keras
https://github.com/keras-team/keras
Python
Deep Learning for humans
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- Issues
- Use JAX's AbstractMesh in distribution lib
- Unable to see any speedup from multi-GPU training using JAX backend for LSTM / GRU
- Output discrepancy between keras.predict and tf_saved_model
- BlackDuck reports arbitrary file write vulnerability in "get_file" function
- JAX Backend: Convolutional Layer Kernel Deleted During Training with RematScope
- InvalidArgumentError: RaggedTensorToTensor Error in YOLOv8 Training with EvaluateCOCOMetricsCallback
- TF+XLA+Mixed Precision: Keras fails to compute gradients
- Torch-cuda backend fails to recover after assertion failed
- pytorch backend lstm very +10x slow (maybe batch size with pytorch backend has different semantics than the traditional Keras semantics?)
- LSTM layer doesn't learn with TextVectorization output (padding ?)
- Docs
- Python not yet supported