Integrate llvm-project and bump dependencies. (iree-org#12562)

* llvm-project: e510d0bda0876c4baa3a270dca39b95da7ec6d9e
* mlir-hlo: e86610442f58b889a57bf814d75c4b50c769c2a3
* tensorflow: 67ba341c869e30ee4a89e040cd875d12b9bc666e

Cherry-picked from LLVM:
```
commit 80074d5fc0ab3f165865b15f5bf55ffac0917bcd (HEAD -> integrate-3-8-2023, fork/integrate-3-8-2023)
Author: Matthias Springer <me@m-sp.org>
Date:   Fri Mar 10 11:25:15 2023 +0100

    [mlir][NFC] reifyResultShapes: Add extra error checking
    
    This change adds a new helper function `mlir::reifyResultShapes` that calls the corresponding interface method and also checks the result produced by the implementation when running in debug mode. Bugs due to incorrect interface implementations can be difficult to debug.
    
    This helper function also reduces the amount of code needed at call sites: the cast to `ReifyRankedShapedTypeOpInterface` is done in the helper function.
    
    Differential Revision: https://reviews.llvm.org/D145777

commit 32b15f601de173e9511f470f7423108d3154e582
Author: Matthias Springer <me@m-sp.org>
Date:   Fri Mar 10 11:24:43 2023 +0100

    [mlir][tensor/linalg] Fix bug in reifyResultShapes
    
    `reifyResultShapes` should return an IntegerAttr if and only if the corresponding dimension is static.
    
    Differential Revision: https://reviews.llvm.org/D145702

commit 894555cd6adf2e0faffe713373a266650b40bb4e
Author: David Green <david.green@arm.com>
Date:   Wed Mar 8 12:48:21 2023 +0000

    [AArch64] Fix load-insert-zero patterns with i8 and negative offsets.
    
    These should have been using the LDURBi instructions where the offset is
    negative, as reported from the reproducer in D144086.
```

Created a new commit on iree-mlir-hlo fork:


https://github.com/iree-org/iree-mhlo-fork/commit/b14e9d9b06255e4476f5698e3bfc531dec793ded

compiler/src/iree/compiler/Codegen/LLVMGPU/LLVMGPUTensorPad.cpp

@@ -85,7 +85,7 @@ static FailureOr<SmallVector<Value>> rewriteAsPaddedOp(
   // Slice out the original shape from the padded result to pass on to
   // consumers. The original linalg op is used to provide the dims for the reify
   // result shapes.
-  SmallVector<SmallVector<Value>> reifiedResultShapes;
+  SmallVector<SmallVector<OpFoldResult>> reifiedResultShapes;
   if (failed(cast<ReifyRankedShapedTypeOpInterface>(linalgOp.getOperation())
                  .reifyResultShapes(rewriter, reifiedResultShapes))) {
     return failure();
@@ -98,8 +98,7 @@ static FailureOr<SmallVector<Value>> rewriteAsPaddedOp(
     int64_t rank = paddedResult.getType().cast<RankedTensorType>().getRank();
     SmallVector<OpFoldResult> offsets(rank, rewriter.getIndexAttr(0));
     SmallVector<OpFoldResult> sizes;
-    for (Value v : reifiedResultShapes[resultNumber])
-      sizes.push_back(getAsOpFoldResult(v));
+    for (OpFoldResult v : reifiedResultShapes[resultNumber]) sizes.push_back(v);
     SmallVector<OpFoldResult> strides(rank, rewriter.getIndexAttr(1));
     paddedSubviewResults.push_back(rewriter.create<tensor::ExtractSliceOp>(
         loc, paddedResult, offsets, sizes, strides));
@@ -148,16 +147,15 @@ static FailureOr<Value> rewriteAsPaddedOp(IRRewriter &rewriter,
 
   // Slice out the original shape from the padded result to pass on to
   // consumers.
-  SmallVector<SmallVector<Value>> reifiedResultShapes;
+  SmallVector<SmallVector<OpFoldResult>> reifiedResultShapes;
   if (failed(op.reifyResultShapes(rewriter, reifiedResultShapes))) {
     return failure();
   }
 
   Value paddedSubviewResults;
   int64_t rank = paddedOp.getDestRank();
   SmallVector<OpFoldResult> offsets(rank, rewriter.getIndexAttr(0));
-  SmallVector<OpFoldResult> sizes =
-      getAsOpFoldResult(ValueRange(reifiedResultShapes[0]));
+  SmallVector<OpFoldResult> sizes = reifiedResultShapes[0];
   SmallVector<OpFoldResult> strides(rank, rewriter.getIndexAttr(1));
   paddedSubviewResults = rewriter.create<tensor::ExtractSliceOp>(
       loc, paddedOp.getResult(), offsets, sizes, strides);

compiler/src/iree/compiler/Codegen/Transforms/RemoveSingleIterationLoop.cpp

@@ -106,7 +106,7 @@ static void replaceOpWithRegion(PatternRewriter &rewriter, Operation *op,
   Block *block = &region.front();
   Operation *terminator = block->getTerminator();
   ValueRange results = terminator->getOperands();
-  rewriter.mergeBlockBefore(block, op, blockArgs);
+  rewriter.inlineBlockBefore(block, op, blockArgs);
   rewriter.replaceOp(op, results);
   rewriter.eraseOp(terminator);
 }

compiler/src/iree/compiler/Dialect/Flow/Conversion/TensorToFlow/Patterns.cpp

@@ -10,6 +10,7 @@
 #include "iree/compiler/Dialect/Flow/IR/FlowDialect.h"
 #include "iree/compiler/Dialect/Flow/IR/FlowOps.h"
 #include "mlir/Dialect/Arith/IR/Arith.h"
+#include "mlir/Dialect/Arith/Utils/Utils.h"
 #include "mlir/Dialect/Func/IR/FuncOps.h"
 #include "mlir/Dialect/Linalg/IR/Linalg.h"
 #include "mlir/Dialect/MemRef/Transforms/Passes.h"
@@ -177,18 +178,19 @@ struct ConvertTensorReshapePattern : public OpRewritePattern<TensorReshapeOp> {
     if (reshapeOp->template getParentOfType<Flow::DispatchWorkgroupsOp>()) {
       return failure();
     }
-    SmallVector<SmallVector<Value>> outputShape;
+    SmallVector<SmallVector<OpFoldResult>> outputShape;
     ReifyRankedShapedTypeOpInterface reifyShapedTypeInterface =
         cast<ReifyRankedShapedTypeOpInterface>(reshapeOp.getOperation());
     if (failed(reifyShapedTypeInterface.reifyResultShapes(rewriter,
                                                           outputShape))) {
       return failure();
     }
     SmallVector<Value> outputDynamicShapes;
-    for (auto [resultShape, outputShape] : llvm::zip_equal(
+    for (auto [resultShape, outputShp] : llvm::zip_equal(
              reshapeOp.getResultType().getShape(), outputShape[0])) {
       if (resultShape != ShapedType::kDynamic) continue;
-      outputDynamicShapes.push_back(outputShape);
+      outputDynamicShapes.push_back(getValueOrCreateConstantIndexOp(
+          rewriter, reshapeOp.getLoc(), outputShp));
     }
     rewriter.replaceOpWithNewOp<IREE::Flow::TensorReshapeOp>(
         reshapeOp, reshapeOp.getResultType(), reshapeOp.getSrc(),

compiler/src/iree/compiler/Dialect/Flow/IR/FlowOps.cpp

@@ -495,15 +495,15 @@ LogicalResult DispatchTieShapeOp::verify() {
 
 LogicalResult DispatchTieShapeOp::reifyResultShapes(
     OpBuilder &b, ReifiedRankedShapedTypeDims &reifiedReturnShapes) {
-  SmallVector<Value> shape;
+  SmallVector<OpFoldResult> shape;
   unsigned dynamicIdx = 0;
   auto tensorType =
       getResult().getType().cast<IREE::Flow::DispatchTensorType>();
   for (int64_t dim : tensorType.getShape()) {
     if (dim == ShapedType::kDynamic) {
       shape.push_back(getDynamicDims()[dynamicIdx++]);
     } else {
-      shape.push_back(b.create<arith::ConstantIndexOp>(getLoc(), dim));
+      shape.push_back(b.getIndexAttr(dim));
     }
   }
   reifiedReturnShapes.push_back(shape);
@@ -635,7 +635,7 @@ void DispatchTensorLoadOp::build(OpBuilder &builder, OperationState &state,
 LogicalResult DispatchTensorLoadOp::reifyResultShapes(
     OpBuilder &b, ReifiedRankedShapedTypeDims &reifiedReturnShapes) {
   auto mixedSizes = getMixedSizes();
-  SmallVector<Value> shape;
+  SmallVector<OpFoldResult> shape;
   if (!mixedSizes.empty()) {
     // Slicing out a tile; return the size sliced.
     shape.reserve(mixedSizes.size());
@@ -644,8 +644,7 @@ LogicalResult DispatchTensorLoadOp::reifyResultShapes(
       if (droppedDims.test(mixedSize.index())) {
         continue;
       }
-      shape.push_back(
-          getValueOrCreateConstantIndexOp(b, getLoc(), mixedSize.value()));
+      shape.push_back(mixedSize.value());
     }
   } else {
     // Result size matches the source size (no slicing).
@@ -654,7 +653,7 @@ LogicalResult DispatchTensorLoadOp::reifyResultShapes(
       if (dim == ShapedType::kDynamic) {
         shape.push_back(getSourceDims()[dynamicIdx++]);
       } else {
-        shape.push_back(b.create<arith::ConstantIndexOp>(getLoc(), dim));
+        shape.push_back(b.getIndexAttr(dim));
       }
     }
   }
@@ -1380,14 +1379,14 @@ LogicalResult TensorTieShapeOp::verify() {
 
 LogicalResult TensorTieShapeOp::reifyResultShapes(
     OpBuilder &b, ReifiedRankedShapedTypeDims &reifiedReturnShapes) {
-  SmallVector<Value> shape;
+  SmallVector<OpFoldResult> shape;
   unsigned dynamicIdx = 0;
   auto tensorType = getResult().getType().cast<RankedTensorType>();
   for (int64_t dim : tensorType.getShape()) {
     if (dim == ShapedType::kDynamic) {
       shape.push_back(getDynamicDims()[dynamicIdx++]);
     } else {
-      shape.push_back(b.create<arith::ConstantIndexOp>(getLoc(), dim));
+      shape.push_back(b.getIndexAttr(dim));
     }
   }
   reifiedReturnShapes.push_back(shape);

compiler/src/iree/compiler/Dialect/Flow/Transforms/RegionOpUtils.cpp

@@ -69,7 +69,7 @@ static SmallVector<Range> getLoopRangesImpl(tensor::ExtractSliceOp sliceOp,
   LogicalResult status = sliceOp.reifyResultShapes(builder, resultDims);
   (void)status;
   assert(succeeded(status) && "reifyResultShapes failed");
-  return llvm::to_vector(llvm::map_range(resultDims[0], [&](Value v) {
+  return llvm::to_vector(llvm::map_range(resultDims[0], [&](OpFoldResult v) {
     return Range{zero, v, one};
   }));
 }
@@ -158,7 +158,7 @@ LogicalResult Flow::reifyDynamicResultDims(OpBuilder &b, Value value,
     if (failed(reifyShapeOp.reifyResultShapes(b, dims))) return failure();
     for (int64_t i = 0; i < shapedType.getRank(); ++i)
       if (shapedType.isDynamicDim(i))
-        dynamicDims.push_back(dims[opResult.getResultNumber()][i]);
+        dynamicDims.push_back(dims[opResult.getResultNumber()][i].get<Value>());
     return success();
   }
 

compiler/src/iree/compiler/Dialect/HAL/Conversion/StreamToHAL/Patterns.cpp

@@ -998,8 +998,8 @@ struct CmdExecuteOpPattern
     // Begin/end recording and inline the execution region between them.
     auto endOp =
         rewriter.create<IREE::HAL::CommandBufferFinalizeOp>(loc, commandBuffer);
-    rewriter.mergeBlockBefore(&executeOp.getBody().front(), endOp,
-                              adaptor.getResourceOperands());
+    rewriter.inlineBlockBefore(&executeOp.getBody().front(), endOp,
+                               adaptor.getResourceOperands());
 
     // Gather wait/signal fence, which are optional.
     Value waitFence =
@@ -1032,7 +1032,7 @@ struct CmdSerialOpPattern
                                 OpBuilder::atBlockBegin(&bodyBlock));
 
     // Inline the serial execution region.
-    rewriter.mergeBlockBefore(&serialOp.getBody().front(), serialOp);
+    rewriter.inlineBlockBefore(&serialOp.getBody().front(), serialOp);
     rewriter.eraseOp(serialOp);
     return success();
   }
@@ -1046,7 +1046,7 @@ struct CmdConcurrentOpPattern
       ConversionPatternRewriter &rewriter) const override {
     // Inline the concurrent execution region.
     // TODO(benvanik): split barriers (event set/wait) when nesting.
-    rewriter.mergeBlockBefore(&concurrentOp.getBody().front(), concurrentOp);
+    rewriter.inlineBlockBefore(&concurrentOp.getBody().front(), concurrentOp);
     rewriter.eraseOp(concurrentOp);
     return success();
   }

compiler/src/iree/compiler/Dialect/VM/IR/VMOpFolders.cpp

@@ -2829,8 +2829,9 @@ struct SimplifyBrToBlockWithSinglePred : public OpRewritePattern<BranchOp> {
     }
 
     // Merge the successor into the current block and erase the branch.
-    rewriter.mergeBlocks(succ, opParent, op.getOperands());
+    SmallVector<Value> operands(op.getOperands());
     rewriter.eraseOp(op);
+    rewriter.mergeBlocks(succ, opParent, operands);
     return success();
   }
 };

compiler/src/iree/compiler/Dialect/VM/Transforms/GlobalInitialization.cpp

@@ -251,7 +251,7 @@ class GlobalInitializationPass
   std::pair<LogicalResult, Value> createConst(Location loc, Attribute value,
                                               OpBuilder &builder) {
     if (auto integerAttr = value.dyn_cast<IntegerAttr>()) {
-      if (integerAttr.getValue().isNullValue()) {
+      if (integerAttr.getValue().isZero()) {
         // Globals are zero-initialized by default.
         return {success(), {}};
       }

compiler/src/iree/compiler/Modules/HAL/Inline/Conversion/StreamToHALInline/Patterns.cpp

@@ -456,8 +456,8 @@ struct CmdExecuteOpPattern
       IREE::Stream::CmdExecuteOp executeOp, OpAdaptor adaptor,
       ConversionPatternRewriter &rewriter) const override {
     // Inline the serial execution region.
-    rewriter.mergeBlockBefore(&executeOp.getBody().front(), executeOp,
-                              adaptor.getResourceOperands());
+    rewriter.inlineBlockBefore(&executeOp.getBody().front(), executeOp,
+                               adaptor.getResourceOperands());
     // Immediately resolve the timepoint.
     auto resolvedTimepoint =
         rewriter.create<arith::ConstantIntOp>(executeOp.getLoc(), 0, 64)
@@ -474,7 +474,7 @@ struct CmdSerialOpPattern
       IREE::Stream::CmdSerialOp serialOp, OpAdaptor adaptor,
       ConversionPatternRewriter &rewriter) const override {
     // Inline the serial execution region.
-    rewriter.mergeBlockBefore(&serialOp.getBody().front(), serialOp);
+    rewriter.inlineBlockBefore(&serialOp.getBody().front(), serialOp);
     rewriter.eraseOp(serialOp);
     return success();
   }
@@ -487,7 +487,7 @@ struct CmdConcurrentOpPattern
       IREE::Stream::CmdConcurrentOp concurrentOp, OpAdaptor adaptor,
       ConversionPatternRewriter &rewriter) const override {
     // Inline the concurrent execution region.
-    rewriter.mergeBlockBefore(&concurrentOp.getBody().front(), concurrentOp);
+    rewriter.inlineBlockBefore(&concurrentOp.getBody().front(), concurrentOp);
     rewriter.eraseOp(concurrentOp);
     return success();
   }

integrations/tensorflow/WORKSPACE

@@ -7,7 +7,7 @@
 
 load("@bazel_tools//tools/build_defs/repo:git.bzl", "git_repository")
 
-TENSORFLOW_COMMIT = "eece4dba1fc65f7977085581852b0d6e6d42f04e"
+TENSORFLOW_COMMIT = "67ba341c869e30ee4a89e040cd875d12b9bc666e"
 
 git_repository(
     name = "org_tensorflow",

integrations/tensorflow/iree_tf_compiler/BUILD

@@ -41,10 +41,10 @@ cc_binary(
         "@llvm-project//mlir:Transforms",
         "@org_tensorflow//tensorflow/compiler/mlir/tensorflow",
         "@org_tensorflow//tensorflow/compiler/mlir/tensorflow:tensorflow_passes",
+        "@org_tensorflow//tensorflow/compiler/mlir/tf2xla:xla_legalize_tf",
         "@org_tensorflow//tensorflow/compiler/mlir/tosa:tf_passes",
         "@org_tensorflow//tensorflow/compiler/mlir/tosa:tf_tfl_passes",
         "@org_tensorflow//tensorflow/compiler/mlir/tosa:tfl_passes",
-        "@org_tensorflow//tensorflow/compiler/mlir/xla:xla_legalize_tf",
         "@org_tensorflow//tensorflow/compiler/xla/mlir_hlo",
         "@stablehlo//:chlo_ops",
     ],

integrations/tensorflow/iree_tf_compiler/TF/BUILD

@@ -56,8 +56,8 @@ cc_library(
         "@org_tensorflow//tensorflow/compiler/mlir/tensorflow:tensorflow_passes",
         "@org_tensorflow//tensorflow/compiler/mlir/tensorflow:tensorflow_types",
         "@org_tensorflow//tensorflow/compiler/mlir/tensorflow:tf_saved_model_passes",
+        "@org_tensorflow//tensorflow/compiler/mlir/tf2xla:xla_legalize_tf",
         "@org_tensorflow//tensorflow/compiler/mlir/tosa:tf_passes",
-        "@org_tensorflow//tensorflow/compiler/mlir/xla:xla_legalize_tf",
         "@org_tensorflow//tensorflow/compiler/xla/mlir_hlo",
         "@org_tensorflow//tensorflow/compiler/xla/mlir_hlo:all_passes",
         "@org_tensorflow//tensorflow/compiler/xla/mlir_hlo:chlo_legalize_to_hlo",

integrations/tensorflow/iree_tf_compiler/TF/ConvertToMHLO.cpp

@@ -22,7 +22,7 @@
 #include "tensorflow/compiler/mlir/tensorflow/ir/tf_ops.h"
 #include "tensorflow/compiler/mlir/tensorflow/ir/tf_saved_model.h"
 #include "tensorflow/compiler/mlir/tensorflow/transforms/lower_tf.h"
-#include "tensorflow/compiler/mlir/xla/transforms/passes.h"
+#include "tensorflow/compiler/mlir/tf2xla/transforms/passes.h"
 
 namespace mlir {
 namespace iree_integrations {

integrations/tensorflow/iree_tf_compiler/TF/LowerGlobalTensors.cpp

@@ -154,8 +154,8 @@ void LowerGlobalTensors::runOnOperation() {
       return;
     }
     auto global = globalBuilder.create<mlir::ml_program::GlobalOp>(
-        globalTensor.getLoc(), name, globalTensor.getValue().getType(),
-        globalTensor.getIsMutable(), globalTensor.getValue(), nullptr);
+        globalTensor.getLoc(), name, globalTensor.getValue()->getType(),
+        globalTensor.getIsMutable(), *globalTensor.getValue(), nullptr);
     global.setPrivate();
     symbolRefMap[globalTensor] = global;
   }

integrations/tensorflow/test/iree_tfl_tests/README.md

@@ -6,13 +6,19 @@ update_tflite_model_documentation.py to update this table.
 
 |       Model        |      Status        |
 | ------------------ | ------------------ |
-person_detect        | PASS ✓
-east_text_detector   | PASS ✓
-vulkan_posenet_i8    | FAIL ✗
+mobilenet_v3         | PASS ✓
+llvmcpu_resnet_50_int8 | PASS ✓
+vulkan_mobilebert_tf2_quant | FAIL ✗
 cartoon_gan          | PASS ✓
+llvmcpu_mobilebert_tf2_quant | PASS ✓
 mnasnet              | PASS ✓
+person_detect        | PASS ✓
+vulkan_posenet_i8    | FAIL ✗
+east_text_detector   | PASS ✓
 gpt2                 | PASS ✓
-llvmcpu_posenet_i8   | PASS ✓
-mobilenet_v3         | PASS ✓
 llvmcpu_mobilenet_v1 | PASS ✓
-vulkan_mobilenet_v1  | FAIL ✗
+llvmcpu_mobilenet_v3-large_uint8 | PASS ✓
+vulkan_mobilenet_v1  | PASS ✓
+vulkan_mobilenet_v3-large_uint8 | FAIL ✗
+llvmcpu_posenet_i8   | FAIL ✗
+vulkan_resnet_50_int8 | FAIL ✗

integrations/tensorflow/test/iree_tfl_tests/llvmcpu_posenet_i8.run

@@ -1,2 +1,3 @@
 # REQUIRES: llvmcpu
 # RUN: %PYTHON -m iree_tfl_tests.posenet_i8_test --target_backend=llvmcpu --artifacts_dir=%t
+# XFAIL: *

integrations/tensorflow/test/iree_tfl_tests/update_tflite_model_documentation.py

@@ -1,3 +1,4 @@
+#!/bin/python3
 # Copyright 2022 The IREE Authors
 #
 # Licensed under the Apache License v2.0 with LLVM Exceptions.

llvm-external-projects/iree-dialects/lib/Dialect/LinalgExt/IR/LinalgExtInterfaces.cpp

@@ -37,12 +37,12 @@ IREE::LinalgExt::detail::verifyLinalgExtOpInterface(Operation *op) {
 
 template <typename Ty, typename DimOpTy>
 static void getDimValues(OpBuilder &b, Location loc, Value v, Ty t,
-                         SmallVector<Value> &dimVals) {
+                         SmallVector<OpFoldResult> &dimVals) {
   for (auto dim : llvm::enumerate(t.getShape())) {
     if (ShapedType::isDynamic(dim.value())) {
-      dimVals.push_back(b.create<DimOpTy>(loc, v, dim.index()));
+      dimVals.push_back(b.create<DimOpTy>(loc, v, dim.index()).getResult());
     } else {
-      dimVals.push_back(b.create<arith::ConstantIndexOp>(loc, dim.value()));
+      dimVals.push_back(b.getIndexAttr(dim.value()));
     }
   }
 }
@@ -51,7 +51,7 @@ LogicalResult LinalgExtOp::reifyResultShapes(
     OpBuilder &b, ReifiedRankedShapedTypeDims &reifiedReturnShapes) {
   Operation *op = getOperation();
   for (auto output : getOutputs()) {
-    SmallVector<Value> dims;
+    SmallVector<OpFoldResult> dims;
     Type outputType = output.getType();
     if (auto rankedTensorType = outputType.dyn_cast<RankedTensorType>()) {
       getDimValues<RankedTensorType, tensor::DimOp>(b, op->getLoc(), output,

llvm-external-projects/iree-dialects/lib/Dialect/LinalgExt/IR/LinalgExtOps.cpp

@@ -1937,14 +1937,17 @@ LogicalResult PackOp::generateScalarImplementation(OpBuilder &builder,
   // over the tile dimensions.
   for (auto dataTileDim :
        llvm::seq<unsigned>(getInputRank(), getOutputRank() - 1)) {
-    Value ub = outputShape[0][dataTileDim];
+    Value ub = getValueOrCreateConstantIndexOp(builder, loc,
+                                               outputShape[0][dataTileDim]);
     scf::ForOp loop = builder.create<scf::ForOp>(loc, zero, ub, one);
     builder.setInsertionPointToStart(loop.getBody());
     ivVec.push_back(loop.getInductionVar());
   }
   // The body of the innermost loops does the actual data movement.
-  builder.create<scf::ForOp>(loc, zero, outputShape[0].back(), one,
-                             ValueRange{},
+  builder.create<scf::ForOp>(loc, zero,
+                             getValueOrCreateConstantIndexOp(
+                                 builder, loc, outputShape[0].back()),
+                             one, ValueRange{},
                              [&](OpBuilder &bodyBuilder, Location bodyLoc,
                                  Value iv, ValueRange regionIterArgs) {
                                ivVec.push_back(iv);
@@ -2681,8 +2684,7 @@ LogicalResult SetEncodingOp::reifyResultShapes(
   OpBuilder::InsertionGuard g(builder);
   builder.setInsertionPoint(getOperation());
   reifiedReturnShapes.resize(1);
-  reifiedReturnShapes[0] = getValueOrCreateConstantIndexOp(
-      builder, getLoc(), getDims(builder, getLoc(), getSource()));
+  reifiedReturnShapes[0] = getDims(builder, getLoc(), getSource());
   return success();
 }
 
@@ -2720,8 +2722,7 @@ LogicalResult UnsetEncodingOp::reifyResultShapes(
   OpBuilder::InsertionGuard g(builder);
   builder.setInsertionPoint(getOperation());
   reifiedReturnShapes.resize(1);
-  reifiedReturnShapes[0] = getValueOrCreateConstantIndexOp(
-      builder, getLoc(), getDims(builder, getLoc(), getSource()));
+  reifiedReturnShapes[0] = getDims(builder, getLoc(), getSource());
   return success();
 }