Data Flow Facilitator for Machine Learning (dffml) v0.3.3 Release Notes
Release Date: 2020-02-11 // about 4 years ago-
[0.3.3] - 2020-02-10
โ Added
- ๐ Moved from TensorFlow 1 to TensorFlow 2.
- IDX Sources to read binary data files and train models on MNIST Dataset
- scikit models
- Clusterers
- KMeans
- Birch
- MiniBatchKMeans
- AffinityPropagation
- MeanShift
- SpectralClustering
- AgglomerativeClustering
- OPTICS
allowempty
added to source config parameters.- Quickstart document to show how to use models from Python.
- ๐ The latest release of the documentation now includes a link to the
๐ documentation for the master branch (on GitHub pages). - ๐ณ Virtual environment, GitPod, and Docker development environment setup notes to
the CONTRIBUTING.md file. - ๐ Changelog now included in documenation website.
- Database abstraction
dffml.db
- SQLite connector
- MySQL connector
- ๐ Documented style for imports.
- ๐ Documented use of numpy docstrings.
Inputs
can now be sanitized using function passed invalidate
parameter- ๐
Helper utilities to take callables with numpy style docstrings and
create config classes out of them usingmake_config
. - File listing endpoint to HTTP service.
- ๐ป When an operation throws an exception the name of the instance and the
parameters it was executed with will be thrown via anOperationException
. - Network utilities to preformed cached downloads with hash validation.
- Development service got a new command, which can retrieve an argument passed
to setuptoolssetup
function within asetup.py
file.
๐ Changed
- All instances of
src_url
changed tokey
. readonly
parameter in source config is now changed toreadwrite
.predict
parameter of all model config classes has been changed fromstr
toFeature
.- ๐ป Defining features on the command line no longer requires that defined features
๐ be prefixed withdef:
- ๐ป The model predict operation will now raise an exception if the model it is
passed via it's config is a class rather than an instance. entry_point
and friends have been renamed toentrypoint
.- ๐ Use
FastChildWatcher
when run via the CLI to preventBlockingIOError
s. - TensorFlow based neural network classifier had the
classification
parameter
in it's config changed topredict
. - SciKit models use
make_config_numpy
. - Predictions in
repos
are now dictionary. - All instances of
label
changed totag
- Subclasses of
BaseConfigurable
will now auto instantiate their respective
config classes usingkwargs
if the config argument isn't given and keyword
arguments are. - ๐ The quickstart documentation was improved as well as the structure of docs.
๐ Fixed
- CONTRIBUTING.md has
-e
in the wrong place in the getting setup section. - Since moving to auto
args()
andconfig()
, BaseConfigurable no longer
๐ produces odd typenames in conjunction with docs.py. - Autoconvert Definitions with spec into their spec
โ Removed
- The model predict operation erroneously had a
msg
parameter in it's config. - Unused imports identified by deepsource.io
- โ Evaluation code from feature.py file as well as tests for those evaluations.