UniRepLKNet
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How to convert TesorRT
I trained the cas-unireplknet-l-fpn model. When I use mmdeploy to convert tensorRT, I get an error like this.
Traceback (most recent call last): File "/miniconda/envs/mmdet_v228/lib/python3.8/multiprocessing/process.py", line 315, in _bootstrap self.run() File "/miniconda/envs/mmdet_v228/lib/python3.8/multiprocessing/process.py", line 108, in run self._target(*self._args, **self._kwargs) File "/home/data/Code/mmdeploy/mmdeploy/apis/core/pipeline_manager.py", line 107, in __call__ ret = func(*args, **kwargs) File "/home/data/Code/mmdeploy/mmdeploy/apis/pytorch2onnx.py", line 98, in torch2onnx export( File "/home/data/Code/mmdeploy/mmdeploy/apis/core/pipeline_manager.py", line 356, in _wrap return self.call_function(func_name_, *args, **kwargs) File "/home/data/Code/mmdeploy/mmdeploy/apis/core/pipeline_manager.py", line 326, in call_function return self.call_function_local(func_name, *args, **kwargs) File "/home/data/Code/mmdeploy/mmdeploy/apis/core/pipeline_manager.py", line 275, in call_function_local return pipe_caller(*args, **kwargs) File "/home/data/Code/mmdeploy/mmdeploy/apis/core/pipeline_manager.py", line 107, in __call__ ret = func(*args, **kwargs) File "/home/data/Code/mmdeploy/mmdeploy/apis/onnx/export.py", line 122, in export torch.onnx.export( File "/miniconda/envs/mmdet_v228/lib/python3.8/site-packages/torch/onnx/__init__.py", line 316, in export return utils.export(model, args, f, export_params, verbose, training, File "/miniconda/envs/mmdet_v228/lib/python3.8/site-packages/torch/onnx/utils.py", line 107, in export _export(model, args, f, export_params, verbose, training, input_names, output_names, File "/miniconda/envs/mmdet_v228/lib/python3.8/site-packages/torch/onnx/utils.py", line 724, in _export _model_to_graph(model, args, verbose, input_names, File "/home/data/Code/mmdeploy/mmdeploy/core/rewriters/rewriter_utils.py", line 402, in wrapper return self.func(self, *args, **kwargs) File "/home/data/Code/mmdeploy/mmdeploy/apis/onnx/optimizer.py", line 10, in model_to_graph__custom_optimizer graph, params_dict, torch_out = ctx.origin_func(*args, **kwargs) File "/miniconda/envs/mmdet_v228/lib/python3.8/site-packages/torch/onnx/utils.py", line 497, in _model_to_graph graph = _optimize_graph(graph, operator_export_type, File "/miniconda/envs/mmdet_v228/lib/python3.8/site-packages/torch/onnx/utils.py", line 216, in _optimize_graph graph = torch._C._jit_pass_onnx(graph, operator_export_type) File "/miniconda/envs/mmdet_v228/lib/python3.8/site-packages/torch/onnx/__init__.py", line 373, in _run_symbolic_function return utils._run_symbolic_function(*args, **kwargs) File "/miniconda/envs/mmdet_v228/lib/python3.8/site-packages/torch/onnx/utils.py", line 1032, in _run_symbolic_function return symbolic_fn(g, *inputs, **attrs) File "/miniconda/envs/mmdet_v228/lib/python3.8/site-packages/torch/onnx/symbolic_helper.py", line 158, in wrapper assert len(arg_descriptors) >= len(args) AssertionError 2024-08-29 16:36:03,513 - mmdeploy - ERROR -
mmdeploy.apis.pytorch2onnx.torch2onnx with Call id: 0 failed. exit.
I tried to use reparameterize.py and then convert tensorRT , but got the same error.