3\envs\mmpose-env\lib\site-packages\torch\nn\modules\module.py:1501](file:///C:/Users/E2K6/anaconda3/envs/mmpose-env/lib/site-packages/torch/nn/modules/module.py:1501), in Module._call_impl(self, *args, **kwargs)
[1496](file:///C:/Users/E2K6/anaconda3/envs/mmpose-env/lib/site-packages/torch/nn/modules/module.py:1496) # If we don't have any hooks, we want to skip the rest of the logic in
[1497](file:///C:/Users/E2K6/anaconda3/envs/mmpose-env/lib/site-packages/torch/nn/modules/module.py:1497) # this function, and just call forward.
[1498](file:///C:/Users/E2K6/anaconda3/envs/mmpose-env/lib/site-packages/torch/nn/modules/module.py:1498) if not (self._backward_hooks or self._backward_pre_hooks or self._forward_hooks or self._forward_pre_hooks
[1499](file:///C:/Users/E2K6/anaconda3/envs/mmpose-env/lib/site-packages/torch/nn/modules/module.py:1499) or _global_backward_pre_hooks or _global_backward_hooks
[1500](file:///C:/Users/E2K6/anaconda3/envs/mmpose-env/lib/site-packages/torch/nn/modules/module.py:1500) or _global_forward_hooks or _global_forward_pre_hooks):
-> [1501](file:///C:/Users/E2K6/anaconda3/envs/mmpose-env/lib/site-packages/torch/nn/modules/module.py:1501) return forward_call(*args, **kwargs)
[1502](file:///C:/Users/E2K6/anaconda3/envs/mmpose-env/lib/site-packages/torch/nn/modules/module.py:1502) # Do not call functions when jit is used
[1503](file:///C:/Users/E2K6/anaconda3/envs/mmpose-env/lib/site-packages/torch/nn/modules/module.py:1503) full_backward_hooks, non_full_backward_hooks = [], []
File [c:\users\e2k6\desktop\daniel\mmpose\mmdeploy\mmdeploy\codebase\mmpose\deploy\pose_detection_model.py:99](file:///C:/users/e2k6/desktop/daniel/mmpose/mmdeploy/mmdeploy/codebase/mmpose/deploy/pose_detection_model.py:99), in End2EndModel.forward(self, inputs, data_samples, mode, **kwargs)
[96](file:///C:/users/e2k6/desktop/daniel/mmpose/mmdeploy/mmdeploy/codebase/mmpose/deploy/pose_detection_model.py:96) assert mode == 'predict', \
[97](file:///C:/users/e2k6/desktop/daniel/mmpose/mmdeploy/mmdeploy/codebase/mmpose/deploy/pose_detection_model.py:97) 'Backend model only support mode==predict,' f' but get {mode}'
[98](file:///C:/users/e2k6/desktop/daniel/mmpose/mmdeploy/mmdeploy/codebase/mmpose/deploy/pose_detection_model.py:98) inputs = inputs.contiguous().to(self.device)
---> [99](file:///C:/users/e2k6/desktop/daniel/mmpose/mmdeploy/mmdeploy/codebase/mmpose/deploy/pose_detection_model.py:99) batch_outputs = self.wrapper({self.input_name: inputs})
[100](file:///C:/users/e2k6/desktop/daniel/mmpose/mmdeploy/mmdeploy/codebase/mmpose/deploy/pose_detection_model.py:100) batch_outputs = self.wrapper.output_to_list(batch_outputs)
[102](file:///C:/users/e2k6/desktop/daniel/mmpose/mmdeploy/mmdeploy/codebase/mmpose/deploy/pose_detection_model.py:102) codebase_cfg = get_codebase_config(self.deploy_cfg)
File [c:\Users\E2K6\anaconda3\envs\mmpose-env\lib\site-packages\torch\nn\modules\module.py:1501](file:///C:/Users/E2K6/anaconda3/envs/mmpose-env/lib/site-packages/torch/nn/modules/module.py:1501), in Module._call_impl(self, *args, **kwargs)
[1496](file:///C:/Users/E2K6/anaconda3/envs/mmpose-env/lib/site-packages/torch/nn/modules/module.py:1496) # If we don't have any hooks, we want to skip the rest of the logic in
[1497](file:///C:/Users/E2K6/anaconda3/envs/mmpose-env/lib/site-packages/torch/nn/modules/module.py:1497) # this function, and just call forward.
[1498](file:///C:/Users/E2K6/anaconda3/envs/mmpose-env/lib/site-packages/torch/nn/modules/module.py:1498) if not (self._backward_hooks or self._backward_pre_hooks or self._forward_hooks or self._forward_pre_hooks
[1499](file:///C:/Users/E2K6/anaconda3/envs/mmpose-env/lib/site-packages/torch/nn/modules/module.py:1499) or _global_backward_pre_hooks or _global_backward_hooks
[1500](file:///C:/Users/E2K6/anaconda3/envs/mmpose-env/lib/site-packages/torch/nn/modules/module.py:1500) or _global_forward_hooks or _global_forward_pre_hooks):
-> [1501](file:///C:/Users/E2K6/anaconda3/envs/mmpose-env/lib/site-packages/torch/nn/modules/module.py:1501) return forward_call(*args, **kwargs)
[1502](file:///C:/Users/E2K6/anaconda3/envs/mmpose-env/lib/site-packages/torch/nn/modules/module.py:1502) # Do not call functions when jit is used
[1503](file:///C:/Users/E2K6/anaconda3/envs/mmpose-env/lib/site-packages/torch/nn/modules/module.py:1503) full_backward_hooks, non_full_backward_hooks = [], []
File [c:\users\e2k6\desktop\daniel\mmpose\mmdeploy\mmdeploy\backend\onnxruntime\wrapper.py:108](file:///C:/users/e2k6/desktop/daniel/mmpose/mmdeploy/mmdeploy/backend/onnxruntime/wrapper.py:108), in ORTWrapper.forward(self, inputs)
[106](file:///C:/users/e2k6/desktop/daniel/mmpose/mmdeploy/mmdeploy/backend/onnxruntime/wrapper.py:106) if self.device_type == 'cuda':
[107](file:///C:/users/e2k6/desktop/daniel/mmpose/mmdeploy/mmdeploy/backend/onnxruntime/wrapper.py:107) torch.cuda.synchronize()
--> [108](file:///C:/users/e2k6/desktop/daniel/mmpose/mmdeploy/mmdeploy/backend/onnxruntime/wrapper.py:108) self.__ort_execute(self.io_binding)
[109](file:///C:/users/e2k6/desktop/daniel/mmpose/mmdeploy/mmdeploy/backend/onnxruntime/wrapper.py:109) output_list = self.io_binding.copy_outputs_to_cpu()
[110](file:///C:/users/e2k6/desktop/daniel/mmpose/mmdeploy/mmdeploy/backend/onnxruntime/wrapper.py:110) outputs = {}
File [c:\users\e2k6\desktop\daniel\mmpose\mmdeploy\mmdeploy\utils\timer.py:67](file:///C:/users/e2k6/desktop/daniel/mmpose/mmdeploy/mmdeploy/utils/timer.py:67), in TimeCounter.count_time.<locals>._register.<locals>.fun(*args, **kwargs)
[64](file:///C:/users/e2k6/desktop/daniel/mmpose/mmdeploy/mmdeploy/utils/timer.py:64) torch.cuda.synchronize()
[65](file:///C:/users/e2k6/desktop/daniel/mmpose/mmdeploy/mmdeploy/utils/timer.py:65) start_time = time.perf_counter()
---> [67](file:///C:/users/e2k6/desktop/daniel/mmpose/mmdeploy/mmdeploy/utils/timer.py:67) result = func(*args, **kwargs)
[69](file:///C:/users/e2k6/desktop/daniel/mmpose/mmdeploy/mmdeploy/utils/timer.py:69) if enable:
[70](file:///C:/users/e2k6/desktop/daniel/mmpose/mmdeploy/mmdeploy/utils/timer.py:70) if with_sync and torch.cuda.is_available():
File [c:\users\e2k6\desktop\daniel\mmpose\mmdeploy\mmdeploy\backend\onnxruntime\wrapper.py:126](file:///C:/users/e2k6/desktop/daniel/mmpose/mmdeploy/mmdeploy/backend/onnxruntime/wrapper.py:126), in ORTWrapper.__ort_execute(self, io_binding)
[118](file:///C:/users/e2k6/desktop/daniel/mmpose/mmdeploy/mmdeploy/backend/onnxruntime/wrapper.py:118) @TimeCounter.count_time(Backend.ONNXRUNTIME.value)
[119](file:///C:/users/e2k6/desktop/daniel/mmpose/mmdeploy/mmdeploy/backend/onnxruntime/wrapper.py:119) def __ort_execute(self, io_binding: ort.IOBinding):
[120](file:///C:/users/e2k6/desktop/daniel/mmpose/mmdeploy/mmdeploy/backend/onnxruntime/wrapper.py:120) """Run inference with ONNXRuntime session.
[121](file:///C:/users/e2k6/desktop/daniel/mmpose/mmdeploy/mmdeploy/backend/onnxruntime/wrapper.py:121)
[122](file:///C:/users/e2k6/desktop/daniel/mmpose/mmdeploy/mmdeploy/backend/onnxruntime/wrapper.py:122) Args:
[123](file:///C:/users/e2k6/desktop/daniel/mmpose/mmdeploy/mmdeploy/backend/onnxruntime/wrapper.py:123) io_binding (ort.IOBinding): To bind input/output to a specified
[124](file:///C:/users/e2k6/desktop/daniel/mmpose/mmdeploy/mmdeploy/backend/onnxruntime/wrapper.py:124) device, e.g. GPU.
[125](file:///C:/users/e2k6/desktop/daniel/mmpose/mmdeploy/mmdeploy/backend/onnxruntime/wrapper.py:125) """
--> [126](file:///C:/users/e2k6/desktop/daniel/mmpose/mmdeploy/mmdeploy/backend/onnxruntime/wrapper.py:126) self.sess.run_with_iobinding(io_binding)
File [c:\Users\E2K6\anaconda3\envs\mmpose-env\lib\site-packages\onnxruntime\capi\onnxruntime_inference_collection.py:229](file:///C:/Users/E2K6/anaconda3/envs/mmpose-env/lib/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py:229), in Session.run_with_iobinding(self, iobinding, run_options)
[222](file:///C:/Users/E2K6/anaconda3/envs/mmpose-env/lib/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py:222) def run_with_iobinding(self, iobinding, run_options=None):
[223](file:///C:/Users/E2K6/anaconda3/envs/mmpose-env/lib/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py:223) """
[224](file:///C:/Users/E2K6/anaconda3/envs/mmpose-env/lib/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py:224) Compute the predictions.
[225](file:///C:/Users/E2K6/anaconda3/envs/mmpose-env/lib/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py:225)
[226](file:///C:/Users/E2K6/anaconda3/envs/mmpose-env/lib/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py:226) :param iobinding: the iobinding object that has graph inputs/outputs bind.
[227](file:///C:/Users/E2K6/anaconda3/envs/mmpose-env/lib/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py:227) :param run_options: See :class:`onnxruntime.RunOptions`.
228 """
--> 229 self._sess.run_with_iobinding(iobinding._iobinding, run_options)
SystemError: Exception escaped from default exception translator!
