Notify failure during torch-to-tosa when AtenEmptyMemoryFormat receives a tensor with a dimension of size zero (#4353)

The lowering for `torch.aten.empty.memory_format` produces a
non-conformant `tosa.const` when the output `!torch.vtensor` has a
zero-sized dimension. This fix detects this case and reports a failure,
preventing the generation of invalid IR. This issue was first observed
in the SAM2 image predictor model.

Co-authored-by: Hariprasad Ravishankar <[email protected]>

Author: hariprasadravi

lib/Conversion/TorchToTosa/TorchToTosa.cpp

@@ -6435,6 +6435,11 @@ class ConvertAtenConstPatternOp : public OpConversionPattern<AtenOpT> {
     for (auto s : shape)
       size *= s;
 
+    if (size == 0) {
+      return rewriter.notifyMatchFailure(
+          op, "Shape must not have a dimension of size zero");
+    }
+
     SmallVector<int32_t> values(size, fillVal);
     auto constOp =
         tosa::getConstTensor<int32_t>(rewriter, op, values, shape).value();

test/Conversion/TorchToTosa/basic.mlir

@@ -4370,3 +4370,17 @@ func.func @torch.aten.linear$f16(%arg0: !torch.vtensor<[2,4],f16>, %arg1: !torch
   %0 = torch.aten.linear %arg0, %arg1, %arg2 : !torch.vtensor<[2,4],f16>, !torch.vtensor<[3,4],f16>, !torch.vtensor<[3],f16> -> !torch.vtensor<[2,3],f16>
   return %0 : !torch.vtensor<[2,3],f16>
 }
+
+// -----
+func.func @torch.aten.empty.memory_format() -> !torch.vtensor<[1,0,256],f32>{
+    %c1 = torch.constant.int 1
+    %c0 = torch.constant.int 0
+    %c256 = torch.constant.int 256
+    %2452 = torch.prim.ListConstruct %c1, %c0, %c256 : (!torch.int, !torch.int, !torch.int) -> !torch.list<int>
+    %none = torch.constant.none
+    %cpu = torch.constant.device "cpu"
+    %false = torch.constant.bool false
+    // expected-error @below {{failed to legalize operation 'torch.aten.empty.memory_format' that was explicitly marked illegal}}
+    %out = torch.aten.empty.memory_format %2452, %none, %none, %cpu, %false, %none : !torch.list<int>, !torch.none, !torch.none, !torch.Device, !torch.bool, !torch.none -> !torch.vtensor<[1,0,256],f32>
+    return %out : !torch.vtensor<[1,0,256],f32>
+}