[Frontend][Tensorflow] SelectV2 and BroadcastArgs op support for tf2 models #7901
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rohanmukh
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Apr 21, 2021
| out.appendleft(s1[s1_size - i]) | ||
| if s1_size < s0_size: | ||
| for i in range(s1_size + 1, s0_size + 1): | ||
| out.appendleft(s0[s0_size - i]) |
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Is it better to use itertools.zip_longest() on the reversed array instead of running three separate loops? Might be helpful to have fill_values set at 1 to avoid handling None values.
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This will require atleast two list inversions (both the inputs as we have to iterate in reverse to verify broadcasting rules). Fill values will only make sense if I use a zip. It is only two loops (one of last two will fail) and merging them to one will give marginal optimization.
rohanmukh
reviewed
Apr 21, 2021
comaniac
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Apr 23, 2021
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Please revert the change of updating submodules.
Also cc @yongwww @kevinthesun @zhiics
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Thanks @srinidhigoud @rohanmukh |
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Adding support in tf parser for new ops SelectV2 and BroadcastArgs introduced by tf2. This is focused on compiling and running the tf2 version of the object detection models such as faster rcnn model. Since both the inputs to BroadcastArgs were constant for every instance of the op in the model there was no need to write a relay op.