mirror of https://github.com/llvm/torch-mlir
aca33f1742
I've upstreamed the necessary quantized linalg Op with the "channel-first" ordering used by torch (https://github.com/llvm/llvm-project/pull/107740) for 2d convolution. This patch changes the lowering for the quantized 2d case of `aten.convolution` accordingly, which saves three transpositions per convolution (input, weights, result) and therefore removes the requirement to try to optimize these away in downstream passes. |
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| .. | ||
| basic.mlir | ||
| broadcast.mlir | ||
| convolution.mlir | ||
| elementwise.mlir | ||
| embeddingBag.mlir | ||
| flatten.mlir | ||
| gridsampler.mlir | ||
| pooling.mlir | ||
| resize.mlir | ||
| sparse.mlir | ||
| squeeze.mlir | ||
| unsqueeze.mlir | ||
| view.mlir | ||
| view_strict.mlir | ||