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Reproduction of ESM-IF1
Deep Learning
AI4S
Deep LearningAI4S
ABOWLofFish
发布于 2023-09-20
推荐镜像 :ABACUS:3.3.2-user-guide
推荐机型 :c32_m128_4 * NVIDIA V100
赞
1
Protein Inverse Folding (ESM-IF1 Reproduction)
Set up
环境配置
加载数据集
加载模型
Test Recovery
Test Perplexity

Protein Inverse Folding (ESM-IF1 Reproduction)

代码
文本

蛋白质逆折叠(Inverse Folding)，是指通过给定蛋白质的折叠结构，预测其对应的氨基酸序列。与蛋白质折叠任务相反，蛋白质逆折叠任务是根据已知的蛋白质结构来推断其组成的氨基酸序列。这个任务对于理解蛋白质的结构与功能之间的关系以及设计新的蛋白质具有重要意义。

代码
文本

ESM-IF1（Evolutionary Scale Modeling for Inverse Folding 1）是一种基于蛋白质序列和进化信息的深度学习模型，用于解决蛋白质逆折叠任务。ESM-IF1模型是基于ESM（Evolutionary Scale Modeling）模型的改进版本，ESM模型是一种使用自监督学习和预测任务预训练的蛋白质深度学习模型。

ESM-IF1模型利用了大规模的蛋白质序列和结构数据来学习蛋白质序列与结构之间的关系。它使用了自监督学习的方法，通过预测蛋白质序列中的缺失部分来训练模型。通过这种方式，ESM-IF1模型能够学习到蛋白质序列中的重要特征和模式，并将其应用于蛋白质逆折叠任务中。 Learning inverse folding from millions of predicted structures. (Hsu et al. 2022).

代码
文本

Set up

代码
文本

环境配置

代码
文本

通过git clone命令下载代码仓库
仓库中有运行esm系列模型所需的conda环境,通过命令conda env create -f environment.yml.一键完成配置

代码
文本
[4]
!nvidia-smi 
Wed Sep 20 11:11:25 2023       
+-----------------------------------------------------------------------------+
| NVIDIA-SMI 525.125.06   Driver Version: 525.125.06   CUDA Version: 12.0     |
|-------------------------------+----------------------+----------------------+
| GPU  Name        Persistence-M| Bus-Id        Disp.A | Volatile Uncorr. ECC |
| Fan  Temp  Perf  Pwr:Usage/Cap|         Memory-Usage | GPU-Util  Compute M. |
|                               |                      |               MIG M. |
|===============================+======================+======================|
|   0  NVIDIA GeForce ...  Off  | 00000000:05:00.0 Off |                  N/A |
| 23%   28C    P8    16W / 250W |   1394MiB / 11264MiB |      0%      Default |
|                               |                      |                  N/A |
+-------------------------------+----------------------+----------------------+
|   1  NVIDIA GeForce ...  Off  | 00000000:06:00.0 Off |                  N/A |
| 23%   20C    P8     8W / 250W |   1098MiB / 11264MiB |      0%      Default |
|                               |                      |                  N/A |
+-------------------------------+----------------------+----------------------+
|   2  NVIDIA GeForce ...  Off  | 00000000:09:00.0 Off |                  N/A |
| 23%   20C    P8     9W / 250W |      2MiB / 11264MiB |      0%      Default |
|                               |                      |                  N/A |
+-------------------------------+----------------------+----------------------+
|   3  NVIDIA TITAN X ...  Off  | 00000000:0A:00.0 Off |                  N/A |
| 23%   19C    P8     8W / 250W |      2MiB / 12288MiB |      0%      Default |
|                               |                      |                  N/A |
+-------------------------------+----------------------+----------------------+
                                                                               
+-----------------------------------------------------------------------------+
| Processes:                                                                  |
|  GPU   GI   CI        PID   Type   Process name                  GPU Memory |
|        ID   ID                                                   Usage      |
|=============================================================================|
|    0   N/A  N/A   4081117      C   python                           1392MiB |
|    1   N/A  N/A   4079471      C   python                           1096MiB |
+-----------------------------------------------------------------------------+
代码
文本
[15]
#!git clone https://github.com/facebookresearch/esm.git #若出现下载失败的问题，可使用代理，命令如下
!git clone https://ghproxy.com/https://github.com/facebookresearch/esm.git
Cloning into 'esm'...
remote: Enumerating objects: 1511, done.
remote: Counting objects: 100% (151/151), done.
remote: Compressing objects: 100% (113/113), done.
remote: Total 1511 (delta 42), reused 126 (delta 36), pack-reused 1360
Receiving objects: 100% (1511/1511), 11.78 MiB | 8.53 MiB/s, done.
Resolving deltas: 100% (891/891), done.
/home/zhuangwanru/models/testesm/esm

EnvironmentFileNotFound: '/home/zhuangwanru/models/testesm/esm/environment.yml.' file not found
代码
文本
[2]
%cd esm
!conda update -n base -c conda-forge conda
!conda env create -f environment.yml #若出现`EnvironmentFileNotFound`，可尝试重启kernel
/home/zhuangwanru/models/testesm/esm/esm
Collecting package metadata (current_repodata.json): - WARNING conda.models.version:get_matcher(538): Using .* with relational operator is superfluous and deprecated and will be removed in a future version of conda. Your spec was 1.7.1.*, but conda is ignoring the .* and treating it as 1.7.1
done
Solving environment: - 
Warning: >10 possible package resolutions (only showing differing packages):
  - https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main/linux-64::ninja-1.10.2-h06a4308_5, https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main/linux-64::ninja-base-1.10.2-hd09550d_5, https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main/linux-64::pytorch-1.12.1-cpu_py39he8d8e81_0, https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main/noarch::conda-repo-cli-1.0.4-pyhd3eb1b0_0
  - https://mirrors.bfsu.edu.cn/anaconda/pkgs/main/noarch::conda-repo-cli-1.0.4-pyhd3eb1b0_0, https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main/linux-64::ninja-1.10.2-h06a4308_5, https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main/linux-64::ninja-base-1.10.2-hd09550d_5, https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main/linux-64::pytorch-1.12.1-cpu_py39he8d8e81_0
  - https://mirrors.bfsu.edu.cn/anaconda/pkgs/main/linux-64::ninja-base-1.10.2-hd09550d_5, https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main/linux-64::ninja-1.10.2-h06a4308_5, https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main/linux-64::pytorch-1.12.1-cpu_py39he8d8e81_0, https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main/noarch::conda-repo-cli-1.0.4-pyhd3eb1b0_0
  - https://mirrors.bfsu.edu.cn/anaconda/pkgs/main/linux-64::ninja-base-1.10.2-hd09550d_5, https://mirrors.bfsu.edu.cn/anaconda/pkgs/main/noarch::conda-repo-cli-1.0.4-pyhd3eb1b0_0, https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main/linux-64::ninja-1.10.2-h06a4308_5, https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main/linux-64::pytorch-1.12.1-cpu_py39he8d8e81_0
  - https://mirrors.bfsu.edu.cn/anaconda/pkgs/main/linux-64::ninja-1.10.2-h06a4308_5, https://mirrors.bfsu.edu.cn/anaconda/pkgs/main/linux-64::ninja-base-1.10.2-hd09550d_5, https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main/linux-64::pytorch-1.12.1-cpu_py39he8d8e81_0, https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main/noarch::conda-repo-cli-1.0.4-pyhd3eb1b0_0
  - https://mirrors.bfsu.edu.cn/anaconda/pkgs/main/linux-64::ninja-1.10.2-h06a4308_5, https://mirrors.bfsu.edu.cn/anaconda/pkgs/main/linux-64::ninja-base-1.10.2-hd09550d_5, https://mirrors.bfsu.edu.cn/anaconda/pkgs/main/noarch::conda-repo-cli-1.0.4-pyhd3eb1b0_0, https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main/linux-64::pytorch-1.12.1-cpu_py39he8d8e81_0
  - https://mirrors.bfsu.edu.cn/anaconda/pkgs/main/linux-64::ninja-1.10.2-h06a4308_5, https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main/linux-64::ninja-base-1.10.2-hd09550d_5, https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main/linux-64::pytorch-1.12.1-cpu_py39he8d8e81_0, https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main/noarch::conda-repo-cli-1.0.4-pyhd3eb1b0_0
  - https://mirrors.bfsu.edu.cn/anaconda/pkgs/main/linux-64::ninja-1.10.2-h06a4308_5, https://mirrors.bfsu.edu.cn/anaconda/pkgs/main/noarch::conda-repo-cli-1.0.4-pyhd3eb1b0_0, https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main/linux-64::ninja-base-1.10.2-hd09550d_5, https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main/linux-64::pytorch-1.12.1-cpu_py39he8d8e81_0
  - https://mirrors.bfsu.edu.cn/anaconda/pkgs/main/linux-64::ninja-1.10.2-h06a4308_5, https://mirrors.bfsu.edu.cn/anaconda/pkgs/main/linux-64::pytorch-1.12.1-cpu_py39he8d8e81_0, https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main/linux-64::ninja-base-1.10.2-hd09550d_5, https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main/noarch::conda-repo-cli-1.0.4-pyhd3eb1b0_0
  - https://mirrors.bfsu.edu.cn/anaconda/pkgs/main/linux-64::pytorch-1.12.1-cpu_py39he8d8e81_0, https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main/linux-64::ninja-1.10.2-h06a4308_5, https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main/linux-64::ninja-base-1.10.2-hd09550d_5, https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main/noarch::conda-repo-cli-1.0.4-pyhd3eb1b0_0
  ... and othedone


==> WARNING: A newer version of conda exists. <==
  current version: 4.14.0
  latest version: 23.7.4

Please update conda by running

    $ conda update -n base -c conda-forge conda



## Package Plan ##

  environment location: /home/zhuangwanru/anaconda3

  added / updated specs:
    - conda


The following packages will be downloaded:

    package                    |            build
    ---------------------------|-----------------
    _libgcc_mutex-0.1          |             main           2 KB  conda-forge
    alabaster-0.7.12           |     pyhd3eb1b0_0          16 KB  https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
    appdirs-1.4.4              |     pyhd3eb1b0_0          12 KB  https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
    argh-0.26.2                |   py39h06a4308_0          36 KB  https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
    argon2-cffi-20.1.0         |   py39h27cfd23_1          46 KB  https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
    asn1crypto-1.4.0           |             py_0          80 KB  https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
    async_generator-1.10       |     pyhd3eb1b0_0          23 KB  https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
    atomicwrites-1.4.0         |             py_0          11 KB  https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
    babel-2.9.1                |     pyhd3eb1b0_0         5.5 MB  https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
    backports.shutil_get_terminal_size-1.0.0|     pyhd3eb1b0_3          10 KB  https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
    backports.tempfile-1.0     |             py_0          10 KB  conda-forge
    backports.weakref-1.0.post1|  pyhd8ed1ab_1003          11 KB  conda-forge
    beautifulsoup4-4.10.0      |     pyh06a4308_0          85 KB  https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
    binaryornot-0.4.4          |     pyhd3eb1b0_1         351 KB  https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
    bkcharts-0.2               |   py39h06a4308_0         132 KB  https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
    black-19.10b0              |             py_0          86 KB  https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
    boto-2.49.0                |   py39h06a4308_0         1.6 MB  https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
    brotli-1.0.9               |       he6710b0_2         375 KB  https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
    brunsli-0.1                |       h2531618_0         164 KB  https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
    cached-property-1.5.2      |             py_0          11 KB  https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
    cairo-1.16.0               |       hf32fb01_1         1.0 MB  https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
    cfitsio-3.470              |       hf0d0db6_6         814 KB  https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
    chardet-4.0.0              |py39h06a4308_1003         194 KB  https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
    charls-2.2.0               |       h2531618_0         117 KB  https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
    click-8.0.3                |     pyhd3eb1b0_0          79 KB  https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
    cloudpickle-2.0.0          |     pyhd3eb1b0_0          32 KB  https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
    clyent-1.2.2               |   py39h06a4308_1          21 KB  https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
    colorama-0.4.4             |     pyhd3eb1b0_0          21 KB  https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
    conda-content-trust-0.1.1  |     pyhd3eb1b0_0          56 KB  https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
    conda-pack-0.7.1           |     pyhd8ed1ab_0          32 KB  conda-forge
    conda-repo-cli-1.0.4       |     pyhd3eb1b0_0          47 KB  https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
    contextlib2-0.6.0.post1    |     pyhd3eb1b0_0          13 KB  https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
    cycler-0.10.0              |   py39h06a4308_0          16 KB  https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
    dbus-1.13.18               |       hb2f20db_0         504 KB  https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
    defusedxml-0.7.1           |     pyhd3eb1b0_0          23 KB  https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
    diff-match-patch-20200713  |     pyhd3eb1b0_0          35 KB  https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
    et_xmlfile-1.1.0           |   py39h06a4308_0          10 KB  https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
    fastcache-1.1.0            |   py39he8ac12f_0          31 KB  https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
    fonttools-4.25.0           |     pyhd3eb1b0_0         632 KB  https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
    freetype-2.10.4            |       h5ab3b9f_0         596 KB  https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
    fribidi-1.0.10             |       h7b6447c_0         103 KB  https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
    future-0.18.3              |     pyhd8ed1ab_0         357 KB  conda-forge
    get_terminal_size-1.0.0    |       haa9412d_0           3 KB  https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
    giflib-5.2.1               |       h7b6447c_0          78 KB  https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
    glib-2.69.1                |       h5202010_0         1.7 MB  https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
    glob2-0.7                  |     pyhd3eb1b0_0          12 KB  https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
    gmp-6.2.1                  |       h2531618_2         539 KB  https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
    graphite2-1.3.14           |       h23475e2_0          99 KB  https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
    hdf5-1.10.6                |       hb1b8bf9_0         3.7 MB  https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
    heapdict-1.0.1             |     pyhd3eb1b0_0           8 KB  https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
    html5lib-1.1               |     pyhd3eb1b0_0          91 KB  https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
    huggingface_hub-0.17.2     |     pyhd8ed1ab_0         190 KB  conda-forge
    icu-58.2                   |       he6710b0_3        10.5 MB  https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
    imagecodecs-2021.8.26      |   py39h4cda21f_0         6.1 MB  https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
    imageio-2.9.0              |     pyhd3eb1b0_0         3.0 MB  https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
    inflection-0.5.1           |   py39h06a4308_0          12 KB  https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
    iniconfig-1.1.1            |     pyhd3eb1b0_0           8 KB  https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
    intervaltree-3.1.0         |     pyhd3eb1b0_0          25 KB  https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
    ipython_genutils-0.2.0     |     pyhd3eb1b0_1          27 KB  https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
    ipywidgets-7.6.5           |     pyhd3eb1b0_1         105 KB  https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
    isort-5.9.3                |     pyhd3eb1b0_0          83 KB  https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
    itsdangerous-2.0.1         |     pyhd3eb1b0_0          18 KB  https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
    jbig-2.1                   |       hdba287a_0          40 KB  https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
    jdcal-1.4.1                |     pyhd3eb1b0_0          10 KB  https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
    jeepney-0.7.1              |     pyhd3eb1b0_0          38 KB  https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
    jinja2-time-0.2.0          |     pyhd3eb1b0_2          17 KB  https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
    joblib-1.1.0               |     pyhd3eb1b0_0         211 KB  https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
    json5-0.9.6                |     pyhd3eb1b0_0          21 KB  https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
    jsonschema-3.2.0           |     pyhd3eb1b0_2          47 KB  https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
    jupyter-1.0.0              |   py39h06a4308_7           8 KB  https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
    jupyter_client-6.1.12      |     pyhd3eb1b0_0          88 KB  https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
    jupyterlab_pygments-0.1.2  |             py_0           8 KB  https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
    jupyterlab_widgets-1.0.0   |     pyhd3eb1b0_1         109 KB  https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
    jxrlib-1.1                 |       h7b6447c_2         223 KB  https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
    lazy-object-proxy-1.6.0    |   py39h27cfd23_0          31 KB  https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
    libaec-1.0.4               |       he6710b0_1          32 KB  https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
    libarchive-3.4.2           |       h62408e4_0         796 KB  https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
    libev-4.33                 |       h7f8727e_1         111 KB  https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
    libgfortran-ng-7.5.0       |      ha8ba4b0_17          22 KB  https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
    libgfortran4-7.5.0         |      ha8ba4b0_17         995 KB  https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
    libllvm11-11.1.0           |       h3826bc1_0        23.6 MB  https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
    libspatialindex-1.9.3      |       h2531618_0         2.1 MB  https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
    libtool-2.4.6              |    h7b6447c_1005         394 KB  https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
    libzopfli-1.0.3            |       he6710b0_0         171 KB  https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
    lzo-2.10                   |       h7b6447c_2         184 KB  https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
    matplotlib-inline-0.1.2    |     pyhd3eb1b0_2          12 KB  https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
    mccabe-0.6.1               |   py39h06a4308_1          16 KB  https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
    mistune-0.8.4              |py39h27cfd23_1000          57 KB  https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
    mock-4.0.3                 |     pyhd3eb1b0_0          29 KB  https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
    mpi-1.0                    |            mpich           4 KB  conda-forge
    mpich-3.3.2                |       hc856adb_0         3.8 MB  https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
    multipledispatch-0.6.0     |   py39h06a4308_0          24 KB  https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
    munkres-1.1.4              |             py_0          13 KB  https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
    mypy_extensions-0.4.3      |   py39h06a4308_0           9 KB  https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
    nbformat-5.1.3             |     pyhd3eb1b0_0          44 KB  https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
    nest-asyncio-1.5.1         |     pyhd3eb1b0_0          10 KB  https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
    ninja-1.10.2               |       h06a4308_5           8 KB  https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
    ninja-base-1.10.2          |       hd09550d_5         109 KB  https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
    nose-1.3.7                 |  pyhd3eb1b0_1006         128 KB  https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
    olefile-0.46               |     pyhd3eb1b0_0          34 KB  https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
    openjpeg-2.4.0             |       h3ad879b_0         331 KB  https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
    openpyxl-3.0.9             |     pyhd3eb1b0_0         164 KB  https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
    pandocfilters-1.4.3        |   py39h06a4308_1          14 KB  https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
    partd-1.2.0                |     pyhd3eb1b0_0          19 KB  https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
    path-16.0.0                |   py39h06a4308_0          37 KB  https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
    path.py-12.5.0             |       hd3eb1b0_0           4 KB  https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
    pathlib2-2.3.6             |   py39h06a4308_2          36 KB  https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
    pathspec-0.7.0             |             py_0          26 KB  https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
    pcre-8.45                  |       h295c915_0         207 KB  https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
    pep8-1.7.1                 |   py39h06a4308_0          54 KB  https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
    pixman-0.40.0              |       h7f8727e_1         373 KB  https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
    ply-3.11                   |   py39h06a4308_0          81 KB  https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
    poyo-0.5.0                 |     pyhd3eb1b0_0          17 KB  https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
    prompt-toolkit-3.0.20      |     pyhd3eb1b0_0         259 KB  https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
    pycodestyle-2.7.0          |     pyhd3eb1b0_0          41 KB  https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
    pydocstyle-6.1.1           |     pyhd3eb1b0_0          36 KB  https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
    pyerfa-2.0.0               |   py39h27cfd23_0         343 KB  https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
    pyflakes-2.3.1             |     pyhd3eb1b0_0          60 KB  https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
    pyjwt-2.8.0                |     pyhd8ed1ab_0          24 KB  conda-forge
    pyls-spyder-0.4.0          |     pyhd3eb1b0_0          11 KB  https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
    pyparsing-3.0.4            |     pyhd3eb1b0_0          81 KB  https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
    pyrsistent-0.18.0          |   py39heee7806_0          94 KB  https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
    python-libarchive-c-2.9    |     pyhd3eb1b0_1          47 KB  https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
    python-lsp-black-1.0.0     |     pyhd3eb1b0_0           8 KB  https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
    python-lsp-jsonrpc-1.0.0   |     pyhd3eb1b0_0          10 KB  https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
    python-slugify-5.0.2       |     pyhd3eb1b0_0          13 KB  https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
    pytorch-1.12.1             |cpu_py39he8d8e81_0        60.8 MB  https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
    pytz-2021.3                |     pyhd3eb1b0_0         171 KB  https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
    pyxdg-0.27                 |     pyhd3eb1b0_0          45 KB  https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
    pyyaml-6.0                 |   py39h7f8727e_1         173 KB  https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
    qdarkstyle-3.0.2           |     pyhd3eb1b0_0         337 KB  https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
    qstylizer-0.1.10           |     pyhd3eb1b0_0          17 KB  https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
    qt-5.9.7                   |       h5867ecd_1        68.5 MB  https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
    seaborn-0.11.2             |     pyhd3eb1b0_0         218 KB  https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
    secretstorage-3.3.1        |   py39h06a4308_0          24 KB  https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
    send2trash-1.8.0           |     pyhd3eb1b0_1          19 KB  https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
    simplegeneric-0.8.1        |   py39h06a4308_2          11 KB  https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
    singledispatch-3.7.0       |  pyhd3eb1b0_1001          12 KB  https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
    six-1.16.0                 |     pyhd3eb1b0_0          18 KB  https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
    sniffio-1.2.0              |   py39h06a4308_1          15 KB  https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
    sortedcollections-2.1.0    |     pyhd3eb1b0_0          12 KB  https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
    sortedcontainers-2.4.0     |     pyhd3eb1b0_0          26 KB  https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
    sphinxcontrib-1.0          |   py39h06a4308_1         218 KB  https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
    sphinxcontrib-applehelp-1.0.2|     pyhd3eb1b0_0          29 KB  https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
    sphinxcontrib-devhelp-1.0.2|     pyhd3eb1b0_0          23 KB  https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
    sphinxcontrib-htmlhelp-2.0.0|     pyhd3eb1b0_0          32 KB  https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
    sphinxcontrib-jsmath-1.0.1 |     pyhd3eb1b0_0           8 KB  https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
    sphinxcontrib-qthelp-1.0.3 |     pyhd3eb1b0_0          26 KB  https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
    sphinxcontrib-serializinghtml-1.1.5|     pyhd3eb1b0_0          25 KB  https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
    sphinxcontrib-websupport-1.2.4|             py_0          34 KB  https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
    tblib-1.7.0                |     pyhd3eb1b0_0          15 KB  https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
    testpath-0.5.0             |     pyhd3eb1b0_0          81 KB  https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
    text-unidecode-1.3         |     pyhd3eb1b0_0          65 KB  https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
    textdistance-4.2.1         |     pyhd3eb1b0_0          29 KB  https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
    threadpoolctl-2.2.0        |     pyh0d69192_0          16 KB  https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
    three-merge-0.1.1          |     pyhd3eb1b0_0          10 KB  https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
    tifffile-2021.7.2          |     pyhd3eb1b0_2         135 KB  https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
    tinycss-0.4                |  pyhd3eb1b0_1002          39 KB  https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
    toml-0.10.2                |     pyhd3eb1b0_0          20 KB  https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
    typed-ast-1.4.3            |   py39h7f8727e_1         187 KB  https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
    typing-extensions-3.10.0.2 |       hd3eb1b0_0          12 KB  https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
    unicodecsv-0.14.1          |   py39h06a4308_0          27 KB  https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
    unidecode-1.2.0            |     pyhd3eb1b0_0         155 KB  https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
    webencodings-0.5.1         |   py39h06a4308_1          20 KB  https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
    whichcraft-0.6.1           |     pyhd3eb1b0_0          11 KB  https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
    xlrd-2.0.1                 |     pyhd3eb1b0_0          90 KB  https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
    xlwt-1.3.0                 |   py39h06a4308_0         160 KB  https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
    xmltodict-0.13.0           |     pyhd8ed1ab_0          13 KB  conda-forge
    yapf-0.31.0                |     pyhd3eb1b0_0         126 KB  https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
    zfp-0.5.5                  |       h2531618_6         173 KB  https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
    zict-2.0.0                 |     pyhd3eb1b0_0          10 KB  https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
    zope-1.0                   |   py39h06a4308_1         218 KB  https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
    zope.event-4.5.0           |   py39h06a4308_0         223 KB  https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
    zope.interface-5.4.0       |   py39h7f8727e_0         305 KB  https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
    zstd-1.4.9                 |       haebb681_0         480 KB  https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
    ------------------------------------------------------------
                                           Total:       208.6 MB

The following packages will be UPDATED:

  backports.functoo~ pkgs/main::backports.functools_lru_ca~ --> conda-forge::backports.functools_lru_cache-1.6.5-pyhd8ed1ab_0
  backports.weakref  pkgs/main::backports.weakref-1.0.post~ --> conda-forge::backports.weakref-1.0.post1-pyhd8ed1ab_1003
  conda-pack         pkgs/main::conda-pack-0.6.0-pyhd3eb1b~ --> conda-forge::conda-pack-0.7.1-pyhd8ed1ab_0
  future             pkgs/main/linux-64::future-0.18.2-py3~ --> conda-forge/noarch::future-0.18.3-pyhd8ed1ab_0
  huggingface_hub    huggingface::huggingface_hub-0.13.4-p~ --> conda-forge::huggingface_hub-0.17.2-pyhd8ed1ab_0
  pyjwt              pkgs/main/linux-64::pyjwt-2.1.0-py39h~ --> conda-forge/noarch::pyjwt-2.8.0-pyhd8ed1ab_0
  xmltodict          pkgs/main::xmltodict-0.12.0-pyhd3eb1b~ --> conda-forge::xmltodict-0.13.0-pyhd8ed1ab_0

The following packages will be SUPERSEDED by a higher-priority channel:

  _libgcc_mutex                                   pkgs/main --> conda-forge
  alabaster                                       pkgs/main --> anaconda/pkgs/main
  appdirs                                         pkgs/main --> anaconda/pkgs/main
  argh                                            pkgs/main --> anaconda/pkgs/main
  argon2-cffi                                     pkgs/main --> anaconda/pkgs/main
  asn1crypto                                      pkgs/main --> anaconda/pkgs/main
  async_generator                                 pkgs/main --> anaconda/pkgs/main
  atomicwrites                                    pkgs/main --> anaconda/pkgs/main
  babel                                           pkgs/main --> anaconda/pkgs/main
  backcall                                        pkgs/main --> anaconda/pkgs/main
  backports.shutil_~                              pkgs/main --> anaconda/pkgs/main
  backports.tempfile pkgs/main::backports.tempfile-1.0-pyh~ --> conda-forge::backports.tempfile-1.0-py_0
  beautifulsoup4                                  pkgs/main --> anaconda/pkgs/main
  binaryornot                                     pkgs/main --> anaconda/pkgs/main
  bkcharts                                        pkgs/main --> anaconda/pkgs/main
  black                                           pkgs/main --> anaconda/pkgs/main
  blas                                            pkgs/main --> anaconda/pkgs/main
  boto                                            pkgs/main --> anaconda/pkgs/main
  brotli                                          pkgs/main --> anaconda/pkgs/main
  brotlipy                                        pkgs/main --> anaconda/pkgs/main
  brunsli                                         pkgs/main --> anaconda/pkgs/main
  bzip2                                           pkgs/main --> anaconda/pkgs/main
  cached-property                                 pkgs/main --> anaconda/pkgs/main
  cairo                                           pkgs/main --> anaconda/pkgs/main
  cfitsio                                         pkgs/main --> anaconda/pkgs/main
  chardet                                         pkgs/main --> anaconda/pkgs/main
  charls                                          pkgs/main --> anaconda/pkgs/main
  charset-normalizer                              pkgs/main --> anaconda/pkgs/main
  click                                           pkgs/main --> anaconda/pkgs/main
  cloudpickle                                     pkgs/main --> anaconda/pkgs/main
  clyent                                          pkgs/main --> anaconda/pkgs/main
  colorama                                        pkgs/main --> anaconda/pkgs/main
  conda-content-tru~                              pkgs/main --> anaconda/pkgs/main
  conda-repo-cli                                  pkgs/main --> anaconda/pkgs/main
  contextlib2                                     pkgs/main --> anaconda/pkgs/main
  cycler                                          pkgs/main --> anaconda/pkgs/main
  dataclasses                                     pkgs/main --> anaconda/pkgs/main
  dbus                                            pkgs/main --> anaconda/pkgs/main
  defusedxml                                      pkgs/main --> anaconda/pkgs/main
  diff-match-patch                                pkgs/main --> anaconda/pkgs/main
  et_xmlfile                                      pkgs/main --> anaconda/pkgs/main
  fastcache                                       pkgs/main --> anaconda/pkgs/main
  fonttools                                       pkgs/main --> anaconda/pkgs/main
  freetype                                        pkgs/main --> anaconda/pkgs/main
  fribidi                                         pkgs/main --> anaconda/pkgs/main
  get_terminal_size                               pkgs/main --> anaconda/pkgs/main
  giflib                                          pkgs/main --> anaconda/pkgs/main
  glib                                            pkgs/main --> anaconda/pkgs/main
  glob2                                           pkgs/main --> anaconda/pkgs/main
  gmp                                             pkgs/main --> anaconda/pkgs/main
  graphite2                                       pkgs/main --> anaconda/pkgs/main
  hdf5                                            pkgs/main --> anaconda/pkgs/main
  heapdict                                        pkgs/main --> anaconda/pkgs/main
  html5lib                                        pkgs/main --> anaconda/pkgs/main
  icu                                             pkgs/main --> anaconda/pkgs/main
  imagecodecs                                     pkgs/main --> anaconda/pkgs/main
  imageio                                         pkgs/main --> anaconda/pkgs/main
  inflection                                      pkgs/main --> anaconda/pkgs/main
  iniconfig                                       pkgs/main --> anaconda/pkgs/main
  intel-openmp                                    pkgs/main --> anaconda/pkgs/main
  intervaltree                                    pkgs/main --> anaconda/pkgs/main
  ipython_genutils                                pkgs/main --> anaconda/pkgs/main
  ipywidgets                                      pkgs/main --> anaconda/pkgs/main
  isort                                           pkgs/main --> anaconda/pkgs/main
  itsdangerous                                    pkgs/main --> anaconda/pkgs/main
  jbig                                            pkgs/main --> anaconda/pkgs/main
  jdcal                                           pkgs/main --> anaconda/pkgs/main
  jeepney                                         pkgs/main --> anaconda/pkgs/main
  jinja2-time                                     pkgs/main --> anaconda/pkgs/main
  joblib                                          pkgs/main --> anaconda/pkgs/main
  json5                                           pkgs/main --> anaconda/pkgs/main
  jsonschema                                      pkgs/main --> anaconda/pkgs/main
  jupyter                                         pkgs/main --> anaconda/pkgs/main
  jupyter_client                                  pkgs/main --> anaconda/pkgs/main
  jupyterlab_pygmen~                              pkgs/main --> anaconda/pkgs/main
  jupyterlab_widgets                              pkgs/main --> anaconda/pkgs/main
  jxrlib                                          pkgs/main --> anaconda/pkgs/main
  lazy-object-proxy                               pkgs/main --> anaconda/pkgs/main
  lcms2                                           pkgs/main --> anaconda/pkgs/main
  lerc                                            pkgs/main --> anaconda/pkgs/main
  libaec                                          pkgs/main --> anaconda/pkgs/main
  libarchive                                      pkgs/main --> anaconda/pkgs/main
  libev                                           pkgs/main --> anaconda/pkgs/main
  libffi                                          pkgs/main --> anaconda/pkgs/main
  libgfortran-ng                                  pkgs/main --> anaconda/pkgs/main
  libgfortran4                                    pkgs/main --> anaconda/pkgs/main
  libllvm11                                       pkgs/main --> anaconda/pkgs/main
  libsodium                                       pkgs/main --> anaconda/pkgs/main
  libspatialindex                                 pkgs/main --> anaconda/pkgs/main
  libtool                                         pkgs/main --> anaconda/pkgs/main
  libzopfli                                       pkgs/main --> anaconda/pkgs/main
  lzo                                             pkgs/main --> anaconda/pkgs/main
  matplotlib-inline                               pkgs/main --> anaconda/pkgs/main
  mccabe                                          pkgs/main --> anaconda/pkgs/main
  mistune                                         pkgs/main --> anaconda/pkgs/main
  mkl                                             pkgs/main --> anaconda/pkgs/main
  mkl-service                                     pkgs/main --> anaconda/pkgs/main
  mkl_random                                      pkgs/main --> anaconda/pkgs/main
  mock                                            pkgs/main --> anaconda/pkgs/main
  mpc                                             pkgs/main --> anaconda/pkgs/main
  mpfr                                            pkgs/main --> anaconda/pkgs/main
  mpi                                             pkgs/main --> conda-forge
  mpich                                           pkgs/main --> anaconda/pkgs/main
  multipledispatch                                pkgs/main --> anaconda/pkgs/main
  munkres                                         pkgs/main --> anaconda/pkgs/main
  mypy_extensions                                 pkgs/main --> anaconda/pkgs/main
  nbformat                                        pkgs/main --> anaconda/pkgs/main
  nest-asyncio                                    pkgs/main --> anaconda/pkgs/main
  ninja                                           pkgs/main --> anaconda/pkgs/main
  ninja-base                                      pkgs/main --> anaconda/pkgs/main
  nose                                            pkgs/main --> anaconda/pkgs/main
  olefile                                         pkgs/main --> anaconda/pkgs/main
  openjpeg                                        pkgs/main --> anaconda/pkgs/main
  openpyxl                                        pkgs/main --> anaconda/pkgs/main
  pandocfilters                                   pkgs/main --> anaconda/pkgs/main
  partd                                           pkgs/main --> anaconda/pkgs/main
  path                                            pkgs/main --> anaconda/pkgs/main
  path.py                                         pkgs/main --> anaconda/pkgs/main
  pathlib2                                        pkgs/main --> anaconda/pkgs/main
  pathspec                                        pkgs/main --> anaconda/pkgs/main
  pcre                                            pkgs/main --> anaconda/pkgs/main
  pep8                                            pkgs/main --> anaconda/pkgs/main
  pexpect                                         pkgs/main --> anaconda/pkgs/main
  pickleshare                                     pkgs/main --> anaconda/pkgs/main
  pixman                                          pkgs/main --> anaconda/pkgs/main
  ply                                             pkgs/main --> anaconda/pkgs/main
  poyo                                            pkgs/main --> anaconda/pkgs/main
  prompt-toolkit                                  pkgs/main --> anaconda/pkgs/main
  ptyprocess                                      pkgs/main --> anaconda/pkgs/main
  pycodestyle                                     pkgs/main --> anaconda/pkgs/main
  pydocstyle                                      pkgs/main --> anaconda/pkgs/main
  pyerfa                                          pkgs/main --> anaconda/pkgs/main
  pyflakes                                        pkgs/main --> anaconda/pkgs/main
  pyls-spyder                                     pkgs/main --> anaconda/pkgs/main
  pyparsing                                       pkgs/main --> anaconda/pkgs/main
  pyrsistent                                      pkgs/main --> anaconda/pkgs/main
  pysocks                                         pkgs/main --> anaconda/pkgs/main
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  zstd                                            pkgs/main --> anaconda/pkgs/main


Proceed ([y]/n)? ^C

CondaSystemExit: 
Operation aborted.  Exiting.


EnvironmentFileNotFound: '/home/zhuangwanru/models/testesm/esm/esm/environment.yml' file not found
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加载数据集

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原论文中使用了CATH4.3数据集进行验证
鉴于蛋白质逆折叠系列任务目前大多测试结果都基于CATH4.2版本，这里采用了CATH4.2版本数据集进行验证

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[9]
import requests
import tarfile
import os
from tqdm import tqdm
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[11]
def load_data():
print("Loading data...")
#需要下载的文件的URL
url = "http://download.cathdb.info/cath/releases/all-releases/v4_2_0/non-redundant-data-sets/cath-dataset-nonredundant-S40-v4_2_0.pdb.tgz"
if not os.path.exists("./esm/inverse_folding/data/cath42"):
os.makedirs("./esm/inverse_folding/data/cath42")

#保存下载文件的名称
file_name = "cath-dataset-nonredundant-S40-v4_2_0.tar.tgz"
# 下载文件
response = requests.get(url, stream=True)
total_size = int(response.headers.get('content-length', 0))
block_size = 1024
progress_bar = tqdm(total=total_size, unit='B', unit_scale=True)
with open(file_name, "wb") as f:
for data in response.iter_content(block_size):
progress_bar.update(len(data))
f.write(data)
progress_bar.close()
#解压文件到cath4.2目录
print("Extracting data...")
with tarfile.open(file_name,"r|gz") as tar:
tar.extractall("./esm/inverse_folding/data/cath42")
tar.close()

files = os.listdir("./esm/inverse_folding/data/cath42")
print(f"Sucess Extracting {len(files)} data...")

load_data()
Loading data...
100%|██████████| 754M/754M [01:03<00:00, 11.8MB/s]   
Extracting data...
Sucess Extracting 1 data...
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我们遵循baselines数据集分割方式，这里可以直接通过下载测试集合文件进行对原始集合进行分割。文件来源于：

https://github.com/A4Bio/PiFold/

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[16]
!wget -O ./esm/inverse_folding/data/cath.zip https://github.com/A4Bio/PiFold/releases/download/Training%26Data/cath4.2.zip
!unzip ./esm/inverse_folding/data/cath.zip -d ./esm/inverse_folding/data/
--2023-09-20 12:11:41--  https://github.com/A4Bio/PiFold/releases/download/Training%26Data/cath4.2.zip
Resolving github.com (github.com)... 20.205.243.166
Connecting to github.com (github.com)|20.205.243.166|:443... connected.
HTTP request sent, awaiting response... 302 Found
Location: https://objects.githubusercontent.com/github-production-release-asset-2e65be/538405150/36fd2f8c-5e3b-4a07-9741-dc881be4a4e5?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=AKIAIWNJYAX4CSVEH53A%2F20230920%2Fus-east-1%2Fs3%2Faws4_request&X-Amz-Date=20230920T041141Z&X-Amz-Expires=300&X-Amz-Signature=f3462ffe3906e72a2467ec7f3fe4a89194c7a5e574932558b5b0cbb4c5fe2bae&X-Amz-SignedHeaders=host&actor_id=0&key_id=0&repo_id=538405150&response-content-disposition=attachment%3B%20filename%3Dcath4.2.zip&response-content-type=application%2Foctet-stream [following]
--2023-09-20 12:11:42--  https://objects.githubusercontent.com/github-production-release-asset-2e65be/538405150/36fd2f8c-5e3b-4a07-9741-dc881be4a4e5?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=AKIAIWNJYAX4CSVEH53A%2F20230920%2Fus-east-1%2Fs3%2Faws4_request&X-Amz-Date=20230920T041141Z&X-Amz-Expires=300&X-Amz-Signature=f3462ffe3906e72a2467ec7f3fe4a89194c7a5e574932558b5b0cbb4c5fe2bae&X-Amz-SignedHeaders=host&actor_id=0&key_id=0&repo_id=538405150&response-content-disposition=attachment%3B%20filename%3Dcath4.2.zip&response-content-type=application%2Foctet-stream
Resolving objects.githubusercontent.com (objects.githubusercontent.com)... 185.199.110.133, 185.199.109.133, 185.199.111.133
Connecting to objects.githubusercontent.com (objects.githubusercontent.com)|185.199.110.133|:443... connected.
HTTP request sent, awaiting response... 200 OK
Length: 188153738 (179M) [application/octet-stream]
Saving to: ‘./esm/inverse_folding/data/cath.zip’

./esm/inverse_foldi 100%[===================>] 179.44M  24.1MB/s    in 7.4s    

2023-09-20 12:11:50 (24.1 MB/s) - ‘./esm/inverse_folding/data/cath.zip’ saved [188153738/188153738]

Archive:  ./esm/inverse_folding/data/cath.zip
  inflating: ./esm/inverse_folding/data/cath4.2/chain_set.jsonl  
  inflating: ./esm/inverse_folding/data/cath4.2/chain_set_splits.json  
  inflating: ./esm/inverse_folding/data/cath4.2/download_cath.sh  
  inflating: ./esm/inverse_folding/data/cath4.2/ollikainen_set.jsonl  
  inflating: ./esm/inverse_folding/data/cath4.2/remove.json  
  inflating: ./esm/inverse_folding/data/cath4.2/test_split_L100.json  
  inflating: ./esm/inverse_folding/data/cath4.2/test_split_sc.json
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加载模型

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[ ]
import numpy as np
import torch
import esm
import esm.inverse_folding
import os
from tqdm import tqdm
import json
device=torch.device('cuda:0')

model, alphabet = esm.pretrained.esm_if1_gvp4_t16_142M_UR50()
model = model.eval()

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[ ]
## 通过data_split_path来指定测试集类型：{single-chain,short,All}
# 这里以short的测试集分割为例，其中short子集指长度<100的序列数据
data_split = "./esm/inverse_folding/data/cath4.2/test_split_L100.json"
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Test Recovery

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Recovery： 在这个任务中，Recovery衡量的是预测得到的氨基酸序列与参考氨基酸序列的相似程度。即预测序列结果与天然序列(native sequence)中完全匹配的氨基酸的比例。Recovery越高，算法性能越好。

代码
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[ ]

def test_recovery():
recovery_list = []
num_data = 0
files = os.listdir("./esm/inverse_folding/data/cath42/dompdb")
if torch.cuda.is_available():
model = model.to(device)
print("Transferred model to GPU")
with open(data_split,'r') as f:
split = json.load(f)
for i, e in enumerate(split['test']):
split['test'][i] = e.split(".")[0]

for pdb in tqdm(files):
if pdb[:4] in split['test'] :
structure = esm.inverse_folding.util.load_structure("./esm/inverse_folding/data/cath42/dompdb/"+pdb)
coords, native_seqs = esm.inverse_folding.multichain_util.extract_coords_from_complex(structure)
target_chain_id = [id for id in native_seqs.keys()]
for id in target_chain_id:
native_seq = native_seqs[id]
sampled_seq = model.sample(coords[id], temperature=0.1, device=device)
recovery = np.mean([(a==b) for a, b in zip(native_seq, sampled_seq)])
print(f'Test Num:{num_data} Recovery(median): {np.median(recovery_list):.4f}')


test_recovery()
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Test Perplexity

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**Perplexity：**在这个任务中，Perplexity衡量的是从蛋白质三级结构预测氨基酸序列时，预测模型所产生的不确定性。这种不确定性通常与预测结果的多样性有关。较低的Perplexity意味着模型能够生成较为简洁且准确的氨基酸序列。

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[ ]
def test_ppl():
total_ll = 0.0
num_data=0
length = 0
if torch.cuda.is_available():
model = model.to(device)
print("Transferred model to GPU")
files = os.listdir("./esm/inverse_folding/data/cath42/dompdb")
with open(data_split,'r') as f:
split = json.load(f)
for i, e in enumerate(split['test']):
split['test'][i] = e.split(".")[0]
for pdb in tqdm(files):
if pdb[:4] in split['test']:
structure = esm.inverse_folding.util.load_structure("./esm/inverse_folding/data/cath42/dompdb/"+pdb)
coords, native_seqs = esm.inverse_folding.multichain_util.extract_coords_from_complex(structure)
target_chain_id = [id for id in native_seqs.keys()]
for id in target_chain_id:
native_seq = native_seqs[id]
ll, _ = esm.inverse_folding.multichain_util.score_sequence_in_complex(
model, alphabet, coords, id, native_seq)
total_ll+=ll
num_data+=1
length += len(native_seq)

print(f'Test Num:{num_data} Perplexity: {np.exp(-total_ll / num_data):.4f}')


test_ppl()
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