问题描述 昨天跟着一篇博客BERT 的 PyTorch 实现从头写了一下BERT的代码,因为原代码是在CPU上运行的,于是就想将模型和数据放到GPU上来跑,会快一点。结果,在将输入数据和模型都放到cuda上之后,仍然提示报错: "RuntimeError: Input, output and indices must be on the current device" 原因与解决方法 通
有时候想在pytorch中修改训练过程中网络模型的参数。比如做网络稀疏化训练,对于某一层卷基层的参数,如果值小于一定阈值就想赋值为0,这时就需要实时修改网络模型的参数,如果直接修改会报错: RuntimeError: leaf variable has been moved into the graph interior 这是因为pytorch中会有叶子张量和非叶子张量之分,这
🏆本文收录于「Bug调优」专栏,主要记录项目实战过程中的Bug之前因后果及提供真实有效的解决方案,希望能够助你一臂之力,帮你早日登顶实现财富自由🚀;同时,欢迎大家关注&&收藏&&订阅!持续更新中,up!up!up!! 问题描述 mmdetection运行mask rcnn,训练模型时运行train.py出现RuntimeError: CUDA out of memory. T
报错信息: File "/root/miniconda3/lib/python3.8/site-packages/torch/nn/modules/conv.py", line 297, in _conv_forwardreturn F.conv1d(input, weight, bias, self.stride,RuntimeError: CUDA error: CUBLAS_STATUS
训练模型时报错: RuntimeError: Attempted to send CUDA tensor received from another process; this is not currently supported. Consider cloning before sending. 翻译:RuntimeError:尝试发送从其他进程接收的 CUDA 张量;目前不支持此
运行guillaumekln/faster-whisper-large-v2模型进行语音识别的时候报错了 RuntimeError: Library cublas64_12.dll is not found or cannot be loaded 代码: from faster_whisper import WhisperModelmodel = WhisperModel("H:\\mode
报错 RuntimeError: OpenSSL 3.0's legacy provider failed to load. This is a fatal error by default, but cryptography supports running without legacy algorithms by setting the environment variable CRYPTO
之前跑的好好的代码,今天一跑竟然报错了。最近总是这样,前一天跑的好好的,第二天就会出现奇奇怪怪的报错。 有一行提示 UserWarning: NumPy 1.14.5 or above is required for this version of SciPy (detected version 1.13.1)。 首先,通过以下代码查看numpy版本 conda activate pytor
报错如下: RuntimeError: call aclnnAddmm failed, detail:E20002: Value [/usr/local/Ascend/nnrt/7.0.0/opp/] for environment variable [ASCEND_OPP_PATH] is invalid when load buildin op store.Solution: Reset t
部分代码如下 for data in train_loader:imgs, targets = data# print("标签为", targets.shape)imgs.byte()output = unet_l2(imgs)loss = criterion(output, targets)optimizer.zero_grad()loss.backward()optimizer.step()