fix matmul rewriting/lowering

fix reshape lowering
add support for grouped-convolution lowering
quieter verifier with capped error messages

src/PIM/Conversion/ONNXToSpatial/Patterns/Tensor/Reshape.cpp

@@ -80,6 +80,22 @@ static bool inferExpandReassociation(ArrayRef<int64_t> sourceShape,
   return sourceIdx == sourceShape.size() && resultIdx == resultShape.size();
 }
 
+static SmallVector<ReassociationIndices> getCollapseTo1DReassociation(size_t rank) {
+  SmallVector<ReassociationIndices> reassociation(1);
+  reassociation.front().reserve(rank);
+  for (size_t dim = 0; dim < rank; ++dim)
+    reassociation.front().push_back(static_cast<int64_t>(dim));
+  return reassociation;
+}
+
+static SmallVector<ReassociationIndices> getExpandFrom1DReassociation(size_t rank) {
+  SmallVector<ReassociationIndices> reassociation(1);
+  reassociation.front().reserve(rank);
+  for (size_t dim = 0; dim < rank; ++dim)
+    reassociation.front().push_back(static_cast<int64_t>(dim));
+  return reassociation;
+}
+
 struct Reshape : OpConversionPattern<ONNXReshapeOp> {
   using OpConversionPattern::OpConversionPattern;
 
@@ -126,6 +142,23 @@ struct Reshape : OpConversionPattern<ONNXReshapeOp> {
         return tensor::ExpandShapeOp::create(rewriter, reshapeOp.getLoc(), resultType, data, reassociation);
       });
 
+    if (sourceType.getNumElements() != resultType.getNumElements())
+      return failure();
+
+    return replaceWithReshape([&](Value data) -> Value {
+      Value reshaped = data;
+      if (sourceType.getRank() != 1) {
+        auto flatType = RankedTensorType::get({sourceType.getNumElements()}, sourceType.getElementType());
+        reshaped = tensor::CollapseShapeOp::create(
+          rewriter, reshapeOp.getLoc(), flatType, reshaped, getCollapseTo1DReassociation(sourceType.getRank()));
+      }
+      if (resultType.getRank() == 1)
+        return reshaped;
+      return tensor::ExpandShapeOp::create(
+               rewriter, reshapeOp.getLoc(), resultType, reshaped, getExpandFrom1DReassociation(resultType.getRank()))
+        .getResult();
+    });
+
     return failure();
   }
 };