[Relay, TOPI] Support dynamic slicing on first few axes, keeping the rest static#8068
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masahi merged 6 commits intoapache:mainfrom May 20, 2021
Merged
[Relay, TOPI] Support dynamic slicing on first few axes, keeping the rest static#8068masahi merged 6 commits intoapache:mainfrom
masahi merged 6 commits intoapache:mainfrom
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masahi
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May 18, 2021
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| @tvm.testing.uses_gpu | ||
| def test_dynamic_strided_slice(): | ||
| def verify(dshape, begin, end, strides, output, slice_mode="end", test_ref=True, dtype="int32"): |
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output is not used in the test, so I removed it.
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This looks good to me. Do we need to do anything to support this behavior in the standard strided slice op? |
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No, I believe it is already supported, although the static version doesn't have a constraint that (No idea why CI is running another job, it already passed). |
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thanks @mbrookhart |
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Jun 17, 2021
…rest static (apache#8068) * Supporting dynamic slice on first few axes * fix index normalization * update dynamic slice tests * pylint fix * fix loop index dtype * fix more dtype issue
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…rest static (apache#8068) * Supporting dynamic slice on first few axes * fix index normalization * update dynamic slice tests * pylint fix * fix loop index dtype * fix more dtype issue
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This PR relaxes the constraint that
begin,endandstridesparams of dynamic strided slice to have the same length as input rank, and enable slicing on only first few axes (in particular, slicing along batch dim only).For example, the output shape of ONNX NMS is
(num_detection, 3). However, when translated to relay, it becomes(?, ?), since current dynamic stride slice always slices on all axes, even if some axes are conceptually static. This posed a problem whenGatherNDis applied to the output of ONNX NMS, since it requires the second dimension to be static:tvm/src/relay/op/tensor/transform.cc
Lines 3348 to 3349 in c999a84
ready for review @mbrookhart @jwfromm @kevinthesun @yongwww