1 files changed, 18 insertions, 14 deletions

diff --git a/tensorflow/contrib/lite/toco/graph_transformations/fuse_binary_into_following_affine.cc b/tensorflow/contrib/lite/toco/graph_transformations/fuse_binary_into_following_affine.cc
index dcbbead517..0de22b8ff4 100644
--- a/tensorflow/contrib/lite/toco/graph_transformations/fuse_binary_into_following_affine.cc
+++ b/tensorflow/contrib/lite/toco/graph_transformations/fuse_binary_into_following_affine.cc
@@ -150,14 +150,17 @@ void FuseMulOrDivParamsIntoFollowingAffine(Model* model, Operator* following_op,
 
 }  // namespace
 
-bool FuseBinaryIntoFollowingAffine::Run(Model* model, std::size_t op_index) {
+::tensorflow::Status FuseBinaryIntoFollowingAffine::Run(Model* model,
+                                                        std::size_t op_index,
+                                                        bool* modified) {
+  *modified = false;
   const auto binary_it = model->operators.begin() + op_index;
   auto* binary_op = binary_it->get();
   if (binary_op->type != OperatorType::kAdd &&
       binary_op->type != OperatorType::kMul &&
       binary_op->type != OperatorType::kSub &&
       binary_op->type != OperatorType::kDiv) {
-    return false;
+    return ::tensorflow::Status::OK();
   }
 
   CHECK_EQ(binary_op->inputs.size(), 2);
@@ -175,12 +178,12 @@ bool FuseBinaryIntoFollowingAffine::Run(Model* model, std::size_t op_index) {
   };
   if (!is_input_constant[0] && !is_input_constant[1]) {
     // Neither input is constant, so nothing we can fuse into a constant.
-    return false;
+    return ::tensorflow::Status::OK();
   }
   if (is_input_constant[0] && is_input_constant[1]) {
     // Both inputs are constants. That's a job for constants
     // propagation, not for us to handle here.
-    return false;
+    return ::tensorflow::Status::OK();
   }
   const int index_of_constant_input = is_input_constant[0] ? 0 : 1;
   const int index_of_variable_input = is_input_constant[0] ? 1 : 0;
@@ -192,7 +195,7 @@ bool FuseBinaryIntoFollowingAffine::Run(Model* model, std::size_t op_index) {
     if (index_of_constant_input != 1) {
       AddMessageF("Not fusing %s because the denominator is not constant",
                   LogName(*binary_op));
-      return false;
+      return ::tensorflow::Status::OK();
     }
   }
 
@@ -204,7 +207,7 @@ bool FuseBinaryIntoFollowingAffine::Run(Model* model, std::size_t op_index) {
           "Not fusing %s into the following affine op, because we only know "
           "how to do so when the constant operand is a scalar",
           LogName(*binary_op));
-      return false;
+      return ::tensorflow::Status::OK();
     }
   }
 
@@ -212,7 +215,7 @@ bool FuseBinaryIntoFollowingAffine::Run(Model* model, std::size_t op_index) {
       FusedActivationFunctionType::kNone) {
     AddMessageF("Not fusing %s because it has a fused activation function",
                 LogName(*binary_op));
-    return false;
+    return ::tensorflow::Status::OK();
   }
 
   Operator* following_op = GetOpWithInput(*model, binary_op->outputs[0]);
@@ -221,7 +224,7 @@ bool FuseBinaryIntoFollowingAffine::Run(Model* model, std::size_t op_index) {
     AddMessageF(
         "Not fusing %s because it is not consumed by exactly one other op",
         LogName(*binary_op));
-    return false;
+    return ::tensorflow::Status::OK();
   }
 
   if (following_op->type != OperatorType::kConv &&
@@ -231,14 +234,14 @@ bool FuseBinaryIntoFollowingAffine::Run(Model* model, std::size_t op_index) {
         "Not fusing %s because the following %s is not of one of the supported "
         "types",
         LogName(*binary_op), LogName(*following_op));
-    return false;
+    return ::tensorflow::Status::OK();
   }
 
   if (following_op->inputs.size() < 3) {
     AddMessageF(
         "Not fusing %s because the following %s does not have a bias vector",
         LogName(*following_op), LogName(*binary_op));
-    return false;
+    return ::tensorflow::Status::OK();
   }
 
   const auto& weights = model->GetArray(following_op->inputs[1]);
@@ -248,7 +251,7 @@ bool FuseBinaryIntoFollowingAffine::Run(Model* model, std::size_t op_index) {
         "Not fusing %s because the following %s has non-constant weights or "
         "bias arrays",
         LogName(*binary_op), LogName(*following_op));
-    return false;
+    return ::tensorflow::Status::OK();
   }
 
   // Try to fuse the binary params into the following op's params
@@ -260,7 +263,7 @@ bool FuseBinaryIntoFollowingAffine::Run(Model* model, std::size_t op_index) {
         AddMessageF(
             "Not fusing %s because the following %s does not use VALID padding",
             LogName(*binary_op), LogName(*following_op));
-        return false;
+        return ::tensorflow::Status::OK();
       }
     }
     if (following_op->type == OperatorType::kDepthwiseConv) {
@@ -269,7 +272,7 @@ bool FuseBinaryIntoFollowingAffine::Run(Model* model, std::size_t op_index) {
         AddMessageF(
             "Not fusing %s because the following %s does not use VALID padding",
             LogName(*binary_op), LogName(*following_op));
-        return false;
+        return ::tensorflow::Status::OK();
       }
     }
     FuseAddOrSubParamsIntoFollowingAffine(model, following_op, binary_op,
@@ -294,7 +297,8 @@ bool FuseBinaryIntoFollowingAffine::Run(Model* model, std::size_t op_index) {
     model->EraseArray(old_constant_param_name);
   }
   model->operators.erase(binary_it);
-  return true;
+  *modified = true;
+  return ::tensorflow::Status::OK();
 }
 
 }  // namespace toco