Ktrain

new:
- N/A

changed
- N/A

fixed:
- Changed NMF to accept optional parameters `nmf_alpha_W` and `nmf_alpha_H` based on changes in `scikit-learn==1.2.0`.
- Change `ktrain.utils` to check for TensorFlow before doing a version check, so that **ktrain** can be imported without TensorFlow being installed.

new:
- N/A

changed
- N/A

fixed:
- In TensorFlow 2.11, the `tf.optimizers.Optimizer` base class points the new keras optimizer that seems to have problems. Users should use legacy optimizers in `tf.keras.optimizers.legacy` with **ktrain** (which evidently will never be deleted). This means that, in TF 2.11, supplying a string representation of an optimizer like `"adam"` to `model.compile` uses the new optimizer instead of the legacy optimizers. In these cases, **ktrain** will issue a warning and automatically recompile the model with the default `tf.keras.optimizers.legacy.Adam` optimizer.

new:
- Support for TensorFlow 2.11. For now, as recommended in the [TF release notes](https://github.com/tensorflow/tensorflow/releases/tag/v2.11.0), **ktrain** has been changed to use the legacy optimizers in `tf.keras.optimizers.legacy`. This means that, when compiling Keras models, you should supply `tf.keras.optimizers.legacy.Adam()` instead of the string `"adam"`.
- Support for Python 3.10. Changed references from `CountVectorizer.get_field_names` to `CountVectorizer.get_field_names_out`. Updated supported versions in `setup.py`.

changed
- N/A

fixed:
- fixed error in docs

new:
- N/A

changed
- N/A

fixed:
- Adjusted tika imports due to issue with `/tmp/tika.log` in multi-user scenario

new:
- N/A

changed
- N/A

fixed:
- Adjustment for kwe
- Fixed problem with importing `ktrain` without TensorFlow installed

new:
- N/A

changed
- N/A

fixed:
- Fixed paragraph tokenization in `AnswerExtractor`