[MLIR] Delete unused functions getCollapsedInitTensor and getExpandedInitTensor

[GMNGeoffrey]

Summary

These are unused since
https://reviews.llvm.org/rG81264dfbe80df08668a325a61613b64243b99c01

mlir/lib/Dialect/Linalg/IR/LinalgOps.cpp

static LogicalResult verify(InitTensorOp op) {
   return success();
 }
 
 Type InitTensorOp::inferResultType(ArrayRef<int64_t> staticSizes,
                                    Type elementType) {
   return RankedTensorType::get(staticSizes, elementType);
 }
 
-static Value getCollapsedInitTensor(OpBuilder &builder,
-                                    TensorReshapeOp reshapeOp) {
-  Location loc = reshapeOp.getLoc();
-  SmallVector<Value, 4> dynamicShapes;
-  SmallVector<int64_t, 4> staticShapes;
-  auto reassociation = reshapeOp.getReassociationMaps();
-  Value src = reshapeOp.src();
-  RankedTensorType srcType = reshapeOp.getSrcType();
-  ArrayRef<int64_t> srcShape = srcType.getShape();
-  for (auto map : reassociation) {
-    Value linearizedDynamicDim = nullptr;
-    int64_t linearizedStaticDim = 1;
-    for (unsigned i : llvm::map_range(map.getResults(), [](AffineExpr e) {
-           return e.cast<AffineDimExpr>().getPosition();
-         })) {
-      if (ShapedType::isDynamic(srcShape[i])) {
-        Value shapeVal = builder.create<DimOp>(loc, src, i);
-        if (linearizedDynamicDim) {
-          linearizedDynamicDim =
-              builder.create<MulIOp>(loc, linearizedDynamicDim, shapeVal);
-        } else {
-          linearizedDynamicDim = shapeVal;
-        }
-      } else {
-        linearizedStaticDim *= srcShape[i];
-      }
-    }
-    if (linearizedDynamicDim) {
-      if (linearizedStaticDim != 1) {
-        linearizedDynamicDim = builder.create<MulIOp>(
-            loc, linearizedDynamicDim,
-            builder.create<ConstantIndexOp>(loc, linearizedStaticDim));
-      }
-      dynamicShapes.push_back(linearizedDynamicDim);
-      staticShapes.push_back(ShapedType::kDynamicSize);
-    } else {
-      staticShapes.push_back(linearizedStaticDim);
-    }
-  }
-  return builder.create<InitTensorOp>(loc, dynamicShapes, staticShapes,
-                                      srcType.getElementType());
-}
-
-static Value getExpandedInitTensor(OpBuilder &builder,
-                                   TensorReshapeOp reshapeOp) {
-  SmallVector<Value, 4> dynamicShapes;
-  SmallVector<int64_t, 4> staticShapes;
-  auto reassociation = reshapeOp.getReassociationMaps();
-  Value src = reshapeOp.src();
-  RankedTensorType srcType = reshapeOp.getSrcType();
-  ArrayRef<int64_t> srcShape = srcType.getShape();
-  ArrayRef<int64_t> dstShape = reshapeOp.getResultType().getShape();
-  Location loc = reshapeOp.getLoc();
-  for (auto map : enumerate(reassociation)) {
-    int64_t linearizedStaticDim = 1;
-    bool hasDynamic = false;
-    for (unsigned i :
-         llvm::map_range(map.value().getResults(), [](AffineExpr e) {
-           return e.cast<AffineDimExpr>().getPosition();
-         })) {
-      if (ShapedType::isDynamic(dstShape[i])) {
-        // Only one of the dimensions of the expanded shape should be dynamic.
-        if (hasDynamic)
-          return nullptr;
-        hasDynamic = true;
-        staticShapes.push_back(ShapedType::kDynamicSize);
-        continue;
-      }
-      staticShapes.push_back(dstShape[i]);
-      linearizedStaticDim *= dstShape[i];
-    }
-    if (hasDynamic) {
-      // If the expanded dimensions has a dynamic shape, the src shape must be
-      // dynamic as well.
-      if (!ShapedType::isDynamic(srcShape[map.index()]))
-        return nullptr;
-      Value dynamicDim = builder.create<DimOp>(loc, src, map.index());
-      if (linearizedStaticDim != 1) {
-        dynamicDim = builder.create<UnsignedDivIOp>(
-            loc, dynamicDim,
-            builder.create<ConstantIndexOp>(loc, linearizedStaticDim));
-      }
-      dynamicShapes.push_back(dynamicDim);
-    }
-  }
-  return builder.create<InitTensorOp>(loc, dynamicShapes, staticShapes,
-                                      srcType.getElementType());
-}
-
 namespace {
 /// Change the type of the result of a `linalg.init_tensor` by making the result
 /// type statically sized along dimension that in the original operation where
 /// defined as dynamic, but the size was defined using a `constant` op. For
 /// example
 ///
 ///  %c5 = constant 5: index
 ///  %0 = linalg.init_tensor [%arg0, %c5] : tensor<?x?xf32>