Add support for customizing const inlining and ops with regions to Is…

…olateGroupOps pass (#87) A few small improvements to the `IsolateGroupOps` pass: - Provide a hook to customize whether a const like op used in the `tcp.group` will get copied into the group or whether it will be passed in as an input argument. The main pass does always returns true so this is a non-functional change in `mlir-tcp`. - The previous version did not handle ops with contained regions and block arguments (such as an `scf.forall` inside the `tcp.group`). We now handle this (see updated lit test). --------- Co-authored-by: Srinath Avadhanula <[email protected]>
cruise-automation · Jul 31, 2024 · a145d84 · a145d84
1 parent 7c50225
commit a145d84
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Showing 3 changed files with 147 additions and 11 deletions.
diff --git a/include/mlir-tcp/Dialect/Transforms/IsolateGroupOpsPass.h b/include/mlir-tcp/Dialect/Transforms/IsolateGroupOpsPass.h
@@ -9,6 +9,7 @@
 
 #pragma once
 
+#include "mlir-tcp/Dialect/IR/TcpOps.h"
 #include "mlir/IR/BuiltinOps.h"
 #include "mlir/Pass/Pass.h"
 #include <memory>
@@ -18,4 +19,14 @@ namespace mlir::tcp {
 std::unique_ptr<mlir::OperationPass<mlir::ModuleOp>>
 createTcpIsolateGroupOpsPass();
 
+// `createTcpIsolateGroupOpsPass` will clone all const operations used
+// inside a `tcp.group` into the new `tcp.isolated_group` it creates. If
+// you want to customize this behavior, you can use this instead to
+// pass a predicate function to control when a `const-like` operation
+// should be cloned into the isolated group or whether it should be added
+// as an argument to the isolated group.
+void populateIsolateGroupPatterns(
+    RewritePatternSet &patterns,
+    std::function<bool(GroupOp, Value)> shouldCopyConstPredicate);
+
 } // namespace mlir::tcp
diff --git a/lib/Dialect/Transforms/IsolateGroupOpsPass.cpp b/lib/Dialect/Transforms/IsolateGroupOpsPass.cpp
@@ -29,9 +29,12 @@ namespace mlir::tcp {
 
 namespace {
 
-class IsolateGroups : public OpRewritePattern<tcp::GroupOp> {
+class IsolateGroups : public OpRewritePattern<GroupOp> {
 public:
-  using OpRewritePattern::OpRewritePattern;
+  IsolateGroups(MLIRContext *context,
+                std::function<bool(tcp::GroupOp, Value)> shouldInlineConst)
+      : OpRewritePattern<GroupOp>(context),
+        shouldInlineConst_(shouldInlineConst) {}
 
   LogicalResult matchAndRewrite(tcp::GroupOp groupOp,
                                 PatternRewriter &rewriter) const override {
@@ -41,33 +44,42 @@ class IsolateGroups : public OpRewritePattern<tcp::GroupOp> {
     llvm::SmallVector<Value> inputs;
     llvm::SmallDenseSet<Value> addedInputs;
     llvm::SmallDenseSet<Value> consts;
-    llvm::SmallDenseSet<Value> defs;
-    for (auto &op : groupOp.getBody().front()) {
-      for (auto operand : op.getOperands()) {
-        if (defs.find(operand) == defs.end()) {
+
+    groupOp->walk([&](Operation *op) {
+      for (auto operand : op->getOperands()) {
+        // Find the operation defining this Value, or whose block argument
+        // this Value is.
+        auto operandDefiningOp = operand.getDefiningOp();
+        if (!operandDefiningOp) {
+          operandDefiningOp = operand.getParentBlock()->getParentOp();
+        }
+        // If that operation lives outside the group, we need to add it as
+        // an input to the newly created isolated group.
+        if (!groupOp->isProperAncestor(operandDefiningOp)) {
           if (operand.getDefiningOp() &&
-              operand.getDefiningOp()->hasTrait<OpTrait::ConstantLike>()) {
+              operand.getDefiningOp()->hasTrait<OpTrait::ConstantLike>() &&
+              shouldInlineConst_(groupOp, operand)) {
             consts.insert(operand);
           } else if (!addedInputs.contains(operand)) {
             inputs.push_back(operand);
             addedInputs.insert(operand);
           }
         }
       }
-      defs.insert(op.getResults().begin(), op.getResults().end());
-    }
+    });
 
     auto isolatedGroupOp = rewriter.create<tcp::IsolatedGroupOp>(
         groupOp.getLoc(), groupOp.getResultTypes(), inputs);
     isolatedGroupOp->setAttrs(groupOp->getAttrs());
 
     isolatedGroupOp.getBody().takeBody(groupOp.getBody());
+
     auto &isolatedGroupBlock = isolatedGroupOp.getBody().front();
     {
       OpBuilder::InsertionGuard guard(rewriter);
       rewriter.setInsertionPointToStart(&isolatedGroupBlock);
       auto belongsToIsolatedGroup = [&](OpOperand &opOperand) {
-        return (opOperand.getOwner()->getParentOp() == isolatedGroupOp);
+        return (isolatedGroupOp->isProperAncestor(opOperand.getOwner()));
       };
 
       // Clone the constants at the start of the isolated group block.
@@ -91,6 +103,23 @@ class IsolateGroups : public OpRewritePattern<tcp::GroupOp> {
     rewriter.eraseOp(groupOp);
     return success();
   }
+
+private:
+  std::function<bool(tcp::GroupOp, Value)> shouldInlineConst_;
+};
+
+class DropSymbolicShapesInsideGroups
+    : public OpRewritePattern<tcp::BindSymbolicShapeOp> {
+  using OpRewritePattern<tcp::BindSymbolicShapeOp>::OpRewritePattern;
+
+  LogicalResult matchAndRewrite(tcp::BindSymbolicShapeOp shapeOp,
+                                PatternRewriter &rewriter) const override {
+    if (isa<tcp::GroupOp>(shapeOp->getParentOp())) {
+      rewriter.eraseOp(shapeOp);
+      return success();
+    }
+    return failure();
+  }
 };
 
 class TcpIsolateGroupOpsPass
@@ -100,7 +129,8 @@ class TcpIsolateGroupOpsPass
     MLIRContext *context = op->getContext();
     RewritePatternSet patterns(context);
 
-    patterns.add<IsolateGroups>(context);
+    auto shouldCopyConstPredicate = [&](tcp::GroupOp, Value) { return true; };
+    populateIsolateGroupPatterns(patterns, shouldCopyConstPredicate);
     if (failed(applyPatternsAndFoldGreedily(op, std::move(patterns))))
       return signalPassFailure();
   }
@@ -112,4 +142,12 @@ std::unique_ptr<OperationPass<ModuleOp>> createTcpIsolateGroupOpsPass() {
   return std::make_unique<TcpIsolateGroupOpsPass>();
 }
 
+void populateIsolateGroupPatterns(
+    RewritePatternSet &patterns,
+    std::function<bool(tcp::GroupOp, Value)> shouldCopyConstPredicate) {
+
+  patterns.add<IsolateGroups>(patterns.getContext(), shouldCopyConstPredicate);
+  patterns.add<DropSymbolicShapesInsideGroups>(patterns.getContext());
+}
+
 } // namespace mlir::tcp
diff --git a/test/Dialect/tcp_isolate_groups.mlir b/test/Dialect/tcp_isolate_groups.mlir
@@ -120,3 +120,90 @@ func.func @test_inputs_with_multiple_uses(%arg0 : tensor<5xi32>) -> tensor<5xi32
   }) : () -> tensor<5xi32>
    return %10 : tensor<5xi32>
 }
+
+
+// -----
+
+// isolate tcp.group ops in the presence of nested regions.
+
+// CHECK: #map = affine_map<(d0, d1) -> (d0, d1)>
+// CHECK: module {
+// CHECK:   func.func @forward(%[[ARG0:.+]]: tensor<?x4096xf32>, %[[ARG1:.+]]: tensor<?x4096xf32>, %[[ARG2:.+]]: tensor<?x4096xf32>) -> tensor<?x4096xf32> {
+// CHECK:     %[[C0:.+]] = arith.constant 0 : index
+// CHECK:     %[[DIM:.+]] = tensor.dim %[[ARG0]], %[[C0]] : tensor<?x4096xf32>
+// CHECK:     %[[V0:.+]] = tcp.isolated_group %[[DIM]], %[[ARG0]], %[[ARG1]] attributes {group_type = "codegen_group"} {
+// CHECK:     ^bb0(%[[ARG3:.+]]: index, %[[ARG4:.+]]: tensor<?x4096xf32>, %[[ARG5:.+]]: tensor<?x4096xf32>):
+// CHECK:       %[[V1:.+]] = tensor.empty(%[[ARG3]]) : tensor<?x4096xf32>
+// CHECK:       %[[V2:.+]] = scf.forall (%[[ARG6:.+]], %[[ARG7:.+]]) in (%[[ARG3]], 4096) shared_outs(%[[ARG8:.+]] = %[[V1]]) -> (tensor<?x4096xf32>) {
+// CHECK:         %[[EXTRACTED_SLICE:.+]] = tensor.extract_slice %[[ARG4]][%[[ARG6]], %[[ARG7]]] [1, 1] [1, 1] : tensor<?x4096xf32> to tensor<1x1xf32>
+// CHECK:         %[[EXTRACTED_SLICE_0:.+]] = tensor.extract_slice %[[ARG5]][%[[ARG6]], %[[ARG7]]] [1, 1] [1, 1] : tensor<?x4096xf32> to tensor<1x1xf32>
+// CHECK:         %[[V3:.+]] = tensor.empty() : tensor<1x1xf32>
+// CHECK:         %[[V4:.+]] = linalg.generic {indexing_maps = [#map, #map, #map], iterator_types = ["parallel", "parallel"]} ins(%[[EXTRACTED_SLICE]], %[[EXTRACTED_SLICE_0]] : tensor<1x1xf32>, tensor<1x1xf32>) outs(%[[V3]] : tensor<1x1xf32>) {
+// CHECK:         ^bb0(%[[IN:.+]]: f32, %[[IN_1:.+]]: f32, %[[OUT:.+]]: f32):
+// CHECK:           %[[V5:.+]] = arith.mulf %[[IN]], %[[IN_1]] : f32
+// CHECK:           linalg.yield %[[V5]] : f32
+// CHECK:         } -> tensor<1x1xf32>
+// CHECK:         scf.forall.in_parallel {
+// CHECK:           tensor.parallel_insert_slice %[[V4]] into %[[ARG8]][%[[ARG6]], %[[ARG7]]] [1, 1] [1, 1] : tensor<1x1xf32> into tensor<?x4096xf32>
+// CHECK:         }
+// CHECK:       }
+// CHECK:       tcp.yield %[[V2]] : tensor<?x4096xf32>
+// CHECK:     } : index, tensor<?x4096xf32>, tensor<?x4096xf32> -> tensor<?x4096xf32>
+// CHECK:     return %[[V0]] : tensor<?x4096xf32>
+// CHECK:   }
+// CHECK: }
+#map = affine_map<(d0, d1) -> (d0, d1)>
+func.func @forward(%arg0: tensor<?x4096xf32>, %arg1: tensor<?x4096xf32>, %arg2: tensor<?x4096xf32>) -> tensor<?x4096xf32> {
+  %c0 = arith.constant 0 : index
+  %dim = tensor.dim %arg0, %c0 : tensor<?x4096xf32>
+  %0 = tcp.group attributes {group_type = "codegen_group"} {
+    %1 = tensor.empty(%dim) : tensor<?x4096xf32>
+    %2 = scf.forall (%arg3, %arg4) in (%dim, 4096) shared_outs(%arg5 = %1) -> (tensor<?x4096xf32>) {
+      %extracted_slice = tensor.extract_slice %arg0[%arg3, %arg4] [1, 1] [1, 1] : tensor<?x4096xf32> to tensor<1x1xf32>
+      %extracted_slice_0 = tensor.extract_slice %arg1[%arg3, %arg4] [1, 1] [1, 1] : tensor<?x4096xf32> to tensor<1x1xf32>
+      %3 = tensor.empty() : tensor<1x1xf32>
+      %4 = linalg.generic {indexing_maps = [#map, #map, #map], iterator_types = ["parallel", "parallel"]} ins(%extracted_slice, %extracted_slice_0 : tensor<1x1xf32>, tensor<1x1xf32>) outs(%3 : tensor<1x1xf32>) {
+      ^bb0(%in: f32, %in_4: f32, %out: f32):
+        %8 = arith.mulf %in, %in_4 : f32
+        linalg.yield %8 : f32
+      } -> tensor<1x1xf32>
+      scf.forall.in_parallel {
+        tensor.parallel_insert_slice %4 into %arg5[%arg3, %arg4] [1, 1] [1, 1] : tensor<1x1xf32> into tensor<?x4096xf32>
+      }
+    }
+    tcp.yield %2 : tensor<?x4096xf32>
+  } : tensor<?x4096xf32>
+  return %0 : tensor<?x4096xf32>
+}
+
+// -----
+
+// Ensure that we correctly drop `tcp.bind_symbolic_shape` ops within the
+// newly created tcp.isolated_group region.
+
+// CHECK:   func.func @test_symbolic_shape_ops(%[[ARG0:.+]]: tensor<?x3xf32>) -> tensor<?x3xf32> {
+// CHECK:     %[[V0:.+]] = tcp.symbolic_int "s0" {min_val = 2, max_val = 9223372036854775806} : i64
+// CHECK:     tcp.bind_symbolic_shape %[[ARG0]], [%[[V0]]], affine_map<()[s0] -> (s0, 3)> : tensor<?x3xf32>
+// CHECK:     %[[V1:.+]] = tcp.isolated_group %[[ARG0]] {
+// CHECK:     ^bb0(%[[ARG1:.+]]: tensor<?x3xf32>):
+// CHECK:       %[[V2:.+]] = tcp.add %[[ARG1]], %[[ARG1]] : tensor<?x3xf32>, tensor<?x3xf32> -> tensor<?x3xf32>
+// CHECK-NOT: tcp.bind_symbolic_shape
+// CHECK:       %[[V3:.+]] = tcp.mul %[[V2]], %[[V2]] : tensor<?x3xf32>, tensor<?x3xf32> -> tensor<?x3xf32>
+// CHECK:       tcp.yield %[[V3]] : tensor<?x3xf32>
+// CHECK:     } : tensor<?x3xf32> -> tensor<?x3xf32>
+// CHECK:     tcp.bind_symbolic_shape %[[V1]], [%[[V0]]], affine_map<()[s0] -> (s0, 3)> : tensor<?x3xf32>
+// CHECK:     return %[[V1]] : tensor<?x3xf32>
+// CHECK:   }
+func.func @test_symbolic_shape_ops(%arg0 : tensor<?x3xf32>) -> tensor<?x3xf32> {
+  %0 = tcp.symbolic_int "s0" {min_val = 2, max_val = 9223372036854775806} : i64
+  tcp.bind_symbolic_shape %arg0, [%0], affine_map<()[s0] -> (s0, 3)> : tensor<?x3xf32>
+  %10 = "tcp.group" () ({
+    ^bb0() :
+      %2 = tcp.add %arg0, %arg0 : tensor<?x3xf32>, tensor<?x3xf32> -> tensor<?x3xf32>
+      tcp.bind_symbolic_shape %2, [%0], affine_map<()[s0] -> (s0, 3)> : tensor<?x3xf32>
+      %3 = tcp.mul %2, %2 : tensor<?x3xf32>, tensor<?x3xf32> -> tensor<?x3xf32>
+      tcp.yield %3 : tensor<?x3xf32>
+  }) : () -> tensor<?x3xf32>
+  tcp.bind_symbolic_shape %10, [%0], affine_map<()[s0] -> (s0, 3)> : tensor<?x3xf32>
+  return %10 : tensor<?x3xf32>
+}