[Mlir-commits] [mlir] [MLIR] Allowing unsupported conv2d op to fail gracefully from vectorization (PR #130181)

[Zhuoran Yin]

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@@ -1990,8 +1990,18 @@ static LogicalResult vectorizeLinalgOpPrecondition(
   // TODO: isaConvolutionOpInterface that can also infer from generic
   // features. But we will still need stride/dilation attributes that will be
   // annoying to reverse-engineer...
-  if (isa<ConvolutionOpInterface>(linalgOp.getOperation()))
+  if (isa<ConvolutionOpInterface>(linalgOp.getOperation())) {
+    // Check if it is 2d+ convolution. If it is, return failure because we don't
+    // support it. To use this pass on a 2d+ convolution, it should have already
+    // been decomposed to 1d convolution via
+    // DecomposeConvolutionToLowerDimOpsPass.
+    if (linalgOp.getNumParallelLoops() >= 4) {
+      LDBG("precondition failed: Regular 2d+ convolutions not supported.\n");
+      return failure();
+    }
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jerryyin wrote:

That sounds like a decent refactor. `Conv1DGenerator`'s constructor indeed is a more robust check compared with `getNumParallelLoops()`. Thanks for the pointers!

https://github.com/llvm/llvm-project/pull/130181