# Change Log
All notable changes to this project will be documented in this file.

The format is based on [Keep a Changelog](http://keepachangelog.com/)
and this project adheres to [Semantic Versioning](http://semver.org/).


## [Unreleased]


## [1.12.0] - 2024-10-14
### Changed
- CLI formatting and file options for training, testing and reporting on
  models.
- Layers expect a torch configuration to fix a model quantization issue.
- Disable fp16 error when creating numpy sparse matrices.


## [1.11.2] - 2024-05-11
### Added
- A new feature to update previously trained model distribution's
  configuration.
- Moved the batch size resource library configuration to `default.conf`.

### Changed
- Moved batch size in resource library `batch.conf` to `default.conf`.


## [1.11.1] - 2024-03-14
### Changed
- Fix missing weighted classification metrics in JSON.


## [1.11.0] - 2024-03-07
### Added
- A model client (`ModelUnpacker`) that uses a bundled and downloaded model
  packaged with `ModelPacker`.  It allows two separate code bases to train the
  model and inference with it.
- A feature to turn off saving results (`ModelResults`) with model, which can
  potentially slow training and bloat models.
- A feature to store the results as a string with the model when the
  `ModelResults` is not saved with it.  These results are accessible in
  packaged models.

### Changed
- Move `TclError` to fix Python bailing if not compiled with Tcl/Tk
  (`tkinter`).
- Fix accuracy "N out of total" accuracy reporting metrics.


## [1.10.0] - 2024-02-27
### Added
- Model signifiance testing module `zensols.deeplearn.result.hypsig`.
- Data sanity checks on predictions when creating prediction dataframes.

### Changed
- Move CLI application imports to method level for faster importing.
- Fold `zensols.deeplearn.cli.app` into `zensols.deeplearn.cli`.  Since `app`
  was imported into the `cli` name space, this is backward compatible for apps
  that doesn't fully qualify.
- More flexible configuration options for `ModelFacade` prediction dataframe
  factory.
- Fix CLI batch action ignoring the `limit` argument.


## [1.9.0] - 2023-12-05
### Changed
- Upgrade to PyTorch 2.1.1, numpy 1.25, scipy 1.9, scikit-learn 1.3, pandas
  2.1, and [zensols.util] 1.14.
- Unit and integration test fixes.

### Added
- Support for Python 3.11.
- Multiple CUDA configuration support.

### Removed
- Support for Python 3.9.


## [1.8.1] - 2023-08-16
### Added
- A feature to *inject* application (or any) configuration into a previously
  packed or persisted model via `ModelManager`.
- `SubsetConfig`: subsets the application configuration
- A command-line option on the `FacadeApplication`'s `info` action that
  specifies the model path to allow a dump of the (packed) model's persisted
  configuration.


## [1.8.0] - 2023-08-16
Downstream moderate risk update release.

### Changed
- Set model type in `TorchConfig.to` only if its comparable and different.
- Upgrade to [zensols.util] v1.13.0.


## [1.7.0] - 2023-06-09
## Changes
- Upgraded [scipy] from 1.8.1 to 1.9.3.


## [1.6.1] - 2023-06-07
### Added
- Use of [zensols.datdesc] model output to create LaTeX tables.

### Changed
- Upgrade from torch 1.12 to torch 1.13.
- `TorchConfig` allows specific torch device name initialization, which is useful for
  macOS `mps` devices.


## [1.6.0] - 2023-01-23
### Added
- `SplitKeyContainer` write method for concrete subclasses.

### Changed
- Updated [zensols.util] to 1.12.0.
- Type hints and code clean up.


## [1.5.2] - 2022-11-06
### Changed
- Add batch size to output directory to allow changes without re-batching
  previous batch size configurations.
- Bug fix to validation metrics reporting.


## [1.5.1] - 2022-10-01
### Changed
- Upgrade `zensols.install`.


## [1.5.0] - 2022-10-01
### Removed
- Remove mask creation in aggregate vectorizer.  Use mask vectorizer instead.

### Added
- Added model packaging API.
- Added `Configurable` that reads from a CSV file with Pandas for nominal model
  labels.


## [1.4.0] - 2022-08-06
### Changed
- Upgrade a significant portion of the dependent libraries.


## [1.3.0] - 2022-06-14
This is primarily a refactoring release to simplify the API and examples.

### Added
- Feature creation resource library.
- Zensols installer and dependency for resource library adds.

### Changed
- Initialize PyTorch system from the `zensols.deepnlp` module.
- Stash prime chain fixes.
- Module logging uses calling logger when not provided.
- Add stratified split app reporting from facade app when available.
- Simplify facade application manager for Jupyter notebooks.
- Memory leak fixes in CLI facade application.
- Split off batch from info facade application.
- More error information for missing dataset splits.
- Fix batch feature mapping for prediction.

### Removed
- The `zensols.deeplearn.plot` module.


## [1.2.0] - 2022-05-15
### Added
- New dynamic batch mapping that no longer requires it to be hard coded in a
  Python source file.

### Changed
- Rename gradient norm to gradient scaling in `ModelSettings`.
- Minor bug fixes to results API.


## [1.1.1] - 2022-05-04
### Changed
- Fix pinned requirements.


## [1.1.0] - 2022-05-04
### Added
- Add label prediction metric calculations.
- Add split, label and key access as a Pandas dataframe.
- Create support for sequence based predictions as a Pandas dataframe.
- Add PyTorch `CrossEntryLoss` ignore index padding

### Changed
- Bug fixes and clean up warnings.
- Recurrent CRF network uses new network settings factory method.
- Remove HuggingFace schedule warnings.
- Default `OneHotEncodedFeatureDocumentVectorizer.optimize_bools = True` is
  needed as the default has been removed.
- Move model name configuration from `ModelExecutor` to `ModelSettings`.
- Guard on missing vectorizers.
- Move name from executor to model settings.


## [1.0.0] - 2022-02-12
Stable release

### Added
- Added observer pattern for model facade, execution and trainer.

### Changed
- Resource library clean up.
- Torch GPU memory reporting bug fix.
- Terminal progress bar fixes.


## [0.1.8] - 2022-01-25
### Changed
- PyTorch upgrade API bug fix.


## [0.1.7] - 2022-01-25
### Changes
- Upgrade to torch 1.9.
- Remove dependency on `pycuda`.
- Suppress `numpy` warnings from results reporting module, PyTorch start up and
  MNIST test cases.
- Better CUDA memory debugging/profiling.


## [0.1.6] - 2021-10-22
### Added
- Much more documentation.

### Changed
- Upgrade to new zensols.util import semantics.

### Removed
- Learning rate parameter from resource library.  It is better for the client
  to be forced to set it to avoid ambiguous spurious settings.
- DeepZensols NLP classification configuration that doesn't belong in this
  package.


## [0.1.5] - 2021-09-21
### Changed
- Rename `DataframeStash` to `SplitKeyDataframeStash`.
- Split out `FacadePredictApplication` from the `FacadeModelApplication`.

### Added
- Class `AutoSplitDataframeStash` to automatically split (add a column) a
  Pandas dataframe in to training, validation and test datasets.
- Configuration resource library.
- Add a default distribution for `StashSplitKeyContainer`.


## [0.1.4] - 2021-09-07
### Changed
- Upgrade to [zensols.util] version 1.6.0.
- Better model facade write behavior.


## [0.1.3] - 2021-08-07
### Changed
- Fix torch config GPU->CPU copy/dealloc; add outcomes/output in batch.

### Added
- CLI application to facade "glue" `FacadeApplication`.
- Sequence classification: model base class and batch iterator.
- Track direct output/outcomes/logits from model in results.
- More GPU side memory de-allocation.
- Support for float/quotient batch limits.


## [0.1.2] - 2021-04-29
### Changed
- Upgraded to torch 1.8 and `sklearn` 0.24.1.
- Protect deallocation of non-copied (GPU to GPU) batches.
- Warning clean up for `numpy`.
- Better model naming and file/directory name output.
- Clone tensor correctly in 1.7 per warning.

### Added
- Sparse support for size 3 tensors.
- New [zensols.util] 1.5 CLI application interface to facade.
- Summary spreadsheet reporting for results.  This scans a directory for
  results and adds performance metrics in to CSV file for easy reporting across
  multiple models.


## [0.1.1] - 2020-12-29
Maintenance release.
### Changed
- Updated dependencies and tested across Python 3.7, 3.8, 3.9.


## [0.1.0] - 2020-12-10
First fully functional major feature release, which includes batch
persistence/processing, layers, vectorizors, debugging and many other
features/support.  See [documentation] for more information.


## [0.0.6] - 2020-05-11
### Changed
- Upgrade to [zensols.util] 1.3.0 and torch 1.4.0.

### Added
- Type conversion from torch to numpy and sparse types.
- Implementation of sparse matrix encoding and decoding to compensate for
  PyTorch bug with hanging child processing in `multiprocessing` API.
- Key split stash implementation for data set splits.
- Vectorization framework
- Model training and testing framework.
- Notebook example usage.
- Unit tests, for which, now give very good coverage.

### Removed
- Travis build: too time consuming to make CUDA, python and xenial etc. all
  play together nicely.


## [0.0.5] - 2020-05-04

### Added
- Create sparse tensors.


## [0.0.4] - 2020-04-27

### Change
- Travis tests.
- Upgraded to Python 3.7.


## [0.0.3] - 2019-12-14
Data classes are now used so Python 3.7 is now a requirement.

### Added
- Arbitrarily deep linear layer using constant or decay parameter counts.
- Conv2d interface to PyTorch.

### Changed
- Better handling of tensor to memory mapping and device handling in general.


### Removed
- Moved `test.py` from this repository to [zensols.actioncli].


## [0.0.2] - 2019-07-07
### Added
- Tests.


## [0.0.1] - 2019-07-07
### Added
- Initial version.


<!-- links -->
[Unreleased]: https://github.com/plandes/deeplearn/compare/v1.12.0...HEAD
[1.12.0]: https://github.com/plandes/deeplearn/compare/v1.11.2...v1.12.0
[1.11.2]: https://github.com/plandes/deeplearn/compare/v1.11.1...v1.11.2
[1.11.1]: https://github.com/plandes/deeplearn/compare/v1.11.0...v1.11.1
[1.11.0]: https://github.com/plandes/deeplearn/compare/v1.10.0...v1.11.0
[1.10.0]: https://github.com/plandes/deeplearn/compare/v1.9.0...v1.10.0
[1.9.0]: https://github.com/plandes/deeplearn/compare/v1.8.1...v1.9.0
[1.8.1]: https://github.com/plandes/deeplearn/compare/v1.8.0...v1.8.1
[1.8.0]: https://github.com/plandes/deeplearn/compare/v1.7.0...v1.8.0
[1.7.0]: https://github.com/plandes/deeplearn/compare/v1.6.1...v1.7.0
[1.6.1]: https://github.com/plandes/deeplearn/compare/v1.6.0...v1.6.1
[1.6.0]: https://github.com/plandes/deeplearn/compare/v1.5.2...v1.6.0
[1.5.2]: https://github.com/plandes/deeplearn/compare/v1.5.1...v1.5.2
[1.5.1]: https://github.com/plandes/deeplearn/compare/v1.5.0...v1.5.1
[1.5.0]: https://github.com/plandes/deeplearn/compare/v1.4.0...v1.5.0
[1.4.0]: https://github.com/plandes/deeplearn/compare/v1.3.0...v1.4.0
[1.3.0]: https://github.com/plandes/deeplearn/compare/v1.2.0...v1.3.0
[1.2.0]: https://github.com/plandes/deeplearn/compare/v1.1.1...v1.2.0
[1.1.1]: https://github.com/plandes/deeplearn/compare/v1.1.0...v1.1.1
[1.1.0]: https://github.com/plandes/deeplearn/compare/v1.0.0...v1.1.0
[1.0.0]: https://github.com/plandes/deeplearn/compare/v0.1.8...v1.0.0
[0.1.8]: https://github.com/plandes/deeplearn/compare/v0.1.7...v0.1.8
[0.1.7]: https://github.com/plandes/deeplearn/compare/v0.1.6...v0.1.7
[0.1.6]: https://github.com/plandes/deeplearn/compare/v0.1.5...v0.1.6
[0.1.5]: https://github.com/plandes/deeplearn/compare/v0.1.4...v0.1.5
[0.1.4]: https://github.com/plandes/deeplearn/compare/v0.1.3...v0.1.4
[0.1.3]: https://github.com/plandes/deeplearn/compare/v0.1.2...v0.1.3
[0.1.2]: https://github.com/plandes/deeplearn/compare/v0.1.1...v0.1.2
[0.1.1]: https://github.com/plandes/deeplearn/compare/v0.1.0...v0.1.1
[0.1.0]: https://github.com/plandes/deeplearn/compare/v0.0.6...v0.1.0
[0.0.6]: https://github.com/plandes/deeplearn/compare/v0.0.5...v0.0.6
[0.0.5]: https://github.com/plandes/deeplearn/compare/v0.0.4...v0.0.5
[0.0.4]: https://github.com/plandes/deeplearn/compare/v0.0.3...v0.0.6
[0.0.3]: https://github.com/plandes/deeplearn/compare/v0.0.2...v0.0.3
[0.0.2]: https://github.com/plandes/deeplearn/compare/v0.0.1...v0.0.2
[0.0.1]: https://github.com/plandes/deeplearn/compare/v0.0.0...v0.0.1

[zensols.actioncli]: https://github.com/plandes/actioncli
[zensols.util]: https://github.com/plandes/util
[zensols.datdesc]: https://github.com/plandes/datdesc
[documentation]: https://plandes.github.io/deeplearn/
[scipy]: https://scipy.org