alphafold | Install alphafold on the local machine , get out of docker | Machine Learning library

by kuixu Python Version: Current License: Apache-2.0

X-Ray Key Features Code Snippets Community Discussions(2)Vulnerabilities Install Support

kandi X-RAY | alphafold Summary

alphafold is a Python library typically used in Artificial Intelligence, Machine Learning applications. alphafold has no vulnerabilities, it has build file available, it has a Permissive License and it has low support. However alphafold has 1 bugs. You can download it from GitHub.

This package provides an implementation of the inference pipeline of AlphaFold v2.0. This is a completely new model that was entered in CASP14 and published in Nature. For simplicity, we refer to this model as AlphaFold throughout the rest of this document. Any publication that discloses findings arising from using this source code or the model parameters should cite the AlphaFold paper.

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Quality

Security

License

Reuse

Support

alphafold has a low active ecosystem.

It has 75 star(s) with 30 fork(s). There are 5 watchers for this library.

It had no major release in the last 6 months.

There are 12 open issues and 4 have been closed. On average issues are closed in 9 days. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of alphafold is current.

Quality

alphafold has 1 bugs (0 blocker, 0 critical, 0 major, 1 minor) and 23 code smells.

Security

alphafold has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

alphafold code analysis shows 0 unresolved vulnerabilities.

There are 4 security hotspots that need review.

License

alphafold is licensed under the Apache-2.0 License. This license is Permissive.

Permissive licenses have the least restrictions, and you can use them in most projects.

Reuse

alphafold releases are not available. You will need to build from source code and install.

Build file is available. You can build the component from source.

Installation instructions, examples and code snippets are available.

It has 8586 lines of code, 443 functions and 59 files.

It has medium code complexity. Code complexity directly impacts maintainability of the code.

Top functions reviewed by kandi - BETA

kandi has reviewed alphafold and discovered the below as its top functions. This is intended to give you an instant insight into alphafold implemented functionality, and help decide if they suit your requirements.

Parse a mmCIF file
Generate the pdb header
Return a list of AtomSite objects
Return the release date of the given info
Predict structure
Compute the confidence metrics for a prediction result
Runs prediction on features
Compute the backbone backbone angles
Return the indices of the chi atoms
Fix the given PDB file
R Compute the within - residue constraints
Decorator to create a layer stack
Make the constants for all backbone atoms
Parses a stockholm string
Return the shape of a feature
Compute the loss
Convert a stockholm format to an A3M table
Compute the predicted TM - score
Make the upper and upper bound of the atoms
Convert sequence to one - hot array
Process tensors from config
Computes the distance between two residues
Process a FASTA file
Calculates the difference between two residues
Run a pipeline
Finds optimal renaming of atoms

Get all kandi verified functions for this library.

alphafold Key Features

No Key Features are available at this moment for alphafold.

alphafold Examples and Code Snippets

No Code Snippets are available at this moment for alphafold.

Community Discussions

Trending Discussions on alphafold

Bash repeating my directory and can not call the file

failed to alloc X bytes unified memory; result: CUDA_ERROR_OUT_OF_MEMORY: out of memory

QUESTION

Bash repeating my directory and can not call the file

Asked 2021-Nov-18 at 20:51

have to use a .sh script to unpack and prep some databases. The code is the following:

...

ANSWER

Answered 2021-Nov-18 at 20:51

To answer your first question: why is it repeating? Because you are repeating it in your code:

Source https://stackoverflow.com/questions/70022234

QUESTION

failed to alloc X bytes unified memory; result: CUDA_ERROR_OUT_OF_MEMORY: out of memory

Asked 2021-Sep-01 at 12:43

I am trying to run a tensorflow project and I am encountering memory problems on the university HPC cluster. I have to run a prediction job for hundreds of inputs, with differing lengths. We have GPU nodes with different amounts of vmem, so I am trying to set up the scripts in a way that will not crash in any combination of GPU node - input length.

After searching the net for solutions, I played around with TF_FORCE_UNIFIED_MEMORY, XLA_PYTHON_CLIENT_MEM_FRACTION, XLA_PYTHON_CLIENT_PREALLOCATE, and TF_FORCE_GPU_ALLOW_GROWTH, and also with tensorflow's set_memory_growth. As I understood, with unified memory, I should be able to use more memory than a GPU has in itself.

This was my final solution (only relevant parts)

...

ANSWER

Answered 2021-Aug-29 at 18:26

Probably this answer will be useful for you. This nvidia_smi python module have some useful tools like checking the gpu total memory. Here I reproduce the code of the answer I mentioned earlier.

Source https://stackoverflow.com/questions/68902851

Community Discussions, Code Snippets contain sources that include Stack Exchange Network

Vulnerabilities

No vulnerabilities reported

Install alphafold

The following steps are required in order to run AlphaFold:.
or step by step. Download genetic databases (see below). Download model parameters (see below).
Requirements NVIDIA cuda driver >= 10.2 Miniconda
Install softwares git clone https://github.com/kuixu/alphafold.git cd alphafold ./install_on_local.sh or step by step conda create -n af2 python=3.8 -y conda activate af2 conda install -y -c conda-forge \ openmm=7.5.1 \ pdbfixer \ pip conda install -y -c bioconda hmmer hhsuite==3.3.0 kalign2 conda install -y -c nvidia cudnn==8.0.4 # python pkgs pip3 install --upgrade pip \ && pip3 install -r ./requirements.txt \ && pip3 install --upgrade "jax[cuda111]" -f \ https://storage.googleapis.com/jax-releases/jax_releases.html \ && pip3 install jaxlib==0.1.70+cuda111 -f \ https://storage.googleapis.com/jax-releases/jax_releases.html # work_path=/path/to/alphafold-code work_path=$(PWD) # update openmm a=$(which python) cd $(dirname $(dirname $a))/lib/python3.8/site-packages patch -p0 < $work_path/docker/openmm.patch
Download genetic databases (see below).
Download model parameters (see below).
Set path. # Set to target of scripts/download_all_databases.sh DOWNLOAD_DIR = '/path/to/database' # Path to a directory that will store the results. output_dir = '/path/to/output_dir'

Support

For any new features, suggestions and bugs create an issue on GitHub. If you have any questions check and ask questions on community page Stack Overflow .

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