DeepEcho Versions Save

This release adds support for Python 3.12!

Maintenance

• Support Python 3.12 - Issue #85 by @fealho
• Transition from using setup.py to pyproject.toml to specify project metadata - Issue #86 by @R-Palazzo
• Remove bumpversion and use bump-my-version - Issue #87 by @R-Palazzo
• Add dependency checker - Issue #96 by @lajohn4747
• Add bandit workflow - Issue #98 by @R-Palazzo

Bugs Fixed

• Fix make check candidate - Issue #91 by @R-Palazzo
• Fix minimum version workflow when pointing to github branch - Issue #99 by @R-Palazzo

This release updates the PAR's model progress bar to show loss values and time elapsed (verbose option).

New Features

• Update progress bar for PAR fitting - Issue #80 by @frances-h

This release drops support for Python 3.7 and adds support for Python 3.11.

Maintenance

• Add support for Python 3.11 - Issue #74 by @fealho
• Drop support for Python 3.7 - Issue #75 by @R-Palazzo

This release adds support for Pandas 2.0 and PyTorch 2.0!

Maintenance

• Remove upper bound for pandas - Issue #69 by @frances-h
• Upgrade to Torch 2.0 - Issue #70 by @frances-h

This release adds support for python 3.10 and 3.11. It also drops support for python 3.6.

Maintenance

• Support Python 3.10 and 3.11 - Issue #63 by @pvk-developer
• DeepEcho Package Maintenance Updates - Issue #62 by @pvk-developer

This release adds support for Python 3.9 and updates dependencies to ensure compatibility with the rest of the SDV ecosystem.

• Add support for Python 3.9 - Issue #41 by @fealho
• Add pip check to CI workflows internal improvements - Issue #39 by @pvk-developer
• Add support for pylint>2.7.2 housekeeping - Issue #33 by @fealho
• Add support for torch>=1.8 housekeeping - Issue #32 by @fealho

This release fixes a bug with how DeepEcho handles NaN values.

• Handling NaN's bug - Issue #35 by @fealho

Maintenance release to update dependencies and ensure compatibility with the rest of the SDV ecosystem libraries.

Minor maintenance version to update dependencies and documentation, and also make the demo data loading function parse dates properly.

This version includes several minor improvements to the PAR model and the way the sequences are generated:

• Sequences can now be generated without dropping the sequence index.
• The PAR model learns the min and max length of the sequence from the input data.
• NaN values are properly supported for both categorical and numerical columns.
• NaN values are generated for numerical columns only if there were NaNs in the input data.
• Constant columns can now be modeled.