RuntimeError: expected scalartypeFloat but found Long 错误原因 错误信息指出了问题所在:模型期望的数据类型是float,但实际上传递给模型的数据类型是 long。 这个错误通常是由于张量数据类型不匹配引起的。在 PyTorch 中,张量数据类型非常重要,因为它们指定了张量中存储的数值的精度和类型。如果您在模型的前向传递中...
在使用PyTorch进行深度学习开发时,遇到“expected scalar type long but found float”错误通常意味着在期望整数(long)类型的操作中错误地使用了浮点数(float)类型。以下是一些解决这个问题的步骤和建议: 理解PyTorch中的数据类型及其用途: torch.float 和torch.double:用于存储浮点数,适用于需要高精度计算的场景,如梯...
RuntimeError: result type Float can‘t be cast to the desired output type Long 使用BCEWithLogitsLoss()时RuntimeError: result type Float can't be cast to the desired output type Long使用BCEWithLogitsLoss(output,target),output 为float类型,target为int64,报错RuntimeError: result type Float can'...
参考https://stackoverflow.com/questions/60440292/runtimeerror-expected-scalar-type-long-but-found-float 原因是categorical target不能为浮点型,只能是整数,比如属于某一类 所以,把target改为整型 >>> x = torch.rand(64, 4)>>> y = torch.randint(0,4, (64,))>>>criterion(x, y) tensor(1.4477)...
Python - RuntimeError: Expected object of scalar type, RuntimeError: Expected object of scalar type Long but got scalar type Float for argument #2 'target' in call to _thnn_nll_loss_forward 0 RuntimeError: expected scalar type Float but ...
If you are, use one of the solutions we’ve outlined in this article to fix the error. By doing that, you can make sure that your Python code runs smoothly without any errors. We hope you found this article helpful in fixing the “Runtimeerror expected scalar type long but found float...
(model, args, verbose, input_names, File "<some_path>/miniconda3/envs/<my-env>/lib/python3.8/site-packages/torch/onnx/utils.py", line 501, in _model_to_graph params_dict = torch._C._jit_pass_onnx_constant_fold(graph, params_dict, RuntimeError: expected scalar type Long but ...
I ran examples/hello-world.py and ended up with RuntimeError: expected scalar type Long but found Float. My environment: pytorch=1.13.1, cudatoolkit=10.0.130, gcc/g++=7.5.0. Here is the complete log. How can I fix it? (base) root@efbc464e2a2e:/~/SparseConvNet# python examples/he...
一个细节:torch.float等同于torch.float32,同样的torch.long等同于torch.int64,torch.double等同于torch.float64等等 a=torch.tensor([1],dtype=torch.float)print(a.dtype)# torch.float32 dtype就是在创建tensor时,要指定的参数,那什么CPU tensor,GPU tensor又是什么东西?顾名思义,就是在cpu和gpu上的数据类型...
expected scalar type Long but found Float Pytorch tensor と numpy ndarray の変換 - Pythonいぬ (hatenablog.com) 主要还是 array 转 tensor的时候要确定类型 x = torch.from_numpy(x.astype(np.float32))