Add a way to specify the optimization order; refactor and add constant folding to meta optimizer.

Change: 152193646

tensorflow/core/grappler/optimizers/BUILD

@@ -17,6 +17,7 @@ filegroup(
     srcs = glob(
         [
             "*_optimizer.*",
+            "constant_folding.*",
             "model_pruner.*",
             "graph_rewriter.*",
         ],
@@ -175,6 +176,7 @@ cc_library(
     ],
     visibility = ["//visibility:public"],
     deps = [
+        ":constant_folding",
         ":graph_optimizer",
         ":layout_optimizer",
         ":model_pruner",

tensorflow/core/grappler/optimizers/constant_folding.cc

@@ -72,8 +72,7 @@ class DeviceSimple : public DeviceBase {
                              Tensor* tensor) override {
     Tensor parsed(tensor_proto.dtype());
     if (!parsed.FromProto(cpu_allocator(), tensor_proto)) {
-      return errors::InvalidArgument("Cannot parse tensor from proto: ",
+      return errors::InvalidArgument("Cannot parse tensor from tensor_proto.");
-                                     tensor_proto.DebugString());
     }
     *tensor = parsed;
     return Status::OK();

tensorflow/core/grappler/optimizers/meta_optimizer.cc

@@ -14,6 +14,8 @@ limitations under the License.
 ==============================================================================*/
 
 #include "tensorflow/core/grappler/optimizers/meta_optimizer.h"
+#include "tensorflow/core/grappler/optimizers/constant_folding.h"
+#include "tensorflow/core/grappler/optimizers/graph_optimizer.h"
 #include "tensorflow/core/grappler/optimizers/layout_optimizer.h"
 #include "tensorflow/core/grappler/optimizers/model_pruner.h"
 #include "tensorflow/core/lib/core/status.h"
@@ -21,25 +23,64 @@ limitations under the License.
 namespace tensorflow {
 namespace grappler {
 
+std::unique_ptr<GraphOptimizer> MetaOptimizer::NewOptimizer(
+    const string& optimizer) {
+  VLOG(1) << "Adding graph optimization pass: " << optimizer;
+  std::unique_ptr<GraphOptimizer> graph_optimizer;
+  if (optimizer == "pruning") {
+    graph_optimizer.reset(new ModelPruner());
+  }
+  if (optimizer == "constfold") {
+    graph_optimizer.reset(new ConstantFolding());
+  }
+  if (optimizer == "layout") {
+    graph_optimizer.reset(new LayoutOptimizer());
+  }
+  return graph_optimizer;
+}
+
 Status MetaOptimizer::Optimize(Cluster* cluster, const GrapplerItem& item,
                                GraphDef* optimized_graph) {
-  bool already_optimized = false;
+  std::vector<std::unique_ptr<GraphOptimizer>> optimizers;
-  if (!cfg_.disable_model_pruning()) {
+  if (cfg_.optimizers().empty()) {
-    already_optimized = true;
+    if (!cfg_.disable_model_pruning()) {
-    ModelPruner pruner;
+      optimizers.push_back(std::unique_ptr<GraphOptimizer>(new ModelPruner()));
-    TF_RETURN_IF_ERROR(pruner.Optimize(nullptr, item, optimized_graph));
+    }
+    if (cfg_.constant_folding()) {
+      optimizers.push_back(
+          std::unique_ptr<GraphOptimizer>(new ConstantFolding()));
+    }
+    if (cfg_.optimize_tensor_layout()) {
+      optimizers.push_back(
+          std::unique_ptr<GraphOptimizer>(new LayoutOptimizer()));
+    }
+  } else {
+    std::set<string> avaliable_optimizers = {"pruning", "constfold", "layout"};
+    for (const auto& optimizer : cfg_.optimizers()) {
+      if (avaliable_optimizers.find(optimizer) != avaliable_optimizers.end()) {
+        optimizers.push_back(NewOptimizer(optimizer));
+      }
+    }
   }
-  if (cfg_.optimize_tensor_layout()) {
+
-    LayoutOptimizer layout_optimizer;
+  if (optimizers.empty()) {
+    *optimized_graph = item.graph;
+    return Status::OK();
+  }
+
+  bool already_optimized = false;
+  for (const auto& optimizer : optimizers) {
     if (!already_optimized) {
-      return layout_optimizer.Optimize(nullptr, item, optimized_graph);
+      TF_RETURN_IF_ERROR(optimizer->Optimize(nullptr, item, optimized_graph));
+      already_optimized = true;
     } else {
       GrapplerItem optimized_item = item;
       optimized_item.graph = *optimized_graph;
-      return layout_optimizer.Optimize(nullptr, optimized_item,
+      TF_RETURN_IF_ERROR(
-                                       optimized_graph);
+          optimizer->Optimize(nullptr, optimized_item, optimized_graph));
     }
   }
+
   return Status::OK();
 }
 

tensorflow/core/grappler/optimizers/meta_optimizer.h

@@ -39,6 +39,7 @@ class MetaOptimizer : public GraphOptimizer {
                 const GraphDef& optimized_graph, double result) override;
 
  private:
+  std::unique_ptr<GraphOptimizer> NewOptimizer(const string& optimizer);
   RewriterConfig cfg_;
 };
 

tensorflow/core/protobuf/rewriter_config.proto

@@ -9,4 +9,8 @@ option java_package = "org.tensorflow.framework";
 message RewriterConfig {
   bool optimize_tensor_layout = 1;
   bool disable_model_pruning = 2;
+  bool constant_folding = 3;
+  // If non-empty, will use this as an alternative way to specify a list of
+  // optimizations to turn on and the order of the optimizations.
+  repeated string optimizers = 100;
 }