Comments (5)
fchollet
commented on May 29, 2024
1
Not yet, but we want to add this feature. Here's a related issue: keras-team/keras#18403
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emi-dm
commented on May 29, 2024
It would be great!!! Thanks @fchollet :)
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emi-dm
commented on May 29, 2024
Hi everyone!!! Here is a colab for reproduce the issue: https://colab.research.google.com/drive/1kFQ4_2qPlHm4P63Qb2ry-lC0OQ_zY0RJ?usp=sharing
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emi-dm
commented on May 29, 2024
@fchollet I thought maybe you could make a class wrapper that wraps the base class of torch.nn to implement the get_config and from_config methods, so that you could serialize. I don't have much knowledge of the internal implementation of Keras and I don't know if I could...
Thanks in advanced guys!
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qlzh727
commented on May 29, 2024
Closing this as a duplication against keras-team/keras#18403. we will track the fix there.
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Related Issues (20)
- tflite cannot fuse `BatchNormalization` in Keras Core as effectively as in the original Keras
- Improve Documentation on KERAS_BACKEND HOT 5
- How can we use `ops.reshape` when the `new_shape` is obtained from `ops.shape`? HOT 3
- GSOC Program Organization ( question ) HOT 1
- Constant Initializer supports only Scalar values HOT 1
- Add support for RaggedTensors to JAX and Pytorch Backend HOT 1
- Saving broken between tf.keras and Keras Core HOT 9
- Ensure workflow reliability by hash-pinning GitHub Actions HOT 1
- Run actions.yml with read-only permissions
- Segmentation metrics HOT 3
- Use of PyTorch loss functions inside Keras
- Expose `Operation` without `src` import hacks HOT 1
- v0.1.6 bug: AttributeError: 'GPT2CausalLM' object has no attribute 'compiled' HOT 2
- Adam with amsgrad=True + JAX backend is broken HOT 1
- Inconsistent type handling between backends HOT 1
- Matmul - tensorflow does not broadcast/expand dimensions correctly HOT 3
- Casting dtype in losses.Loss base class HOT 2
- TypeError: copy() got an unexpected keyword argument 'overwrite' HOT 2
- Error when running the model.fit on the wrapped model "Only input tensors may be passed as positional arguments."
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