What happened to the tensorflow.keras package?
Nadie ha tomado este issue todavía.
- Lenguaje dominante
- Java
- Estrellas
- 928
- Forks
- 227
- Métricas de merge de PR
- Sin PR fusionados en 30 d
Descripción
Please make sure that this is a feature request. As per our GitHub Policy, we only address code/doc bugs, performance issues, feature requests and build/installation issues on GitHub. tag:feature_template
System information
- TensorFlow version (you are using):
- Are you willing to contribute it (Yes/No):
TF 2.3.1
Yes, if able
Describe the feature and the current behavior/state.
There used to be a separate repo tensorflow-keras. That page said the worked got merged into this. Yet, I don't see a org.tensorflow.keras package and my ide complains when I try to access stuff from it. I want to be able to, at a minimum, load models from Keras. But yes, it would also be nice to create models on the Java side as well.
Will this change the current api? How?
I suppose so because I do not see a org.tensorflow.keras package currently.
Who will benefit with this feature?
Everyone who is already familiar with Keras. But also those newer to deep learning as well because Keras is higher level and easier to use than vanilla tensorflow.
Any Other info.
If there have been massive conversations and decisions made behind the scenes, I would hope that at least the README.md is updated to say the level of support, if any, for Keras and why that decision was made so that people aren't scratching their heads.
Guía de contribución
Primeros pasos
- Lee el issue completo y luego la guía de contribución del proyecto.
- Comenta en el issue que vas a ocuparte — evita que dos personas hagan lo mismo.
- Haz un fork del repositorio y trabaja en una rama.
- Abre un pull request que haga referencia al número del issue.
Línea de trabajo
Empieza revisando el historial del repositorio tensorflow-keras y la API de Java relacionada con el paquete solicitado org.tensorflow.keras. Revisa README.md para conocer el nivel actual de compatibilidad con Keras y determina si el objetivo es la carga de modelos, la creación de modelos desde Java o ambas cosas; «done» debe definirse como una decisión de compatibilidad documentada o como un alcance de funcionalidad completo.
Escrito por el modelo de indexación a partir del texto del issue.
Evaluación
- Stack tecnológico
- java, tensorflow
- Área
- machine-learning
- Tipo de issue
- Nueva funcionalidad
- Dificultad
- 5/5
- Tiempo estimado
- Más de una semana
- Estado de actividad
- Estancado
- Claridad
- Necesita aclaración
- Aptitud para principiantes
- 25/100