Comments (2)
Hey, did you solve this issue?
from edge-informed-sisr.
开始训练...
训练时期:1 /usr/local/lib/python3.6/dist-packages/torchvision/transforms/functional.py:92:UserWarning:给定的 NumPy 数组不可写,PyTorch 不支持不可写张量。这意味着您可以使用张量写入底层(假定不可写)NumPy 数组。您可能希望复制数组以保护其数据或使其可写,然后再将其转换为张量。对于该程序的其余部分,将禁止此类警告。(在 /pytorch/torch/csrc/utils/tensor_numpy.cpp:141 内部触发。) img = torch.from_numpy(np.array(pic, np.float32, copy=False)) /usr/local/lib/python3.6/dist-packages/torchvision/transforms/functional.py:92:用户警告:给定的 NumPy 数组不可写,并且 PyTorch 不支持不可写张量。这意味着您可以使用张量写入底层(假定不可写)NumPy 数组。您可能希望复制数组以保护其数据或使其可写,然后再将其转换为张量。对于该程序的其余部分,将禁止此类警告。(在 /pytorch/torch/csrc/utils/tensor_numpy.cpp:141 内部触发。) img = torch.from_numpy(np.array(pic, np.float32, copy=False)) /usr/local/lib/python3.6/dist-packages/torchvision/transforms/functional.py:92:用户警告:给定的 NumPy 数组不可写,并且 PyTorch 不支持不可写张量。这意味着您可以使用张量写入底层(假定不可写)NumPy 数组。您可能希望复制数组以保护其数据或使其可写,然后再将其转换为张量。对于该程序的其余部分,将禁止此类警告。(在 /pytorch/torch/csrc/utils/tensor_numpy.cpp:141 内部触发。) img = torch.from_numpy(np.array(pic, np.float32, copy=False)) /usr/local/lib/python3.6/dist-packages/torchvision/transforms/functional.py:92:用户警告:给定的 NumPy 数组不可写,并且 PyTorch 不支持不可写张量。这意味着您可以使用张量写入底层(假定不可写)NumPy 数组。您可能希望复制数组以保护其数据或使其可写,然后再将其转换为张量。对于该程序的其余部分,将禁止此类警告。(在 /pytorch/torch/csrc/utils/tensor_numpy.cpp:141 内部触发。) img = torch.from_numpy(np.array(pic, np.float32, copy=False)) Traceback(最近一次调用最后一次): 文件“main.py”,第 120 行,在 main(mode=1) 文件“main.py”,第 50 行,在 main model.train() 文件“/content/drive/MyDrive/Colab Notebooks/SR/edge-informed-sisr-master/src/edge_match.py”,第 133 行,在火车 self.sr_model.backward(gen_loss, dis_loss) 文件“/content/drive /MyDrive/Colab Notebooks/SR/edge-informed-sisr-master/src/models.py”,第 283 行,在向后的 gen_loss.backward() 文件中“/usr/local/lib/python3.6/dist-packages/ torch/tensor.py”,第 221 行,后向 torch.autograd.backward(self, gradient, retain_graph, create_graph)文件 “/usr/local/lib/python3.6/dist-packages/torch/autograd/init .py ",第 132 行,后向 allow_unreachable=True) #allow_unreachable 标志****
RuntimeError:梯度计算所需的变量之一已被就地操作修改:[torch.cuda.FloatTensor [1, 512, 4, 4]] 为版本 2;而是预期的版本 1。提示:启用异常检测以查找未能计算其梯度的操作,使用 torch.autograd.set_detect_anomaly(True)。
有人知道这个错误并回答吗?
Hey, did you solve this issue?
Hey, did you solve this issue?
from edge-informed-sisr.
Related Issues (12)
- TypeError: torch.FloatTensor is not a Module subclass HOT 2
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- BrokenPipeError: [Errno 32] Broken pipe HOT 1
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- TypeError: torch.FloatTensor is not a Module subclass
- invalid argument 0: Sizes of tensors must match except in dimension 1. Got 256 and 130 in dimension 2 at /pytorch/aten/src/THC/generic/THCTensorMath.cu:71
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