cb2e651800
For convolution, the input window dimension's access affine map is of the form `(d0 * s0 + d1)`, where `d0`/`d1` is the output/ filter window dimension, and `s0` is the stride. When tiling, https://reviews.llvm.org/D109267 changed how the way dimensions are acquired. Instead of directly querying using `*.dim` ops on the original convolution op, we now get it by applying the access affine map to the loop upper bounds. This is fine for dimensions having single-dimension affine maps, like matmul, but not for convolution input. It will cause incorrect compuation and out of bound. A concrete example, say we have 1x225x225x3 (NHWC) input, 3x3x3x32 (HWCF) filter, and 1x112x112x3 (NHWC) output with stride 2, (112 * 2 + 3) would be 227, which is different from the correct input window dimension size 225. Instead, we should first calculate the max indices for each loop, and apply the affine map to them, and then plus one to get the dimension size. Note this makes no difference for matmul-like ops given they will have `d0 - 1 + 1` effectively. Reviewed By: nicolasvasilache Differential Revision: https://reviews.llvm.org/D110849 |
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Multi-Level Intermediate Representation
See https://mlir.llvm.org/ for more information.