keras
https://github.com/keras-team/keras
Python
Deep Learning for humans
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- Issues
- `mixed_bfloat16` in TPU is slower than `float32`
- Passing inputs to a sequential model in a custom training step called with fit to calculate loss fails - requires a layer redefinition
- Layer does not have a default tensorflow namespace; requires passing `initial_value` in lambda function
- `keras_core/trainers/trainers_test.py` wrong result on fit (graph mode + no XLA + TF backend)
- Rescaling layer defaults to "float32" if dtype not specified - input is uint8
- Compatibility Matrix for GPU based workflow
- Torch backend planning
- DTensor support in TF backend
- Jax Error with Stochastic Depth
- does Functional Model support "string" dtype for end-to-end pipelines?
- Docs
- Python not yet supported