一些问题归档
comments: true
git
git clone 卡住
解决方法:
1. 别忘了网址最后的.git
2. 先Ctrl+C,尝试再跑一次
3. git config --global http.sslVerify "false"
git推送大型文件
解决方法:缓冲区大小默认是1MB, git config --global http.postBuffer 524288000
修改为500MB
RPC failed; curl 16 Error in the HTTP2 framing layer
各种包的安装
import sru 卡住,实际上是出现无限循环
参考https://github.com/asappresearch/sru/issues/196
解决方法:删除~/.cache/torch_extensions文件夹 然后重新import,会出现以下warning,但不影响使用
UserWarning: Just-in-time loading and compiling the CUDA kernels of SRU was unsuccessful. Got the following error:
cannot open shared object file: No such file or directory
warnings.warn("Just-in-time loading and compiling the CUDA kernels of SRU was unsuccessful. "
pip install torch-cluster包 build很慢
解决方法:因为只是慢,所以耐心等待一般都能跑出来的,不用着急 似乎这里有更快的方法 参考
biopython版本问题 部分函数找不到 importError: cannot import name 'three_to_one' from 'Bio.PDB.Polypeptide'
解决方法: 搜索biopython.org three_to_one, 发现这个函数在biopython 1.75里面有,而本地安装的版本没有. pip修改版本
ESM和ESMFold
ESM和ESMFold都已经封装成了包,直接pip install,不需要clone代码
ESM(只需要语言模型当encoder的情况):
ESMFold要容易踩坑一些:
pip install "fair-esm[esmfold]"
# OpenFold and its remaining dependency
pip install 'dllogger @ git+https://github.com/NVIDIA/dllogger.git'
pip install 'openfold @ git+https://github.com/aqlaboratory/openfold.git@4b41059694619831a7db195b7e0988fc4ff3a307'
但是这样pip源匹配的cudatoolkit版本容易出问题。建议用官方给的conda
conda env create -f environment.yml
pip install "fair-esm[esmfold]"
pip install 'openfold @ git+https://github.com/aqlaboratory/openfold.
import torch出现 undefined symbol: iJIT_NotifyEvent
pip install mkl==2024.0.0 不能2024.1及之后的版本,参考
nvcc fatal : Unsupported gpu architecture 'compute_89'
系统CUDA版本,需要>=11.8
RuntimeError: CUDA error: CUBLAS_STATUS_INVALID_VALUE when calling
cublasGemmEx( handle, opa, opb, m, n, k, &falpha, a, CUDA_R_16F, lda, b, CUDA_R_16F, ldb, &fbeta, c, CUDA_R_16F, ldc, CUDA_R_32F, CUBLAS_GEMM_DFALT_TENSOR_OP)
动态链接库问题解决方案, unset LD_LIBRARY_PATH
即可
def einsum(tensor: Tensor, pattern: str, /) -> Tensor:SyntaxError: invalid syntax
参考issue, 应该安装einops=0.6.1
Linux
一般是模型文件下载不完整 重新下载
matplotlib 教程