DeepChem has a number of "soft" requirements. These are packages which are needed for various submodules of DeepChem but not for the package as a whole.
conda install-c deepchem -c rdkit -c conda-forge -c omnia deepchem=2.3.0
pip install tensorflow==1.15
conda install-c deepchem -c rdkit -c conda-forge -c omnia deepchem==2.3.0
```
If you want GPU support:
```bash
conda install-c deepchem -c rdkit -c conda-forge -c omnia deepchem-gpu=2.3.0
conda install-y-q scikit-learn=0.22
conda install-c deepchem -c rdkit -c conda-forge -c omnia deepchem-gpu==2.3.0
```
**Note:** The above commands install the latest stable version of `deepchem` and _do not install from source_. If you need to install from source make sure you follow the steps [here](#using-a-conda-environment).
### Install via pip (WIP)
### Using a Docker Image
Using a docker image requires an NVIDIA GPU. If you do not have a GPU please follow the directions for [using a conda environment](#installing-from-source-in-a-conda-environment)
In order to get GPU support you will have to use the [nvidia-docker](https://github.com/NVIDIA/nvidia-docker) plugin.
``` bash
# This will the download the latest stable deepchem docker image into your images
docker pull deepchemio/deepchem
You are able to try to install deepchem via pip using the following command.
However, pip installation is under development, so this command may not work well.
# This will create a container out of our latest image with GPU support
nvidia-docker run -i-t deepchemio/deepchem
`deepchem>=2.4.0`
# You are now in a docker container whose python has deepchem installed
# For example you can run our tox21 benchmark
cd deepchem/examples
python benchmark.py -d tox21
Coming soon...
# Or you can start playing with it in the command line
You can install deepchem in a new conda environment using the conda commands in scripts/install_deepchem_conda.sh
Installing via this script will ensure that you are **installing from the source**.
### Install from source
You can install deepchem in a new conda environment using the conda commands in `scripts/install_deepchem_conda.sh.` Installing via this script will ensure that you are **installing from the source**.
The following script requires `conda>=4.4` because it uses the `conda activate` command. (Please see the detail from [here](https://github.com/conda/conda/blob/a4c4feae404b2b378e106bd25f62cc8be15c768f/CHANGELOG.md#440-2017-12-20))
First, please clone the deepchem repository from GitHub.
```bash
git clone https://github.com/deepchem/deepchem.git# Clone deepchem source code from GitHub
bash scripts/install_deepchem_conda.sh deepchem # If you don't want GPU support
```
If you want GPU support:
```
gpu=1 bash scripts/install_deepchem_conda.sh deepchem # If you want GPU support
Then, follow each instruction on your OS.
### General installation
```bash
bash scripts/install_deepchem_conda.sh deepchem
```
Note : `gpu=0 bash scripts/install_deepchem_conda.sh deepchem` will also install CPU supported `deepchem`.
Before activating deepchem environment, make sure conda has been initialized.
Check if there is a `(base)` in your command line.
If not, use `conda init bash` to activate it, then:
```
source activate deepchem
conda activate deepchem
python setup.py install # Manual install
nosetests -a '!slow' -v deepchem --nologcapture # Run tests
```
This creates a new conda environment `deepchem` and installs in it the dependencies that
are needed. To access it, use the `conda activate deepchem` command (if your conda version >= 4.4) and use `source activate deepchem` command (if your conda version < 4.4).
Check [this link](https://conda.io/docs/using/envs.html) for more information about
the benefits and usage of conda environments. **Warning**: Segmentation faults can [still happen](https://github.com/deepchem/deepchem/pull/379#issuecomment-277013514)
via this installation procedure.
Check [this link](https://conda.io/projects/conda/en/latest/user-guide/install/index.html) for more information about the installation of conda environments.
### Installing in Windows
### Use powershell (Windows)
Currently you have to install from source in windows. The following scripts requires `conda>4.6`.
Currently you have to install from source in windows.
If you want gpu support, use the following command in powershell:
Before activating deepchem envrionment, make sure conda-powershell has been initialized.
Check if there is a `(base)` before `PS` in powershell. If not, use `conda init powershell`
to activate it, then:
```
Before activating deepchem environment, make sure conda-powershell has been initialized.
Check if there is a `(base)` before `PS` in powershell.
If not, use `conda init powershell` to activate it, then:
```bash
conda activate deepchem
python setup.py install
nosetests -a'!slow'-v deepchem --nologcapture
```
### Install using a Docker (WIP)
### Build the image from Dockerfile
We prepare for [sample Dockerfiles](https://github.com/deepchem/deepchem/tree/master/docker) to install deepchem from source codes and conda package manager. Please check them!
### Use the official deepchem image (WIP)
We couldn't check if this introduction works well or not.
First, you pull the latest stable deepchem docker image.
```bash
docker pull deepchemio/deepchem
```
Then, you create a container based on our latest image.
```bash
docker run -it deepchemio/deepchem
```
If you want GPU support:
```bash
# If nvidia-docker is installed
nvidia-docker run -it deepchemio/deepchem
docker run --runtime nvidia -it deepchemio/deepchem
# If nvidia-container-toolkit is installed
docker run --gpus all -it deepchemio/deepchem
```
You are now in a docker container whose python has deepchem installed.
```bash
# you can start playing with it in the command line
pip install jupyter
ipython
import deepchem as dc
# you can run our tox21 benchmark
cd /deepchem/examples
python benchmark.py -d tox21
```
## FAQ and Troubleshooting
1. DeepChem currently supports Python 3.5 through 3.7, and is supported on 64 bit Linux and Mac OSX. Note that DeepChem is not currently maintained for older versions of Python or with other operating systems.
2. Question: I'm seeing some failures in my test suite having to do with MKL
```Intel MKL FATAL ERROR: Cannot load libmkl_avx.so or libmkl_def.so.```
`Intel MKL FATAL ERROR: Cannot load libmkl_avx.so or libmkl_def.so.`
Answer: This is a general issue with the newest version of `scikit-learn` enabling MKL by default. This doesn't play well with many linux systems. See [BVLC/caffe#3884](https://github.com/BVLC/caffe/issues/3884) for discussions. The following seems to fix the issue
3. Note that when using Ubuntu 16.04 server or similar environments, you may need to ensure libxrender is provided via e.g.:
```bash
sudo apt-get install-y libxrender-dev
```
## Getting Started
The DeepChem project maintains an extensive colelction of [tutorials](https://github.com/deepchem/deepchem/tree/master/examples/tutorials). All tutorials are designed to be run on Google colab (or locally if you prefer). Tutorials are arranged in a suggested learning sequence which will take you from beginner to proficient at molecular machine learning and computational biology more broadly.
After working through the tutorials, you can also go through other [examples](https://github.com/deepchem/deepchem/tree/master/examples). To apply `deepchem` to a new problem, try starting from one of the existing examples or tutorials and modifying it step by step to work with your new use-case. If you have questions or comments you can raise them on our [gitter](https://gitter.im/deepchem/Lobby).
### Gitter
Join us on gitter at [https://gitter.im/deepchem/Lobby](https://gitter.im/deepchem/Lobby). Probably the easiest place to ask simple questions or float requests for new features.
## About Us
DeepChem is managed by a team of open source contributors. Anyone is free to join and contribute!
## Citing DeepChem
@@ -177,4 +242,5 @@ To cite this book, please use this bibtex entry:
