[Mlir-commits] [mlir] [mlir][draft] Support 1:N dialect conversion (PR #112141)

Matthias Springer llvmlistbot at llvm.org
Sun Oct 27 21:31:52 PDT 2024


https://github.com/matthias-springer updated https://github.com/llvm/llvm-project/pull/112141

>From 6cd79796eca875feebbed5fdb5dea0de93b8b38d Mon Sep 17 00:00:00 2001
From: Matthias Springer <mspringer at nvidia.com>
Date: Sat, 5 Oct 2024 17:29:12 +0200
Subject: [PATCH 1/3] [WIP] 1:N conversion pattern

---
 mlir/artifacts/jq-linux64                     | Bin 0 -> 3953824 bytes
 .../mlir/Conversion/LLVMCommon/Pattern.h      |  35 +++++++++--
 .../mlir/Transforms/DialectConversion.h       |  57 ++++++++++++++++++
 .../Transforms/Utils/DialectConversion.cpp    |  45 ++++++++++----
 4 files changed, 122 insertions(+), 15 deletions(-)
 create mode 100755 mlir/artifacts/jq-linux64

diff --git a/mlir/artifacts/jq-linux64 b/mlir/artifacts/jq-linux64
new file mode 100755
index 0000000000000000000000000000000000000000..f48b0ca92144ffdf18a2a142c295fa8f547dcca7
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HcmV?d00001

diff --git a/mlir/include/mlir/Conversion/LLVMCommon/Pattern.h b/mlir/include/mlir/Conversion/LLVMCommon/Pattern.h
index f3bf5b66398e09..6751c3ef2eca95 100644
--- a/mlir/include/mlir/Conversion/LLVMCommon/Pattern.h
+++ b/mlir/include/mlir/Conversion/LLVMCommon/Pattern.h
@@ -143,6 +143,8 @@ template <typename SourceOp>
 class ConvertOpToLLVMPattern : public ConvertToLLVMPattern {
 public:
   using OpAdaptor = typename SourceOp::Adaptor;
+  using OneToNOpAdaptor =
+      typename SourceOp::template GenericAdaptor<ArrayRef<ArrayRef<Value>>>;
 
   explicit ConvertOpToLLVMPattern(const LLVMTypeConverter &typeConverter,
                                   PatternBenefit benefit = 1)
@@ -153,8 +155,13 @@ class ConvertOpToLLVMPattern : public ConvertToLLVMPattern {
   /// Wrappers around the RewritePattern methods that pass the derived op type.
   void rewrite(Operation *op, ArrayRef<Value> operands,
                ConversionPatternRewriter &rewriter) const final {
-    rewrite(cast<SourceOp>(op), OpAdaptor(operands, cast<SourceOp>(op)),
-            rewriter);
+    auto sourceOp = cast<SourceOp>(op);
+    rewrite(sourceOp, OpAdaptor(operands, sourceOp), rewriter);
+  }
+  void rewrite(Operation *op, ArrayRef<ArrayRef<Value>> operands,
+               ConversionPatternRewriter &rewriter) const final {
+    auto sourceOp = cast<SourceOp>(op);
+    rewrite(sourceOp, OneToNOpAdaptor(operands, sourceOp), rewriter);
   }
   LogicalResult match(Operation *op) const final {
     return match(cast<SourceOp>(op));
@@ -162,8 +169,15 @@ class ConvertOpToLLVMPattern : public ConvertToLLVMPattern {
   LogicalResult
   matchAndRewrite(Operation *op, ArrayRef<Value> operands,
                   ConversionPatternRewriter &rewriter) const final {
-    return matchAndRewrite(cast<SourceOp>(op),
-                           OpAdaptor(operands, cast<SourceOp>(op)), rewriter);
+    auto sourceOp = cast<SourceOp>(op);
+    return matchAndRewrite(sourceOp, OpAdaptor(operands, sourceOp), rewriter);
+  }
+  LogicalResult
+  matchAndRewrite(Operation *op, ArrayRef<ArrayRef<Value>> operands,
+                  ConversionPatternRewriter &rewriter) const final {
+    auto sourceOp = cast<SourceOp>(op);
+    return matchAndRewrite(sourceOp, OneToNOpAdaptor(operands, sourceOp),
+                           rewriter);
   }
 
   /// Rewrite and Match methods that operate on the SourceOp type. These must be
@@ -175,6 +189,12 @@ class ConvertOpToLLVMPattern : public ConvertToLLVMPattern {
                        ConversionPatternRewriter &rewriter) const {
     llvm_unreachable("must override rewrite or matchAndRewrite");
   }
+  virtual void rewrite(SourceOp op, OneToNOpAdaptor adaptor,
+                       ConversionPatternRewriter &rewriter) const {
+    SmallVector<Value> oneToOneOperands =
+        getOneToOneAdaptorOperands(adaptor.getOperands());
+    rewrite(op, OpAdaptor(oneToOneOperands, adaptor), rewriter);
+  }
   virtual LogicalResult
   matchAndRewrite(SourceOp op, OpAdaptor adaptor,
                   ConversionPatternRewriter &rewriter) const {
@@ -183,6 +203,13 @@ class ConvertOpToLLVMPattern : public ConvertToLLVMPattern {
     rewrite(op, adaptor, rewriter);
     return success();
   }
+  virtual LogicalResult
+  matchAndRewrite(SourceOp op, OneToNOpAdaptor adaptor,
+                  ConversionPatternRewriter &rewriter) const {
+    SmallVector<Value> oneToOneOperands =
+        getOneToOneAdaptorOperands(adaptor.getOperands());
+    return matchAndRewrite(op, OpAdaptor(oneToOneOperands, adaptor), rewriter);
+  }
 
 private:
   using ConvertToLLVMPattern::match;
diff --git a/mlir/include/mlir/Transforms/DialectConversion.h b/mlir/include/mlir/Transforms/DialectConversion.h
index 5e5957170e646c..9ee681e57e21b7 100644
--- a/mlir/include/mlir/Transforms/DialectConversion.h
+++ b/mlir/include/mlir/Transforms/DialectConversion.h
@@ -537,6 +537,10 @@ class ConversionPattern : public RewritePattern {
                        ConversionPatternRewriter &rewriter) const {
     llvm_unreachable("unimplemented rewrite");
   }
+  virtual void rewrite(Operation *op, ArrayRef<ArrayRef<Value>> operands,
+                       ConversionPatternRewriter &rewriter) const {
+    rewrite(op, getOneToOneAdaptorOperands(operands), rewriter);
+  }
 
   /// Hook for derived classes to implement combined matching and rewriting.
   virtual LogicalResult
@@ -547,6 +551,11 @@ class ConversionPattern : public RewritePattern {
     rewrite(op, operands, rewriter);
     return success();
   }
+  virtual LogicalResult
+  matchAndRewrite(Operation *op, ArrayRef<ArrayRef<Value>> operands,
+                  ConversionPatternRewriter &rewriter) const {
+    return matchAndRewrite(op, getOneToOneAdaptorOperands(operands), rewriter);
+  }
 
   /// Attempt to match and rewrite the IR root at the specified operation.
   LogicalResult matchAndRewrite(Operation *op,
@@ -574,6 +583,9 @@ class ConversionPattern : public RewritePattern {
       : RewritePattern(std::forward<Args>(args)...),
         typeConverter(&typeConverter) {}
 
+  static SmallVector<Value>
+  getOneToOneAdaptorOperands(ArrayRef<ArrayRef<Value>> operands);
+
 protected:
   /// An optional type converter for use by this pattern.
   const TypeConverter *typeConverter = nullptr;
@@ -589,6 +601,8 @@ template <typename SourceOp>
 class OpConversionPattern : public ConversionPattern {
 public:
   using OpAdaptor = typename SourceOp::Adaptor;
+  using OneToNOpAdaptor =
+      typename SourceOp::template GenericAdaptor<ArrayRef<ArrayRef<Value>>>;
 
   OpConversionPattern(MLIRContext *context, PatternBenefit benefit = 1)
       : ConversionPattern(SourceOp::getOperationName(), benefit, context) {}
@@ -607,12 +621,24 @@ class OpConversionPattern : public ConversionPattern {
     auto sourceOp = cast<SourceOp>(op);
     rewrite(sourceOp, OpAdaptor(operands, sourceOp), rewriter);
   }
+  void rewrite(Operation *op, ArrayRef<ArrayRef<Value>> operands,
+               ConversionPatternRewriter &rewriter) const final {
+    auto sourceOp = cast<SourceOp>(op);
+    rewrite(sourceOp, OneToNOpAdaptor(operands, sourceOp), rewriter);
+  }
   LogicalResult
   matchAndRewrite(Operation *op, ArrayRef<Value> operands,
                   ConversionPatternRewriter &rewriter) const final {
     auto sourceOp = cast<SourceOp>(op);
     return matchAndRewrite(sourceOp, OpAdaptor(operands, sourceOp), rewriter);
   }
+  LogicalResult
+  matchAndRewrite(Operation *op, ArrayRef<ArrayRef<Value>> operands,
+                  ConversionPatternRewriter &rewriter) const final {
+    auto sourceOp = cast<SourceOp>(op);
+    return matchAndRewrite(sourceOp, OneToNOpAdaptor(operands, sourceOp),
+                           rewriter);
+  }
 
   /// Rewrite and Match methods that operate on the SourceOp type. These must be
   /// overridden by the derived pattern class.
@@ -623,6 +649,12 @@ class OpConversionPattern : public ConversionPattern {
                        ConversionPatternRewriter &rewriter) const {
     llvm_unreachable("must override matchAndRewrite or a rewrite method");
   }
+  virtual void rewrite(SourceOp op, OneToNOpAdaptor adaptor,
+                       ConversionPatternRewriter &rewriter) const {
+    SmallVector<Value> oneToOneOperands =
+        getOneToOneAdaptorOperands(adaptor.getOperands());
+    rewrite(op, OpAdaptor(oneToOneOperands, adaptor), rewriter);
+  }
   virtual LogicalResult
   matchAndRewrite(SourceOp op, OpAdaptor adaptor,
                   ConversionPatternRewriter &rewriter) const {
@@ -631,6 +663,13 @@ class OpConversionPattern : public ConversionPattern {
     rewrite(op, adaptor, rewriter);
     return success();
   }
+  virtual LogicalResult
+  matchAndRewrite(SourceOp op, OneToNOpAdaptor adaptor,
+                  ConversionPatternRewriter &rewriter) const {
+    SmallVector<Value> oneToOneOperands =
+        getOneToOneAdaptorOperands(adaptor.getOperands());
+    return matchAndRewrite(op, OpAdaptor(oneToOneOperands, adaptor), rewriter);
+  }
 
 private:
   using ConversionPattern::matchAndRewrite;
@@ -656,11 +695,20 @@ class OpInterfaceConversionPattern : public ConversionPattern {
                ConversionPatternRewriter &rewriter) const final {
     rewrite(cast<SourceOp>(op), operands, rewriter);
   }
+  void rewrite(Operation *op, ArrayRef<ArrayRef<Value>> operands,
+               ConversionPatternRewriter &rewriter) const final {
+    rewrite(cast<SourceOp>(op), operands, rewriter);
+  }
   LogicalResult
   matchAndRewrite(Operation *op, ArrayRef<Value> operands,
                   ConversionPatternRewriter &rewriter) const final {
     return matchAndRewrite(cast<SourceOp>(op), operands, rewriter);
   }
+  LogicalResult
+  matchAndRewrite(Operation *op, ArrayRef<ArrayRef<Value>> operands,
+                  ConversionPatternRewriter &rewriter) const final {
+    return matchAndRewrite(cast<SourceOp>(op), operands, rewriter);
+  }
 
   /// Rewrite and Match methods that operate on the SourceOp type. These must be
   /// overridden by the derived pattern class.
@@ -668,6 +716,10 @@ class OpInterfaceConversionPattern : public ConversionPattern {
                        ConversionPatternRewriter &rewriter) const {
     llvm_unreachable("must override matchAndRewrite or a rewrite method");
   }
+  virtual void rewrite(SourceOp op, ArrayRef<ArrayRef<Value>> operands,
+                       ConversionPatternRewriter &rewriter) const {
+    rewrite(op, getOneToOneAdaptorOperands(operands), rewriter);
+  }
   virtual LogicalResult
   matchAndRewrite(SourceOp op, ArrayRef<Value> operands,
                   ConversionPatternRewriter &rewriter) const {
@@ -676,6 +728,11 @@ class OpInterfaceConversionPattern : public ConversionPattern {
     rewrite(op, operands, rewriter);
     return success();
   }
+  virtual LogicalResult
+  matchAndRewrite(SourceOp op, ArrayRef<ArrayRef<Value>> operands,
+                  ConversionPatternRewriter &rewriter) const {
+    return matchAndRewrite(op, getOneToOneAdaptorOperands(operands), rewriter);
+  }
 
 private:
   using ConversionPattern::matchAndRewrite;
diff --git a/mlir/lib/Transforms/Utils/DialectConversion.cpp b/mlir/lib/Transforms/Utils/DialectConversion.cpp
index 9f8a482d6e2d22..fcc82f8c2778b6 100644
--- a/mlir/lib/Transforms/Utils/DialectConversion.cpp
+++ b/mlir/lib/Transforms/Utils/DialectConversion.cpp
@@ -776,7 +776,7 @@ struct ConversionPatternRewriterImpl : public RewriterBase::Listener {
   LogicalResult remapValues(StringRef valueDiagTag,
                             std::optional<Location> inputLoc,
                             PatternRewriter &rewriter, ValueRange values,
-                            SmallVectorImpl<Value> &remapped);
+                            SmallVector<SmallVector<Value, 1>> &remapped);
 
   /// Return "true" if the given operation is ignored, and does not need to be
   /// converted.
@@ -1099,7 +1099,7 @@ void ConversionPatternRewriterImpl::undoRewrites(unsigned numRewritesToKeep) {
 LogicalResult ConversionPatternRewriterImpl::remapValues(
     StringRef valueDiagTag, std::optional<Location> inputLoc,
     PatternRewriter &rewriter, ValueRange values,
-    SmallVectorImpl<Value> &remapped) {
+    SmallVector<SmallVector<Value, 1>> &remapped) {
   remapped.reserve(llvm::size(values));
 
   for (const auto &it : llvm::enumerate(values)) {
@@ -1111,7 +1111,7 @@ LogicalResult ConversionPatternRewriterImpl::remapValues(
       // The current pattern does not have a type converter. I.e., it does not
       // distinguish between legal and illegal types. For each operand, simply
       // pass through the most recently mapped value.
-      remapped.push_back(mapping.lookupOrDefault(operand));
+      remapped.push_back({mapping.lookupOrDefault(operand)});
       continue;
     }
 
@@ -1133,7 +1133,7 @@ LogicalResult ConversionPatternRewriterImpl::remapValues(
       // improvements to the `ConversionValueMapping` (to be able to store 1:N
       // mappings) and to the `ConversionPattern` adaptor handling (to be able
       // to pass multiple remapped values for a single operand to the adaptor).
-      remapped.push_back(mapping.lookupOrDefault(operand));
+      remapped.push_back({mapping.lookupOrDefault(operand)});
       continue;
     }
 
@@ -1153,7 +1153,7 @@ LogicalResult ConversionPatternRewriterImpl::remapValues(
       mapping.map(newOperand, castValue);
       newOperand = castValue;
     }
-    remapped.push_back(newOperand);
+    remapped.push_back({newOperand});
   }
   return success();
 }
@@ -1541,11 +1541,12 @@ void ConversionPatternRewriter::replaceUsesOfBlockArgument(BlockArgument from,
 }
 
 Value ConversionPatternRewriter::getRemappedValue(Value key) {
-  SmallVector<Value> remappedValues;
+  SmallVector<SmallVector<Value, 1>> remappedValues;
   if (failed(impl->remapValues("value", /*inputLoc=*/std::nullopt, *this, key,
                                remappedValues)))
     return nullptr;
-  return remappedValues.front();
+  assert(remappedValues.front().size() == 1 && "1:N conversion not supported");
+  return remappedValues.front().front();
 }
 
 LogicalResult
@@ -1553,8 +1554,15 @@ ConversionPatternRewriter::getRemappedValues(ValueRange keys,
                                              SmallVectorImpl<Value> &results) {
   if (keys.empty())
     return success();
-  return impl->remapValues("value", /*inputLoc=*/std::nullopt, *this, keys,
-                           results);
+  SmallVector<SmallVector<Value, 1>> remapped;
+  if (failed(impl->remapValues("value", /*inputLoc=*/std::nullopt, *this, keys,
+                               remapped)))
+    return failure();
+  for (const auto &values : remapped) {
+    assert(values.size() == 1 && "1:N conversion not supported");
+    results.push_back(values.front());
+  }
+  return success();
 }
 
 void ConversionPatternRewriter::inlineBlockBefore(Block *source, Block *dest,
@@ -1648,6 +1656,16 @@ detail::ConversionPatternRewriterImpl &ConversionPatternRewriter::getImpl() {
 // ConversionPattern
 //===----------------------------------------------------------------------===//
 
+SmallVector<Value> ConversionPattern::getOneToOneAdaptorOperands(
+    ArrayRef<ArrayRef<Value>> operands) {
+  SmallVector<Value> oneToOneOperands;
+  oneToOneOperands.reserve(operands.size());
+  for (ArrayRef<Value> operand : operands) {
+    assert(operand.size() == 1 && "pattern does not support 1:N conversion");
+    oneToOneOperands.push_back(operand.front());
+  }
+}
+
 LogicalResult
 ConversionPattern::matchAndRewrite(Operation *op,
                                    PatternRewriter &rewriter) const {
@@ -1659,11 +1677,16 @@ ConversionPattern::matchAndRewrite(Operation *op,
                                              getTypeConverter());
 
   // Remap the operands of the operation.
-  SmallVector<Value, 4> operands;
+  SmallVector<SmallVector<Value, 1>> remapped;
   if (failed(rewriterImpl.remapValues("operand", op->getLoc(), rewriter,
-                                      op->getOperands(), operands))) {
+                                      op->getOperands(), remapped))) {
     return failure();
   }
+  SmallVector<Value, 4> operands;
+  for (const auto &values : remapped) {
+    assert(values.size() == 1 && "1:N conversion not supported");
+    operands.push_back(values.front());
+  }
   return matchAndRewrite(op, operands, dialectRewriter);
 }
 

>From 01ba3d917f1ec4568545b6f3808d9b74be7614f4 Mon Sep 17 00:00:00 2001
From: Matthias Springer <mspringer at nvidia.com>
Date: Sat, 21 Sep 2024 20:03:17 +0200
Subject: [PATCH 2/3] [mlir][Transforms] Dialect conversion: Extra checks
 during `replaceOp`

This commit adds extra checks/assertions to the `ConversionPatternRewriterImpl::notifyOpReplaced` to improve its robustness.

Replacing an `unrealized_conversion_cast` op that was created by the driver is forbidden and is now caught early during `replaceOp`. It may work in some cases, but is generally dangerous because the conversion driver keeps track of these ops. (Erasing is them is fine.) This change is also in preparation of a subsequent commit that splits the `ConversionValueMapping` into replacements and materializations (with the goal of simplifying block signature conversions).

`null` replacement values are no longer registered in the `ConversionValueMapping`. This was an oversight in #106760. `null` values in the mapping could result in crashes when using the `ConversionValueMapping` API.
---
 .../Transforms/Utils/DialectConversion.cpp    | 31 ++++++++++++++-----
 1 file changed, 23 insertions(+), 8 deletions(-)

diff --git a/mlir/lib/Transforms/Utils/DialectConversion.cpp b/mlir/lib/Transforms/Utils/DialectConversion.cpp
index fcc82f8c2778b6..6aacfedc96a6f9 100644
--- a/mlir/lib/Transforms/Utils/DialectConversion.cpp
+++ b/mlir/lib/Transforms/Utils/DialectConversion.cpp
@@ -1382,16 +1382,21 @@ void ConversionPatternRewriterImpl::notifyOpReplaced(Operation *op,
   assert(newValues.size() == op->getNumResults());
   assert(!ignoredOps.contains(op) && "operation was already replaced");
 
+  // Check if replaced op is an unresolved materialization, i.e., an
+  // unrealized_conversion_cast op that was created by the conversion driver.
+  bool isUnresolvedMaterialization = false;
+  if (auto castOp = dyn_cast<UnrealizedConversionCastOp>(op))
+    if (unresolvedMaterializations.contains(castOp))
+      isUnresolvedMaterialization = true;
+
   // Create mappings for each of the new result values.
   for (auto [newValue, result] : llvm::zip(newValues, op->getResults())) {
     if (!newValue) {
       // This result was dropped and no replacement value was provided.
-      if (auto castOp = dyn_cast<UnrealizedConversionCastOp>(op)) {
-        if (unresolvedMaterializations.contains(castOp)) {
-          // Do not create another materializations if we are erasing a
-          // materialization.
-          continue;
-        }
+      if (isUnresolvedMaterialization) {
+        // Do not create another materializations if we are erasing a
+        // materialization.
+        continue;
       }
 
       // Materialize a replacement value "out of thin air".
@@ -1400,10 +1405,20 @@ void ConversionPatternRewriterImpl::notifyOpReplaced(Operation *op,
           result.getLoc(), /*inputs=*/ValueRange(),
           /*outputType=*/result.getType(), /*originalType=*/Type(),
           currentTypeConverter);
+    } else {
+      // Make sure that the user does not mess with unresolved materializations
+      // that were inserted by the conversion driver. We keep track of these
+      // ops in internal data structures. Erasing them must be allowed because
+      // this can happen when the user is erasing an entire block (including
+      // its body). But replacing them with another value should be forbidden
+      // to avoid problems with the `mapping`.
+      assert(!isUnresolvedMaterialization &&
+             "attempting to replace an unresolved materialization");
     }
 
-    // Remap, and check for any result type changes.
-    mapping.map(result, newValue);
+    // Remap result to replacement value.
+    if (newValue)
+      mapping.map(result, newValue);
   }
 
   appendRewrite<ReplaceOperationRewrite>(op, currentTypeConverter);

>From 9156faf00cad8fbb3b9f609044ed8fbd74718a68 Mon Sep 17 00:00:00 2001
From: Matthias Springer <mspringer at nvidia.com>
Date: Sun, 22 Sep 2024 12:36:46 +0200
Subject: [PATCH 3/3] do not build argument materializations anymore

---
 .../mlir/Transforms/DialectConversion.h       |   7 +-
 .../Conversion/LLVMCommon/TypeConverter.cpp   |  52 +-
 .../Conversion/MemRefToLLVM/MemRefToLLVM.cpp  |  81 ++++
 .../Transforms/StructuralTypeConversions.cpp  | 104 ++--
 .../Transforms/SparseTensorCodegen.cpp        | 236 +++++----
 .../Transforms/Utils/DialectConversion.cpp    | 451 +++++++++++-------
 .../FuncToLLVM/calling-convention.mlir        |   4 +-
 mlir/test/lib/Dialect/Test/TestPatterns.cpp   |   1 +
 mlir/test/mlir-cpu-runner/async-value.mlir    |   2 +-
 .../mlir-cpu-runner/bare-ptr-call-conv.mlir   |   2 +-
 .../memref-reinterpret-cast.mlir              |   2 +-
 mlir/test/mlir-cpu-runner/memref-reshape.mlir |   2 +-
 .../mlir-cpu-runner/sgemm-naive-codegen.mlir  |   2 +-
 .../test/mlir-cpu-runner/unranked-memref.mlir |   2 +-
 mlir/unittests/ExecutionEngine/Invoke.cpp     |   2 +-
 15 files changed, 599 insertions(+), 351 deletions(-)

diff --git a/mlir/include/mlir/Transforms/DialectConversion.h b/mlir/include/mlir/Transforms/DialectConversion.h
index 9ee681e57e21b7..8a996bc8d8fc48 100644
--- a/mlir/include/mlir/Transforms/DialectConversion.h
+++ b/mlir/include/mlir/Transforms/DialectConversion.h
@@ -583,8 +583,8 @@ class ConversionPattern : public RewritePattern {
       : RewritePattern(std::forward<Args>(args)...),
         typeConverter(&typeConverter) {}
 
-  static SmallVector<Value>
-  getOneToOneAdaptorOperands(ArrayRef<ArrayRef<Value>> operands);
+  SmallVector<Value>
+  getOneToOneAdaptorOperands(ArrayRef<ArrayRef<Value>> operands) const;
 
 protected:
   /// An optional type converter for use by this pattern.
@@ -858,6 +858,9 @@ class ConversionPatternRewriter final : public PatternRewriter {
   /// PatternRewriter hook for replacing an operation.
   void replaceOp(Operation *op, Operation *newOp) override;
 
+  /// PatternRewriter hook for replacing an operation.
+  void replaceOpWithMultiple(Operation *op, ArrayRef<ValueRange> newValues);
+
   /// PatternRewriter hook for erasing a dead operation. The uses of this
   /// operation *must* be made dead by the end of the conversion process,
   /// otherwise an assert will be issued.
diff --git a/mlir/lib/Conversion/LLVMCommon/TypeConverter.cpp b/mlir/lib/Conversion/LLVMCommon/TypeConverter.cpp
index 4e7758bf46d9cf..7400f5947c665a 100644
--- a/mlir/lib/Conversion/LLVMCommon/TypeConverter.cpp
+++ b/mlir/lib/Conversion/LLVMCommon/TypeConverter.cpp
@@ -153,6 +153,7 @@ LLVMTypeConverter::LLVMTypeConverter(MLIRContext *ctx,
                                        type.isVarArg());
   });
 
+/*
   // Argument materializations convert from the new block argument types
   // (multiple SSA values that make up a memref descriptor) back to the
   // original block argument type. The dialect conversion framework will then
@@ -198,12 +199,14 @@ LLVMTypeConverter::LLVMTypeConverter(MLIRContext *ctx,
     return builder.create<UnrealizedConversionCastOp>(loc, resultType, desc)
         .getResult(0);
   });
+
+*/
   // Add generic source and target materializations to handle cases where
   // non-LLVM types persist after an LLVM conversion.
   addSourceMaterialization([&](OpBuilder &builder, Type resultType,
                                ValueRange inputs, Location loc) {
-    if (inputs.size() != 1)
-      return Value();
+    //if (inputs.size() != 1)
+    //  return Value();
 
     return builder.create<UnrealizedConversionCastOp>(loc, resultType, inputs)
         .getResult(0);
@@ -216,6 +219,51 @@ LLVMTypeConverter::LLVMTypeConverter(MLIRContext *ctx,
     return builder.create<UnrealizedConversionCastOp>(loc, resultType, inputs)
         .getResult(0);
   });
+  addTargetMaterialization([&](OpBuilder &builder, Type resultType,
+                               ValueRange inputs,
+                               Location loc, Type originalType) -> Value {
+    llvm::errs() << "TARGET MAT: -> " << resultType << "\n";
+    if (!originalType) {
+      llvm::errs() << " -- no orig\n";
+      return Value();
+    }
+    if (auto memrefType = dyn_cast<MemRefType>(originalType)) {
+      assert(isa<LLVM::LLVMStructType>(resultType) && "expected struct type");
+      if (inputs.size() == 1) {
+        Value input = inputs.front();
+        if (auto castOp =input.getDefiningOp<UnrealizedConversionCastOp>()) {
+          if (castOp.getInputs().size() == 1 && isa<LLVM::LLVMPointerType>(castOp.getInputs()[0].getType())) {
+            input = castOp.getInputs()[0];
+          }
+        }
+        if (!isa<LLVM::LLVMPointerType>(input.getType()))
+          return Value();
+        BlockArgument barePtr = dyn_cast<BlockArgument>(input);
+        if (!barePtr)
+          return Value();
+        Block *block = barePtr.getOwner();
+        if (!block->isEntryBlock() ||
+            !isa<FunctionOpInterface>(block->getParentOp()))
+          return Value();
+        // Bare ptr
+        return MemRefDescriptor::fromStaticShape(builder, loc, *this, memrefType,
+                                                 input);
+      }
+      return MemRefDescriptor::pack(builder, loc, *this, memrefType, inputs);
+    }
+    if (auto memrefType = dyn_cast<UnrankedMemRefType>(originalType)) {
+      assert(isa<LLVM::LLVMStructType>(resultType) && "expected struct type");
+      if (inputs.size() == 1) {
+          // Bare pointers are not supported for unranked memrefs because a
+          // memref descriptor cannot be built just from a bare pointer.
+          return Value();
+      }
+      return UnrankedMemRefDescriptor::pack(builder, loc, *this,
+                                                    memrefType, inputs);
+    }
+
+      return Value();
+  });
 
   // Integer memory spaces map to themselves.
   addTypeAttributeConversion(
diff --git a/mlir/lib/Conversion/MemRefToLLVM/MemRefToLLVM.cpp b/mlir/lib/Conversion/MemRefToLLVM/MemRefToLLVM.cpp
index 4bfa536cc8a44a..25019802f28dd8 100644
--- a/mlir/lib/Conversion/MemRefToLLVM/MemRefToLLVM.cpp
+++ b/mlir/lib/Conversion/MemRefToLLVM/MemRefToLLVM.cpp
@@ -1664,6 +1664,80 @@ class ExtractStridedMetadataOpLowering
   }
 };
 
+struct UnrealizedConversionCastOpLowering
+    : public ConvertOpToLLVMPattern<UnrealizedConversionCastOp> {
+public:
+  using ConvertOpToLLVMPattern<
+      UnrealizedConversionCastOp>::ConvertOpToLLVMPattern;
+
+  static bool canLower(const LLVMTypeConverter &converter, BaseMemRefType type, ValueRange inputs) {
+    if (inputs.size() == 1 && isa<LLVM::LLVMPointerType>(inputs.front().getType())) {
+      // Bare pointer.
+      return true;
+    }
+
+    Type converted = converter.convertType(type);
+    if (!converted) return false;
+
+    auto llvmTy = cast<LLVM::LLVMStructType>(converted);
+    SmallVector<Type> flattened;
+    std::function<void(Type)> flattenType = [&](Type t) {
+      if (auto structTy = dyn_cast<LLVM::LLVMStructType>(t)) {
+        for (Type t : structTy.getBody())
+          flattenType(t);
+      } else if (auto arrayTy = dyn_cast<LLVM::LLVMArrayType>(t)) {
+        for (uint64_t i =0, e=arrayTy.getNumElements(); i < e; ++i) {
+          flattenType(arrayTy.getElementType());
+        }
+      } else {
+        flattened.push_back(t);
+      }
+    };
+
+    flattenType(converted);
+    return TypeRange(flattened) == TypeRange(inputs);
+  }
+
+  LogicalResult
+  matchAndRewrite(UnrealizedConversionCastOp op,
+                  OpAdaptor adaptor,
+                  ConversionPatternRewriter &rewriter) const override {
+    if (op->getNumResults() != 1)
+      return failure();
+
+    op.dump();
+    Location loc = op.getLoc();
+    Value result = op->getResult(0);
+    
+    if (auto rankedMemrefType = dyn_cast<MemRefType>(result.getType())){
+      if (op.getInputs().size() == 1 && isa<LLVM::LLVMPointerType>(op.getInputs().front().getType())) {
+        // Converting a bare pointer.
+        Value repl = MemRefDescriptor::fromStaticShape(rewriter, loc, *getTypeConverter(), rankedMemrefType,
+                                                 op.getInputs().front());
+        rewriter.replaceOp(op, repl);
+        return success();
+      }
+
+      // Converting memref descriptor elements.
+      // TODO: Check types.
+      Value repl = MemRefDescriptor::pack(rewriter, loc, *getTypeConverter(), rankedMemrefType, op.getInputs());
+        rewriter.replaceOp(op, repl);
+        return success();
+    } else if(auto unrankedMemrefType = dyn_cast<UnrankedMemRefType>(result.getType())) {
+      if (op.getInputs().size() == 1 && isa<LLVM::LLVMPointerType>(op.getInputs().front().getType())) {
+        return failure();
+      }
+
+      // TODO: Check types.
+      Value repl = UnrankedMemRefDescriptor::pack(rewriter, loc, *getTypeConverter(),
+                                                    unrankedMemrefType, op.getInputs());
+        rewriter.replaceOp(op, repl);
+        return success();
+    }
+
+    return failure();
+  }
+};
 } // namespace
 
 void mlir::populateFinalizeMemRefToLLVMConversionPatterns(
@@ -1693,6 +1767,7 @@ void mlir::populateFinalizeMemRefToLLVMConversionPatterns(
       StoreOpLowering,
       SubViewOpLowering,
       TransposeOpLowering,
+      UnrealizedConversionCastOpLowering,
       ViewOpLowering>(converter);
   // clang-format on
   auto allocLowering = converter.getOptions().allocLowering;
@@ -1728,6 +1803,12 @@ struct FinalizeMemRefToLLVMConversionPass
     RewritePatternSet patterns(&getContext());
     populateFinalizeMemRefToLLVMConversionPatterns(typeConverter, patterns);
     LLVMConversionTarget target(getContext());
+  target.addDynamicallyLegalOp<UnrealizedConversionCastOp>([&](UnrealizedConversionCastOp op) {
+    // TODO: Better checking
+    auto memrefType =dyn_cast<BaseMemRefType>(op->getResult(0).getType());
+    bool canConvert = op->getNumResults() == 1 && memrefType && UnrealizedConversionCastOpLowering::canLower(typeConverter, memrefType, op.getInputs());
+    return !canConvert;
+  });
     target.addLegalOp<func::FuncOp>();
     if (failed(applyPartialConversion(op, target, std::move(patterns))))
       signalPassFailure();
diff --git a/mlir/lib/Dialect/SCF/Transforms/StructuralTypeConversions.cpp b/mlir/lib/Dialect/SCF/Transforms/StructuralTypeConversions.cpp
index 93a78056db1944..4d154b0868c322 100644
--- a/mlir/lib/Dialect/SCF/Transforms/StructuralTypeConversions.cpp
+++ b/mlir/lib/Dialect/SCF/Transforms/StructuralTypeConversions.cpp
@@ -16,20 +16,16 @@ using namespace mlir::scf;
 
 namespace {
 
-// Unpacks the single unrealized_conversion_cast using the list of inputs
-// e.g., return [%b, %c, %d] for %a = unrealized_conversion_cast(%b, %c, %d)
-static void unpackUnrealizedConversionCast(Value v,
-                                           SmallVectorImpl<Value> &unpacked) {
-  if (auto cast =
-          dyn_cast_or_null<UnrealizedConversionCastOp>(v.getDefiningOp())) {
-    if (cast.getInputs().size() != 1) {
-      // 1 : N type conversion.
-      unpacked.append(cast.getInputs().begin(), cast.getInputs().end());
-      return;
-    }
-  }
-  // 1 : 1 type conversion.
-  unpacked.push_back(v);
+static SmallVector<Value> flattenValues(ArrayRef<ArrayRef<Value>> values) {
+  SmallVector<Value> result;
+  for (ArrayRef<Value> v : values)
+    llvm::append_range(result, v);
+  return result;
+}
+
+static Value getSingleValue(ArrayRef<Value> values) {
+  assert(values.size() == 1 && "expected single value");
+  return values.front();
 }
 
 // CRTP
@@ -40,19 +36,21 @@ class Structural1ToNConversionPattern : public OpConversionPattern<SourceOp> {
 public:
   using OpConversionPattern<SourceOp>::typeConverter;
   using OpConversionPattern<SourceOp>::OpConversionPattern;
-  using OpAdaptor = typename OpConversionPattern<SourceOp>::OpAdaptor;
+  using OneToNOpAdaptor =
+      typename OpConversionPattern<SourceOp>::OneToNOpAdaptor;
 
   //
   // Derived classes should provide the following method which performs the
   // actual conversion. It should return std::nullopt upon conversion failure
   // and return the converted operation upon success.
   //
-  // std::optional<SourceOp> convertSourceOp(SourceOp op, OpAdaptor adaptor,
-  //                                    ConversionPatternRewriter &rewriter,
-  //                                    TypeRange dstTypes) const;
+  // std::optional<SourceOp> convertSourceOp(
+  //     SourceOp op, OneToNOpAdaptor adaptor,
+  //     ConversionPatternRewriter &rewriter,
+  //     TypeRange dstTypes) const;
 
   LogicalResult
-  matchAndRewrite(SourceOp op, OpAdaptor adaptor,
+  matchAndRewrite(SourceOp op, OneToNOpAdaptor adaptor,
                   ConversionPatternRewriter &rewriter) const override {
     SmallVector<Type> dstTypes;
     SmallVector<unsigned> offsets;
@@ -73,28 +71,15 @@ class Structural1ToNConversionPattern : public OpConversionPattern<SourceOp> {
       return rewriter.notifyMatchFailure(op, "could not convert operation");
 
     // Packs the return value.
-    SmallVector<Value> packedRets;
+    SmallVector<ValueRange> packedRets;
     for (unsigned i = 1, e = offsets.size(); i < e; i++) {
       unsigned start = offsets[i - 1], end = offsets[i];
       unsigned len = end - start;
       ValueRange mappedValue = newOp->getResults().slice(start, len);
-      if (len != 1) {
-        // 1 : N type conversion.
-        Type origType = op.getResultTypes()[i - 1];
-        Value mat = typeConverter->materializeSourceConversion(
-            rewriter, op.getLoc(), origType, mappedValue);
-        if (!mat) {
-          return rewriter.notifyMatchFailure(
-              op, "Failed to materialize 1:N type conversion");
-        }
-        packedRets.push_back(mat);
-      } else {
-        // 1 : 1 type conversion.
-        packedRets.push_back(mappedValue.front());
-      }
+      packedRets.push_back(mappedValue);
     }
 
-    rewriter.replaceOp(op, packedRets);
+    rewriter.replaceOpWithMultiple(op, packedRets);
     return success();
   }
 };
@@ -105,7 +90,7 @@ class ConvertForOpTypes
   using Structural1ToNConversionPattern::Structural1ToNConversionPattern;
 
   // The callback required by CRTP.
-  std::optional<ForOp> convertSourceOp(ForOp op, OpAdaptor adaptor,
+  std::optional<ForOp> convertSourceOp(ForOp op, OneToNOpAdaptor adaptor,
                                        ConversionPatternRewriter &rewriter,
                                        TypeRange dstTypes) const {
     // Create a empty new op and inline the regions from the old op.
@@ -129,16 +114,13 @@ class ConvertForOpTypes
     if (failed(rewriter.convertRegionTypes(&op.getRegion(), *typeConverter)))
       return std::nullopt;
 
-    // Unpacked the iteration arguments.
-    SmallVector<Value> flatArgs;
-    for (Value arg : adaptor.getInitArgs())
-      unpackUnrealizedConversionCast(arg, flatArgs);
-
     // We can not do clone as the number of result types after conversion
     // might be different.
-    ForOp newOp = rewriter.create<ForOp>(op.getLoc(), adaptor.getLowerBound(),
-                                         adaptor.getUpperBound(),
-                                         adaptor.getStep(), flatArgs);
+    ForOp newOp = rewriter.create<ForOp>(
+        op.getLoc(), getSingleValue(adaptor.getLowerBound()),
+        getSingleValue(adaptor.getUpperBound()),
+        getSingleValue(adaptor.getStep()),
+        flattenValues(adaptor.getInitArgs()));
 
     // Reserve whatever attributes in the original op.
     newOp->setAttrs(op->getAttrs());
@@ -160,12 +142,12 @@ class ConvertIfOpTypes
 public:
   using Structural1ToNConversionPattern::Structural1ToNConversionPattern;
 
-  std::optional<IfOp> convertSourceOp(IfOp op, OpAdaptor adaptor,
+  std::optional<IfOp> convertSourceOp(IfOp op, OneToNOpAdaptor adaptor,
                                       ConversionPatternRewriter &rewriter,
                                       TypeRange dstTypes) const {
 
-    IfOp newOp = rewriter.create<IfOp>(op.getLoc(), dstTypes,
-                                       adaptor.getCondition(), true);
+    IfOp newOp = rewriter.create<IfOp>(
+        op.getLoc(), dstTypes, getSingleValue(adaptor.getCondition()), true);
     newOp->setAttrs(op->getAttrs());
 
     // We do not need the empty blocks created by rewriter.
@@ -189,15 +171,11 @@ class ConvertWhileOpTypes
 public:
   using Structural1ToNConversionPattern::Structural1ToNConversionPattern;
 
-  std::optional<WhileOp> convertSourceOp(WhileOp op, OpAdaptor adaptor,
+  std::optional<WhileOp> convertSourceOp(WhileOp op, OneToNOpAdaptor adaptor,
                                          ConversionPatternRewriter &rewriter,
                                          TypeRange dstTypes) const {
-    // Unpacked the iteration arguments.
-    SmallVector<Value> flatArgs;
-    for (Value arg : adaptor.getOperands())
-      unpackUnrealizedConversionCast(arg, flatArgs);
-
-    auto newOp = rewriter.create<WhileOp>(op.getLoc(), dstTypes, flatArgs);
+    auto newOp = rewriter.create<WhileOp>(op.getLoc(), dstTypes,
+                                          flattenValues(adaptor.getOperands()));
 
     for (auto i : {0u, 1u}) {
       if (failed(rewriter.convertRegionTypes(&op.getRegion(i), *typeConverter)))
@@ -218,13 +196,10 @@ class ConvertYieldOpTypes : public OpConversionPattern<scf::YieldOp> {
 public:
   using OpConversionPattern::OpConversionPattern;
   LogicalResult
-  matchAndRewrite(scf::YieldOp op, OpAdaptor adaptor,
+  matchAndRewrite(scf::YieldOp op, OneToNOpAdaptor adaptor,
                   ConversionPatternRewriter &rewriter) const override {
-    SmallVector<Value> unpackedYield;
-    for (Value operand : adaptor.getOperands())
-      unpackUnrealizedConversionCast(operand, unpackedYield);
-
-    rewriter.replaceOpWithNewOp<scf::YieldOp>(op, unpackedYield);
+    rewriter.replaceOpWithNewOp<scf::YieldOp>(
+        op, flattenValues(adaptor.getOperands()));
     return success();
   }
 };
@@ -235,13 +210,10 @@ class ConvertConditionOpTypes : public OpConversionPattern<ConditionOp> {
 public:
   using OpConversionPattern<ConditionOp>::OpConversionPattern;
   LogicalResult
-  matchAndRewrite(ConditionOp op, OpAdaptor adaptor,
+  matchAndRewrite(ConditionOp op, OneToNOpAdaptor adaptor,
                   ConversionPatternRewriter &rewriter) const override {
-    SmallVector<Value> unpackedYield;
-    for (Value operand : adaptor.getOperands())
-      unpackUnrealizedConversionCast(operand, unpackedYield);
-
-    rewriter.modifyOpInPlace(op, [&]() { op->setOperands(unpackedYield); });
+    rewriter.modifyOpInPlace(
+        op, [&]() { op->setOperands(flattenValues(adaptor.getOperands())); });
     return success();
   }
 };
diff --git a/mlir/lib/Dialect/SparseTensor/Transforms/SparseTensorCodegen.cpp b/mlir/lib/Dialect/SparseTensor/Transforms/SparseTensorCodegen.cpp
index 062a0ea6cc47cb..7459c692e8fb81 100644
--- a/mlir/lib/Dialect/SparseTensor/Transforms/SparseTensorCodegen.cpp
+++ b/mlir/lib/Dialect/SparseTensor/Transforms/SparseTensorCodegen.cpp
@@ -39,25 +39,16 @@ using namespace mlir::sparse_tensor;
 // Helper methods.
 //===----------------------------------------------------------------------===//
 
-/// Flattens a list of operands that may contain sparse tensors.
-static void flattenOperands(ValueRange operands,
-                            SmallVectorImpl<Value> &flattened) {
-  // In case of
-  // sparse_tensor, c, sparse_tensor
-  // ==>
-  // memref ..., c, memref ...
-  for (auto operand : operands) {
-    if (getSparseTensorEncoding(operand.getType())) {
-      auto tuple = getTuple(operand);
-      // An unrealized_conversion_cast will be inserted by type converter to
-      // inter-mix the gap between 1:N conversion between sparse tensors and
-      // fields. In this case, take the operands in the cast and replace the
-      // sparse tensor output with the flattened type array.
-      flattened.append(tuple.getOperands().begin(), tuple.getOperands().end());
-    } else {
-      flattened.push_back(operand);
-    }
-  }
+static SmallVector<Value> flattenValues(ArrayRef<ArrayRef<Value>> values) {
+  SmallVector<Value> result;
+  for (ArrayRef<Value> v : values)
+    llvm::append_range(result, v);
+  return result;
+}
+
+static Value getSingleValue(ArrayRef<Value> values) {
+  assert(values.size() == 1 && "expected single value");
+  return values.front();
 }
 
 /// Generates a load with proper `index` typing.
@@ -567,12 +558,11 @@ class SparseReturnConverter : public OpConversionPattern<func::ReturnOp> {
 public:
   using OpConversionPattern::OpConversionPattern;
   LogicalResult
-  matchAndRewrite(func::ReturnOp op, OpAdaptor adaptor,
+  matchAndRewrite(func::ReturnOp op, OneToNOpAdaptor adaptor,
                   ConversionPatternRewriter &rewriter) const override {
-    SmallVector<Value> flattened;
-    flattenOperands(adaptor.getOperands(), flattened);
     // Create a return with the flattened value extracted from sparse tensors.
-    rewriter.replaceOpWithNewOp<func::ReturnOp>(op, flattened);
+    rewriter.replaceOpWithNewOp<func::ReturnOp>(
+        op, flattenValues(adaptor.getOperands()));
     return success();
   }
 };
@@ -583,7 +573,7 @@ class SparseCallConverter : public OpConversionPattern<func::CallOp> {
   // The default CallOp converter can not handle 1:N type conversion.
   using OpConversionPattern::OpConversionPattern;
   LogicalResult
-  matchAndRewrite(func::CallOp op, OpAdaptor adaptor,
+  matchAndRewrite(func::CallOp op, OneToNOpAdaptor adaptor,
                   ConversionPatternRewriter &rewriter) const override {
     Location loc = op.getLoc();
     // In case of:
@@ -596,12 +586,10 @@ class SparseCallConverter : public OpConversionPattern<func::CallOp> {
       return failure();
 
     // (1) Generates new call with flattened return value.
-    SmallVector<Value> flattened;
-    flattenOperands(adaptor.getOperands(), flattened);
-    auto newCall = rewriter.create<func::CallOp>(loc, op.getCallee(),
-                                                 finalRetTy, flattened);
-    // (2) Create cast operation for sparse tensor returns.
-    SmallVector<Value> castedRet;
+    auto newCall = rewriter.create<func::CallOp>(
+        loc, op.getCallee(), finalRetTy, flattenValues(adaptor.getOperands()));
+    // (2) Gather sparse tensor returns.
+    SmallVector<SmallVector<Value>> packedResultVals;
     // Tracks the offset of current return value (of the original call)
     // relative to the new call (after sparse tensor flattening);
     unsigned retOffset = 0;
@@ -618,21 +606,27 @@ class SparseCallConverter : public OpConversionPattern<func::CallOp> {
       assert(!sparseFlat.empty());
       if (sparseFlat.size() > 1) {
         auto flatSize = sparseFlat.size();
-        ValueRange fields(iterator_range<ResultRange::iterator>(
-            newCall.result_begin() + retOffset,
-            newCall.result_begin() + retOffset + flatSize));
-        castedRet.push_back(genTuple(rewriter, loc, retType, fields));
+        packedResultVals.push_back(SmallVector<Value>());
+        llvm::append_range(packedResultVals.back(),
+                           iterator_range<ResultRange::iterator>(
+                               newCall.result_begin() + retOffset,
+                               newCall.result_begin() + retOffset + flatSize));
         retOffset += flatSize;
       } else {
         // If this is an 1:1 conversion, no need for casting.
-        castedRet.push_back(newCall.getResult(retOffset));
+        packedResultVals.push_back(SmallVector<Value>());
+        packedResultVals.back().push_back(newCall.getResult(retOffset));
         retOffset++;
       }
       sparseFlat.clear();
     }
 
-    assert(castedRet.size() == op.getNumResults());
-    rewriter.replaceOp(op, castedRet);
+    assert(packedResultVals.size() == op.getNumResults());
+    SmallVector<ValueRange> ranges;
+    ranges.reserve(packedResultVals.size());
+    for (const SmallVector<Value> &vec : packedResultVals)
+      ranges.push_back(ValueRange(vec));
+    rewriter.replaceOpWithMultiple(op, ranges);
     return success();
   }
 };
@@ -642,13 +636,15 @@ class SparseLvlOpConverter : public OpConversionPattern<LvlOp> {
 public:
   using OpConversionPattern::OpConversionPattern;
   LogicalResult
-  matchAndRewrite(LvlOp op, OpAdaptor adaptor,
+  matchAndRewrite(LvlOp op, OneToNOpAdaptor adaptor,
                   ConversionPatternRewriter &rewriter) const override {
     std::optional<int64_t> lvl = op.getConstantLvlIndex();
-    if (!lvl || !getSparseTensorEncoding(adaptor.getSource().getType()))
+    if (!lvl || !getSparseTensorEncoding(op.getSource().getType()))
       return failure();
 
-    auto desc = getDescriptorFromTensorTuple(adaptor.getSource());
+    SparseTensorDescriptor desc(
+        SparseTensorType(cast<RankedTensorType>(op.getSource().getType())),
+        adaptor.getSource());
     auto sz = desc.getLvlSize(rewriter, op.getLoc(), *lvl);
 
     rewriter.replaceOp(op, sz);
@@ -660,7 +656,7 @@ class SparseLvlOpConverter : public OpConversionPattern<LvlOp> {
 struct SparseReorderCOOConverter : public OpConversionPattern<ReorderCOOOp> {
   using OpConversionPattern::OpConversionPattern;
   LogicalResult
-  matchAndRewrite(ReorderCOOOp op, ReorderCOOOpAdaptor adaptor,
+  matchAndRewrite(ReorderCOOOp op, OneToNOpAdaptor adaptor,
                   ConversionPatternRewriter &rewriter) const override {
     Location loc = op.getLoc();
     MLIRContext *ctx = op.getContext();
@@ -674,8 +670,10 @@ struct SparseReorderCOOConverter : public OpConversionPattern<ReorderCOOOp> {
     assert(dstStt.hasSameDimToLvl(srcStt));
 
     // We don't need a mutable descriptor here as we perform sorting in-place.
-    auto nnz = genValMemSize(rewriter, op.getLoc(), adaptor.getInputCoo());
-    auto desc = getDescriptorFromTensorTuple(adaptor.getInputCoo());
+    SparseTensorDescriptor desc(
+        SparseTensorType(cast<RankedTensorType>(op.getInputCoo().getType())),
+        adaptor.getInputCoo());
+    auto nnz = desc.getValMemSize(rewriter, op.getLoc());
     auto crd = desc.getAOSMemRef();
     auto val = desc.getValMemRef();
 
@@ -690,7 +688,7 @@ struct SparseReorderCOOConverter : public OpConversionPattern<ReorderCOOOp> {
 
     // Since we do in-place sorting, the destinate tensor will have the same set
     // of memrefs as the source tensor.
-    rewriter.replaceOp(op, adaptor.getInputCoo());
+    rewriter.replaceOpWithMultiple(op, {adaptor.getInputCoo()});
     return success();
   }
 };
@@ -700,10 +698,13 @@ class SparseSliceGetterOpConverter : public OpConversionPattern<Op> {
 public:
   using OpConversionPattern<Op>::OpConversionPattern;
   LogicalResult
-  matchAndRewrite(Op op, typename Op::Adaptor adaptor,
+  matchAndRewrite(Op op,
+                  typename OpConversionPattern<Op>::OneToNOpAdaptor adaptor,
                   ConversionPatternRewriter &rewriter) const override {
     // Simply lowers to specifer.get <field> operation.
-    auto desc = getDescriptorFromTensorTuple(adaptor.getSlice());
+    SparseTensorDescriptor desc(
+        SparseTensorType(cast<RankedTensorType>(op.getSlice().getType())),
+        adaptor.getSlice());
     auto v = desc.getSpecifierField(rewriter, op.getLoc(), kind,
                                     op.getDim().getZExtValue());
 
@@ -717,14 +718,14 @@ class SparseCastConverter : public OpConversionPattern<tensor::CastOp> {
 public:
   using OpConversionPattern::OpConversionPattern;
   LogicalResult
-  matchAndRewrite(tensor::CastOp op, OpAdaptor adaptor,
+  matchAndRewrite(tensor::CastOp op, OneToNOpAdaptor adaptor,
                   ConversionPatternRewriter &rewriter) const override {
     // Only rewrite identically annotated source/dest.
     auto encDst = getSparseTensorEncoding(op.getType());
     auto encSrc = getSparseTensorEncoding(op.getSource().getType());
     if (!encDst || encDst != encSrc)
       return failure();
-    rewriter.replaceOp(op, adaptor.getOperands());
+    rewriter.replaceOpWithMultiple(op, {adaptor.getSource()});
     return success();
   }
 };
@@ -733,10 +734,10 @@ class SparseReMapConverter : public OpConversionPattern<ReinterpretMapOp> {
 public:
   using OpConversionPattern::OpConversionPattern;
   LogicalResult
-  matchAndRewrite(ReinterpretMapOp op, OpAdaptor adaptor,
+  matchAndRewrite(ReinterpretMapOp op, OneToNOpAdaptor adaptor,
                   ConversionPatternRewriter &rewriter) const override {
     // Simply fold the operation.
-    rewriter.replaceOp(op, adaptor.getSource());
+    rewriter.replaceOpWithMultiple(op, {adaptor.getSource()});
     return success();
   }
 };
@@ -752,7 +753,7 @@ class SparseTensorAllocConverter
         enableBufferInitialization(enableInit) {}
 
   LogicalResult
-  matchAndRewrite(bufferization::AllocTensorOp op, OpAdaptor adaptor,
+  matchAndRewrite(bufferization::AllocTensorOp op, OneToNOpAdaptor adaptor,
                   ConversionPatternRewriter &rewriter) const override {
     const auto resType = getSparseTensorType(op);
     if (!resType.hasEncoding())
@@ -761,7 +762,9 @@ class SparseTensorAllocConverter
     Location loc = op.getLoc();
     // Deal with copy.
     if (op.getCopy()) {
-      auto desc = getDescriptorFromTensorTuple(adaptor.getCopy());
+      SparseTensorDescriptor desc(
+          SparseTensorType(cast<RankedTensorType>(op.getCopy().getType())),
+          adaptor.getCopy());
       SmallVector<Value> fields;
       fields.reserve(desc.getNumFields());
       // Memcpy on memref fields.
@@ -776,7 +779,7 @@ class SparseTensorAllocConverter
       // Reuses specifier.
       fields.push_back(desc.getSpecifier());
       assert(fields.size() == desc.getNumFields());
-      rewriter.replaceOp(op, genTuple(rewriter, loc, resType, fields));
+      rewriter.replaceOpWithMultiple(op, {fields});
       return success();
     }
 
@@ -786,7 +789,8 @@ class SparseTensorAllocConverter
     }
     // Level size equals to dimension size since lvl2dim map is an identity map.
     SmallVector<Value> lvlSizesValues;
-    createDimSizes(rewriter, loc, resType, adaptor.getDynamicSizes(),
+    createDimSizes(rewriter, loc, resType,
+                   flattenValues(adaptor.getDynamicSizes()),
                    /*dimSizesValues=*/lvlSizesValues);
 
     // Construct allocation for each field.
@@ -796,7 +800,7 @@ class SparseTensorAllocConverter
                       sizeHint, lvlSizesValues, fields);
 
     // Replace operation with resulting memrefs.
-    rewriter.replaceOp(op, genTuple(rewriter, loc, resType, fields));
+    rewriter.replaceOpWithMultiple(op, {fields});
     return success();
   }
 
@@ -837,7 +841,7 @@ class SparseTensorEmptyConverter : public OpConversionPattern<tensor::EmptyOp> {
                       sizeHint, lvlSizesValues, fields);
 
     // Replace operation with resulting memrefs.
-    rewriter.replaceOp(op, genTuple(rewriter, loc, resType, fields));
+    rewriter.replaceOpWithMultiple(op, {fields});
     return success();
   }
 
@@ -856,7 +860,7 @@ class SparseTensorDeallocConverter
         createDeallocs(createDeallocs) {}
 
   LogicalResult
-  matchAndRewrite(bufferization::DeallocTensorOp op, OpAdaptor adaptor,
+  matchAndRewrite(bufferization::DeallocTensorOp op, OneToNOpAdaptor adaptor,
                   ConversionPatternRewriter &rewriter) const override {
     auto enc = getSparseTensorEncoding(op.getTensor().getType());
     if (!enc)
@@ -867,7 +871,9 @@ class SparseTensorDeallocConverter
     if (createDeallocs) {
       // Replace the sparse tensor deallocation with field deallocations.
       Location loc = op.getLoc();
-      auto desc = getDescriptorFromTensorTuple(adaptor.getTensor());
+      SparseTensorDescriptor desc(
+          SparseTensorType(cast<RankedTensorType>(op.getTensor().getType())),
+          adaptor.getTensor());
       for (auto input : desc.getMemRefFields())
         // Deallocate every buffer used to store the sparse tensor handler.
         rewriter.create<memref::DeallocOp>(loc, input);
@@ -885,15 +891,17 @@ class SparseTensorLoadConverter : public OpConversionPattern<LoadOp> {
 public:
   using OpConversionPattern::OpConversionPattern;
   LogicalResult
-  matchAndRewrite(LoadOp op, OpAdaptor adaptor,
+  matchAndRewrite(LoadOp op, OneToNOpAdaptor adaptor,
                   ConversionPatternRewriter &rewriter) const override {
     // Prepare descriptor.
-    auto desc = getDescriptorFromTensorTuple(adaptor.getTensor());
+    SparseTensorDescriptor desc(
+        SparseTensorType(cast<RankedTensorType>(op.getTensor().getType())),
+        adaptor.getTensor());
     // Generate optional insertion finalization code.
     if (op.getHasInserts())
       genEndInsert(rewriter, op.getLoc(), desc);
     // Replace operation with resulting memrefs.
-    rewriter.replaceOp(op, genTuple(rewriter, op.getLoc(), desc));
+    rewriter.replaceOpWithMultiple(op, {desc.getFields()});
     return success();
   }
 };
@@ -903,12 +911,14 @@ class SparseExpandConverter : public OpConversionPattern<ExpandOp> {
 public:
   using OpConversionPattern::OpConversionPattern;
   LogicalResult
-  matchAndRewrite(ExpandOp op, OpAdaptor adaptor,
+  matchAndRewrite(ExpandOp op, OneToNOpAdaptor adaptor,
                   ConversionPatternRewriter &rewriter) const override {
     if (!getSparseTensorEncoding(op.getTensor().getType()))
       return failure();
     Location loc = op->getLoc();
-    auto desc = getDescriptorFromTensorTuple(adaptor.getTensor());
+    SparseTensorDescriptor desc(
+        SparseTensorType(cast<RankedTensorType>(op.getTensor().getType())),
+        adaptor.getTensor());
     const auto srcType = getSparseTensorType(op.getTensor());
     Type eltType = srcType.getElementType();
     Type boolType = rewriter.getIntegerType(1);
@@ -954,15 +964,18 @@ class SparseCompressConverter : public OpConversionPattern<CompressOp> {
 public:
   using OpConversionPattern::OpConversionPattern;
   LogicalResult
-  matchAndRewrite(CompressOp op, OpAdaptor adaptor,
+  matchAndRewrite(CompressOp op, OneToNOpAdaptor adaptor,
                   ConversionPatternRewriter &rewriter) const override {
     Location loc = op->getLoc();
     SmallVector<Value> fields;
-    auto desc = getMutDescriptorFromTensorTuple(adaptor.getTensor(), fields);
-    Value values = adaptor.getValues();
-    Value filled = adaptor.getFilled();
-    Value added = adaptor.getAdded();
-    Value count = adaptor.getCount();
+    llvm::append_range(fields, adaptor.getTensor());
+    MutSparseTensorDescriptor desc(
+        SparseTensorType(cast<RankedTensorType>(op.getTensor().getType())),
+        fields);
+    Value values = getSingleValue(adaptor.getValues());
+    Value filled = getSingleValue(adaptor.getFilled());
+    Value added = getSingleValue(adaptor.getAdded());
+    Value count = getSingleValue(adaptor.getCount());
     const SparseTensorType dstType(desc.getRankedTensorType());
     Type eltType = dstType.getElementType();
 
@@ -995,7 +1008,8 @@ class SparseCompressConverter : public OpConversionPattern<CompressOp> {
     SmallVector<Value> params(desc.getFields().begin(), desc.getFields().end());
     SmallVector<Type> flatSpTensorTps = llvm::to_vector(
         llvm::map_range(desc.getFields(), [](Value v) { return v.getType(); }));
-    params.append(adaptor.getLvlCoords().begin(), adaptor.getLvlCoords().end());
+    SmallVector<Value> flatLvlCoords = flattenValues(adaptor.getLvlCoords());
+    params.append(flatLvlCoords.begin(), flatLvlCoords.end());
     params.push_back(crd);
     params.push_back(value);
     SparseInsertGenerator insertGen(op.getTensor().getType(), flatSpTensorTps,
@@ -1006,7 +1020,6 @@ class SparseCompressConverter : public OpConversionPattern<CompressOp> {
     rewriter.create<scf::YieldOp>(loc, insertRet);
 
     rewriter.setInsertionPointAfter(loop);
-    Value result = genTuple(rewriter, loc, dstType, loop->getResults());
     // Deallocate the buffers on exit of the full loop nest.
     Operation *parent = getTop(op);
     rewriter.setInsertionPointAfter(parent);
@@ -1014,7 +1027,7 @@ class SparseCompressConverter : public OpConversionPattern<CompressOp> {
     rewriter.create<memref::DeallocOp>(loc, filled);
     rewriter.create<memref::DeallocOp>(loc, added);
     // Replace operation with resulting memrefs.
-    rewriter.replaceOp(op, result);
+    rewriter.replaceOpWithMultiple(op, {loop->getResults()});
     return success();
   }
 };
@@ -1024,25 +1037,27 @@ class SparseInsertConverter : public OpConversionPattern<tensor::InsertOp> {
 public:
   using OpConversionPattern::OpConversionPattern;
   LogicalResult
-  matchAndRewrite(tensor::InsertOp op, OpAdaptor adaptor,
+  matchAndRewrite(tensor::InsertOp op, OneToNOpAdaptor adaptor,
                   ConversionPatternRewriter &rewriter) const override {
-    auto stt = getSparseTensorType(adaptor.getDest());
+    auto stt = getSparseTensorType(op.getDest());
     if (!stt.hasEncoding())
       return failure();
     assert(stt.isIdentity() && "Run reinterpret-map before conversion.");
 
     Location loc = op.getLoc();
-    auto desc = getDescriptorFromTensorTuple(adaptor.getDest());
+    SparseTensorDescriptor desc(
+        SparseTensorType(cast<RankedTensorType>(op.getDest().getType())),
+        adaptor.getDest());
     TypeRange flatSpTensorTps = desc.getFields().getTypes();
     SmallVector<Value> params = llvm::to_vector(desc.getFields());
-    params.append(adaptor.getIndices().begin(), adaptor.getIndices().end());
-    params.push_back(adaptor.getScalar());
+    SmallVector<Value> flatIndices = flattenValues(adaptor.getIndices());
+    params.append(flatIndices.begin(), flatIndices.end());
+    params.push_back(getSingleValue(adaptor.getScalar()));
     SparseInsertGenerator insertGen(op.getDest().getType(), flatSpTensorTps,
                                     params, /*genCall=*/true);
     SmallVector<Value> ret = insertGen.genCallOrInline(rewriter, loc);
     // Replace operation with resulting memrefs.
-    rewriter.replaceOp(op,
-                       genTuple(rewriter, loc, op.getDest().getType(), ret));
+    rewriter.replaceOpWithMultiple(op, {ret});
     return success();
   }
 };
@@ -1053,14 +1068,16 @@ class SparseToPositionsConverter : public OpConversionPattern<ToPositionsOp> {
   using OpAdaptor = typename ToPositionsOp::Adaptor;
   using OpConversionPattern<ToPositionsOp>::OpConversionPattern;
   LogicalResult
-  matchAndRewrite(ToPositionsOp op, OpAdaptor adaptor,
+  matchAndRewrite(ToPositionsOp op, OneToNOpAdaptor adaptor,
                   ConversionPatternRewriter &rewriter) const override {
     // Replace the requested position access with corresponding field.
     // The view is restricted to the actual size to ensure clients
     // of this operation truly observe size, not capacity!
     Location loc = op.getLoc();
     Level lvl = op.getLevel();
-    auto desc = getDescriptorFromTensorTuple(adaptor.getTensor());
+    SparseTensorDescriptor desc(
+        SparseTensorType(cast<RankedTensorType>(op.getTensor().getType())),
+        adaptor.getTensor());
     auto mem = desc.getPosMemRef(lvl);
     auto size = desc.getPosMemSize(rewriter, loc, lvl);
     rewriter.replaceOp(op, genSliceToSize(rewriter, loc, mem, size));
@@ -1075,14 +1092,16 @@ class SparseToCoordinatesConverter
   using OpAdaptor = typename ToCoordinatesOp::Adaptor;
   using OpConversionPattern<ToCoordinatesOp>::OpConversionPattern;
   LogicalResult
-  matchAndRewrite(ToCoordinatesOp op, OpAdaptor adaptor,
+  matchAndRewrite(ToCoordinatesOp op, OneToNOpAdaptor adaptor,
                   ConversionPatternRewriter &rewriter) const override {
     // Replace the requested coordinates access with corresponding field.
     // The view is restricted to the actual size to ensure clients
     // of this operation truly observe size, not capacity!
     Location loc = op.getLoc();
     Level lvl = op.getLevel();
-    auto desc = getDescriptorFromTensorTuple(adaptor.getTensor());
+    SparseTensorDescriptor desc(
+        SparseTensorType(cast<RankedTensorType>(op.getTensor().getType())),
+        adaptor.getTensor());
     auto mem = desc.getCrdMemRefOrView(rewriter, loc, lvl);
     if (lvl < getSparseTensorType(op.getTensor()).getAoSCOOStart()) {
       auto size = desc.getCrdMemSize(rewriter, loc, lvl);
@@ -1100,14 +1119,16 @@ class SparseToCoordinatesBufferConverter
   using OpAdaptor = typename ToCoordinatesBufferOp::Adaptor;
   using OpConversionPattern<ToCoordinatesBufferOp>::OpConversionPattern;
   LogicalResult
-  matchAndRewrite(ToCoordinatesBufferOp op, OpAdaptor adaptor,
+  matchAndRewrite(ToCoordinatesBufferOp op, OneToNOpAdaptor adaptor,
                   ConversionPatternRewriter &rewriter) const override {
     // Replace the requested coordinates access with corresponding field.
     // The view is restricted to the actual size to ensure clients
     // of this operation truly observe size, not capacity!
     Location loc = op.getLoc();
     Level lvl = getSparseTensorType(op.getTensor()).getAoSCOOStart();
-    auto desc = getDescriptorFromTensorTuple(adaptor.getTensor());
+    SparseTensorDescriptor desc(
+        SparseTensorType(cast<RankedTensorType>(op.getTensor().getType())),
+        adaptor.getTensor());
     auto mem = desc.getAOSMemRef();
     auto size = desc.getCrdMemSize(rewriter, loc, lvl);
     rewriter.replaceOp(op, genSliceToSize(rewriter, loc, mem, size));
@@ -1121,13 +1142,15 @@ class SparseToValuesConverter : public OpConversionPattern<ToValuesOp> {
   using OpAdaptor = typename ToValuesOp::Adaptor;
   using OpConversionPattern<ToValuesOp>::OpConversionPattern;
   LogicalResult
-  matchAndRewrite(ToValuesOp op, OpAdaptor adaptor,
+  matchAndRewrite(ToValuesOp op, OneToNOpAdaptor adaptor,
                   ConversionPatternRewriter &rewriter) const override {
     // Replace the requested values access with corresponding field.
     // The view is restricted to the actual size to ensure clients
     // of this operation truly observe size, not capacity!
     Location loc = op.getLoc();
-    auto desc = getDescriptorFromTensorTuple(adaptor.getTensor());
+    SparseTensorDescriptor desc(
+        SparseTensorType(cast<RankedTensorType>(op.getTensor().getType())),
+        adaptor.getTensor());
     auto mem = desc.getValMemRef();
     auto size = desc.getValMemSize(rewriter, loc);
     rewriter.replaceOp(op, genSliceToSize(rewriter, loc, mem, size));
@@ -1140,7 +1163,7 @@ class SparseConvertConverter : public OpConversionPattern<ConvertOp> {
 public:
   using OpConversionPattern::OpConversionPattern;
   LogicalResult
-  matchAndRewrite(ConvertOp op, OpAdaptor adaptor,
+  matchAndRewrite(ConvertOp op, OneToNOpAdaptor adaptor,
                   ConversionPatternRewriter &rewriter) const override {
     SparseTensorEncodingAttr encDst = getSparseTensorEncoding(op.getType());
     SparseTensorEncodingAttr encSrc =
@@ -1160,7 +1183,7 @@ class SparseConvertConverter : public OpConversionPattern<ConvertOp> {
     Type srcElemTp = op.getSource().getType().getElementType();
     // Fold the trivial cases.
     if (retElemTp == srcElemTp && encDst == encSrc) {
-      rewriter.replaceOp(op, adaptor.getSource());
+      rewriter.replaceOpWithMultiple(op, {adaptor.getSource()});
       return success();
     }
     //
@@ -1173,7 +1196,9 @@ class SparseConvertConverter : public OpConversionPattern<ConvertOp> {
     //   else:
     //     dst = memref.copy(src)
     Location loc = op.getLoc();
-    auto srcDesc = getDescriptorFromTensorTuple(adaptor.getSource());
+    SparseTensorDescriptor srcDesc(
+        SparseTensorType(cast<RankedTensorType>(op.getSource().getType())),
+        adaptor.getSource());
     SmallVector<Value> fields;
     foreachFieldAndTypeInSparseTensor(
         SparseTensorType(cast<RankedTensorType>(op.getResult().getType())),
@@ -1215,8 +1240,7 @@ class SparseConvertConverter : public OpConversionPattern<ConvertOp> {
           return true;
         });
 
-    rewriter.replaceOp(
-        op, genTuple(rewriter, loc, op.getResult().getType(), fields));
+    rewriter.replaceOpWithMultiple(op, {fields});
     return success();
   }
 };
@@ -1226,7 +1250,7 @@ class SparseExtractSliceConverter
 public:
   using OpConversionPattern::OpConversionPattern;
   LogicalResult
-  matchAndRewrite(tensor::ExtractSliceOp op, OpAdaptor adaptor,
+  matchAndRewrite(tensor::ExtractSliceOp op, OneToNOpAdaptor adaptor,
                   ConversionPatternRewriter &rewriter) const override {
     Location loc = op.getLoc();
     MLIRContext *ctx = op.getContext();
@@ -1238,7 +1262,10 @@ class SparseExtractSliceConverter
     assert(srcEnc.withoutDimSlices() == dstEnc.withoutDimSlices());
 
     SmallVector<Value> fields;
-    auto desc = getMutDescriptorFromTensorTuple(adaptor.getSource(), fields);
+    llvm::append_range(fields, adaptor.getSource());
+    MutSparseTensorDescriptor desc(
+        SparseTensorType(cast<RankedTensorType>(op.getSource().getType())),
+        fields);
 
     auto newSpec = rewriter.create<StorageSpecifierInitOp>(
         loc, StorageSpecifierType::get(ctx, dstEnc), desc.getSpecifier());
@@ -1271,8 +1298,7 @@ class SparseExtractSliceConverter
     // NOTE: we can not generate tuples directly from descriptor here, as the
     // descriptor is holding the original type, yet we want the slice type
     // here (they shared every memref but with an updated specifier).
-    rewriter.replaceOp(op, genTuple(rewriter, loc, op.getResult().getType(),
-                                    desc.getFields()));
+    rewriter.replaceOpWithMultiple(op, {desc.getFields()});
     return success();
   }
 };
@@ -1283,13 +1309,15 @@ class SparseNumberOfEntriesConverter
 public:
   using OpConversionPattern::OpConversionPattern;
   LogicalResult
-  matchAndRewrite(NumberOfEntriesOp op, OpAdaptor adaptor,
+  matchAndRewrite(NumberOfEntriesOp op, OneToNOpAdaptor adaptor,
                   ConversionPatternRewriter &rewriter) const override {
     // Query memSizes for the actually stored values.
     // FIXME: the nse value computed in this way might be wrong when there is
     // any "loose_compressed" level.
-    rewriter.replaceOp(
-        op, genValMemSize(rewriter, op.getLoc(), adaptor.getTensor()));
+    SparseTensorDescriptor desc(
+        SparseTensorType(cast<RankedTensorType>(op.getTensor().getType())),
+        adaptor.getTensor());
+    rewriter.replaceOp(op, desc.getValMemSize(rewriter, op.getLoc()));
     return success();
   }
 };
@@ -1403,7 +1431,7 @@ struct SparseAssembleOpConverter : public OpConversionPattern<AssembleOp> {
     }
     desc.setValMemSize(rewriter, loc, memSize);
 
-    rewriter.replaceOp(op, genTuple(rewriter, loc, desc));
+    rewriter.replaceOpWithMultiple(op, {desc.getFields()});
     return success();
   }
 };
@@ -1416,9 +1444,11 @@ struct SparseDisassembleOpConverter
       : OpConversionPattern(typeConverter, context) {}
 
   LogicalResult
-  matchAndRewrite(DisassembleOp op, OpAdaptor adaptor,
+  matchAndRewrite(DisassembleOp op, OneToNOpAdaptor adaptor,
                   ConversionPatternRewriter &rewriter) const override {
-    auto desc = getDescriptorFromTensorTuple(adaptor.getTensor());
+    SparseTensorDescriptor desc(
+        SparseTensorType(cast<RankedTensorType>(op.getTensor().getType())),
+        adaptor.getTensor());
     Location loc = op.getLoc();
     SmallVector<Value> retMem;
     SmallVector<Value> retLen;
@@ -1577,7 +1607,7 @@ struct SparseNewConverter : public OpConversionPattern<NewOp> {
                    EmitCInterface::Off);
 
     // Replace operation with resulting memrefs.
-    rewriter.replaceOp(op, genTuple(rewriter, loc, dstTp, fields));
+    rewriter.replaceOpWithMultiple(op, {fields});
     return success();
   }
 };
diff --git a/mlir/lib/Transforms/Utils/DialectConversion.cpp b/mlir/lib/Transforms/Utils/DialectConversion.cpp
index 6aacfedc96a6f9..841dd92738cb08 100644
--- a/mlir/lib/Transforms/Utils/DialectConversion.cpp
+++ b/mlir/lib/Transforms/Utils/DialectConversion.cpp
@@ -53,8 +53,6 @@ static void logFailure(llvm::ScopedPrinter &os, StringRef fmt, Args &&...args) {
   });
 }
 
-/// Helper function that computes an insertion point where the given value is
-/// defined and can be used without a dominance violation.
 static OpBuilder::InsertPoint computeInsertPoint(Value value) {
   Block *insertBlock = value.getParentBlock();
   Block::iterator insertPt = insertBlock->begin();
@@ -63,94 +61,230 @@ static OpBuilder::InsertPoint computeInsertPoint(Value value) {
   return OpBuilder::InsertPoint(insertBlock, insertPt);
 }
 
+/// Helper function that computes an insertion point where the given value is
+/// defined and can be used without a dominance violation.
+static OpBuilder::InsertPoint computeInsertPoint(ArrayRef<Value> vals) {
+  assert(!vals.empty() && "expected at least one value");
+  OpBuilder::InsertPoint pt = computeInsertPoint(vals.front());
+  for (Value v : vals.drop_front()) {
+    OpBuilder::InsertPoint pt2 = computeInsertPoint(v);
+    assert(pt.getBlock() == pt2.getBlock());
+    if (pt.getPoint() == pt.getBlock()->begin()) {
+      pt = pt2;
+      continue;
+    }
+    if (pt2.getPoint() == pt2.getBlock()->begin()) {
+      continue;
+    }
+    if (pt.getPoint()->isBeforeInBlock(&*pt2.getPoint()))
+      pt = pt2;
+  }
+  return pt;
+}
+
 //===----------------------------------------------------------------------===//
 // ConversionValueMapping
 //===----------------------------------------------------------------------===//
 
 namespace {
+struct SmallVectorMapInfo {
+  static SmallVector<Value, 1> getEmptyKey() { return SmallVector<Value, 1>{}; }
+  static SmallVector<Value, 1> getTombstoneKey() {
+    return SmallVector<Value, 1>{};
+  }
+  static ::llvm::hash_code getHashValue(SmallVector<Value, 1> val) {
+    return ::llvm::hash_combine_range(val.begin(), val.end());
+  }
+  static bool isEqual(SmallVector<Value, 1> LHS, SmallVector<Value, 1> RHS) {
+    return LHS == RHS;
+  }
+};
+
 /// This class wraps a IRMapping to provide recursive lookup
 /// functionality, i.e. we will traverse if the mapped value also has a mapping.
 struct ConversionValueMapping {
-  /// Lookup the most recently mapped value with the desired type in the
-  /// mapping.
+  /// Find the most recently mapped values for the given value. If the value is
+  /// not mapped at all, return the given value.
+  SmallVector<Value, 1> lookupOrDefault(Value from) const;
+
+  /// TODO: Find most recently mapped or materialization with matching type. May
+  /// return the given value if the type matches.
+  SmallVector<Value, 1>
+  lookupOrDefault(Value from, SmallVector<Type, 1> desiredTypes) const;
+
+  /// Find the most recently mapped values for the given value. If the value is
+  /// not mapped at all, return an empty vector.
+  SmallVector<Value, 1> lookupOrNull(Value from) const;
+
+  /// Find the most recently mapped values for the given value. If those values
+  /// have the desired types, return them. Otherwise, try to find a
+  /// materialization to the desired types.
   ///
-  /// Special cases:
-  /// - If the desired type is "null", simply return the most recently mapped
-  ///   value.
-  /// - If there is no mapping to the desired type, also return the most
-  ///   recently mapped value.
-  /// - If there is no mapping for the given value at all, return the given
-  ///   value.
-  Value lookupOrDefault(Value from, Type desiredType = nullptr) const;
-
-  /// Lookup a mapped value within the map, or return null if a mapping does not
-  /// exist. If a mapping exists, this follows the same behavior of
-  /// `lookupOrDefault`.
-  Value lookupOrNull(Value from, Type desiredType = nullptr) const;
-
-  /// Map a value to the one provided.
-  void map(Value oldVal, Value newVal) {
-    LLVM_DEBUG({
-      for (Value it = newVal; it; it = mapping.lookupOrNull(it))
-        assert(it != oldVal && "inserting cyclic mapping");
-    });
-    mapping.map(oldVal, newVal);
+  /// If the given value is not mapped at all or if there are no mapped values/
+  /// materialization results with the desired types, return an empty vector.
+  SmallVector<Value, 1> lookupOrNull(Value from,
+                                     SmallVector<Type, 1> desiredTypes) const;
+
+  Value lookupOrNull(Value from, Type desiredType) {
+    SmallVector<Value, 1> vals =
+        lookupOrNull(from, SmallVector<Type, 1>{desiredType});
+    if (vals.empty())
+      return Value();
+    assert(vals.size() == 1 && "expected single value");
+    return vals.front();
+  }
+
+  void erase(Value from) { mapping.erase(from); }
+
+  void map(Value from, ArrayRef<BlockArgument> to) {
+    SmallVector<Value> vals;
+    for (Value v : to)
+      vals.push_back(v);
+    map(from, vals);
+  }
+
+  void map(Value from, ArrayRef<Value> to) {
+#ifndef NDEBUG
+    assert(from && "expected non-null value");
+    assert(!to.empty() && "cannot map to zero values");
+    for (Value v : to)
+      assert(v && "expected non-null value");
+#endif
+    // assert(from != to && "cannot map value to itself");
+    //  TODO: Check for cyclic mapping.
+    assert(!mapping.contains(from) && "value is already mapped");
+    mapping[from].assign(to.begin(), to.end());
   }
 
-  /// Try to map a value to the one provided. Returns false if a transitive
-  /// mapping from the new value to the old value already exists, true if the
-  /// map was updated.
-  bool tryMap(Value oldVal, Value newVal);
+  void mapMaterialization(SmallVector<Value, 1> from,
+                          SmallVector<Value, 1> to) {
+#ifndef NDEBUG
+    assert(!from.empty() && "from cannot be empty");
+    assert(!to.empty() && "to cannot be empty");
+    for (Value v : from) {
+      assert(v && "expected non-null value");
+      assert(!mapping.contains(v) &&
+             "cannot add materialization for mapped value");
+    }
+    for (Value v : to) {
+      assert(v && "expected non-null value");
+    }
+    assert(TypeRange(from) != TypeRange(to) &&
+           "cannot add materialization for identical type");
+    for (const SmallVector<Value, 1> &mat : materializations[from])
+      assert(TypeRange(mat) != TypeRange(to) &&
+             "cannot register duplicate materialization");
+#endif // NDEBUG
+    materializations[from].push_back(to);
+  }
 
-  /// Drop the last mapping for the given value.
-  void erase(Value value) { mapping.erase(value); }
+  void eraseMaterialization(SmallVector<Value, 1> from,
+                            SmallVector<Value, 1> to) {
+    auto it = llvm::find(materializations[from], to);
+    if (it == materializations[from].end())
+      return;
+    materializations[from].erase(it);
+  }
 
   /// Returns the inverse raw value mapping (without recursive query support).
   DenseMap<Value, SmallVector<Value>> getInverse() const {
     DenseMap<Value, SmallVector<Value>> inverse;
-    for (auto &it : mapping.getValueMap())
-      inverse[it.second].push_back(it.first);
+
+    for (auto &it : mapping)
+      for (Value v : it.second)
+        inverse[v].push_back(it.first);
+
+    for (auto &it : materializations)
+      for (const SmallVector<Value, 1> &mat : it.second)
+        for (Value v : mat)
+          for (Value v2 : it.first)
+            inverse[v].push_back(v2);
+
     return inverse;
   }
 
 private:
-  /// Current value mappings.
-  IRMapping mapping;
+  /// Replacement mapping: Value -> ValueRange
+  DenseMap<Value, SmallVector<Value, 1>> mapping;
+
+  /// Materializations: ValueRange -> ValueRange*
+  DenseMap<SmallVector<Value, 1>, SmallVector<SmallVector<Value, 1>>,
+           SmallVectorMapInfo>
+      materializations;
 };
 } // namespace
 
-Value ConversionValueMapping::lookupOrDefault(Value from,
-                                              Type desiredType) const {
-  // Try to find the deepest value that has the desired type. If there is no
-  // such value, simply return the deepest value.
-  Value desiredValue;
-  do {
-    if (!desiredType || from.getType() == desiredType)
-      desiredValue = from;
-
-    Value mappedValue = mapping.lookupOrNull(from);
-    if (!mappedValue)
-      break;
-    from = mappedValue;
-  } while (true);
+SmallVector<Value, 1>
+ConversionValueMapping::lookupOrDefault(Value from) const {
+  SmallVector<Value, 1> to = lookupOrNull(from);
+  return to.empty() ? SmallVector<Value, 1>{from} : to;
+}
 
-  // If the desired value was found use it, otherwise default to the leaf value.
-  return desiredValue ? desiredValue : from;
+SmallVector<Value, 1> ConversionValueMapping::lookupOrDefault(
+    Value from, SmallVector<Type, 1> desiredTypes) const {
+#ifndef NDEBUG
+  assert(desiredTypes.size() > 0 && "expected non-empty types");
+  for (Type t : desiredTypes)
+    assert(t && "expected non-null type");
+#endif // NDEBUG
+
+  SmallVector<Value, 1> vals = lookupOrNull(from);
+  if (vals.empty()) {
+    // Value is not mapped. Return if the type matches.
+    if (TypeRange(from) == desiredTypes)
+      return {from};
+    // Check materializations.
+    auto it = materializations.find({from});
+    if (it == materializations.end())
+      return {};
+    for (const SmallVector<Value, 1> &mat : it->second)
+      if (TypeRange(mat) == desiredTypes)
+        return mat;
+    return {};
+  }
+
+  return lookupOrNull(from, desiredTypes);
 }
 
-Value ConversionValueMapping::lookupOrNull(Value from, Type desiredType) const {
-  Value result = lookupOrDefault(from, desiredType);
-  if (result == from || (desiredType && result.getType() != desiredType))
-    return nullptr;
+SmallVector<Value, 1> ConversionValueMapping::lookupOrNull(Value from) const {
+  auto it = mapping.find(from);
+  if (it == mapping.end())
+    return {};
+  SmallVector<Value, 1> result;
+  for (Value v : it->second) {
+    llvm::append_range(result, lookupOrDefault(v));
+  }
   return result;
 }
 
-bool ConversionValueMapping::tryMap(Value oldVal, Value newVal) {
-  for (Value it = newVal; it; it = mapping.lookupOrNull(it))
-    if (it == oldVal)
-      return false;
-  map(oldVal, newVal);
-  return true;
+SmallVector<Value, 1>
+ConversionValueMapping::lookupOrNull(Value from,
+                                     SmallVector<Type, 1> desiredTypes) const {
+#ifndef NDEBUG
+  assert(desiredTypes.size() > 0 && "expected non-empty types");
+  for (Type t : desiredTypes)
+    assert(t && "expected non-null type");
+#endif // NDEBUG
+
+  SmallVector<Value, 1> vals = lookupOrNull(from);
+  if (vals.empty())
+    return {};
+
+  // There is a mapping and the types match.
+  if (TypeRange(vals) == desiredTypes)
+    return vals;
+
+  // There is a mapping, but the types do not match. Try to find a matching
+  // materialization.
+  auto it = materializations.find(vals);
+  if (it == materializations.end())
+    return {};
+  for (const SmallVector<Value, 1> &mat : it->second)
+    if (TypeRange(mat) == desiredTypes)
+      return mat;
+
+  // No materialization found. Return an empty vector.
+  return {};
 }
 
 //===----------------------------------------------------------------------===//
@@ -812,11 +946,12 @@ struct ConversionPatternRewriterImpl : public RewriterBase::Listener {
 
   /// Build an unresolved materialization operation given an output type and set
   /// of input operands.
-  Value buildUnresolvedMaterialization(MaterializationKind kind,
-                                       OpBuilder::InsertPoint ip, Location loc,
-                                       ValueRange inputs, Type outputType,
-                                       Type originalType,
-                                       const TypeConverter *converter);
+  ValueRange buildUnresolvedMaterialization(MaterializationKind kind,
+                                            OpBuilder::InsertPoint ip,
+                                            Location loc, ValueRange inputs,
+                                            TypeRange outputTypes,
+                                            Type originalType,
+                                            const TypeConverter *converter);
 
   //===--------------------------------------------------------------------===//
   // Rewriter Notification Hooks
@@ -827,7 +962,8 @@ struct ConversionPatternRewriterImpl : public RewriterBase::Listener {
                                OpBuilder::InsertPoint previous) override;
 
   /// Notifies that an op is about to be replaced with the given values.
-  void notifyOpReplaced(Operation *op, ValueRange newValues);
+  void notifyOpReplaced(Operation *op,
+                        ArrayRef<SmallVector<Value, 1>> newValues);
 
   /// Notifies that a block is about to be erased.
   void notifyBlockIsBeingErased(Block *block);
@@ -1051,10 +1187,8 @@ UnresolvedMaterializationRewrite::UnresolvedMaterializationRewrite(
 }
 
 void UnresolvedMaterializationRewrite::rollback() {
-  if (getMaterializationKind() == MaterializationKind::Target) {
-    for (Value input : op->getOperands())
-      rewriterImpl.mapping.erase(input);
-  }
+  rewriterImpl.mapping.eraseMaterialization(op->getOperands(),
+                                            op->getResults());
   rewriterImpl.unresolvedMaterializations.erase(getOperation());
   op->erase();
 }
@@ -1111,7 +1245,8 @@ LogicalResult ConversionPatternRewriterImpl::remapValues(
       // The current pattern does not have a type converter. I.e., it does not
       // distinguish between legal and illegal types. For each operand, simply
       // pass through the most recently mapped value.
-      remapped.push_back({mapping.lookupOrDefault(operand)});
+      SmallVector<Value, 1> vals = mapping.lookupOrDefault(operand);
+      remapped.push_back(vals);
       continue;
     }
 
@@ -1125,35 +1260,24 @@ LogicalResult ConversionPatternRewriterImpl::remapValues(
       return failure();
     }
 
-    if (legalTypes.size() != 1) {
-      // TODO: Parts of the dialect conversion infrastructure do not support
-      // 1->N type conversions yet. Therefore, if a type is converted to 0 or
-      // multiple types, the only thing that we can do for now is passing
-      // through the most recently mapped value. Fixing this requires
-      // improvements to the `ConversionValueMapping` (to be able to store 1:N
-      // mappings) and to the `ConversionPattern` adaptor handling (to be able
-      // to pass multiple remapped values for a single operand to the adaptor).
-      remapped.push_back({mapping.lookupOrDefault(operand)});
+    // Try to find a mapped value with the desired type.
+    SmallVector<Value, 1> mat = mapping.lookupOrDefault(operand, legalTypes);
+    if (!mat.empty()) {
+      // Mapped value has the correct type or there is an existing
+      // materialization. Or the value is not mapped at all and has the
+      // correct type.
+      remapped.push_back(mat);
       continue;
     }
 
-    // Handle 1->1 type conversions.
-    Type desiredType = legalTypes.front();
-    // Try to find a mapped value with the desired type. (Or the operand itself
-    // if the value is not mapped at all.)
-    Value newOperand = mapping.lookupOrDefault(operand, desiredType);
-    if (newOperand.getType() != desiredType) {
-      // If the looked up value's type does not have the desired type, it means
-      // that the value was replaced with a value of different type and no
-      // source materialization was created yet.
-      Value castValue = buildUnresolvedMaterialization(
-          MaterializationKind::Target, computeInsertPoint(newOperand),
-          operandLoc, /*inputs=*/newOperand, /*outputType=*/desiredType,
-          /*originalType=*/origType, currentTypeConverter);
-      mapping.map(newOperand, castValue);
-      newOperand = castValue;
-    }
-    remapped.push_back({newOperand});
+    // Create a materialization for the most recently mapped value.
+    SmallVector<Value, 1> vals = mapping.lookupOrDefault(operand);
+    ValueRange castValues = buildUnresolvedMaterialization(
+        MaterializationKind::Target, computeInsertPoint(vals), operandLoc,
+        /*inputs=*/vals, /*outputTypes=*/legalTypes, /*originalType=*/origType, currentTypeConverter);
+
+    mapping.mapMaterialization(vals, castValues);
+    remapped.push_back(castValues);
   }
   return success();
 }
@@ -1265,7 +1389,7 @@ Block *ConversionPatternRewriterImpl::applySignatureConversion(
           MaterializationKind::Source,
           OpBuilder::InsertPoint(newBlock, newBlock->begin()), origArg.getLoc(),
           /*inputs=*/ValueRange(),
-          /*outputType=*/origArgType, /*originalType=*/Type(), converter);
+          /*outputTypes=*/origArgType, /*originalType=*/Type(), converter)[0];
       mapping.map(origArg, repl);
       appendRewrite<ReplaceBlockArgRewrite>(block, origArg);
       continue;
@@ -1281,39 +1405,10 @@ Block *ConversionPatternRewriterImpl::applySignatureConversion(
       continue;
     }
 
-    // This is a 1->1+ mapping. 1->N mappings are not fully supported in the
-    // dialect conversion. Therefore, we need an argument materialization to
-    // turn the replacement block arguments into a single SSA value that can be
-    // used as a replacement.
+    // Map to replacement arguments.
     auto replArgs =
         newBlock->getArguments().slice(inputMap->inputNo, inputMap->size);
-    Value argMat = buildUnresolvedMaterialization(
-        MaterializationKind::Argument,
-        OpBuilder::InsertPoint(newBlock, newBlock->begin()), origArg.getLoc(),
-        /*inputs=*/replArgs, /*outputType=*/origArgType,
-        /*originalType=*/Type(), converter);
-    mapping.map(origArg, argMat);
-
-    Type legalOutputType;
-    if (converter) {
-      legalOutputType = converter->convertType(origArgType);
-    } else if (replArgs.size() == 1) {
-      // When there is no type converter, assume that the new block argument
-      // types are legal. This is reasonable to assume because they were
-      // specified by the user.
-      // FIXME: This won't work for 1->N conversions because multiple output
-      // types are not supported in parts of the dialect conversion. In such a
-      // case, we currently use the original block argument type (produced by
-      // the argument materialization).
-      legalOutputType = replArgs[0].getType();
-    }
-    if (legalOutputType && legalOutputType != origArgType) {
-      Value targetMat = buildUnresolvedMaterialization(
-          MaterializationKind::Target, computeInsertPoint(argMat),
-          origArg.getLoc(), /*inputs=*/argMat, /*outputType=*/legalOutputType,
-          /*originalType=*/origArgType, converter);
-      mapping.map(argMat, targetMat);
-    }
+    mapping.map(origArg, replArgs);
     appendRewrite<ReplaceBlockArgRewrite>(block, origArg);
   }
 
@@ -1332,26 +1427,21 @@ Block *ConversionPatternRewriterImpl::applySignatureConversion(
 
 /// Build an unresolved materialization operation given an output type and set
 /// of input operands.
-Value ConversionPatternRewriterImpl::buildUnresolvedMaterialization(
+ValueRange ConversionPatternRewriterImpl::buildUnresolvedMaterialization(
     MaterializationKind kind, OpBuilder::InsertPoint ip, Location loc,
-    ValueRange inputs, Type outputType, Type originalType,
-    const TypeConverter *converter) {
-  assert((!originalType || kind == MaterializationKind::Target) &&
-         "original type is valid only for target materializations");
-
+    ValueRange inputs, TypeRange outputTypes, Type originalType, const TypeConverter *converter) {
   // Avoid materializing an unnecessary cast.
-  if (inputs.size() == 1 && inputs.front().getType() == outputType)
-    return inputs.front();
+  if (TypeRange(inputs) == outputTypes)
+    return inputs;
 
   // Create an unresolved materialization. We use a new OpBuilder to avoid
   // tracking the materialization like we do for other operations.
-  OpBuilder builder(outputType.getContext());
+  OpBuilder builder(outputTypes.front().getContext());
   builder.setInsertionPoint(ip.getBlock(), ip.getPoint());
   auto convertOp =
-      builder.create<UnrealizedConversionCastOp>(loc, outputType, inputs);
-  appendRewrite<UnresolvedMaterializationRewrite>(convertOp, converter, kind,
-                                                  originalType);
-  return convertOp.getResult(0);
+      builder.create<UnrealizedConversionCastOp>(loc, outputTypes, inputs);
+  appendRewrite<UnresolvedMaterializationRewrite>(convertOp, converter, kind, originalType);
+  return convertOp.getResults();
 }
 
 //===----------------------------------------------------------------------===//
@@ -1377,8 +1467,8 @@ void ConversionPatternRewriterImpl::notifyOperationInserted(
   appendRewrite<MoveOperationRewrite>(op, previous.getBlock(), prevOp);
 }
 
-void ConversionPatternRewriterImpl::notifyOpReplaced(Operation *op,
-                                                     ValueRange newValues) {
+void ConversionPatternRewriterImpl::notifyOpReplaced(
+    Operation *op, ArrayRef<SmallVector<Value, 1>> newValues) {
   assert(newValues.size() == op->getNumResults());
   assert(!ignoredOps.contains(op) && "operation was already replaced");
 
@@ -1390,8 +1480,9 @@ void ConversionPatternRewriterImpl::notifyOpReplaced(Operation *op,
       isUnresolvedMaterialization = true;
 
   // Create mappings for each of the new result values.
-  for (auto [newValue, result] : llvm::zip(newValues, op->getResults())) {
-    if (!newValue) {
+  for (auto [n, result] : llvm::zip(newValues, op->getResults())) {
+    SmallVector<Value, 1> repl = n;
+    if (repl.empty()) {
       // This result was dropped and no replacement value was provided.
       if (isUnresolvedMaterialization) {
         // Do not create another materializations if we are erasing a
@@ -1400,7 +1491,7 @@ void ConversionPatternRewriterImpl::notifyOpReplaced(Operation *op,
       }
 
       // Materialize a replacement value "out of thin air".
-      newValue = buildUnresolvedMaterialization(
+      repl = buildUnresolvedMaterialization(
           MaterializationKind::Source, computeInsertPoint(result),
           result.getLoc(), /*inputs=*/ValueRange(),
           /*outputType=*/result.getType(), /*originalType=*/Type(),
@@ -1417,8 +1508,8 @@ void ConversionPatternRewriterImpl::notifyOpReplaced(Operation *op,
     }
 
     // Remap result to replacement value.
-    if (newValue)
-      mapping.map(result, newValue);
+    if (!repl.empty())
+      mapping.map(result, repl);
   }
 
   appendRewrite<ReplaceOperationRewrite>(op, currentTypeConverter);
@@ -1497,7 +1588,25 @@ void ConversionPatternRewriter::replaceOp(Operation *op, ValueRange newValues) {
     impl->logger.startLine()
         << "** Replace : '" << op->getName() << "'(" << op << ")\n";
   });
-  impl->notifyOpReplaced(op, newValues);
+  SmallVector<SmallVector<Value, 1>> newVals(newValues.size(), {});
+  for (auto it : llvm::enumerate(newValues))
+    if (it.value())
+      newVals[it.index()].push_back(it.value());
+  impl->notifyOpReplaced(op, newVals);
+}
+
+void ConversionPatternRewriter::replaceOpWithMultiple(
+    Operation *op, ArrayRef<ValueRange> newValues) {
+  assert(op->getNumResults() == newValues.size() &&
+         "incorrect # of replacement values");
+  LLVM_DEBUG({
+    impl->logger.startLine()
+        << "** Replace : '" << op->getName() << "'(" << op << ")\n";
+  });
+  SmallVector<SmallVector<Value, 1>> newVals(newValues.size(), {});
+  for (auto it : llvm::enumerate(newValues))
+    llvm::append_range(newVals[it.index()], it.value());
+  impl->notifyOpReplaced(op, newVals);
 }
 
 void ConversionPatternRewriter::eraseOp(Operation *op) {
@@ -1505,7 +1614,7 @@ void ConversionPatternRewriter::eraseOp(Operation *op) {
     impl->logger.startLine()
         << "** Erase   : '" << op->getName() << "'(" << op << ")\n";
   });
-  SmallVector<Value, 1> nullRepls(op->getNumResults(), nullptr);
+  SmallVector<SmallVector<Value, 1>> nullRepls(op->getNumResults(), {});
   impl->notifyOpReplaced(op, nullRepls);
 }
 
@@ -1552,7 +1661,7 @@ void ConversionPatternRewriter::replaceUsesOfBlockArgument(BlockArgument from,
                              << "'(" << from.getOwner()->getParentOp() << ")\n";
   });
   impl->appendRewrite<ReplaceBlockArgRewrite>(from.getOwner(), from);
-  impl->mapping.map(impl->mapping.lookupOrDefault(from), to);
+  impl->mapping.map(from, to);
 }
 
 Value ConversionPatternRewriter::getRemappedValue(Value key) {
@@ -1672,13 +1781,16 @@ detail::ConversionPatternRewriterImpl &ConversionPatternRewriter::getImpl() {
 //===----------------------------------------------------------------------===//
 
 SmallVector<Value> ConversionPattern::getOneToOneAdaptorOperands(
-    ArrayRef<ArrayRef<Value>> operands) {
+    ArrayRef<ArrayRef<Value>> operands) const {
   SmallVector<Value> oneToOneOperands;
   oneToOneOperands.reserve(operands.size());
   for (ArrayRef<Value> operand : operands) {
-    assert(operand.size() == 1 && "pattern does not support 1:N conversion");
+    if (operand.size() != 1)
+      llvm::report_fatal_error("pattern '" + getDebugName() +
+                               "' does not support 1:N conversion");
     oneToOneOperands.push_back(operand.front());
   }
+  return oneToOneOperands;
 }
 
 LogicalResult
@@ -1697,12 +1809,13 @@ ConversionPattern::matchAndRewrite(Operation *op,
                                       op->getOperands(), remapped))) {
     return failure();
   }
-  SmallVector<Value, 4> operands;
-  for (const auto &values : remapped) {
-    assert(values.size() == 1 && "1:N conversion not supported");
-    operands.push_back(values.front());
-  }
-  return matchAndRewrite(op, operands, dialectRewriter);
+
+  // Convert to ArrayRef.
+  // TODO: This should not be necessary.
+  SmallVector<ArrayRef<Value>> remappedArrayRef;
+  for (const auto &vals : remapped)
+    remappedArrayRef.push_back(vals);
+  return matchAndRewrite(op, remappedArrayRef, dialectRewriter);
 }
 
 //===----------------------------------------------------------------------===//
@@ -2616,16 +2729,16 @@ void OperationConverter::finalize(ConversionPatternRewriter &rewriter) {
         continue;
 
       // Legalize this value replacement.
-      Value newValue = rewriterImpl.mapping.lookupOrNull(originalValue);
-      assert(newValue && "replacement value not found");
+      SmallVector<Value, 1> newValues =
+          rewriterImpl.mapping.lookupOrNull(originalValue);
+      assert(!newValues.empty() && "replacement value not found");
       Value castValue = rewriterImpl.buildUnresolvedMaterialization(
-          MaterializationKind::Source, computeInsertPoint(newValue),
+          MaterializationKind::Source, computeInsertPoint(newValues),
           originalValue.getLoc(),
-          /*inputs=*/newValue, /*outputType=*/originalValue.getType(),
-          /*originalType=*/Type(), converter);
-      rewriterImpl.mapping.map(originalValue, castValue);
-      inverseMapping[castValue].push_back(originalValue);
-      llvm::erase(inverseMapping[newValue], originalValue);
+          /*inputs=*/newValues, /*outputTypes=*/originalValue.getType(), /*originalType=*/Type(),
+          converter)[0];
+      rewriterImpl.mapping.mapMaterialization(newValues, {castValue});
+      llvm::append_range(inverseMapping[castValue], newValues);
     }
   }
 }
diff --git a/mlir/test/Conversion/FuncToLLVM/calling-convention.mlir b/mlir/test/Conversion/FuncToLLVM/calling-convention.mlir
index 18734d19e335c9..9143b9334d9354 100644
--- a/mlir/test/Conversion/FuncToLLVM/calling-convention.mlir
+++ b/mlir/test/Conversion/FuncToLLVM/calling-convention.mlir
@@ -1,5 +1,5 @@
-// RUN: mlir-opt -finalize-memref-to-llvm -llvm-request-c-wrappers -convert-func-to-llvm -reconcile-unrealized-casts %s | FileCheck %s
-// RUN: mlir-opt -finalize-memref-to-llvm -convert-func-to-llvm -reconcile-unrealized-casts %s | FileCheck %s --check-prefix=EMIT_C_ATTRIBUTE
+// RUN: mlir-opt -llvm-request-c-wrappers -convert-func-to-llvm -finalize-memref-to-llvm -reconcile-unrealized-casts %s | FileCheck %s
+// RUN: mlir-opt -convert-func-to-llvm -finalize-memref-to-llvm -reconcile-unrealized-casts %s | FileCheck %s --check-prefix=EMIT_C_ATTRIBUTE
 
 // This tests the default memref calling convention and the emission of C
 // wrappers. We don't need to separate runs because the wrapper-emission
diff --git a/mlir/test/lib/Dialect/Test/TestPatterns.cpp b/mlir/test/lib/Dialect/Test/TestPatterns.cpp
index 3eade0369f7654..e1bbf42f761fa9 100644
--- a/mlir/test/lib/Dialect/Test/TestPatterns.cpp
+++ b/mlir/test/lib/Dialect/Test/TestPatterns.cpp
@@ -994,6 +994,7 @@ struct TestUpdateConsumerType : public ConversionPattern {
   LogicalResult
   matchAndRewrite(Operation *op, ArrayRef<Value> operands,
                   ConversionPatternRewriter &rewriter) const final {
+    llvm::errs() << "TestUpdateConsumerType operand: " << operands.front() << "\n";
     // Verify that the incoming operand has been successfully remapped to F64.
     if (!operands[0].getType().isF64())
       return failure();
diff --git a/mlir/test/mlir-cpu-runner/async-value.mlir b/mlir/test/mlir-cpu-runner/async-value.mlir
index 836b40a222a9e6..b20d8e48da94cd 100644
--- a/mlir/test/mlir-cpu-runner/async-value.mlir
+++ b/mlir/test/mlir-cpu-runner/async-value.mlir
@@ -1,4 +1,4 @@
-// RUN:   mlir-opt %s -pass-pipeline="builtin.module(async-to-async-runtime,func.func(async-runtime-ref-counting,async-runtime-ref-counting-opt),convert-async-to-llvm,func.func(convert-arith-to-llvm),convert-vector-to-llvm,finalize-memref-to-llvm,convert-func-to-llvm,reconcile-unrealized-casts)" \
+// RUN:   mlir-opt %s -pass-pipeline="builtin.module(async-to-async-runtime,func.func(async-runtime-ref-counting,async-runtime-ref-counting-opt),convert-async-to-llvm,func.func(convert-arith-to-llvm),convert-vector-to-llvm,convert-func-to-llvm,finalize-memref-to-llvm,reconcile-unrealized-casts)" \
 // RUN: | mlir-cpu-runner                                                      \
 // RUN:     -e main -entry-point-result=void -O0                               \
 // RUN:     -shared-libs=%mlir_c_runner_utils  \
diff --git a/mlir/test/mlir-cpu-runner/bare-ptr-call-conv.mlir b/mlir/test/mlir-cpu-runner/bare-ptr-call-conv.mlir
index 8bbaf3fbcd5f33..05927ae371bad9 100644
--- a/mlir/test/mlir-cpu-runner/bare-ptr-call-conv.mlir
+++ b/mlir/test/mlir-cpu-runner/bare-ptr-call-conv.mlir
@@ -1,4 +1,4 @@
-// RUN: mlir-opt %s -pass-pipeline="builtin.module(func.func(convert-scf-to-cf,convert-arith-to-llvm),finalize-memref-to-llvm,convert-func-to-llvm{use-bare-ptr-memref-call-conv=1},reconcile-unrealized-casts)" | mlir-cpu-runner -shared-libs=%mlir_c_runner_utils -entry-point-result=void | FileCheck %s
+// RUN: mlir-opt %s -pass-pipeline="builtin.module(func.func(convert-scf-to-cf,convert-arith-to-llvm),convert-func-to-llvm{use-bare-ptr-memref-call-conv=1},finalize-memref-to-llvm,reconcile-unrealized-casts)" | mlir-cpu-runner -shared-libs=%mlir_c_runner_utils -entry-point-result=void | FileCheck %s
 
 // Verify bare pointer memref calling convention. `simple_add1_add2_test`
 // gets two 2xf32 memrefs, adds 1.0f to the first one and 2.0f to the second
diff --git a/mlir/test/mlir-cpu-runner/memref-reinterpret-cast.mlir b/mlir/test/mlir-cpu-runner/memref-reinterpret-cast.mlir
index f8f9d353fa3def..c981389786cd7d 100644
--- a/mlir/test/mlir-cpu-runner/memref-reinterpret-cast.mlir
+++ b/mlir/test/mlir-cpu-runner/memref-reinterpret-cast.mlir
@@ -1,4 +1,4 @@
-// RUN: mlir-opt %s -pass-pipeline="builtin.module(func.func(convert-scf-to-cf),finalize-memref-to-llvm,func.func(convert-arith-to-llvm),convert-func-to-llvm,reconcile-unrealized-casts)" \
+// RUN: mlir-opt %s -pass-pipeline="builtin.module(func.func(convert-scf-to-cf),func.func(convert-arith-to-llvm),convert-func-to-llvm,finalize-memref-to-llvm,reconcile-unrealized-casts)" \
 // RUN: | mlir-cpu-runner -e main -entry-point-result=void \
 // RUN: -shared-libs=%mlir_runner_utils,%mlir_c_runner_utils \
 // RUN: | FileCheck %s
diff --git a/mlir/test/mlir-cpu-runner/memref-reshape.mlir b/mlir/test/mlir-cpu-runner/memref-reshape.mlir
index fc74d644c1587f..cbd0c11ca1bda5 100644
--- a/mlir/test/mlir-cpu-runner/memref-reshape.mlir
+++ b/mlir/test/mlir-cpu-runner/memref-reshape.mlir
@@ -1,4 +1,4 @@
-// RUN: mlir-opt %s -pass-pipeline="builtin.module(func.func(convert-scf-to-cf,memref-expand,convert-arith-to-llvm),finalize-memref-to-llvm,convert-func-to-llvm,reconcile-unrealized-casts)" \
+// RUN: mlir-opt %s -pass-pipeline="builtin.module(func.func(convert-scf-to-cf,memref-expand,convert-arith-to-llvm),convert-func-to-llvm,finalize-memref-to-llvm,reconcile-unrealized-casts)" \
 // RUN: | mlir-cpu-runner -e main -entry-point-result=void \
 // RUN: -shared-libs=%mlir_runner_utils,%mlir_c_runner_utils \
 // RUN: | FileCheck %s
diff --git a/mlir/test/mlir-cpu-runner/sgemm-naive-codegen.mlir b/mlir/test/mlir-cpu-runner/sgemm-naive-codegen.mlir
index c82e78b4c6a187..5c45a874aaee6f 100644
--- a/mlir/test/mlir-cpu-runner/sgemm-naive-codegen.mlir
+++ b/mlir/test/mlir-cpu-runner/sgemm-naive-codegen.mlir
@@ -1,4 +1,4 @@
-// RUN: mlir-opt -pass-pipeline="builtin.module(func.func(convert-linalg-to-loops,lower-affine,convert-scf-to-cf,convert-arith-to-llvm),convert-vector-to-llvm,finalize-memref-to-llvm,convert-func-to-llvm,reconcile-unrealized-casts)" %s | mlir-cpu-runner -O3 -e main -entry-point-result=void -shared-libs=%mlir_c_runner_utils | FileCheck %s
+// RUN: mlir-opt -pass-pipeline="builtin.module(func.func(convert-linalg-to-loops,lower-affine,convert-scf-to-cf,convert-arith-to-llvm),convert-vector-to-llvm,convert-func-to-llvm,finalize-memref-to-llvm,reconcile-unrealized-casts)" %s | mlir-cpu-runner -O3 -e main -entry-point-result=void -shared-libs=%mlir_c_runner_utils | FileCheck %s
 
 func.func @main() {
   %A = memref.alloc() : memref<16x16xf32>
diff --git a/mlir/test/mlir-cpu-runner/unranked-memref.mlir b/mlir/test/mlir-cpu-runner/unranked-memref.mlir
index 5b33ecb4519074..3d05defe0b630d 100644
--- a/mlir/test/mlir-cpu-runner/unranked-memref.mlir
+++ b/mlir/test/mlir-cpu-runner/unranked-memref.mlir
@@ -1,4 +1,4 @@
-// RUN: mlir-opt %s -pass-pipeline="builtin.module(func.func(convert-linalg-to-loops,convert-scf-to-cf,convert-arith-to-llvm),finalize-memref-to-llvm,convert-func-to-llvm,reconcile-unrealized-casts)" |        \
+// RUN: mlir-opt %s -pass-pipeline="builtin.module(func.func(convert-linalg-to-loops,convert-scf-to-cf,convert-arith-to-llvm),convert-func-to-llvm,finalize-memref-to-llvm,reconcile-unrealized-casts)" |        \
 // RUN: mlir-cpu-runner -e main -entry-point-result=void \
 // RUN: -shared-libs=%mlir_runner_utils,%mlir_c_runner_utils | FileCheck %s
 
diff --git a/mlir/unittests/ExecutionEngine/Invoke.cpp b/mlir/unittests/ExecutionEngine/Invoke.cpp
index ff87fc9fad805a..b945396bd6384e 100644
--- a/mlir/unittests/ExecutionEngine/Invoke.cpp
+++ b/mlir/unittests/ExecutionEngine/Invoke.cpp
@@ -53,9 +53,9 @@ static struct LLVMInitializer {
 /// dialects lowering to LLVM Dialect.
 static LogicalResult lowerToLLVMDialect(ModuleOp module) {
   PassManager pm(module->getName());
-  pm.addPass(mlir::createFinalizeMemRefToLLVMConversionPass());
   pm.addNestedPass<func::FuncOp>(mlir::createArithToLLVMConversionPass());
   pm.addPass(mlir::createConvertFuncToLLVMPass());
+  pm.addPass(mlir::createFinalizeMemRefToLLVMConversionPass());
   pm.addPass(mlir::createReconcileUnrealizedCastsPass());
   return pm.run(module);
 }



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