Comments (3)
Have you successfully run the linked notebook from README end to end? I don't have any issues with using the metric as documented.
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@DieseKartoffel Have you encountered this error again? If yes, can you share a reproducible end to end (toy) example? I can't reproduce this error either locally in notebook or in unit tests: https://github.com/ck37/coral-ordinal/blob/master/coral_ordinal/tests/test_metrics.py
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Will close this for now since not reproducible locally or in unit test. @DieseKartoffel Reopen if this is still an issue for you on latest dev branch.
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Related Issues (19)
- AttributeError: module 'tensorflow.python.ops' has no attribute 'convert_to_tensor_v2' HOT 5
- OrdinalCrossEntropy should not require `num_classes`; can be inferred from `y_pred`
- OrdinalCrossEntropy does not use `reduction` argument
- Implement CORN loss for logit outputs
- Add option to pass kernel_* and bias_* regularizers to Coral layer HOT 3
- Drop 'units' from get_config() in CornLayer to enable serialization
- Can you provide an example for functional API? HOT 2
- How to have an output of the CoralOrdinal layer to be a single integer of predicted class? HOT 1
- Turning a multi-class classification into ordinal regression HOT 2
- coral-ordinal consistently predicts only 0 in classification task
- Using corn loss with existing ordinal regression task.
- Class weights and coral.OrdinalCrossEntropy()
- InvalidArgumentError: Dimension -1 must be >=0
- Unsupported upperand error when using OrdinalCrossEntropy HOT 4
- bug in Colab notebook's MNIST example HOT 1
- Usage for segmentation HOT 1
- What is the recommended way to handle imbalanced data? HOT 1
- Loss function pug HOT 1
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