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Description
This fix handles the edge case of flattening a batch of zero size. It is a good quality metric for a software function to be able to handle zero data input even if the calling function could detect this case and create a fake expected output (that was my work-around before).
Before this fix, this exception would have been thrown:
Caused by: ai.djl.engine.EngineException: cannot reshape tensor of 0 elements into shape [0, -1] because the unspecified dimension size -1 can be any value and is ambiguous
at ai.djl.pytorch.jni.PyTorchLibrary.torchReshape(Native Method)