Merge pull request #2257 from nd-02110114/fix-docs-build

Improve documents
deepchem · Nov 3, 2020 · 27a8ef1 · 27a8ef1
2 parents d79c5ea + 4f26c4a
commit 27a8ef1
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Showing 39 changed files with 541 additions and 429 deletions.
diff --git a/.gitignore b/.gitignore
@@ -71,15 +71,15 @@ target/
 datasets/2008-2011_USPTO_reactionSmiles_filtered.zip
 datasets/2008-2011_USPTO_reactionSmiles_filtered/
 datasets/autodock_vina_1_1_2_mac_catalina_64bit/
-datasets/chembl_25-featurized/          
-datasets/chembl_25.csv.gz                 
+datasets/chembl_25-featurized/
+datasets/chembl_25.csv.gz
 datasets/delaney-featurized/  
-datasets/from-pdbbind/                                   
-datasets/kinase/                                         
-datasets/pdbbind/                                        
+datasets/from-pdbbind/
+datasets/kinase/
+datasets/pdbbind/
 datasets/pdbbind_v2015.tar.gz
 datasets/qm7-featurized/ 
-datasets/qm7.csv                                         
+datasets/qm7.csv
 datasets/qm7.mat
 datasets/sider-featurized/
 datasets/sider.csv.gz
@@ -101,3 +101,4 @@ datasets/pdbbind_v2019_refined.tar.gz
 datasets/qm8.csv
 
 .vscode/
+.python-version
diff --git a/.readthedocs.yml b/.readthedocs.yml
@@ -7,11 +7,7 @@ version: 2
 
 # Build documentation in the docs/ directory with Sphinx
 sphinx:
-  configuration: docs/conf.py
-
-# Build documentation with MkDocs
-# mkdocs:
-#   configuration: mkdocs.yml
+  configuration: docs/source/conf.py
 
 # Optionally build your docs in additional formats such as PDF and ePub
 formats: all

diff --git a/.travis.yml b/.travis.yml
@@ -44,6 +44,7 @@ script:
   - if [[ "$CHECK_ONLY_DOCS" == "true" ]]; then
       cd docs && pip install -r requirements.txt;
       make clean html;
+      make doctest_tutorials;
       make doctest_examples;
       travis_terminate $?;
     fi

diff --git a/README.md b/README.md
@@ -30,7 +30,7 @@ materials science, quantum chemistry, and biology.
 
 ## Requirements
 
-DeepChem currently supports Python 3.5 through 3.7 and requires these packages on any condition.
+DeepChem currently supports Python 3.6 through 3.7 and requires these packages on any condition.
 
 - [joblib](https://pypi.python.org/pypi/joblib)
 - [NumPy](https://numpy.org/)

diff --git a/deepchem/models/sklearn_models/sklearn_model.py b/deepchem/models/sklearn_models/sklearn_model.py
@@ -35,7 +35,7 @@ class SklearnModel(Model):
   perhaps you want to use the hyperparameter tuning capabilities in
   `dc.hyper`. The `SklearnModel` class provides a wrapper around scikit-learn
   models that allows scikit-learn models to be trained on `Dataset` objects
-  and evaluated with the same metrics as other DeepChem models.`
+  and evaluated with the same metrics as other DeepChem models.
 
   Notes
   -----

diff --git a/docs/.gitignore b/docs/.gitignore
diff --git a/docs/Makefile b/docs/Makefile
@@ -5,8 +5,8 @@
 # from the environment for the first two.
 SPHINXOPTS    ?=
 SPHINXBUILD   ?= sphinx-build
-SOURCEDIR     = .
-BUILDDIR      = _build
+SOURCEDIR     = source
+BUILDDIR      = build
 
 # Put it first so that "make" without argument is like "make help".
 help:
@@ -15,8 +15,10 @@ help:
 .PHONY: help Makefile
 
 doctest_examples:
-	export PYTHONWARNINGS= 
-	@$(SPHINXBUILD) -M doctest "$(SOURCEDIR)" "$(BUILDDIR)" examples.rst;
+	@$(SPHINXBUILD) -M doctest "$(SOURCEDIR)" "$(BUILDDIR)" source/get_started/examples.rst;
+
+doctest_tutorials:
+	@$(SPHINXBUILD) -M doctest "$(SOURCEDIR)" "$(BUILDDIR)" source/get_started/tutorials.rst;
 
 # Catch-all target: route all unknown targets to Sphinx using the new
 # "make mode" option.  $(O) is meant as a shortcut for $(SPHINXOPTS).

diff --git a/docs/README.md b/docs/README.md
@@ -7,17 +7,24 @@ and examples.
 ## Building the Documentation
 
 To build the docs, you can use the `Makefile` that's been added to
-this directory. (Note that `deepchem` must be installed first.) To
-generate docs in html, run
+this directory. To generate docs in html, run following commands.
 
 ```
-pip install -r requirements.txt
-make html
-open _build/html/index.html
+$ pip install -r requirements.txt
+$ make html
+// clean build
+$ make clean html
+$ open build/html/index.html
 ```
 
-You can generate docs in other formats as well if you like. To clean up past builds run
+If you want to confirm logs in more details,
 
 ```
-make clean
+$ make clean html SPHINXOPTS=-vvv
 ```
+
+If you want to confirm the example tests,
+
+```
+$ make doctest_examples
+```
diff --git a/docs/index.rst b/docs/index.rst
diff --git a/docs/requirements.txt b/docs/requirements.txt
@@ -3,5 +3,4 @@ scikit-learn
 sphinx_rtd_theme
 tensorflow==2.3.0
 transformers
-xgboost
 torch==1.6.0
diff --git a/docs/_static/logo.png → docs/source/_static/logo.png b/docs/_static/logo.png → docs/source/_static/logo.png
diff --git a/docs/_static/theme_overrides.css → docs/source/_static/theme_overrides.css b/docs/_static/theme_overrides.css → docs/source/_static/theme_overrides.css
diff --git a/docs/dataclasses.rst → docs/source/api_reference/dataclasses.rst b/docs/dataclasses.rst → docs/source/api_reference/dataclasses.rst
diff --git a/docs/dataloaders.rst → docs/source/api_reference/dataloaders.rst b/docs/dataloaders.rst → docs/source/api_reference/dataloaders.rst
diff --git a/docs/datasets.rst → docs/source/api_reference/datasets.rst b/docs/datasets.rst → docs/source/api_reference/datasets.rst
diff --git a/docs/docking.rst → docs/source/api_reference/docking.rst b/docs/docking.rst → docs/source/api_reference/docking.rst
diff --git a/docs/featurizers.rst → docs/source/api_reference/featurizers.rst b/docs/featurizers.rst → docs/source/api_reference/featurizers.rst
@@ -93,7 +93,7 @@ WeaveFeaturizer
   :members:
 
 MACCSKeysFingerprint
-^^^^^^^^^^^^^^^^^^^
+^^^^^^^^^^^^^^^^^^^^
 
 .. autoclass:: deepchem.feat.MACCSKeysFingerprint
   :members:
@@ -105,13 +105,13 @@ CircularFingerprint
   :members:
 
 PubChemFingerprint
-^^^^^^^^^^^^^^^^^^^
+^^^^^^^^^^^^^^^^^^
 
 .. autoclass:: deepchem.feat.PubChemFingerprint
   :members:
 
 Mol2VecFingerprint
-^^^^^^^^^^^^^^^^^^^
+^^^^^^^^^^^^^^^^^^
 
 .. autoclass:: deepchem.feat.Mol2VecFingerprint
   :members:

diff --git a/docs/hyper.rst → docs/source/api_reference/hyper.rst b/docs/hyper.rst → docs/source/api_reference/hyper.rst
diff --git a/docs/layers.rst → docs/source/api_reference/layers.rst b/docs/layers.rst → docs/source/api_reference/layers.rst
diff --git a/docs/metalearning.rst → docs/source/api_reference/metalearning.rst b/docs/metalearning.rst → docs/source/api_reference/metalearning.rst
diff --git a/docs/metrics.rst → docs/source/api_reference/metrics.rst b/docs/metrics.rst → docs/source/api_reference/metrics.rst
@@ -1,6 +1,6 @@
 Metrics
 =======
-Metrics are one of the most import parts of machine learning. Unlike
+Metrics are one of the most important parts of machine learning. Unlike
 traditional software, in which algorithms either work or don't work,
 machine learning models work in degrees. That is, there's a continuous
 range of "goodness" for a model. "Metrics" are functions which measure

diff --git a/docs/models.rst → docs/source/api_reference/models.rst b/docs/models.rst → docs/source/api_reference/models.rst
@@ -199,9 +199,6 @@ Losses
 .. autoclass:: deepchem.models.losses.SparseSoftmaxCrossEntropy
   :members:
 
-.. autoclass:: deepchem.models.losses.SparseSoftmaxCrossEntropy
-  :members:
-
 .. autoclass:: deepchem.models.losses.VAE_ELBO
   :members:
 
@@ -241,9 +238,6 @@ Optimizers
 .. autoclass:: deepchem.models.optimizers.LinearCosineDecay
   :members:
 
-.. autoclass:: deepchem.models.optimizers.LinearCosineDecay
-  :members:
-
 
 Keras Models
 ============

diff --git a/docs/moleculenet.rst → docs/source/api_reference/moleculenet.rst b/docs/moleculenet.rst → docs/source/api_reference/moleculenet.rst
diff --git a/docs/rl.rst → docs/source/api_reference/rl.rst b/docs/rl.rst → docs/source/api_reference/rl.rst
diff --git a/docs/splitters.rst → docs/source/api_reference/splitters.rst b/docs/splitters.rst → docs/source/api_reference/splitters.rst
@@ -4,7 +4,7 @@ DeepChem :code:`dc.splits.Splitter` objects are a tool to meaningfully
 split DeepChem datasets for machine learning testing. The core idea is
 that when evaluating a machine learning model, it's useful to creating
 training, validation and test splits of your source data. The training
-split is used to train models, the validatation is used to benchmark
+split is used to train models, the validation is used to benchmark
 different model architectures. The test is ideally held out till the
 very end when it's used to gauge a final estimate of the model's
 performance.

diff --git a/docs/tokenizers.rst → docs/source/api_reference/tokenizers.rst b/docs/tokenizers.rst → docs/source/api_reference/tokenizers.rst
diff --git a/docs/transformers.rst → docs/source/api_reference/transformers.rst b/docs/transformers.rst → docs/source/api_reference/transformers.rst
diff --git a/docs/utils.rst → docs/source/api_reference/utils.rst b/docs/utils.rst → docs/source/api_reference/utils.rst