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Merck / deepbgc

BGC Detection and Classification Using Deep Learning
https://doi.org/10.1093/nar/gkz654
MIT License
127 stars 27 forks source link

ERROR: Could not find a version that satisfies the requirement tensorflow<2.0.0,>=1.15.4 (from deepbgc) #52

Closed Bollie15 closed 3 years ago

Bollie15 commented 3 years ago

Hello, I am sorry to ask you for help again. 😥 I have some problem when I install deepbgc on WSL2.

First try: I follow your instruction to install deepbgc by conda install deepbgc. But it is not the latest version, it is 0.1.10.

(base) b07@SB:~$ deepbgc --version
 _____                  ____    ____   ____
 |  _ \  ___  ___ ____ | __ )  / ___) / ___)
 | | \ \/ _ \/ _ \  _ \|  _ \ | |  _ | |
 | |_/ /  __/  __/ |_) | |_) || |_| || |___
 |____/ \___|\___| ___/|____/  \____| \____)
=================|_|===== version 0.1.10 =====
usage: deepbgc [-h] COMMAND ...

DeepBGC - Biosynthetic Gene Cluster detection and classification

Second try: I want to try your latest version to get the *.json file. So I follow this issue How to use DeepBGC's results to the antiSMASH to install special version by conda install deepbgc==0.1.23

(base) b07@SB:~$ conda install deepbgc==0.1.23
Collecting package metadata (current_repodata.json): -
done
Solving environment: failed with initial frozen solve. Retrying with flexible solve.
Collecting package metadata (repodata.json): / 
done
Solving environment: failed with initial frozen solve. Retrying with flexible solve.
Solving environment: |
Found conflicts! Looking for incompatible packages.
This can take several minutes.  Press CTRL-C to abort.
failed

UnsatisfiableError: The following specifications were found to be incompatible with each other:

Output in format: Requested package -> Available versions

Third try: Finally, I just download this file to manually install deepbgc. image Then I uncompressed it and tried to type pip install . in current directory. https://github.com/Merck/deepbgc/issues/45#issuecomment-784134359

(base) b07@SB:~/deepbgc-0.1.25$ tree
.
├── LICENSE
├── LICENSES_THIRD_PARTY
├── Makefile
├── README.md
├── deepbgc
│   ├── __init__.py
│   ├── __version__.py
│   ├── command
│   │   ├── __init__.py
│   │   ├── base.py
│   │   ├── download.py
│   │   ├── info.py
│   │   ├── pipeline.py
│   │   ├── prepare.py
│   │   └── train.py
│   ├── data.py
│   ├── features.py
│   ├── main.py
│   ├── models
│   │   ├── __init__.py
│   │   ├── hmm.py
│   │   ├── random_forest.py
│   │   ├── rnn.py
│   │   └── wrapper.py
│   ├── output
│   │   ├── __init__.py
│   │   ├── antismash_json.py
│   │   ├── bgc_genbank.py
│   │   ├── cluster_tsv.py
│   │   ├── evaluation
│   │   │   ├── __init__.py
│   │   │   ├── bgc_region_plot.py
│   │   │   ├── pfam_score_plot.py
│   │   │   ├── pr_plot.py
│   │   │   └── roc_plot.py
│   │   ├── genbank.py
│   │   ├── pfam_tsv.py
│   │   ├── readme.py
│   │   └── writer.py
│   ├── pipeline
│   │   ├── __init__.py
│   │   ├── annotator.py
│   │   ├── classifier.py
│   │   ├── detector.py
│   │   ├── pfam.py
│   │   ├── protein.py
│   │   └── step.py
│   └── util.py
├── images
│   ├── deepbgc.architecture.png
│   ├── deepbgc.bgc.png
│   └── deepbgc.pipeline.png
├── setup.py
└── test
    ├── __init__.py
    ├── data
    │   ├── BGC0000015.classes.csv
    │   ├── BGC0000015.fa
    │   ├── BGC0000015.fa.gz
    │   ├── BGC0000015.gbk
    │   ├── BGC0000015.pfam.csv
    │   ├── BGC0000015.protein.fa
    │   ├── Pfam-A.PF00005.clans.tsv
    │   ├── Pfam-A.PF00005.hmm
    │   ├── Pfam-A.PF00005.hmm.h3f
    │   ├── Pfam-A.PF00005.hmm.h3i
    │   ├── Pfam-A.PF00005.hmm.h3m
    │   ├── Pfam-A.PF00005.hmm.h3p
    │   ├── clusterfinder_geneborder_test.json
    │   ├── deepbgc_test.json
    │   ├── negative.pfam.csv
    │   ├── pfam2vec.test.tsv
    │   └── random_forest_test.json
    ├── integration
    │   ├── __init__.py
    │   ├── commands
    │   │   ├── __init__.py
    │   │   ├── test_integration_pipeline.py
    │   │   └── test_integration_prepare.py
    │   └── pipeline
    │       ├── __init__.py
    │       ├── test_integration_pfam.py
    │       └── test_integration_protein.py
    ├── test_util.py
    └── unit
        ├── __init__.py
        ├── commands
        │   ├── __init__.py
        │   ├── test_unit_pipeline.py
        │   └── test_unit_train.py
        ├── output
        │   ├── __init__.py
        │   └── test_unit_writers.py
        └── test_unit_main.py

15 directories, 79 files

(base) b07@SB:~/deepbgc-0.1.25$  pip install .
Collecting argparse
  Using cached argparse-1.4.0-py2.py3-none-any.whl (23 kB)
Requirement already satisfied: biopython<=1.76,>=1.70 in /home/b07/miniconda3/lib/python3.8/site-packages (from deepbgc==0.1.25) (1.76)
Collecting scikit-learn<=0.21.3,>=0.18.2
  Downloading scikit-learn-0.21.3.tar.gz (12.2 MB)
     |████████████████████████████████| 12.2 MB 294 kB/s
Collecting pandas>=0.24.1
  Downloading pandas-1.2.3-cp38-cp38-manylinux1_x86_64.whl (9.7 MB)
     |████████████████████████████████| 9.7 MB 1.3 MB/s
Collecting numpy<1.17,>=1.16.1
  Downloading numpy-1.16.6.zip (5.1 MB)
     |████████████████████████████████| 5.1 MB 442 kB/s
Collecting keras<2.3.0,>=2.2.4
  Downloading Keras-2.2.5-py2.py3-none-any.whl (336 kB)
     |████████████████████████████████| 336 kB 104 kB/s
ERROR: Could not find a version that satisfies the requirement tensorflow<2.0.0,>=1.15.4 (from deepbgc)
ERROR: No matching distribution found for tensorflow<2.0.0,>=1.15.4

Unfortunately, I failed again. I hope you can help me, I want to this antismash.json file. Thank you in advance. image

prihoda commented 3 years ago

Hi @Bollie15, can you try conda install python==3.7 deepbgc==0.1.26 and share the commandline output?

Bollie15 commented 3 years ago

Hi @Bollie15, can you try conda install python==3.7 deepbgc==0.1.26 and share the commandline output?

I am so happy to tell you that I successfully install this powerful tool by conda install python==3.7 deepbgc==0.1.26. Thanks!

(base) b07@SB:~$ conda install python==3.7 deepbgc==0.1.26
Collecting package metadata (current_repodata.json): \ 
done
Solving environment: failed with initial frozen solve. Retrying with flexible solve.
Collecting package metadata (repodata.json): - 
done
Solving environment: done

## Package Plan ##

  environment location: /home/b07/miniconda3

  added / updated specs:
    - deepbgc==0.1.26
    - python==3.7

The following packages will be downloaded:

    package                    |            build
    ---------------------------|-----------------
    _tflow_select-2.3.0        |              mkl           2 KB
    absl-py-0.11.0             |   py37h89c1867_0         168 KB  conda-forge
    asn1crypto-1.4.0           |     pyh9f0ad1d_0          78 KB  conda-forge
    binutils_impl_linux-64-2.35.1|       h193b22a_2         9.3 MB  conda-forge
    binutils_linux-64-2.35     |      h67ddf6f_30          22 KB  conda-forge
    biopython-1.76             |   py37h516909a_0         2.6 MB  conda-forge
    blas-2.14                  |         openblas          10 KB  conda-forge
    brotlipy-0.7.0             |py37h5e8e339_1001         341 KB  conda-forge
    bzip2-1.0.8                |       h7f98852_4         484 KB  conda-forge
    c-ares-1.17.1              |       h7f98852_1         109 KB  conda-forge
    certifi-2020.12.5          |   py37h89c1867_1         143 KB  conda-forge
    cffi-1.14.4                |   py37h11fe52a_0         224 KB  conda-forge
    chardet-4.0.0              |   py37h89c1867_1         204 KB  conda-forge
    conda-4.9.2                |   py37h89c1867_0         3.0 MB  conda-forge
    conda-package-handling-1.7.2|   py37hb5d75c8_0         915 KB  conda-forge
    cryptography-2.5           |   py37hb7f436b_1         643 KB  conda-forge
    deepbgc-0.1.26             |             py_0          47 KB  bioconda
    freetype-2.10.4            |       h0708190_1         890 KB  conda-forge
    gast-0.4.0                 |     pyh9f0ad1d_0          12 KB  conda-forge
    gcc_impl_linux-64-9.3.0    |      h70c0ae5_18        43.1 MB  conda-forge
    gcc_linux-64-9.3.0         |      hf25ea35_30          23 KB  conda-forge
    grpcio-1.16.0              |py37h4f00d22_1000         1.0 MB  conda-forge
    gxx_impl_linux-64-9.3.0    |      hd87eabc_18        10.7 MB  conda-forge
    gxx_linux-64-9.3.0         |      h3fbe746_30          23 KB  conda-forge
    h5py-2.10.0                |nompi_py37h90cd8ad_104         1.0 MB  conda-forge
    icu-58.2                   |    hf484d3e_1000        22.6 MB  conda-forge
    importlib-metadata-3.7.2   |   py37h89c1867_0          24 KB  conda-forge
    keras-2.2.4                |           py37_1         492 KB  conda-forge
    keras-applications-1.0.8   |             py_1          30 KB  conda-forge
    kernel-headers_linux-64-2.6.32|      h77966d4_13         707 KB  conda-forge
    kiwisolver-1.3.1           |   py37h2527ec5_1          78 KB  conda-forge
    libblas-3.8.0              |      14_openblas          10 KB  conda-forge
    libcblas-3.8.0             |      14_openblas          10 KB  conda-forge
    libffi-3.2.1               |    he1b5a44_1007          47 KB  conda-forge
    libgcc-devel_linux-64-9.3.0|      h7864c58_18         4.0 MB  conda-forge
    libgpuarray-0.7.6          |    h7f98852_1003         245 KB  conda-forge
    liblapack-3.8.0            |      14_openblas          10 KB  conda-forge
    liblapacke-3.8.0           |      14_openblas          10 KB  conda-forge
    libopenblas-0.3.7          |       h5ec1e0e_6         7.6 MB  conda-forge
    libprotobuf-3.15.5         |       h780b84a_0         2.5 MB  conda-forge
    libstdcxx-devel_linux-64-9.3.0|      hb016644_18        13.9 MB  conda-forge
    mako-1.1.4                 |     pyh44b312d_0          58 KB  conda-forge
    markupsafe-1.1.1           |   py37h5e8e339_3          27 KB  conda-forge
    matplotlib-base-2.2.3      |   py37h60b886d_1         6.4 MB  conda-forge
    numpy-1.16.1               |   py37h99e49ec_1          48 KB
    numpy-base-1.16.1          |   py37h2f8d375_1         3.4 MB
    openssl-1.0.2u             |       h516909a_0         3.2 MB  conda-forge
    pandas-0.24.1              |   py37hf484d3e_0        11.1 MB  conda-forge
    protobuf-3.15.5            |   py37hcd2ae1e_0         344 KB  conda-forge
    pycosat-0.6.3              |py37h5e8e339_1006         107 KB  conda-forge
    pygpu-0.7.6                |py37h03ebfcd_1001         629 KB  conda-forge
    pyopenssl-19.0.0           |           py37_0          81 KB  conda-forge
    pysocks-1.7.1              |   py37h89c1867_3          27 KB  conda-forge
    python-3.7.0               |    hd21baee_1006        31.5 MB  conda-forge
    python_abi-3.7             |          1_cp37m           4 KB  conda-forge
    pyyaml-5.4.1               |   py37h5e8e339_0         189 KB  conda-forge
    readline-7.0               |    hf8c457e_1001         391 KB  conda-forge
    ruamel_yaml-0.15.80        |py37h5e8e339_1004         270 KB  conda-forge
    scikit-learn-0.21.3        |   py37hcdab131_0         6.7 MB  conda-forge
    scipy-1.2.0                |   py37he2b7bc3_0        13.7 MB
    setuptools-49.6.0          |   py37h89c1867_3         947 KB  conda-forge
    sqlite-3.28.0              |       h8b20d00_0         1.9 MB  conda-forge
    sysroot_linux-64-2.12      |      h77966d4_13        30.2 MB  conda-forge
    tensorboard-1.14.0         |           py37_0         3.2 MB  conda-forge
    tensorflow-1.14.0          |mkl_py37h45c423b_0           4 KB
    tensorflow-base-1.14.0     |mkl_py37h7ce6ba3_0        84.4 MB
    tensorflow-estimator-1.14.0|   py37h5ca1d4c_0         645 KB  conda-forge
    theano-1.0.5               |   py37hcd2ae1e_1         3.6 MB  conda-forge
    tornado-6.1                |   py37h5e8e339_1         646 KB  conda-forge
    wrapt-1.12.1               |   py37h5e8e339_3          47 KB  conda-forge
    ------------------------------------------------------------
                                           Total:       331.1 MB

The following NEW packages will be INSTALLED:

  _tflow_select      pkgs/main/linux-64::_tflow_select-2.3.0-mkl
  absl-py            conda-forge/linux-64::absl-py-0.11.0-py37h89c1867_0
  appdirs            conda-forge/noarch::appdirs-1.4.4-pyh9f0ad1d_0
  asn1crypto         conda-forge/noarch::asn1crypto-1.4.0-pyh9f0ad1d_0
  astor              conda-forge/noarch::astor-0.8.1-pyh9f0ad1d_0
  binutils_impl_lin~ conda-forge/linux-64::binutils_impl_linux-64-2.35.1-h193b22a_2
  binutils_linux-64  conda-forge/linux-64::binutils_linux-64-2.35-h67ddf6f_30
  biopython          conda-forge/linux-64::biopython-1.76-py37h516909a_0
  blas               conda-forge/linux-64::blas-2.14-openblas
  bzip2              conda-forge/linux-64::bzip2-1.0.8-h7f98852_4
  c-ares             conda-forge/linux-64::c-ares-1.17.1-h7f98852_1
  cycler             conda-forge/noarch::cycler-0.10.0-py_2
  deepbgc            bioconda/noarch::deepbgc-0.1.26-py_0
  freetype           conda-forge/linux-64::freetype-2.10.4-h0708190_1
  gast               conda-forge/noarch::gast-0.4.0-pyh9f0ad1d_0
  gcc_impl_linux-64  conda-forge/linux-64::gcc_impl_linux-64-9.3.0-h70c0ae5_18
  gcc_linux-64       conda-forge/linux-64::gcc_linux-64-9.3.0-hf25ea35_30
  google-pasta       conda-forge/noarch::google-pasta-0.2.0-pyh8c360ce_0
  grpcio             conda-forge/linux-64::grpcio-1.16.0-py37h4f00d22_1000
  gxx_impl_linux-64  conda-forge/linux-64::gxx_impl_linux-64-9.3.0-hd87eabc_18
  gxx_linux-64       conda-forge/linux-64::gxx_linux-64-9.3.0-h3fbe746_30
  h5py               conda-forge/linux-64::h5py-2.10.0-nompi_py37h90cd8ad_104
  hdf5               conda-forge/linux-64::hdf5-1.10.6-nompi_h3c11f04_101
  hmmer              bioconda/linux-64::hmmer-3.3.2-he1b5a44_0
  icu                conda-forge/linux-64::icu-58.2-hf484d3e_1000
  importlib-metadata conda-forge/linux-64::importlib-metadata-3.7.2-py37h89c1867_0
  joblib             conda-forge/noarch::joblib-1.0.1-pyhd8ed1ab_0
  keras              conda-forge/linux-64::keras-2.2.4-py37_1
  keras-applications conda-forge/noarch::keras-applications-1.0.8-py_1
  keras-preprocessi~ conda-forge/noarch::keras-preprocessing-1.1.2-pyhd8ed1ab_0
  kernel-headers_li~ conda-forge/noarch::kernel-headers_linux-64-2.6.32-h77966d4_13
  kiwisolver         conda-forge/linux-64::kiwisolver-1.3.1-py37h2527ec5_1
  libblas            conda-forge/linux-64::libblas-3.8.0-14_openblas
  libcblas           conda-forge/linux-64::libcblas-3.8.0-14_openblas
  libgcc-devel_linu~ conda-forge/linux-64::libgcc-devel_linux-64-9.3.0-h7864c58_18
  libgfortran-ng     conda-forge/linux-64::libgfortran-ng-7.5.0-h14aa051_18
  libgfortran4       conda-forge/linux-64::libgfortran4-7.5.0-h14aa051_18
  libgpuarray        conda-forge/linux-64::libgpuarray-0.7.6-h7f98852_1003
  liblapack          conda-forge/linux-64::liblapack-3.8.0-14_openblas
  liblapacke         conda-forge/linux-64::liblapacke-3.8.0-14_openblas
  libopenblas        conda-forge/linux-64::libopenblas-0.3.7-h5ec1e0e_6
  libpng             conda-forge/linux-64::libpng-1.6.37-h21135ba_2
  libprotobuf        conda-forge/linux-64::libprotobuf-3.15.5-h780b84a_0
  libstdcxx-devel_l~ conda-forge/linux-64::libstdcxx-devel_linux-64-9.3.0-hb016644_18
  mako               conda-forge/noarch::mako-1.1.4-pyh44b312d_0
  markdown           conda-forge/noarch::markdown-3.3.4-pyhd8ed1ab_0
  markupsafe         conda-forge/linux-64::markupsafe-1.1.1-py37h5e8e339_3
  matplotlib-base    conda-forge/linux-64::matplotlib-base-2.2.3-py37h60b886d_1
  numpy              pkgs/main/linux-64::numpy-1.16.1-py37h99e49ec_1
  numpy-base         pkgs/main/linux-64::numpy-base-1.16.1-py37h2f8d375_1
  pandas             conda-forge/linux-64::pandas-0.24.1-py37hf484d3e_0
  prodigal           bioconda/linux-64::prodigal-2.6.3-h516909a_2
  protobuf           conda-forge/linux-64::protobuf-3.15.5-py37hcd2ae1e_0
  pygpu              conda-forge/linux-64::pygpu-0.7.6-py37h03ebfcd_1001
  pyparsing          conda-forge/noarch::pyparsing-2.4.7-pyh9f0ad1d_0
  python-dateutil    conda-forge/noarch::python-dateutil-2.8.1-py_0
  pytz               conda-forge/noarch::pytz-2021.1-pyhd8ed1ab_0
  pyyaml             conda-forge/linux-64::pyyaml-5.4.1-py37h5e8e339_0
  scikit-learn       conda-forge/linux-64::scikit-learn-0.21.3-py37hcdab131_0
  scipy              pkgs/main/linux-64::scipy-1.2.0-py37he2b7bc3_0
  sysroot_linux-64   conda-forge/noarch::sysroot_linux-64-2.12-h77966d4_13
  tensorboard        conda-forge/linux-64::tensorboard-1.14.0-py37_0
  tensorflow         pkgs/main/linux-64::tensorflow-1.14.0-mkl_py37h45c423b_0
  tensorflow-base    pkgs/main/linux-64::tensorflow-base-1.14.0-mkl_py37h7ce6ba3_0
  tensorflow-estima~ conda-forge/linux-64::tensorflow-estimator-1.14.0-py37h5ca1d4c_0
  termcolor          conda-forge/noarch::termcolor-1.1.0-py_2
  theano             conda-forge/linux-64::theano-1.0.5-py37hcd2ae1e_1
  tornado            conda-forge/linux-64::tornado-6.1-py37h5e8e339_1
  typing_extensions  conda-forge/noarch::typing_extensions-3.7.4.3-py_0
  werkzeug           conda-forge/noarch::werkzeug-1.0.1-pyh9f0ad1d_0
  wrapt              conda-forge/linux-64::wrapt-1.12.1-py37h5e8e339_3
  zipp               conda-forge/noarch::zipp-3.4.1-pyhd8ed1ab_0

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

  pyopenssl          conda-forge/noarch::pyopenssl-20.0.1-~ --> conda-forge/linux-64::pyopenssl-19.0.0-py37_0
  python                 pkgs/main::python-3.8.5-h7579374_1 --> conda-forge::python-3.7.0-hd21baee_1006

The following packages will be DOWNGRADED:

  brotlipy                          0.7.0-py38h497a2fe_1001 --> 0.7.0-py37h5e8e339_1001
  certifi                          2020.12.5-py38h578d9bd_1 --> 2020.12.5-py37h89c1867_1
  cffi                                1.14.5-py38ha65f79e_0 --> 1.14.4-py37h11fe52a_0
  chardet                              4.0.0-py38h578d9bd_1 --> 4.0.0-py37h89c1867_1
  conda                                4.9.2-py38h578d9bd_0 --> 4.9.2-py37h89c1867_0
  conda-package-han~                   1.7.2-py38h8df0ef7_0 --> 1.7.2-py37hb5d75c8_0
  cryptography                         3.4.4-py38h3e25421_0 --> 2.5-py37hb7f436b_1
  libffi                                     3.3-h58526e2_2 --> 3.2.1-he1b5a44_1007
  openssl                                 1.1.1j-h7f98852_0 --> 1.0.2u-h516909a_0
  pycosat                           0.6.3-py38h497a2fe_1006 --> 0.6.3-py37h5e8e339_1006
  pysocks                              1.7.1-py38h578d9bd_3 --> 1.7.1-py37h89c1867_3
  python_abi                                     3.8-1_cp38 --> 3.7-1_cp37m
  readline                                   8.0-he28a2e2_2 --> 7.0-hf8c457e_1001
  ruamel_yaml                     0.15.80-py38h497a2fe_1004 --> 0.15.80-py37h5e8e339_1004
  setuptools                          49.6.0-py38h578d9bd_3 --> 49.6.0-py37h89c1867_3
  sqlite                                  3.34.0-h74cdb3f_0 --> 3.28.0-h8b20d00_0

Proceed ([y]/n)? y

Downloading and Extracting Packages
readline-7.0         | 391 KB    |                                                                               |   0% |############################################################################# | 100%
sysroot_linux-64-2.1 | 30.2 MB   | ############################################################################# | 100%
h5py-2.10.0          | 1.0 MB    | ############################################################################# | 100%
gcc_linux-64-9.3.0   | 23 KB     | ############################################################################# | 100%
deepbgc-0.1.26       | 47 KB     | ############################################################################# | 100%
libprotobuf-3.15.5   | 2.5 MB    | ############################################################################# | 100%
libcblas-3.8.0       | 10 KB     | ############################################################################# | 100%
keras-2.2.4          | 492 KB    | ############################################################################# | 100%
binutils_impl_linux- | 9.3 MB    | ############################################################################# | 100%
mako-1.1.4           | 58 KB     | ############################################################################# | 100%
biopython-1.76       | 2.6 MB    | ############################################################################# | 100%
pandas-0.24.1        | 11.1 MB   | ############################################################################# | 100%
c-ares-1.17.1        | 109 KB    | ############################################################################# | 100%
tornado-6.1          | 646 KB    | ############################################################################# | 100%
markupsafe-1.1.1     | 27 KB     | ############################################################################# | 100%
libgpuarray-0.7.6    | 245 KB    | ############################################################################# | 100%
conda-4.9.2          | 3.0 MB    | ############################################################################# | 100%
blas-2.14            | 10 KB     | ############################################################################# | 100%
certifi-2020.12.5    | 143 KB    | ############################################################################# | 100%
ruamel_yaml-0.15.80  | 270 KB    | ############################################################################# | 100%
numpy-base-1.16.1    | 3.4 MB    |                                                                               |   0% 
numpy-base-1.16.1    | 3.4 MB    | ############################################################################# | 100%
keras-applications-1 | 30 KB     | ############################################################################# | 100%
pysocks-1.7.1        | 27 KB     | ############################################################################# | 100%
python_abi-3.7       | 4 KB      | ############################################################################# | 100%
brotlipy-0.7.0       | 341 KB    | ############################################################################# | 100%
numpy-1.16.1         | 48 KB     | ############################################################################# | 100%
cffi-1.14.4          | 224 KB    | ############################################################################# | 100%
theano-1.0.5         | 3.6 MB    | ############################################################################# | 100%
pyopenssl-19.0.0     | 81 KB     | ############################################################################# | 100%
tensorflow-1.14.0    | 4 KB      | ############################################################################# | 100%
_tflow_select-2.3.0  | 2 KB      | ############################################################################# | 100%
gxx_impl_linux-64-9. | 10.7 MB   | ############################################################################# | 100%
gast-0.4.0           | 12 KB     | ############################################################################# | 100%
scipy-1.2.0          | 13.7 MB   | ############################################################################# | 100%
libgcc-devel_linux-6 | 4.0 MB    | ############################################################################# | 100%
gcc_impl_linux-64-9. | 43.1 MB   | ############################################################################# | 100%
conda-package-handli | 915 KB    | ############################################################################# | 100%
tensorflow-base-1.14 | 84.4 MB   | ############################################################################# | 100%
binutils_linux-64-2. | 22 KB     | ############################################################################# | 100%
pygpu-0.7.6          | 629 KB    | ############################################################################# | 100%
kiwisolver-1.3.1     | 78 KB     | ############################################################################# | 100%
freetype-2.10.4      | 890 KB    | ############################################################################# | 100%
asn1crypto-1.4.0     | 78 KB     | ############################################################################# | 100%
cryptography-2.5     | 643 KB    | ############################################################################# | 100%
icu-58.2             | 22.6 MB   | ############################################################################# | 100%
grpcio-1.16.0        | 1.0 MB    | ############################################################################# | 100%
pyyaml-5.4.1         | 189 KB    | ############################################################################# | 100%
setuptools-49.6.0    | 947 KB    | ############################################################################# | 100%
libstdcxx-devel_linu | 13.9 MB   | ############################################################################# | 100%
liblapack-3.8.0      | 10 KB     | ############################################################################# | 100%
liblapacke-3.8.0     | 10 KB     | ############################################################################# | 100%
sqlite-3.28.0        | 1.9 MB    | ############################################################################# | 100%
gxx_linux-64-9.3.0   | 23 KB     | ############################################################################# | 100%
openssl-1.0.2u       | 3.2 MB    | ############################################################################# | 100%
scikit-learn-0.21.3  | 6.7 MB    | ############################################################################# | 100%
libffi-3.2.1         | 47 KB     | ############################################################################# | 100%
libblas-3.8.0        | 10 KB     | ############################################################################# | 100%
tensorboard-1.14.0   | 3.2 MB    | ############################################################################# | 100%
libopenblas-0.3.7    | 7.6 MB    | ############################################################################# | 100%
chardet-4.0.0        | 204 KB    | ############################################################################# | 100%
wrapt-1.12.1         | 47 KB     | ############################################################################# | 100%
importlib-metadata-3 | 24 KB     | ############################################################################# | 100%
python-3.7.0         | 31.5 MB   | ############################################################################# | 100%
tensorflow-estimator | 645 KB    | ############################################################################# | 100%
absl-py-0.11.0       | 168 KB    | ############################################################################# | 100%
bzip2-1.0.8          | 484 KB    | ############################################################################# | 100%
kernel-headers_linux | 707 KB    | ############################################################################# | 100%
protobuf-3.15.5      | 344 KB    | ############################################################################# | 100%
pycosat-0.6.3        | 107 KB    | ############################################################################# | 100%
matplotlib-base-2.2. | 6.4 MB    | ############################################################################# | 100%
Preparing transaction: done
Verifying transaction: done
Executing transaction: done

Then typing deepbgc download, and finally I do it!

(base) b07@SB:~$ deepbgc info
 _____                  ____    ____   ____
 |  _ \  ___  ___ ____ | __ )  / ___) / ___)
 | | \ \/ _ \/ _ \  _ \|  _ \ | |  _ | |
 | |_/ /  __/  __/ |_) | |_) || |_| || |___
 |____/ \___|\___| ___/|____/  \____| \____)
=================|_|===== version 0.1.26 =====
INFO    09/03 16:53:56   Available data files: ['Pfam-A.31.0.hmm.h3i', 'Pfam-A.31.0.hmm.h3f', 'Pfam-A.31.0.clans.tsv', 'Pfam-A.31.0.hmm.h3m', 'Pfam-A.31.0.hmm.h3p', 'Pfam-A.31.0.hmm']
INFO    09/03 16:53:56   ================================================================================
INFO    09/03 16:53:56   Available detectors: ['clusterfinder_geneborder', 'clusterfinder_original', 'deepbgc', 'clusterfinder_retrained']INFO    09/03 16:53:56   --------------------------------------------------------------------------------
INFO    09/03 16:53:56   Model: clusterfinder_geneborder
INFO    09/03 16:53:56   Loading model from: /home/b07/.local/share/deepbgc/data/0.1.0/detector/clusterfinder_geneborder.pkl
WARNING 09/03 16:53:56   Model not supported: ('Package "hmmlearn" needs to be installed to run ClusterFinder HMM. ', 'Install extra dependencies using: \n    pip install "deepbgc[hmm]"')
INFO    09/03 16:53:56   --------------------------------------------------------------------------------
INFO    09/03 16:53:56   Model: clusterfinder_original
INFO    09/03 16:53:56   Loading model from: /home/b07/.local/share/deepbgc/data/0.1.0/detector/clusterfinder_original.pkl
WARNING 09/03 16:53:56   Model not supported: ('Package "hmmlearn" needs to be installed to run ClusterFinder HMM. ', 'Install extra dependencies using: \n    pip install "deepbgc[hmm]"')
INFO    09/03 16:53:56   --------------------------------------------------------------------------------
INFO    09/03 16:53:56   Model: deepbgc
INFO    09/03 16:53:56   Loading model from: /home/b07/.local/share/deepbgc/data/0.1.0/detector/deepbgc.pkl
Using TensorFlow backend.
WARNING 09/03 16:53:58   From /home/b07/miniconda3/lib/python3.7/site-packages/keras/backend/tensorflow_backend.py:74: The name tf.get_default_graph is deprecated. Please use tf.compat.v1.get_default_graph instead.

WARNING 09/03 16:53:58   From /home/b07/miniconda3/lib/python3.7/site-packages/keras/backend/tensorflow_backend.py:517: The name tf.placeholder is deprecated. Please use tf.compat.v1.placeholder instead.

WARNING 09/03 16:53:58   From /home/b07/miniconda3/lib/python3.7/site-packages/keras/backend/tensorflow_backend.py:4138: The name tf.random_uniform is deprecated. Please use tf.random.uniform instead.

WARNING 09/03 16:53:58   From /home/b07/miniconda3/lib/python3.7/site-packages/keras/backend/tensorflow_backend.py:133: The name tf.placeholder_with_default is deprecated. Please use tf.compat.v1.placeholder_with_default instead.

WARNING 09/03 16:53:58   From /home/b07/miniconda3/lib/python3.7/site-packages/keras/backend/tensorflow_backend.py:3445: calling dropout (from tensorflow.python.ops.nn_ops) with keep_prob is deprecated and will be removed in a future version.
Instructions for updating:
Please use `rate` instead of `keep_prob`. Rate should be set to `rate = 1 - keep_prob`.
WARNING 09/03 16:53:58   From /home/b07/miniconda3/lib/python3.7/site-packages/keras/backend/tensorflow_backend.py:174: The name tf.get_default_session is deprecated. Please use tf.compat.v1.get_default_session instead.

OMP: Info #212: KMP_AFFINITY: decoding x2APIC ids.
OMP: Info #210: KMP_AFFINITY: Affinity capable, using global cpuid leaf 11 info
OMP: Info #154: KMP_AFFINITY: Initial OS proc set respected: 0-3
OMP: Info #156: KMP_AFFINITY: 4 available OS procs
OMP: Info #157: KMP_AFFINITY: Uniform topology
OMP: Info #179: KMP_AFFINITY: 1 packages x 4 cores/pkg x 1 threads/core (4 total cores)
OMP: Info #214: KMP_AFFINITY: OS proc to physical thread map:
OMP: Info #171: KMP_AFFINITY: OS proc 0 maps to package 0 core 0
OMP: Info #171: KMP_AFFINITY: OS proc 1 maps to package 0 core 1
OMP: Info #171: KMP_AFFINITY: OS proc 2 maps to package 0 core 2
OMP: Info #171: KMP_AFFINITY: OS proc 3 maps to package 0 core 3
OMP: Info #250: KMP_AFFINITY: pid 5810 tid 5810 thread 0 bound to OS proc set 0
INFO    09/03 16:53:59   Type: KerasRNN
INFO    09/03 16:53:59   Version: 0.1.0
INFO    09/03 16:53:59   Timestamp: 1551305667.986168 (2019-02-27T14:14:27.986168)
INFO    09/03 16:53:59   --------------------------------------------------------------------------------
INFO    09/03 16:53:59   Model: clusterfinder_retrained
INFO    09/03 16:53:59   Loading model from: /home/b07/.local/share/deepbgc/data/0.1.0/detector/clusterfinder_retrained.pkl
WARNING 09/03 16:53:59   Model not supported: ('Package "hmmlearn" needs to be installed to run ClusterFinder HMM. ', 'Install extra dependencies using: \n    pip install "deepbgc[hmm]"')
INFO    09/03 16:53:59   ================================================================================
INFO    09/03 16:53:59   Available classifiers: ['product_class', 'product_activity']
INFO    09/03 16:53:59   --------------------------------------------------------------------------------
INFO    09/03 16:53:59   Model: product_class
INFO    09/03 16:53:59   Loading model from: /home/b07/.local/share/deepbgc/data/0.1.0/classifier/product_class.pkl
/home/b07/miniconda3/lib/python3.7/site-packages/sklearn/base.py:306: UserWarning: Trying to unpickle estimator DecisionTreeClassifier from version 0.18.2 when using version 0.21.3. This might lead to breaking code or invalid results. Use at your own risk.
  UserWarning)
/home/b07/miniconda3/lib/python3.7/site-packages/sklearn/base.py:306: UserWarning: Trying to unpickle estimator RandomForestClassifier from version 0.18.2 when using version 0.21.3. This might lead to breaking code or invalid results. Use at your own risk.
  UserWarning)
INFO    09/03 16:53:59   Type: RandomForestClassifier
INFO    09/03 16:53:59   Version: 0.1.0
INFO    09/03 16:53:59   Timestamp: 1551781410.019103 (2019-03-05T02:23:30.019103)
INFO    09/03 16:53:59   --------------------------------------------------------------------------------
INFO    09/03 16:53:59   Model: product_activity
INFO    09/03 16:53:59   Loading model from: /home/b07/.local/share/deepbgc/data/0.1.0/classifier/product_activity.pkl
INFO    09/03 16:53:59   Type: RandomForestClassifier
INFO    09/03 16:53:59   Version: 0.1.0
INFO    09/03 16:53:59   Timestamp: 1551781433.886473 (2019-03-05T02:23:53.886473)
INFO    09/03 16:53:59   ================================================================================
WARNING 09/03 16:53:59   Some warnings detected, check the output above

By the way, do I need to care about this WARNING message? Thank you👍

prihoda commented 3 years ago

Great! The warning is fine, you should be good to go 👍