[mlir][Vector] Add constant folding for vector.from_elements operation (llvm#145849)

### Summary

This PR adds a new folding pattern for **vector.from_elements** that
canonicalizes it to **arith.constant** when all input operands are
constants.

### Implementation Details

**Leverages FoldAdaptor capabilities**: Uses adaptor.getElements() to
access **pre-computed** constant attributes, avoiding redundant pattern
matching on operands.

### Example Transformation
```
Before:
%c0_i32 = arith.constant 0 : i32
%c1_i32 = arith.constant 1 : i32
%c2_i32 = arith.constant 2 : i32
%c3_i32 = arith.constant 3 : i32
%v = vector.from_elements %c0_i32, %c1_i32, %c2_i32, %c3_i32 : vector<2x2xi32>

After:
%v = arith.constant dense<[[0, 1], [2, 3]]> : vector<2x2xi32>
```

---------

Co-authored-by: Yang Bai <[email protected]>

Author: yangtetris

mlir/lib/Dialect/Vector/IR/VectorOps.cpp

@@ -398,6 +398,18 @@ std::optional<int64_t> vector::getConstantVscaleMultiplier(Value value) {
   return {};
 }
 
+/// Converts an IntegerAttr to have the specified type if needed.
+/// This handles cases where constant attributes have a different type than the
+/// target element type. If the input attribute is not an IntegerAttr or already
+/// has the correct type, returns it unchanged.
+static Attribute convertIntegerAttr(Attribute attr, Type expectedType) {
+  if (auto intAttr = mlir::dyn_cast<IntegerAttr>(attr)) {
+    if (intAttr.getType() != expectedType)
+      return IntegerAttr::get(expectedType, intAttr.getInt());
+  }
+  return attr;
+}
+
 //===----------------------------------------------------------------------===//
 // CombiningKindAttr
 //===----------------------------------------------------------------------===//
@@ -2464,8 +2476,37 @@ static OpFoldResult foldFromElementsToElements(FromElementsOp fromElementsOp) {
   return {};
 }
 
+/// Fold vector.from_elements to a constant when all operands are constants.
+/// Example:
+///   %c1 = arith.constant 1 : i32
+///   %c2 = arith.constant 2 : i32
+///   %v = vector.from_elements %c1, %c2 : vector<2xi32>
+/// =>
+///   %v = arith.constant dense<[1, 2]> : vector<2xi32>
+///
+static OpFoldResult foldFromElementsToConstant(FromElementsOp fromElementsOp,
+                                               ArrayRef<Attribute> elements) {
+  if (llvm::any_of(elements, [](Attribute attr) { return !attr; }))
+    return {};
+
+  auto destVecType = fromElementsOp.getDest().getType();
+  auto destEltType = destVecType.getElementType();
+  // Constant attributes might have a different type than the return type.
+  // Convert them before creating the dense elements attribute.
+  auto convertedElements = llvm::map_to_vector(elements, [&](Attribute attr) {
+    return convertIntegerAttr(attr, destEltType);
+  });
+
+  return DenseElementsAttr::get(destVecType, convertedElements);
+}
+
 OpFoldResult FromElementsOp::fold(FoldAdaptor adaptor) {
-  return foldFromElementsToElements(*this);
+  if (auto res = foldFromElementsToElements(*this))
+    return res;
+  if (auto res = foldFromElementsToConstant(*this, adaptor.getElements()))
+    return res;
+
+  return {};
 }
 
 /// Rewrite a vector.from_elements into a vector.splat if all elements are the
@@ -3332,17 +3373,6 @@ foldDenseElementsAttrDestInsertOp(InsertOp insertOp, Attribute srcAttr,
 
   /// Converts the expected type to an IntegerAttr if there's
   /// a mismatch.
-  auto convertIntegerAttr = [](Attribute attr, Type expectedType) -> Attribute {
-    if (auto intAttr = mlir::dyn_cast<IntegerAttr>(attr)) {
-      if (intAttr.getType() != expectedType)
-        return IntegerAttr::get(expectedType, intAttr.getInt());
-    }
-    return attr;
-  };
-
-  // The `convertIntegerAttr` method specifically handles the case
-  // for `llvm.mlir.constant` which can hold an attribute with a
-  // different type than the return type.
   if (auto denseSource = llvm::dyn_cast<DenseElementsAttr>(srcAttr)) {
     for (auto value : denseSource.getValues<Attribute>())
       insertedValues.push_back(convertIntegerAttr(value, destEltType));

mlir/test/Dialect/Vector/canonicalize.mlir

@@ -3075,6 +3075,33 @@ func.func @from_elements_to_elements_shuffle(%a: vector<4x2xf32>) -> vector<4x2x
 
 // -----
 
+// CHECK-LABEL: func @from_elements_all_elements_constant(
+func.func @from_elements_all_elements_constant() -> vector<2x2xi32> {
+  %c0_i32 = arith.constant 0 : i32
+  %c1_i32 = arith.constant 1 : i32
+  %c2_i32 = arith.constant 2 : i32
+  %c3_i32 = arith.constant 3 : i32
+  // CHECK: %[[RES:.*]] = arith.constant dense<{{\[\[0, 1\], \[2, 3\]\]}}> : vector<2x2xi32>
+  %res = vector.from_elements %c0_i32, %c1_i32, %c2_i32, %c3_i32 : vector<2x2xi32>
+  // CHECK: return %[[RES]]
+  return %res : vector<2x2xi32>
+}
+
+// -----
+
+// CHECK-LABEL: func @from_elements_partial_elements_constant(
+// CHECK-SAME:     %[[A:.*]]: f32
+func.func @from_elements_partial_elements_constant(%arg0: f32) -> vector<2xf32> {
+  // CHECK: %[[C:.*]] = arith.constant 1.000000e+00 : f32
+  %c = arith.constant 1.0 : f32
+  // CHECK: %[[RES:.*]] = vector.from_elements %[[A]], %[[C]] : vector<2xf32>
+  %res = vector.from_elements %arg0, %c : vector<2xf32>
+  // CHECK: return %[[RES]]
+  return %res : vector<2xf32>
+}
+
+// -----
+
 // CHECK-LABEL: func @vector_insert_const_regression(
 //       CHECK:   llvm.mlir.undef
 //       CHECK:   vector.insert