Comments (1)
Keras was written with Python 2.7 in mind. But I would expect 2to3 to be enough for use with Python 3.
I'll update the README.md with the Python version.
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Related Issues (20)
- [Feature request] When using PyTorch backend, use torch.data.tensorboard in keras.callbacks.TensorBoard HOT 2
- [Bug] With TensorFlow backend, using PyTorch DataLoader with different per-batch size does not work. HOT 5
- Incorrect error message given for named inputs when unnamed input provided to fit() HOT 1
- ExportArchive.track() adds unwanted empty variable collections
- model.export on JAX saves all model weights as constants embedded in the graph HOT 4
- ExportArchive cannot be used with JAX HOT 4
- Spectral normalization raises OperatorNotAllowedInGraphError HOT 6
- TypeError: Cannot serialize object Ellipsis of type <class 'ellipsis'> HOT 7
- merging deep learning models HOT 6
- Keras 3.0 AttributeError: keras.backend has no set_value() or get_value() HOT 4
- Tendorflow metric per class issue HOT 4
- ValueError: No gradients provided for any variable: HOT 3
- loading layers with lambda in from .h5 files HOT 17
- Change keras.Model inheritance for improved static analysis support
- Bug in UpSampling2D with channels_first and Torch backend HOT 4
- Incompatibility in 'tf.GradientTape.watch' of TensorFlow 2.15 in Keras 3.0 HOT 4
- TorchDataLoaderAdapter is not compatible with torch.utils.data.IterableDataset (no __len__() dataset) HOT 3
- multi-output logs HOT 3
- enable_lora() API introduces new weights with a different path than other model weights HOT 3
- oserror:unable to open file (file signature not found ) HOT 4
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