Merge branch 'master' into update-feat-docs

      with:

        file: ./coverage.xml

  deploy:

  pypi-build:

    if: github.event_name == 'push' && github.ref == 'refs/heads/master'

    needs: [build]

    runs-on: ubuntu-latest

      run: |

        python setup.py sdist bdist_wheel

        twine upload dist/*

  docker-build:

    if: github.event_name == 'push' && github.ref == 'refs/heads/master'

    needs: [build, pypi-build]

    runs-on: ubuntu-latest

    steps:

    - uses: actions/checkout@v2

    - name: Set up Docker Buildx

      id: buildx

      uses: docker/setup-buildx-action@master

    - name: Cache Docker layers

      uses: actions/cache@v2

      with:

        path: /tmp/.buildx-cache

        key: ${{ runner.os }}-buildx-${{ github.sha }}

        restore-keys: ${{ runner.os }}-buildx-

    - name: Login to DockerHub

      uses: docker/login-action@v1 

      with:

        username: ${{ secrets.DOCKER_HUB_USERNAME }}

        password: ${{ secrets.DOCKER_HUB_ACCESS_TOKEN }}

    - name: Build and push

      id: docker_build

      uses: docker/build-push-action@v2

      with:

        builder: ${{ steps.buildx.outputs.name }}

        context: ./docker/nightly

        push: true

        tags: deepchemio/deepchem:latest

        cache-from: type=local,src=/tmp/.buildx-cache

        cache-to: type=local,dest=/tmp/.buildx-cache

    - name: Image digest

      run: echo ${{ steps.docker_build.outputs.digest }}

name: Release PyPI packages

name: Release

on:

  push:

    tags:

      - '*' # ci work when pushing a tag

jobs:

  release:

  pypi:

    runs-on: ubuntu-latest

    strategy:

      fail-fast: false

      matrix:

        python-version: [3.7]

    steps:

      run: |

        python setup.py sdist bdist_wheel --release

        twine upload dist/*

  docker:

    needs: [pypi]

    runs-on: ubuntu-latest

    steps:

    - uses: actions/checkout@v2

    - name: Get the tag version

      id: get_tag_version

      run: echo ::set-output name=VERSION::${GITHUB_REF#refs/tags/}

    - name: Login to DockerHub

      uses: docker/login-action@v1 

      with:

        username: ${{ secrets.DOCKER_HUB_USERNAME }}

        password: ${{ secrets.DOCKER_HUB_ACCESS_TOKEN }}

    - name: Build and push

      id: docker_build

      uses: docker/build-push-action@v2

      with:

        context: ./docker/tag

        push: true

        tags: deepchemio/deepchem:${{ steps.get_tag_version.outputs.VERSION }}

    - name: Image digest

      run: echo ${{ steps.docker_build.outputs.digest }}

### Stable version

**Caution!! : The latest stable version was published nearly a year ago. If you are a pip user or you face some errors, we recommend the nightly build version.**

Please install tensorflow v2.3.* before installing deepchem.

RDKit is a soft requirement package, but many useful methods like molnet depend on it. We recommend installing RDKit with deepchem.

```bash

pip install tensorflow==2.3.*

```

Then, you install deepchem via pip or conda.  

```bash

pip install tensorflow==1.14

conda install -y -c conda-forge rdkit deepchem==2.3.0

pip install deepchem

```

or 

```

conda install -c conda-forge deepchem

```

If you want GPU support:

RDKit is a soft requirement package, but many useful methods like molnet depend on it.

We recommend installing RDKit with deepchem if you use conda.

```bash

pip install tensorflow-gpu==1.14

conda install -y -c conda-forge rdkit deepchem==2.3.0

conda install -y -c conda-forge rdkit

```

### Nightly build version

You install the nightly build version via pip. The nightly version is built by the HEAD of DeepChem.

The nightly version is built by the HEAD of DeepChem.

```bash

pip install tensorflow==2.3.*

pip install --pre deepchem

```

RDKit is a soft requirement package, but many useful methods like molnet depend on it. We recommend installing RDKit with deepchem if you use conda.

```bash

conda install -y -c conda-forge rdkit

```

### Docker

If you want to install deepchem using a docker, you can pull two kinds of images.  

- `deepchemio/deepchem:x.x.x`

  - Image built by using a conda (x.x.x is a version of deepchem)

  - The x.x.x image is built when we push x.x.x. tag

  - Dockerfile is put in `docker/conda-forge` directory

  - Dockerfile is put in `docker/tag` directory

- `deepchemio/deepchem:latest`

  - Image built from source codes

  - The latest image is built every time we commit to the master branch

  - Dockerfile is put in `docker/master` directory

  - Dockerfile is put in `docker/nightly` directory

You pull the image like this.

```bash

docker pull deepchemio/deepchem:2.3.0

docker pull deepchemio/deepchem:2.4.0

```

If you want to know docker usages with deepchem in more detail, please check [the document](https://deepchem.readthedocs.io/en/latest/installation.html#docker).

"""

# If you push the tag, please remove `.dev`

__version__ = '2.4.0-rc1.dev'

__version__ = '2.5.0.dev'

import deepchem.data

import deepchem.feat

  (in this case, `n_tasks` and `n_features` which are properties of a

  dataset and not hyperparameters to search over.)

  >>> def model_builder(**model_params):

  >>> def model_builder(model_dir, **model_params):

  ...   n_layers = model_params['layers']

  ...   layer_width = model_params['width']

  ...   dropout = model_params['dropout']