Fix Bug in Bilinear Interpolation and Add Deform Conv to PT FrontEnd #7397
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cc @vinx13 |
vinx13
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Feb 5, 2021
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Thanks @codeislife99 @vinx13 This is merged |
alexwong
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…pache#7397) * Fix Bug in Bilinear Interpolation * Add NHWC Tests * clean * Fix Bug and Add Deformable Conv PyTorch for completeness * Add Tensor Utils * Remove stuff * Include vector * PR Comments * Empty Commit for CI Co-authored-by: Ubuntu <[email protected]>
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…pache#7397) * Fix Bug in Bilinear Interpolation * Add NHWC Tests * clean * Fix Bug and Add Deformable Conv PyTorch for completeness * Add Tensor Utils * Remove stuff * Include vector * PR Comments * Empty Commit for CI Co-authored-by: Ubuntu <[email protected]>
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Mar 2, 2021
…pache#7397) * Fix Bug in Bilinear Interpolation * Add NHWC Tests * clean * Fix Bug and Add Deformable Conv PyTorch for completeness * Add Tensor Utils * Remove stuff * Include vector * PR Comments * Empty Commit for CI Co-authored-by: Ubuntu <[email protected]>
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This PR adds deform_conv to PT Frontend. It also fixes a bug in bilinear interpolation which was causing wrong output with deformable convolutions from PT framework. The "bug" occurs when one or more the interpolation index(y, x) is outside one or more of the boundary points
(y_max, x_max), but within(y_max + 1, x_max + 1). In the current implementation both interpolation source points are on the boundary even if the point is closer to one or more of(y_max+1, x_max+1). In the corrected version, the first point is on the boundary and the second point value is 0 which is more logically sound and matches with how frameworks have implemented it.PS : It might seem that this is a corner case, but it really changes the accuracy by a lot
For e.g: Without this change , the relative and absolute tolerances are around 1 and 1e-2 with tolerances being more than 1e-2 for 25-40% of the output elements in deformable convolution.
Since ROI align is dependent on this change, I have made the corresponding necessary changes in ROIAlign and verified that it works like before as expected.