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View Code? Open in Web Editor NEWgRNAde: Geometric Deep Learning for RNA Design
Home Page: https://arxiv.org/abs/2305.14749
License: MIT License
gRNAde: Geometric Deep Learning for RNA Design
Home Page: https://arxiv.org/abs/2305.14749
License: MIT License
Hello,
Thanks for your paper and open source codes. Currently I am working on the implementation of your codes. I found one problem which is missing from tools.ribonanzanet.network import RibonanzaNet in notebooks/design.ipynb. How can I solve this issue?
Thanks in advance!
Best,
作者你好,
请问我在复现实验的时候,出现了eval 和 test的时间很长的现象,这是正常情况吗?
因为数据集和原始数据集有了一些更新,导致出现了很多新的数据(这些数据中有部分的 sec_struc中 左括号数量多于右括号,导致计算对应的adj的时候报错),于是我对原始的代码做了如下修改,将计算过程放到了try里面,如果是错误的就跳出:
def dotbracket_to_adjacency(sec_struct: str) -> np.ndarray: """ Convert secondary structure in dot-bracket notation to adjacency matrix. """ n = len(sec_struct) adj = np.zeros((n, n), dtype=np.int8) stack = [] empty_count = 0 for i, db_char in enumerate(sec_struct): if db_char == '(': stack.append(i) elif db_char == ')': try: j = stack.pop() adj[i, j] = 1 adj[j, i] = 1 except IndexError: break return adj
其他地方都没有改变
大概eval 和 test 每个都要接近8小时,查看占用,发现gpu长时间不用,一直是cpu在跑一个叫做contrafold的进程,希望大佬解惑。
Hi,
Congrats on the great work. As I understand data/seqid_split.pt
data/das_split.pt
and data/structsim_split.pt
contains the train, test, validation idx
for different splits. And the corresponding pdbid_<chain>
for those can be extracted from processed_df.csv
. Can you provide this preprocessed processed_df.csv
file or directly the PDB ids for easier access?
Thanks!
Hi @chaitjo,
Thanks for your great work first!
Could you provide a pretrained checkpoint to run inference directly?
Best regards,
Han
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