keras
https://github.com/keras-team/keras
Python
Deep Learning for humans
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- Issues
- `keras.ops.roll` rejects tensor `shift`/`axis` on the TensorFlow backend
- Fix resize size check for NumPy integers
- Handle dynamic-shape tensors in pad_sequences inside tf.function
- Fix RandomShear config round trip for float factors
- `Distiller.fit()` executes student model twice per step, causing duplicate BatchNorm updates and mismatched Dropout masks
- Handle negative and out-of-range indices in `ops.split`
- Fix Hashing one-hot output shape
- Hashing with output_mode="one_hot" gives the wrong output shape when the last axis isn't 1
- Torch backend: `ops.take` and `ops.take_along_axis` with `axis=None` mishandle negative indices for inputs with more than one dimension
- RandomShear with float factors cannot be loaded from its own config
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