Add Pad operator #1180
Add Pad operator #1180
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Signed-off-by: Serge Panev <spanev@nvidia.com>
Signed-off-by: Serge Panev <spanev@nvidia.com>
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| const auto &input = ws.Input<GPUBackend>(0); | ||
| auto &output = ws.Output<GPUBackend>(0); | ||
| std::size_t number_of_axes = input.shape().sample_dim(); | ||
| DALI_TYPE_SWITCH_WITH_FP16(input.type().id(), DataType, |
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Not for now, but it may be worth it to only switch over type's size, copy the pad value to some opaque buffer and run the function on a type-erased buffer. This would reduce the number of switch cases to just 4: 1,2,4,8 bytes.
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| std::vector<Arguments> basic_args = {{{"fill_value", -1.0f}, {"axes", std::vector<int>{0}}}}; | ||
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| std::vector<Arguments> two_d_args = {{{"fill_value", 42.0f}, {"axes", std::vector<int>{1}}}}; |
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At least manually run a test which tests multiple, but not all axes.
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Signed-off-by: Serge Panev <spanev@nvidia.com>
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Why we need this PR?
We need an operator to pad batches of non-uniform shape elements.
A use case would be padding the bboxes batch in detections models (as YOLOv3) where the number of bboxes per sample varies.
What happened in this PR?
We can reuse the
SliceFlipNormalizePermutePadCUDA kernel and provide an easy interface to use it through thePadoperator for the GPU (CPU to be implemented).Add Pad DALI Kernel, Pad operator and Pad unit tests
The
Padkernel implementation.It is tested with unit tests in
dali/pipeline/operators/util/pad_test.ccYes, adding the docstring for the operator