clean unused inference_optimize c++ implementation

paddle/fluid/framework/prune.cc

@@ -183,28 +183,5 @@ void Prune(const proto::ProgramDesc& input, proto::ProgramDesc* output) {
   output->clear_blocks();
   prune_impl(input, output, 0, -1, &dependent_vars);
 }
-
-void inference_optimize_impl(proto::ProgramDesc* input, int block_id) {
-  auto* op_field = input->mutable_blocks(block_id)->mutable_ops();
-  for (auto& op_desc : *op_field) {
-    for (auto& attr : *op_desc.mutable_attrs()) {
-      if (attr.name() == "is_test") {
-        attr.set_b(true);
-        break;
-      }
-    }
-  }
-}
-
-void InferenceOptimize(const proto::ProgramDesc& input,
-                       proto::ProgramDesc* output) {
-  *output = input;
-  int num_blocks = output->blocks_size();
-  PADDLE_ENFORCE_GT(num_blocks, 0, "ProgramDesc must have at least one block");
-  for (int i = 0; i < num_blocks; ++i) {
-    inference_optimize_impl(output, i);
-  }
-}
-
 }  // namespace framework
 }  // namespace paddle

paddle/fluid/framework/prune.h

@@ -22,8 +22,5 @@ namespace framework {
 
 void Prune(const proto::ProgramDesc& input, proto::ProgramDesc* output);
 
-void InferenceOptimize(const proto::ProgramDesc& input,
-                       proto::ProgramDesc* output);
-
 }  // namespace framework
 }  // namespace paddle

paddle/fluid/pybind/pybind.cc

@@ -396,11 +396,6 @@ All parameter, weight, gradient are variables in Paddle.
     Prune(*prog_with_targets.Proto(), &pruned_desc);
     return new ProgramDesc(pruned_desc);
   });
-  m.def("inference_optimize", [](ProgramDesc &origin) {
-    proto::ProgramDesc pruned_desc;
-    InferenceOptimize(*(origin.Proto()), &pruned_desc);
-    return new ProgramDesc(pruned_desc);
-  });
   m.def("empty_var_name",
         []() { return std::string(framework::kEmptyVarName); });
   m.def("grad_var_suffix",

python/paddle/fluid/framework.py

@@ -1738,8 +1738,6 @@ class Program(object):
         Returns:
             Program: The new program.
         """
-        # this is an alternative implement before
-        # core.inference_optimize being fixed.
         res = Program()
         res.desc = core.ProgramDesc(self.desc)