keras
https://github.com/keras-team/keras
Python
Deep Learning for humans
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- Issues
- OpenVINO backend: ops return wrong values or fail (scalar operands in the wrong element type, three CPU-plugin bugs, shape bugs)
- Backend kernels do not follow the op spec: ignored `dtype` arguments, rejected index dtypes, wrong output structure
- Layer.__delattr__ does not untrack sub-layers
- Ensure categorical and sparse categorical crossentropy return output dtype
- pearson_correlation has no zero-variance guard, unlike concordance_correlation in the same file
- `categorical_crossentropy` and `sparse_categorical_crossentropy` do not return the dtype of `output`
- Resolve weak float to bfloat16 under bfloat16 floatx
- Integer and bool inputs give wrong values in several activations, with no error
- torch: float64 `Dense` returns float32 since #23225, and float64 handling on torch is inconsistent
- rms_normalization and layer_normalization truncate integer and bool inputs to the input dtype
- Docs
- Python not yet supported