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+/* Copyright 2018 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+
+#ifndef TENSORFLOW_COMPILER_JIT_DEADNESS_ANALYSIS_H_
+#define TENSORFLOW_COMPILER_JIT_DEADNESS_ANALYSIS_H_
+
+#include "tensorflow/core/graph/graph.h"
+
+namespace tensorflow {
+
+// This analyzes a TensorFlow graph to identify nodes which may have partially
+// dead inputs (i.e. these nodes may have some dead inputs and some alive
+// inputs).
+//
+// For example, the ADD node in the following graph
+//
+//      V0  PRED0    V1  PRED1
+//       |    |       |    |
+//       v    v       v    v
+//       SWITCH       SWITCH
+//          |            |
+//          +---+   + ---+
+//              |   |
+//              v   v
+//               ADD
+//
+// can have its inputs independently dead or alive based on the runtime values
+// of PRED0 and PRED1.
+//
+// It is tempting to call this a liveness analysis but I avoided that because
+// "liveness" already has other connotations.
+class DeadnessAnalysis {
+ public:
+  // Returns true if `node` may have some live inputs and some dead inputs.
+  //
+  // This is a conservatively correct routine -- if it returns false then `node`
+  // is guaranteed to not have inputs with mismatching liveness, but not the
+  // converse.
+  //
+  // REQUIRES: node is not a Merge operation.
+  virtual bool HasInputsWithMismatchingDeadness(const Node& node) = 0;
+
+  // Prints out the internal state of this instance.  For debugging purposes
+  // only.
+  virtual void Print() const = 0;
+  virtual ~DeadnessAnalysis();
+
+  // Run the deadness analysis over `graph` and returns an error or a populated
+  // instance of DeadnessAnalysis in `result`.
+  static Status Run(const Graph& graph,
+                    std::unique_ptr<DeadnessAnalysis>* result);
+};
+
+}  // namespace tensorflow
+
+#endif  // TENSORFLOW_COMPILER_JIT_DEADNESS_ANALYSIS_H_