Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment Assignees Xia-Weiwen Labels matrix multiplication module: correctness (silent) module: cpu needs reproduction triaged Projects None yet Milestone No milestone Development No branches or pull ...
查找替代方案:如果 torch_int_div 函数确实不存在,你可能需要查找其他函数或方法来实现相同的功能。 如果你仍然无法解决问题,可以考虑在 transformers 库的GitHub 仓库中搜索相关的问题或提交一个新的 issue,寻求社区的帮助。
TypeError: 'int' object is not callable。但是检查代码发现并没有与TensorDataset重名的函数。 经过研究TensorDataset函数的源码发现,这个函数传入的参数必须是tensor类型的,所以把x_train与y_train转换为tensor类型在执行这个函数就不报错了,更改后的代码为: train_dataset = Data.TensorDataset(pt.tensor(x_train),pt...
问升级到PyTorch 1.9 ImportError时可能出现错误:无法从'torch._six‘导入名称'int_classes’ENyum 出现...
在https://github.com/pytorch/pytorch/issues/13962页面下有我的同名回答(mtxing69) /pytorch/torch/lib/THD/base/data_channels/DataChannelNccl.cpp:31:17: error: ‘ncclInt8’ was not declared in this scope 和 Failed to run 'bash ../tools/build_pytorch_libs.sh --use-cuda --use-nnpack --us...
Traceback (most recent call last): File "examples/export_int8_model.py", line 10, in from smoothquant.opt import Int8OPTForCausalLM File "", line 259, in load_module File "/root/anaconda3/envs/smoothquant/lib/python3.8/site-packages/smoo...
In [1]: import torch In [2]: torch.randint(2, (2**31-2,), device="cuda", dtype=torch.int8).sum() # BAD Out[2]: tensor(0, device='cuda:0') In [3]: torch.randint(2, (2**30-2,), device="cuda", dtype=torch.int8).sum() # smaller input works Out[3]: tensor(...
assign The following actions use a deprecated Node.js version and will be forced to run on node20: actions/github-script@v6. For more info: https://github.blog/changelog/2024-03-07-github-actions-all-actions-will-run-on-node20-instead-of-node16-by-default/ Show more ...
System Info Copy-and-paste the text below in your GitHub issue and FILL OUT the two last points. transformers version: 4.49.0.dev0 Platform: Linux-4.18.0-425.3.1.el8.x86_64-x86_64-with-glibc2.39 Python version: 3.12.3 Huggingface_hub ver...
strint 主页:strint.github.io torch的1.11开始尝试支持cuda graph,一个利用cuda graph特性的静态图方案,减少cpu的调度开销。链接对静态图执行有需求的的小伙伴,在易用性、高效性、完善程度上,在oneflow发布的0.5都已经可以轻易获取到了 [教程](链接) [API](链接)链接...