recipe biobb_pytorch

biobb_pytorch is the Biobb module collection to create and train ML & DL models.




APACHE / Apache Software License



# biobb_pytorch

### Introduction Biobb_Pytorch is the Biobb module collection to create and train ML & DL models using the popular [PyTorch]( Python library. Biobb (BioExcel building blocks) packages are Python building blocks that create new layer of compatibility and interoperability over popular bioinformatics tools. The latest documentation of this package can be found in our readthedocs site: [latest API documentation](

### Copyright & Licensing This software has been developed in the [MMB group]( at the [BSC]( & [IRB]( for the [European BioExcel](, funded by the European Commission (EU H2020 [823830](, EU H2020 [675728](

* (c) 2015-2024 [Barcelona Supercomputing Center]( * (c) 2015-2024 [Institute for Research in Biomedicine]( Licensed under the [Apache License 2.0](, see the file LICENSE for details.

![]( "Bioexcel")

package biobb_pytorch

(downloads) docker_biobb_pytorch



depends biobb_common:


depends python:


depends pytorch:



You need a conda-compatible package manager (currently either micromamba, mamba, or conda) and the Bioconda channel already activated (see set-up-channels).

While any of above package managers is fine, it is currently recommended to use either micromamba or mamba (see here for installation instructions). We will show all commands using mamba below, but the arguments are the same for the two others.

Given that you already have a conda environment in which you want to have this package, install with:

   mamba install biobb_pytorch

and update with::

   mamba update biobb_pytorch

To create a new environment, run:

mamba create --name myenvname biobb_pytorch

with myenvname being a reasonable name for the environment (see e.g. the mamba docs for details and further options).

Alternatively, use the docker container:

   docker pull<tag>

(see `biobb_pytorch/tags`_ for valid values for ``<tag>``)

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