RuntimeError: There were no tensor arguments to this function (e.g., you passed an empty list of ...

最新推荐文章于 2024-05-23 17:07:40 发布
原创 最新推荐文章于 2024-05-23 17:07:40 发布 · 1.8k 阅读 · 0 ·
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#python #pycharm #计算机视觉 #深度学习 #机器学习

在遇到`torch.cat()`函数报错时，检查到问题源于尝试对一个空列表操作。通过确保列表非空避免了该错误，从而保证代码逻辑的正确执行。
部署运行你感兴趣的模型镜像

当发生这个错误时，先寻找发生错误的代码，我的是

tensor_x = torch.cat(X, dim=0).to(device)

最终发现是因为我的 X 是一个空列表，所以才报了这个错误，仔细检查代码逻辑，使 X 不为空就不会报错了

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PyTorch 2.5

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PyTorch 是一个开源的 Python 机器学习库，基于 Torch 库，底层由 C++ 实现，应用于人工智能领域，如计算机视觉和自然语言处理

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raise NotImplementedError
【踩坑】RuntimeError: There were no tensor arguments to this function (e.g., you passed an empty list of
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RuntimeError: There were no tensor arguments to this function (e.g., you passed an empty list of Tensors), but no fallback function is registered for schema aten::_cat. This usually means that this function requires a non-empty list of Tensors. Available
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问题： RuntimeError: There were no tensor arguments to this function (e.g., you passed an empty list of Tensors), but no fallback function i [CUDATensorId, CPUTensorId, VariableTensorId] 出问题处的函数栈如下图。 从函数栈中可以看出最后一个函数是torch.cat([...])，所以问题出现在这个函数中。此外这个函数也是
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RuntimeError: There were no tensor arguments to this function (e.g., you passed an empty list of Tensors), but no fallback function is registered for schema aten::_cat. This usually means that this function requires a non-empty list of Tensors. Available
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跑yolov3时，出现RuntimeError: There were no tensor arguments to this function (e.g., you passed。。。如何解决 如图yolov3出现以下报错， 首先我已解决， 我出现的原因是test.py文件中的路径对不上，仔细该文件中出现的路径； 另外还应检查如何你检测的是2个类别，而你用的是80个类别的权重，此时也应修改。 ...
测试模型时RuntimeError: There were no tensor arguments to this function 解决方案
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标题RuntimeError: There were no tensor arguments to this function (e.g., you passed an empty list of Tensors), but no fallback function is registered for schema aten::_cat. This usually means that this...
RuntimeError: There were no tensor arguments to this function (e.g., you passed an empty list of Tensors), but no fallback function is registered for schema aten::_cat. This usually means that this function requires a non-empty list of Tensors. Available functions are [CPU, QuantizedCPU, BackendSelect, Named, AutogradOther, AutogradCPU, AutogradCUDA, AutogradXLA, AutogradNestedTensor, UNKNOWN_TENSOR_TYPE_ID, AutogradPrivateUse1, AutogradPrivateUse2, AutogradPrivateUse3, Tracer, Autocast, Batched, VmapMode].
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好的，我现在需要帮助用户解决PyTorch中的RuntimeError: no tensor arguments for aten::_cat fallback function required non-empty list错误。首先，我得理解这个错误的原因。根据错误信息，aten::_cat函数需要一...
Traceback (most recent call last): File "D:\资料\图片视屏大模型\yolov11\yolov11\train.py", line 11, in <module> model.train( File "D:\资料\图片视屏大模型\yolov11\yolov11\ultralytics\engine\model.py", line 796, in train self.trainer.train() File "D:\资料\图片视屏大模型\yolov11\yolov11\ultralytics\engine\trainer.py", line 211, in train self._do_train(world_size) File "D:\资料\图片视屏大模型\yolov11\yolov11\ultralytics\engine\trainer.py", line 443, in _do_train self.metrics, self.fitness = self.validate() File "D:\资料\图片视屏大模型\yolov11\yolov11\ultralytics\engine\trainer.py", line 639, in validate metrics = self.validator(self) File "E:\Anaconda\envs\yolovPhone\lib\site-packages\torch\autograd\grad_mode.py", line 27, in decorate_context return func(*args, **kwargs) File "D:\资料\图片视屏大模型\yolov11\yolov11\ultralytics\engine\validator.py", line 231, in __call__ stats = self.get_stats() File "D:\资料\图片视屏大模型\yolov11\yolov11\ultralytics\models\yolo\detect\val.py", line 247, in get_stats stats = {k: torch.cat(v, 0).cpu().numpy() for k, v in self.stats.items()} # to numpy File "D:\资料\图片视屏大模型\yolov11\yolov11\ultralytics\models\yolo\detect\val.py", line 247, in <dictcomp> stats = {k: torch.cat(v, 0).cpu().numpy() for k, v in self.stats.items()} # to numpy NotImplementedError: There were no tensor arguments to this function (e.g., you passed an empty list of Tensors), but no fallback function is registered for schema aten::_cat. This usually means that this function requires a non-empty list of Tensors, or that you (the operator writer) forgot to register a fallback function. Available functions are [CPU, CUDA, QuantizedCPU, BackendSelect, Python, Named, Conjugate, Negative, ZeroTensor, ADInplaceOrView, AutogradOther, AutogradCPU, AutogradCUDA, AutogradXLA, AutogradLazy, AutogradXPU, AutogradMLC, AutogradHPU, AutogradNestedTensor, AutogradPrivateUse1, AutogradPrivateUse2, AutogradPrivateUse3, Tracer, AutocastCPU, Autocast, Batched, VmapMode, Functionalize]. CPU: registered at C:\actions-runner\_work\pytorch\pytorch\builder\windows\pytorch\build\aten\src\ATen\RegisterCPU.cpp:21063 [kernel] CUDA: registered at C:\actions-runner\_work\pytorch\pytorch\builder\windows\pytorch\build\aten\src\ATen\RegisterCUDA.cpp:29726 [kernel] QuantizedCPU: registered at C:\actions-runner\_work\pytorch\pytorch\builder\windows\pytorch\build\aten\src\ATen\RegisterQuantizedCPU.cpp:1258 [kernel] BackendSelect: fallthrough registered at C:\actions-runner\_work\pytorch\pytorch\builder\windows\pytorch\aten\src\ATen\core\BackendSelectFallbackKernel.cpp:3 [backend fallback] Python: registered at C:\actions-runner\_work\pytorch\pytorch\builder\windows\pytorch\aten\src\ATen\core\PythonFallbackKernel.cpp:47 [backend fallback] Named: registered at C:\actions-runner\_work\pytorch\pytorch\builder\windows\pytorch\aten\src\ATen\core\NamedRegistrations.cpp:7 [backend fallback] Conjugate: registered at C:\actions-runner\_work\pytorch\pytorch\builder\windows\pytorch\aten\src\ATen\ConjugateFallback.cpp:18 [backend fallback] Negative: registered at C:\actions-runner\_work\pytorch\pytorch\builder\windows\pytorch\aten\src\ATen\native\NegateFallback.cpp:18 [backend fallback] ZeroTensor: registered at C:\actions-runner\_work\pytorch\pytorch\builder\windows\pytorch\aten\src\ATen\ZeroTensorFallback.cpp:86 [backend fallback] ADInplaceOrView: fallthrough registered at C:\actions-runner\_work\pytorch\pytorch\builder\windows\pytorch\aten\src\ATen\core\VariableFallbackKernel.cpp:64 [backend fallback] AutogradOther: registered at C:\actions-runner\_work\pytorch\pytorch\builder\windows\pytorch\torch\csrc\autograd\generated\VariableType_3.cpp:11380 [autograd kernel] AutogradCPU: registered at C:\actions-runner\_work\pytorch\pytorch\builder\windows\pytorch\torch\csrc\autograd\generated\VariableType_3.cpp:11380 [autograd kernel] AutogradCUDA: registered at C:\actions-runner\_work\pytorch\pytorch\builder\windows\pytorch\torch\csrc\autograd\generated\VariableType_3.cpp:11380 [autograd kernel] AutogradXLA: registered at C:\actions-runner\_work\pytorch\pytorch\builder\windows\pytorch\torch\csrc\autograd\generated\VariableType_3.cpp:11380 [autograd kernel] AutogradLazy: registered at C:\actions-runner\_work\pytorch\pytorch\builder\windows\pytorch\torch\csrc\autograd\generated\VariableType_3.cpp:11380 [autograd kernel] AutogradXPU: registered at C:\actions-runner\_work\pytorch\pytorch\builder\windows\pytorch\torch\csrc\autograd\generated\VariableType_3.cpp:11380 [autograd kernel] AutogradMLC: registered at C:\actions-runner\_work\pytorch\pytorch\builder\windows\pytorch\torch\csrc\autograd\generated\VariableType_3.cpp:11380 [autograd kernel] AutogradHPU: registered at C:\actions-runner\_work\pytorch\pytorch\builder\windows\pytorch\torch\csrc\autograd\generated\VariableType_3.cpp:11380 [autograd kernel] AutogradNestedTensor: registered at C:\actions-runner\_work\pytorch\pytorch\builder\windows\pytorch\torch\csrc\autograd\generated\VariableType_3.cpp:11380 [autograd kernel] AutogradPrivateUse1: registered at C:\actions-runner\_work\pytorch\pytorch\builder\windows\pytorch\torch\csrc\autograd\generated\VariableType_3.cpp:11380 [autograd kernel] AutogradPrivateUse2: registered at C:\actions-runner\_work\pytorch\pytorch\builder\windows\pytorch\torch\csrc\autograd\generated\VariableType_3.cpp:11380 [autograd kernel] AutogradPrivateUse3: registered at C:\actions-runner\_work\pytorch\pytorch\builder\windows\pytorch\torch\csrc\autograd\generated\VariableType_3.cpp:11380 [autograd kernel] Tracer: registered at C:\actions-runner\_work\pytorch\pytorch\builder\windows\pytorch\torch\csrc\autograd\generated\TraceType_3.cpp:11220 [kernel] AutocastCPU: fallthrough registered at C:\actions-runner\_work\pytorch\pytorch\builder\windows\pytorch\aten\src\ATen\autocast_mode.cpp:461 [backend fallback] Autocast: fallthrough registered at C:\actions-runner\_work\pytorch\pytorch\builder\windows\pytorch\aten\src\ATen\autocast_mode.cpp:305 [backend fallback] Batched: registered at C:\actions-runner\_work\pytorch\pytorch\builder\windows\pytorch\aten\src\ATen\BatchingRegistrations.cpp:1059 [backend fallback] VmapMode: fallthrough registered at C:\actions-runner\_work\pytorch\pytorch\builder\windows\pytorch\aten\src\ATen\VmapModeRegistrations.cpp:33 [backend fallback] Functionalize: registered at C:\actions-runner\_work\pytorch\pytorch\builder\windows\pytorch\aten\src\ATen\FunctionalizeFallbackKernel.cpp:52 [backend fallback] 表示的意思
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