Add support for positions array in keras_nlp.layers.RotaryEmbedding layer
#1571
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mattdangerw
reviewed
Apr 10, 2024
| tensor = ops.cast(positions, dtype="float32") | ||
| else: | ||
| seq_len = ops.shape(inputs)[sequence_axis] | ||
| tensor = ops.arange(seq_len, dtype="float32") + start_index |
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Let's move this branch into it's own sub function?
That might make it easier to try overriding.
if positions is None:
positions = self._compute_positions(inputs, start_index=0)
else:
positions = ops.cast(positions, dtype="float32")There was a problem hiding this comment.
Since we are renaming the tensor var to positions, we can simply remove the else statement. Did that in the latest commit, let me know if it looks good!
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I would actually keep the self._compute_positions over-ridable method for a somewhat hacky reason. Since we don't have great "layer wrappinig" or generation mutation functionality right now, this allows for a patch on the layer itself that would control this computation.
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Adds support for a
positionsarray in our RotaryEmbedding layer. This is useful when non-arange positions arrays are required like the one used in this paper.