Merge remote-tracking branch 'upstream/main' into splitesequence

docs/mnist_example/requirements.txt

@@ -1,4 +1,4 @@
 numpy~=1.22.2
-pillow~=10.2.0
-torch~=2.0.0
-torchvision~=0.15.1
+pillow~=10.3.0
+torch~=2.5.0
+torchvision~=0.20.0

src/Accelerators/NNPA/Compiler/CMakeLists.txt

@@ -19,6 +19,7 @@ add_onnx_mlir_library(OMNNPACompilerOptions
 
 add_onnx_mlir_library(OMNNPACompilerUtils
   NNPACompilerUtils.cpp
+  ZHighDisposableGarbageCollector.cpp
 
   EXCLUDE_FROM_OM_LIBS
 

src/Accelerators/NNPA/Compiler/NNPACompilerUtils.cpp

@@ -32,6 +32,7 @@
 
 #include "src/Accelerators/NNPA/Compiler/NNPACompilerOptions.hpp"
 #include "src/Accelerators/NNPA/Compiler/NNPACompilerUtils.hpp"
+#include "src/Accelerators/NNPA/Compiler/ZHighDisposableGarbageCollector.hpp"
 #include "src/Accelerators/NNPA/Dialect/ZHigh/ZHighOps.hpp"
 #include "src/Accelerators/NNPA/Dialect/ZLow/ZLowOps.hpp"
 #include "src/Accelerators/NNPA/Pass/NNPAPasses.hpp"
@@ -120,10 +121,6 @@ void addONNXToZHighPasses(mlir::PassManager &pm) {
     pm.addNestedPass<func::FuncOp>(onnx_mlir::createShapeInferencePass());
   }
 
-  // Replace every DisposableElementsAttr with DenseElementsAttr.
-  // ZHighConstPropagation currently assumes that DenseElementsAttr is used.
-  pm.addPass(createScrubDisposablePass());
-
   // Experimental feature: Decompose stick/unstick into two phases: layout
   // transform and data conversion. Do some optimizations after decomposing.
   // Then, recompose again layout and data conversion if they are not optimized.
@@ -146,15 +143,17 @@ void addONNXToZHighPasses(mlir::PassManager &pm) {
   // Only support BE machines.
   bool isBE = llvm::endianness::native == llvm::endianness::big;
   if (isBE)
-    pm.addNestedPass<func::FuncOp>(
-        onnx_mlir::zhigh::createZHighConstPropagationPass());
+    pm.addPass(onnx_mlir::zhigh::createZHighConstPropagationPass());
 
   // Remove common sub-expressions.
   pm.addPass(mlir::createCSEPass());
 
   // Clean dead code.
   pm.addPass(mlir::createSymbolDCEPass());
 
+  // Replace every DisposableElementsAttr with DenseElementsAttr.
+  pm.addPass(onnx_mlir::zhigh::createZHighScrubDisposablePass());
+
   // Insert an instrumentation after lowering onnx to zhigh to get profiling
   // for onnx and zhigh ops.
   // Keep this pass at the end of this function.
@@ -195,6 +194,9 @@ void addPassesNNPA(mlir::OwningOpRef<mlir::ModuleOp> &module,
 
   // LLVM_DEBUG(llvm::dbgs() << "Adding NNPA passes" << std::endl;);
   if (emissionTarget >= EmitONNXIR) {
+    pm.addInstrumentation(
+        std::make_unique<onnx_mlir::zhigh::ZHighDisposableGarbageCollector>(
+            pm.getContext()));
     addONNXToMLIRPasses(pm, /*target CPU*/ maccel.empty(),
         /*donotScrubDisposableElementsAttr*/ true);
     pm.addPass(onnx_mlir::createDevicePlacementPass(nnpaLoadDevicePlacementFile,

src/Accelerators/NNPA/Compiler/ZHighDisposableGarbageCollector.cpp

@@ -0,0 +1,43 @@
+/*
+ * SPDX-License-Identifier: Apache-2.0
+ */
+
+//===---------------- ZHighDisposableGarbageCollector.cpp -----------------===//
+//
+// Garbage collects DisposableElementsAttr attributes.
+//
+//===----------------------------------------------------------------------===//
+
+#include "src/Accelerators/NNPA/Compiler/ZHighDisposableGarbageCollector.hpp"
+#include "src/Accelerators/NNPA/Dialect/ZHigh/ZHighOps.hpp"
+#include "src/Dialect/ONNX/ElementsAttr/DisposablePool.hpp"
+#include "src/Dialect/ONNX/ONNXDialect.hpp"
+#include "src/Dialect/ONNX/ONNXOps.hpp"
+
+#include "mlir/IR/BuiltinOps.h"
+
+using namespace mlir;
+
+namespace onnx_mlir {
+namespace zhigh {
+
+ZHighDisposableGarbageCollector::ZHighDisposableGarbageCollector(
+    MLIRContext *context)
+    : disposablePool(*DisposablePool::get<ONNXDialect>(context)) {}
+
+ZHighDisposableGarbageCollector::~ZHighDisposableGarbageCollector() {}
+
+void ZHighDisposableGarbageCollector::runAfterPass(Pass *pass, Operation *op) {
+  if (!disposablePool.isActive())
+    return;
+  ModuleOp moduleOp = mlir::dyn_cast<ModuleOp>(op);
+  if (!moduleOp)
+    return;
+  disposablePool.garbageCollectUnreachable(
+      moduleOp, {{ONNXConstantOp::getOperationName(), "value"},
+                    {ONNXConstantOfShapeOp::getOperationName(), "value"},
+                    {ZHighStickifiedConstantOp::getOperationName(), "value"}});
+}
+
+} // namespace zhigh
+} // namespace onnx_mlir

src/Accelerators/NNPA/Compiler/ZHighDisposableGarbageCollector.hpp

@@ -0,0 +1,37 @@
+/*
+ * SPDX-License-Identifier: Apache-2.0
+ */
+
+//===---------------- ZHighDisposableGarbageCollector.hpp -----------------===//
+//
+// Garbage collects DisposableElementsAttr attributes.
+//
+//===----------------------------------------------------------------------===//
+
+#ifndef ONNX_MLIR_ZHIGH_GARBAGE_COLLECTOR_H
+#define ONNX_MLIR_ZHIGH_GARBAGE_COLLECTOR_H
+
+#include "mlir/Pass/PassInstrumentation.h"
+
+namespace mlir {
+class MLIRContext;
+}
+
+namespace onnx_mlir {
+class DisposablePool;
+
+namespace zhigh {
+
+struct ZHighDisposableGarbageCollector : public mlir::PassInstrumentation {
+  ZHighDisposableGarbageCollector(mlir::MLIRContext *context);
+  ~ZHighDisposableGarbageCollector() override;
+
+  void runAfterPass(mlir::Pass *pass, mlir::Operation *op) override;
+
+private:
+  DisposablePool &disposablePool;
+};
+
+} // namespace zhigh
+} // namespace onnx_mlir
+#endif

src/Accelerators/NNPA/Conversion/ONNXToZHigh/ONNXToZHighCommon.cpp

@@ -83,8 +83,7 @@ bool isF32ScalarConstantTensor(Value v) {
 FloatAttr getScalarF32AttrFromConstant(Value v) {
   if (!isF32ScalarConstantTensor(v))
     return nullptr;
-  DenseElementsAttr constElements = ElementsAttrBuilder::toDenseElementsAttr(
-      getElementAttributeFromONNXValue(v));
+  ElementsAttr constElements = getElementAttributeFromONNXValue(v);
   return constElements.getSplatValue<FloatAttr>();
 }
 

src/Accelerators/NNPA/Conversion/ONNXToZHigh/ONNXToZHighCommon.hpp

@@ -2,8 +2,7 @@
  * SPDX-License-Identifier: Apache-2.0
  */
 
-//===---------- ONNXToZHighCommon.hpp - Common functions in ONNXToZHigh
-//---------===//
+//===---- ONNXToZHighCommon.hpp - Common functions in ONNXToZHigh ---------===//
 //
 // Copyright 2019-2024 The IBM Research Authors.
 //
@@ -117,4 +116,4 @@ mlir::Value getDynShape(
     mlir::Location loc, mlir::PatternRewriter &rewriter, mlir::Value x);
 
 } // namespace onnx_mlir
-#endif
+#endif

src/Accelerators/NNPA/Conversion/ZHighToZLow/ZHighToZLow.cpp

@@ -168,6 +168,25 @@ static Value insertAllocForWorkAreaForRNNOps(IndexExprBuilderForKrnl &createIE,
   return create.mem.alignedAlloc(resultType, dims, gAlignment);
 }
 
+/// Get a dense resource attribute to store stickified data of a given i8 value.
+/// Attribute type: tensor<sizeInBytes x i8>
+DenseResourceElementsAttr getDenseResourceElementsAttrOfValue(
+    PatternRewriter &rewriter, ZHighStickifiedConstantOp stickifiedConstant,
+    int8_t val, int64_t sizeInBytes) {
+  char *rawData = static_cast<char *>(malloc(sizeInBytes));
+  assert(rawData && "failed to allocate memory for stickified data");
+  memset(rawData, val, sizeInBytes);
+  DenseResourceElementsAttr valueAttr = DenseUI8ResourceElementsAttr::get(
+      RankedTensorType::get({sizeInBytes}, rewriter.getI8Type()),
+      stickifiedConstant.getOperation()
+          ->getDialect()
+          ->getNamespace(), // use the dialect as the blob "hint"
+      HeapAsmResourceBlob::allocateAndCopyWithAlign(
+          llvm::ArrayRef(rawData, sizeInBytes), alignof(char)));
+  free(rawData);
+  return valueAttr;
+}
+
 /// This function emits a buffer of zero elements for the given dimensions and
 /// layout. If the given dimensions are static, then a stickified constant is
 /// returned.
@@ -190,48 +209,18 @@ Value insertAllocOrEmitZeroConstant(ArrayRef<IndexExpr> dims,
         affine::normalizeMemRefType(mlir::cast<MemRefType>(zMemRefType.value));
 
     // Create a ZHighStickifiedConstantOp.
-
-    // Keep previous implementation about generating stickified data at
-    // ZHighConstPropagationPass. To use this, comment in and set directive "
-    // NNPA_ZHIGH_STICKIFIEDCONST_GEN"
-    //
-    // #ifdef NNPA_ZHIGH_STICKIFIEDCONST_GEN
-    //     // Set zero in value attribute as DenseResourceElementsAttribute.
-    //     ZHighStickifiedConstantOp stickifiedConstant =
-    //         rewriter.create<ZHighStickifiedConstantOp>(loc, resType,
-    //             /*stickified=*/rewriter.getBoolAttr(true),
-    //             /*value=*/nullptr,
-    //             /*alignment=*/rewriter.getI64IntegerAttr(4096));
-    //
-    //     // Use an dense resource attribute to store stickified data.
-    //     // Attribute type: tensor<sizeInBytes x i8>
-    //     int64_t sizeInBytes =
-    //         affine::getIntOrFloatMemRefSizeInBytes(resType).value();
-    //     char *rawData = static_cast<char *>(malloc(sizeInBytes));
-    //     assert(rawData && "failed to allocate memory for stickified data");
-    //     memset(rawData, 0, sizeInBytes);
-    //     DenseResourceElementsAttr valueAttr =
-    //     DenseUI8ResourceElementsAttr::get(
-    //         RankedTensorType::get({sizeInBytes}, rewriter.getI8Type()),
-    //         stickifiedConstant.getOperation()
-    //             ->getDialect()
-    //             ->getNamespace(), // use the dialect as the blob "hint"
-    //         HeapAsmResourceBlob::allocateAndCopyWithAlign(
-    //             llvm::ArrayRef(rawData, sizeInBytes), alignof(char)));
-    //     stickifiedConstant.setValueAttr(valueAttr);
-    //     free(rawData);
-    // #else
-
-    // Set zero in value attribute as SplatElementsAttr.
-    FloatAttr floatZero = rewriter.getFloatAttr(resType.getElementType(), 0.0);
-    ZHighStickifiedConstantOp stickifiedConstant = rewriter.create<
-        ZHighStickifiedConstantOp>(loc, resType,
-        /*stickified=*/rewriter.getBoolAttr(true),
-        /*value=*/SplatElementsAttr::get(cast<ShapedType>(resType), floatZero),
-        /*alignment=*/rewriter.getI64IntegerAttr(4096));
-
-    // #endif // NNPA_ZHIGH_STICKIFIEDCONST_GEN
-
+    ZHighStickifiedConstantOp stickifiedConstant =
+        rewriter.create<ZHighStickifiedConstantOp>(loc, resType,
+            /*value=*/nullptr,
+            /*alignment=*/rewriter.getI64IntegerAttr(4096));
+
+    // Use an dense resource attribute to store stickified data.
+    // Attribute type: tensor<sizeInBytes x i8>
+    int64_t sizeInBytes =
+        affine::getIntOrFloatMemRefSizeInBytes(resType).value();
+    DenseResourceElementsAttr valueAttr = getDenseResourceElementsAttrOfValue(
+        rewriter, stickifiedConstant, 0, sizeInBytes);
+    stickifiedConstant.setValueAttr(valueAttr);
     res = stickifiedConstant.getResult();
   } else {
     MultiDialectBuilder<KrnlBuilder, MathBuilder> create(rewriter, loc);
@@ -706,7 +695,7 @@ struct ZHighToZLowUnstickOpLowering : public ConversionPattern {
 };
 
 //===----------------------------------------------------------------------===//
-// Lower ZHigh Stickified Constant to ZLow Stickified Constant
+// Lower ZHigh Stickified Constant to KrnlGlobal
 //===----------------------------------------------------------------------===//
 
 struct ZHighToZLowStickifiedConstantOpLowering : public ConversionPattern {
@@ -719,7 +708,7 @@ struct ZHighToZLowStickifiedConstantOpLowering : public ConversionPattern {
   LogicalResult matchAndRewrite(Operation *op, ArrayRef<Value> operands,
       ConversionPatternRewriter &rewriter) const final {
     Location loc = op->getLoc();
-    ZHighStickifiedConstantOp zhighStickifiedConstOp =
+    ZHighStickifiedConstantOp stickifiedConstOp =
         llvm::dyn_cast<ZHighStickifiedConstantOp>(op);
 
     // Convert ZTensor type to MemRefType.
@@ -733,59 +722,53 @@ struct ZHighToZLowStickifiedConstantOpLowering : public ConversionPattern {
         affine::normalizeMemRefType(mlir::cast<MemRefType>(zMemRefType.value));
     ArrayRef<int64_t> normalizedShape = normalizedType.getShape();
 
-    // Create ZLowStickifiedConstantOp.
-    StringAttr layout =
-        getZTensorLayoutAttr(rewriter, *op->result_type_begin());
+    // Validate the stickified tensor.
+    Attribute valueAttr = stickifiedConstOp.getValueAttr();
+    int64_t sizeInBytes = getMemRefEltSizeInBytes(normalizedType);
+    sizeInBytes *= normalizedType.getNumElements();
+    if (auto denseAttr = mlir::dyn_cast_or_null<DenseElementsAttr>(valueAttr)) {
+      ArrayRef<char> data = denseAttr.getRawData();
+      if (denseAttr.isSplat()) {
+        // Constant ztensor's buffer is tensor<sizeInBytes x i8>.
+        int8_t v = denseAttr.getSplatValue<int8_t>();
+        // NNPA does not work with a splat buffer.
+        // Expand the memory buffer for NNPA by using DenseResourceElementsAttr.
+        valueAttr = getDenseResourceElementsAttrOfValue(
+            rewriter, stickifiedConstOp, v, sizeInBytes);
+      } else {
+        assert(
+            (data.size() == static_cast<uint64_t>(sizeInBytes)) &&
+            "The stickified tensor's buffer size and MemRef's size mismatched");
+      }
+    } else if (auto resourceAttr =
+                   mlir::dyn_cast_or_null<DenseResourceElementsAttr>(
+                       valueAttr)) {
+      auto blob = resourceAttr.getRawHandle().getBlob();
+      assert(blob && "Expecting dense resource with a valid blob");
+      ArrayRef<char> data = blob->getData();
+      assert(
+          (data.size() == static_cast<uint64_t>(sizeInBytes)) &&
+          "The stickified tensor's buffer size and MemRef's size mismatched");
+    } else {
+      llvm_unreachable("Unsupported ElementsAttr");
+    }
 
-    // Keep previous implementation about generating stickified data at
-    // ZHighConstPropagationPass. To use this, comment in and set directive "
-    // NNPA_ZHIGH_STICKIFIEDCONST_GEN"
-    //
-    // #ifdef NNPA_ZHIGH_STICKIFIEDCONST_GEN
-    //     // Lower to KrnlGlobalOp
-    //     // Get dense resource attribute.
-    //     auto blob = mlir::cast<DenseResourceElementsAttr>(
-    //         zhighStickifiedConstOp.getValue().value())
-    //                     .getRawHandle()
-    //                     .getBlob();
-    //     assert(blob && "Expecting dense resource with a valid blob");
-    //     ArrayRef<char> data = blob->getData();
-    //     // Validate the stickified tensor.
-    //     int64_t memRefSizeInBytes = getMemRefEltSizeInBytes(normalizedType);
-    //     memRefSizeInBytes *= normalizedType.getNumElements();
-    //     assert((data.size() == static_cast<uint64_t>(memRefSizeInBytes)) &&
-    //            "The stickified tensor's buffer size and MemRef's size
-    //            mismatched");
-    //     // Create a KrnlGlobalOp.
-    //     KrnlGlobalOp constantOp =
-    //         rewriter.create<KrnlGlobalOp>(loc, zMemRefType.value,
-    //             /*shape=*/
-    //             rewriter.getI64ArrayAttr(normalizedShape),
-    //             /*name=*/
-    //             rewriter.getStringAttr(
-    //                 "constant_stickify_" + std::to_string(constantID)),
-    //             /*value=*/zhighStickifiedConstOp.getValueAttr(),
-    //             /*offset=*/nullptr,
-    //             /*alignment=*/zhighStickifiedConstOp.getAlignmentAttr());
-    // #else
-    ZLowStickifiedConstantOp constantOp =
-        rewriter.create<ZLowStickifiedConstantOp>(loc,
-            mlir::cast<MemRefType>(zMemRefType.value),
+    // Create a KrnlGlobalOp.
+    KrnlGlobalOp constantGlobal =
+        rewriter.create<KrnlGlobalOp>(loc, zMemRefType.value,
             /*shape=*/
             rewriter.getI64ArrayAttr(normalizedShape),
             /*name=*/
             rewriter.getStringAttr(
                 "constant_stickify_" + std::to_string(constantID)),
-            /*stickified=*/zhighStickifiedConstOp.getStickifiedAttr(),
-            /*value=*/zhighStickifiedConstOp.getValueAttr(),
-            /*layout=*/layout,
-            /*offset=*/rewriter.getI64IntegerAttr(0),
-            /*alignment=*/zhighStickifiedConstOp.getAlignmentAttr());
-    // #endif  // NNPA_ZHIGH_STICKIFIEDCONST_GEN
+            /*value=*/valueAttr,
+            /*offset=*/nullptr,
+            /*alignment=*/stickifiedConstOp.getAlignmentAttr());
+
     // Increment constant ID:
     constantID++;
 
-    rewriter.replaceOp(op, constantOp.getResult());
+    rewriter.replaceOp(op, constantGlobal.getResult());
     return success();
   }
 };

src/Accelerators/NNPA/Dialect/ZHigh/CMakeLists.txt

@@ -47,7 +47,6 @@ add_onnx_mlir_library(OMZHighOps
   OMONNXOps # Use ONNXShapeHelper 
   OMLayoutHelper
   OMShapeHelperOpInterface
-  OMStickify
   OMNNPACompilerOptions
   MLIRIR