Flash v2 #137
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Flash v2 #137
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* readme * add contributing and dco
* rename scripts * fix bug * refine scripts * fix renaming bug * keep 10 ckps * dump outputs * readme * hierachy * title * introduction * rm converter readme * intro * log interval * README * intro
…rp#7) * add the convert script and alphafold original configs * add the convert script for alphafold and modify the README * add the convert script for alphafold * merge from main
* add script for benchmarking * code clean * add benchmark in memory cost * remove use_lma * add option for LMA
* add evaluation results * par * compress img * figure layout * white bg * png -> jpg * Revert "figure layout" * revert to green
* Update README.md * Update README.md
* optional msa col attn mask * chunk attention * fix chunk_size * code clean Co-authored-by: Guolin Ke <guolin.ke@outlook.com>
* add the colab version of Uni-Fold * add the description of Uni-Fold Colab at README
* refine notebook * rephrase * rephrase * rephrase * rephrase * rm output * rephrase * rephrase Co-authored-by: Guolin Ke <guolin.ke@outlook.com>
change default model name to avoid confusion
* fix uf-symmetry wget url * fix url
* do not download af2 params * do not download af params
* refactor the notebook * change branch * add init * fix auto chunk size * optim plot & fix pae * fix ssave file bug * merge cell * finalize
* fix wrong version * change from google drive to github release
* Update unifold.ipynb * Update unifold.ipynb * Update unifold.ipynb
* update get assembly from mmcif * add comment
* add dataset download via Volcengine * rephrase --------- Co-authored-by: Ziyao Li <36321246+ZiyaoLi@users.noreply.github.com>
* add symmetry utils to process input structures * fix import
…-corp#119) * tolerate inconsistencies between pdb_assembly and multi_label * Update dataset.py
hypnopump
commented
Oct 21, 2023
| @@ -2,15 +2,16 @@ | |||
| [ -z "${n_gpu}" ] && n_gpu=$(nvidia-smi -L | wc -l) | |||
| export NCCL_ASYNC_ERROR_HANDLING=1 | |||
| export OMP_NUM_THREADS=1 | |||
| mkdir -p $1 | |||
| mkdir -p temp | |||
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once this proposal is validated, modifications to this file can be dropped; was just for easy testing of the code
guolinke
reviewed
Oct 23, 2023
unifold/modules/attentions.py
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| k = k.view(*k.shape[:-1], self.num_heads, self.head_dim).transpose(-2, -3).contiguous() | ||
| v = v.view(*v.shape[:-1], self.num_heads, self.head_dim).transpose(-2, -3) | ||
| # (b, n, h, i, dim_head), (b, n, h, j, dim_head) -> (b, n, h, i, dim_head) | ||
| o = torch.nn.functional.scaled_dot_product_attention(q, k, v, attn_mask=mask) |
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How about its speed/memory compared with the one with softmax_dropout?
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Uses flash attention v2. Works for any sequence length.
WARNING! Pls install the custom fork from trident provided below as a zip file. You might need to install
triton-nightlyafterwards (maybe alsonvtx) to get it working (see triton repo for instructions). Check withipython; import trident as tdtrident.zip