RuntimeError: Inference tensors do not track version counter.

问题：

Testing DataLoader 0:   0%|          | 0/78 [00:00<?, ?it/s]Failed to collect metadata on function, produced code may be suboptimal.  Known situations this can occur are inference mode only compilation involving resize_ or prims (!schema.hasAnyAliasInfo() INTERNAL ASSERT FAILED); if your situation looks different please file a bug to PyTorch.
Traceback (most recent call last):File "/home/buty/.local/lib/python3.8/site-packages/torch/_functorch/aot_autograd.py", line 1674, in aot_wrapper_dedupefw_metadata, _out = run_functionalized_fw_and_collect_metadata(File "/home/buty/.local/lib/python3.8/site-packages/torch/_functorch/aot_autograd.py", line 606, in innerflat_f_outs = f(*flat_f_args)File "/home/buty/.local/lib/python3.8/site-packages/torch/_functorch/aot_autograd.py", line 2776, in functional_callout = Interpreter(mod).run(*args[params_len:], **kwargs)File "/home/buty/.local/lib/python3.8/site-packages/torch/fx/interpreter.py", line 136, in runself.env[node] = self.run_node(node)File "/home/buty/.local/lib/python3.8/site-packages/torch/fx/interpreter.py", line 177, in run_nodereturn getattr(self, n.op)(n.target, args, kwargs)File "/home/buty/.local/lib/python3.8/site-packages/torch/fx/interpreter.py", line 294, in call_modulereturn submod(*args, **kwargs)File "/home/buty/.local/lib/python3.8/site-packages/torch/nn/modules/module.py", line 1501, in _call_implreturn forward_call(*args, **kwargs)File "/home/buty/.local/lib/python3.8/site-packages/torch/nn/modules/linear.py", line 114, in forwardreturn F.linear(input, self.weight, self.bias)File "/home/buty/.local/lib/python3.8/site-packages/torch/_inductor/overrides.py", line 38, in __torch_function__return func(*args, **kwargs)
RuntimeError: Inference tensors do not track version counter.While executing %self_model_fc : [#users=3] = call_module[target=self_model_fc](args = (%flatten,), kwargs = {})
Original traceback:File "/home/buty/.local/lib/python3.8/site-packages/torchvision/models/resnet.py", line 280, in _forward_implx = self.fc(x)|   File "/home/buty/.local/lib/python3.8/site-packages/torchvision/models/resnet.py", line 285, in forwardreturn self._forward_impl(x)|   File "/opt/extend/buty/work/ocr/YuzuMarker.FontDetection/detector/model.py", line 53, in forwardX = self.model(X)Traceback (most recent call last):File "/home/buty/.local/lib/python3.8/site-packages/torch/_dynamo/output_graph.py", line 670, in call_user_compilercompiled_fn = compiler_fn(gm, self.fake_example_inputs())File "/home/buty/.local/lib/python3.8/site-packages/torch/_dynamo/debug_utils.py", line 1055, in debug_wrappercompiled_gm = compiler_fn(gm, example_inputs)File "/home/buty/.local/lib/python3.8/site-packages/torch/__init__.py", line 1390, in __call__return compile_fx(model_, inputs_, config_patches=self.config)File "/home/buty/.local/lib/python3.8/site-packages/torch/_inductor/compile_fx.py", line 455, in compile_fxreturn aot_autograd(File "/home/buty/.local/lib/python3.8/site-packages/torch/_dynamo/backends/common.py", line 48, in compiler_fncg = aot_module_simplified(gm, example_inputs, **kwargs)File "/home/buty/.local/lib/python3.8/site-packages/torch/_functorch/aot_autograd.py", line 2805, in aot_module_simplifiedcompiled_fn = create_aot_dispatcher_function(File "/home/buty/.local/lib/python3.8/site-packages/torch/_dynamo/utils.py", line 163, in time_wrapperr = func(*args, **kwargs)File "/home/buty/.local/lib/python3.8/site-packages/torch/_functorch/aot_autograd.py", line 2498, in create_aot_dispatcher_functioncompiled_fn = compiler_fn(flat_fn, fake_flat_args, aot_config)File "/home/buty/.local/lib/python3.8/site-packages/torch/_functorch/aot_autograd.py", line 1802, in aot_wrapper_dedupecompiled_fn = compiler_fn(wrapped_flat_fn, deduped_flat_args, aot_config)File "/home/buty/.local/lib/python3.8/site-packages/torch/_functorch/aot_autograd.py", line 1278, in aot_dispatch_base_fw_metadata, _out = run_functionalized_fw_and_collect_metadata(File "/home/buty/.local/lib/python3.8/site-packages/torch/_functorch/aot_autograd.py", line 606, in innerflat_f_outs = f(*flat_f_args)File "/home/buty/.local/lib/python3.8/site-packages/torch/_functorch/aot_autograd.py", line 1800, in wrapped_flat_fnreturn flat_fn(*add_dupe_args(args))File "/home/buty/.local/lib/python3.8/site-packages/torch/_functorch/aot_autograd.py", line 2776, in functional_callout = Interpreter(mod).run(*args[params_len:], **kwargs)File "/home/buty/.local/lib/python3.8/site-packages/torch/fx/interpreter.py", line 136, in runself.env[node] = self.run_node(node)File "/home/buty/.local/lib/python3.8/site-packages/torch/fx/interpreter.py", line 177, in run_nodereturn getattr(self, n.op)(n.target, args, kwargs)File "/home/buty/.local/lib/python3.8/site-packages/torch/fx/interpreter.py", line 294, in call_modulereturn submod(*args, **kwargs)File "/home/buty/.local/lib/python3.8/site-packages/torch/nn/modules/module.py", line 1501, in _call_implreturn forward_call(*args, **kwargs)File "/home/buty/.local/lib/python3.8/site-packages/torch/nn/modules/linear.py", line 114, in forwardreturn F.linear(input, self.weight, self.bias)File "/home/buty/.local/lib/python3.8/site-packages/torch/_inductor/overrides.py", line 38, in __torch_function__return func(*args, **kwargs)
RuntimeError: Inference tensors do not track version counter.While executing %self_model_fc : [#users=3] = call_module[target=self_model_fc](args = (%flatten,), kwargs = {})
Original traceback:File "/home/buty/.local/lib/python3.8/site-packages/torchvision/models/resnet.py", line 280, in _forward_implx = self.fc(x)|   File "/home/buty/.local/lib/python3.8/site-packages/torchvision/models/resnet.py", line 285, in forwardreturn self._forward_impl(x)|   File "/opt/extend/buty/work/ocr/YuzuMarker.FontDetection/detector/model.py", line 53, in forwardX = self.model(X)The above exception was the direct cause of the following exception:

主要是因为使用了torch.compile()

if torch.__version__ >= "2.0" and os.name == "posix":model = torch.compile(model)。。。。。。#trainer.fit(detector, datamodule=data_module, ckpt_path=args.checkpoint)
trainer.test(detector, datamodule=data_module)

解决办法：把model = torch.compile(model)去掉

#if torch.__version__ >= "2.0" and os.name == "posix":
#    model = torch.compile(model)。。。。。。#trainer.fit(detector, datamodule=data_module, ckpt_path=args.checkpoint)
trainer.test(detector, datamodule=data_module)