[XLA] remove extraneous copies in copy_insertion related to nested conditionals and while loops. The change increases the precision of LiveRangeBefore analysis inside copy_insertion to accommodate disjoint branches inside conditionals that never overlap.

PiperOrigin-RevId: 347677692
Change-Id: I1fa3de590042078b7a6dde4c4bf8227c4c6416bb

tensorflow/compiler/xla/service/copy_insertion.cc

@@ -881,7 +881,16 @@ class CopyRemover {
       return ordering_.IsDefinedBefore(*a.value, *b.value);
     }
     return absl::c_all_of(a.uses, [&](const HloUse* use) {
-      return ordering_.UseIsBeforeValueDefinition(*use, *b.value, dataflow_);
+      switch (ordering_.GetExecutionConstraint(use->instruction,
+                                               b.value->instruction())) {
+        case HloOrdering::ExecutionConstraint::kIsSame:
+        case HloOrdering::ExecutionConstraint::kRunExclusiveAfter:
+        case HloOrdering::ExecutionConstraint::kRunExclusiveBefore:
+          return true;
+        default:
+          return ordering_.UseIsBeforeValueDefinition(*use, *b.value,
+                                                      dataflow_);
+      }
     });
   }
 

tensorflow/compiler/xla/service/copy_insertion_test.cc

@@ -2473,6 +2473,52 @@ ENTRY TestComputation {
               op::While(op::Copy(op::Parameter())));
 }
 
+TEST_F(CopyInsertionTest, NestedWhileAndConditional) {
+  const string& hlo_string = R"(
+HloModule TestModule
+
+on_true
+ {
+  v1 = f32[2] parameter(0)
+  ROOT v2 = f32[2] add(v1,v1)
+}
+
+on_false
+ {
+  v1 = f32[2] parameter(0)
+  ROOT v2 = f32[2] multiply(v1,v1)
+}
+
+cond.outer {
+  param.1 = (pred[], f32[2]) parameter(0)
+  ROOT param.cond.outer = pred[] get-tuple-element(param.1), index=0
+}
+
+body.outer {
+  param.1 = (pred[], f32[2]) parameter(0)
+  pred.1 = pred[] get-tuple-element(param.1), index=0
+  arg_tuple.11 = f32[2] get-tuple-element(param.1), index=1
+  if = f32[2] conditional(pred.1, arg_tuple.11, arg_tuple.11), true_computation=on_true, false_computation=on_false
+  ROOT res = (pred[], f32[2]) tuple(pred.1,if)
+}
+
+ENTRY TestComputation {
+  entry_param.1 = pred[] parameter(0)
+  float_param = f32[2] parameter(1)
+  entry_param = (pred[], f32[2]) tuple(entry_param.1, float_param)
+  ROOT while = (pred[], f32[2]) while(entry_param), condition=cond.outer, body=body.outer
+}
+)";
+  TF_ASSERT_OK_AND_ASSIGN(std::unique_ptr<HloModule> module,
+                          ParseAndReturnVerifiedModule(hlo_string));
+  InsertCopies(module.get());
+  VLOG(2) << module->ToString() << "\n";
+
+  // There should only be a single copy inserted, and it's in the entry
+  // computation.
+  EXPECT_EQ(CountCopies(*module), 2);
+}
+
 TEST_F(CopyInsertionTest, FixpointComputationRequired) {
   const string& hlo_string = R"(
 HloModule Module

tensorflow/compiler/xla/service/hlo_ordering.cc

@@ -34,6 +34,21 @@ namespace xla {
 
 bool HloOrdering::ExecutesBefore(const HloInstruction* a,
                                  const HloInstruction* b) const {
+  switch (GetExecutionConstraint(a, b)) {
+    case ExecutionConstraint::kIsSame:  // a and b are the same instruction;
+      return false;
+    case ExecutionConstraint::kRunBefore:
+    case ExecutionConstraint::kRunExclusiveBefore:
+      return true;
+    case ExecutionConstraint::kRunExclusiveAfter:
+    case ExecutionConstraint::kRunAfter:
+    case ExecutionConstraint::kUnordered:
+      return false;
+  }
+}
+
+HloOrdering::ExecutionConstraint HloOrdering::GetExecutionConstraint(
+    const HloInstruction* a, const HloInstruction* b) const {
   // 'a' and 'b' may be in different computations. In this case, find the
   // callgraph ancestor instructions which call (potentially transitively) the
   // computations containing 'a' and 'b' and use these ancestor instructions to
@@ -47,7 +62,7 @@ bool HloOrdering::ExecutesBefore(const HloInstruction* a,
   if (a_ancestor == nullptr) {
     // Ancestors in a common computation could not be found so consider the
     // instructions 'a' and 'b' to be unordered.
-    return false;
+    return ExecutionConstraint::kUnordered;
   }
   // a_ancestor and b_ancestor must be either both null or both non-null.
   CHECK_NE(b_ancestor, nullptr);
@@ -62,7 +77,7 @@ bool HloOrdering::ExecutesBefore(const HloInstruction* a,
     const HloComputation* condition = a_ancestor->while_condition();
     if (call_graph_->InstructionIsNestedIn(a, condition) &&
         call_graph_->InstructionIsNestedIn(b, body)) {
-      return true;
+      return ExecutionConstraint::kRunBefore;
     }
   }
 
@@ -85,17 +100,40 @@ bool HloOrdering::ExecutesBefore(const HloInstruction* a,
         b_branch = j;
       }
     }
-    if (a_branch != -1 && a_branch < b_branch) {
-      return true;
+    // If neither a nor b is inside the branches they both are the ancestor.
+    if (a_branch == -1 && b_branch == -1) {
+      CHECK_EQ(a, a_ancestor);
+      CHECK_EQ(b, b_ancestor);
+      CHECK_EQ(a, b);
+      return ExecutionConstraint::kIsSame;
     }
     // If 'b' is the conditional ancestor, and 'a' is within a branch
     // computation, 'a' executes before 'b'.
-    if (b == a_ancestor && a_branch != -1) {
-      return true;
+    if (b_branch == -1) {
+      CHECK_EQ(b, a_ancestor);
+      return ExecutionConstraint::kRunBefore;
+    }
+    if (a_branch == -1) {
+      CHECK_EQ(a, a_ancestor);
+      return ExecutionConstraint::kRunAfter;
+    }
+    if (a_branch < b_branch) {
+      return ExecutionConstraint::kRunExclusiveBefore;
+    }
+    if (b_branch < a_branch) {
+      return ExecutionConstraint::kRunExclusiveAfter;
     }
   }
 
-  return ExecutesBeforeInSameComputation(a_ancestor, b_ancestor);
+  if (ExecutesBeforeInSameComputation(a_ancestor, b_ancestor)) {
+    return ExecutionConstraint::kRunBefore;
+  }
+  if (ExecutesBeforeInSameComputation(b_ancestor, a_ancestor)) {
+    return ExecutionConstraint::kRunAfter;
+  }
+  VLOG(1) << "Cannot determine order between:" << a_ancestor->ToString() << "\n"
+          << "and " << b_ancestor->ToString() << "\n";
+  return ExecutionConstraint::kUnordered;
 }
 
 bool HloOrdering::IsDefinedBefore(const HloValue& a, const HloValue& b) const {

tensorflow/compiler/xla/service/hlo_ordering.h

@@ -37,10 +37,30 @@ namespace xla {
 // determine live range overlap of HLO instruction output buffers.
 class HloOrdering {
  public:
-  HloOrdering(const HloModule* module)
+  explicit HloOrdering(const HloModule* module)
       : module_(module), call_graph_(CallGraph::Build(module)) {}
   virtual ~HloOrdering() = default;
 
+  // Specify the ordering constraints between a pair of instructions a and b.
+  enum class ExecutionConstraint {
+    // Indicate a and b are the same instruction;
+    kIsSame,
+    // Indicate a runs before b;
+    kRunBefore,
+    // Only one of a or b runs each time their common ancestor is evaluated,
+    // and a is in an earlier branch than b.
+    kRunExclusiveBefore,
+    // Only one of a or b runs each time, and a is in a later branch than b.
+    kRunExclusiveAfter,
+    // Indicate a runs after b
+    kRunAfter,
+    // An order cannot be detrermined as a and b do not have a common ancestor.
+    kUnordered,
+  };
+  // Return the execution constraint between a and b.
+  HloOrdering::ExecutionConstraint GetExecutionConstraint(
+      const HloInstruction* a, const HloInstruction* b) const;
+
   // Returns true if instruction 'a' executes before instruction 'b'. This is
   // not reflexive, that is, an instruction does not execute before itself.
   bool ExecutesBefore(const HloInstruction* a, const HloInstruction* b) const;
@@ -181,8 +201,8 @@ class DependencyHloOrdering : public PredecessorHloOrdering {
 // interference is reduced relative to DependencyHloOrdering.
 class SequentialHloOrdering : public HloOrdering {
  public:
-  SequentialHloOrdering(const HloSchedule& schedule);
-  SequentialHloOrdering(HloSchedule&& schedule);
+  explicit SequentialHloOrdering(const HloSchedule& schedule);
+  explicit SequentialHloOrdering(HloSchedule&& schedule);
   ~SequentialHloOrdering() override = default;
 
   // Returns the sequential instruction order for the given computation.