[NewIR][BugFix] fix empty_var_name problem (#55546)

* fix empty_var_name problem

* fix coverage ci

* fix coverage ci

paddle/fluid/ir_adaptor/translator/op_translator.cc

@@ -480,14 +480,7 @@ OpTranscriber::GenerateOperationOutput(ir::IrContext* ctx,
       continue;
     }
 
-    const auto& origin_legacy_output_vars = op_desc.Output(legacy_output_name);
-    std::vector<std::string> legacy_output_vars;
-    std::copy_if(
-        origin_legacy_output_vars.begin(),
-        origin_legacy_output_vars.end(),
-        std::back_inserter(legacy_output_vars),
-        [](const auto& var_name) { return var_name != kEmptyVarName; });
-
+    const auto& legacy_output_vars = op_desc.Output(legacy_output_name);
     bool is_vector = (info.type_name.find("VectorType") != std::string::npos);
 
     // Specially process TensorArray, this because we cannot distinguish it with
@@ -534,6 +527,11 @@ OpTranscriber::GenerateOperationOutput(ir::IrContext* ctx,
                << info.type_name << " " << legacy_output_name;
       std::vector<ir::Type> types;
       for (const auto& var_name : legacy_output_vars) {
+        if (var_name == kEmptyVarName) {
+          types.push_back(ir::Type(nullptr));
+          arg_to_idx[var_name] = cur_output_idx;
+          continue;
+        }
         VarDesc* var = block->FindVarRecursive(var_name);
         VLOG(10) << "[output translating]"
                  << "[" << op_desc.Type() << "]" << info.name << " " << var_name
@@ -562,7 +560,8 @@ ir::AttributeMap OpTranscriber::TranslateOpAttribute(
   for (const auto& info : op_attr_infos) {
     auto legacy_attr_name =
         op_normalizer.GetLegacyAttrName(op_desc.Type(), info.name);
-
+    VLOG(10) << "[op: " << op_desc.Type()
+             << "][attr] from: " << legacy_attr_name << " to: " << info.name;
     if (op_desc.HasAttr(legacy_attr_name)) {
       paddle::framework::Attribute legacy_attr =
           op_desc.GetAttr(legacy_attr_name);

paddle/fluid/ir_adaptor/translator/program_translator.cc

@@ -179,6 +179,7 @@ void ProgramTranslator::SetParameterFromSingleBlock(const BlockDesc& block) {
         bool need_set_parameter_op = (parameter_name_mappings_.find(var_name) !=
                                       parameter_name_mappings_.end());
         need_set_parameter_op &= (parameter_visited_.count(var_name) == 0);
+        need_set_parameter_op &= (param_map_.count(var_name) != 0);
         if (need_set_parameter_op) {
           ir::OpResult defining_op_result = param_map_[var_name].value;
           ir::Operation* op = InsertSetParamaterOp(

test/ir/new_ir/test_special_op_translator.py

@@ -33,10 +33,7 @@ class TestCastOpTranscriber(unittest.TestCase):
                 x = paddle.to_tensor([2, 3, 4], 'float64')
                 y = paddle.cast(x, 'uint8')
 
-                default_job = core.Job("default")
-                type_to_program = {"default": main_program.desc}
-                plan = core.Plan([default_job], type_to_program)
-                new_exe = core.StandaloneExecutor(place, plan, new_scope)
+        _ = paddle.fluid.core.translate_newirprogram(main_program.desc)
 
 
 class TestEmbeddingOpTranscriber(unittest.TestCase):
@@ -53,10 +50,7 @@ class TestEmbeddingOpTranscriber(unittest.TestCase):
                 )
                 output = embedding(x)
 
-                default_job = core.Job("default")
-                type_to_program = {"default": main_program.desc}
-                plan = core.Plan([default_job], type_to_program)
-                new_exe = core.StandaloneExecutor(place, plan, new_scope)
+        _ = paddle.fluid.core.translate_newirprogram(main_program.desc)
 
 
 class TestIncrementOpTranscriber(unittest.TestCase):
@@ -70,10 +64,7 @@ class TestIncrementOpTranscriber(unittest.TestCase):
                 data = paddle.zeros(shape=[1], dtype='float32')
                 counter = paddle.increment(data)
 
-                default_job = core.Job("default")
-                type_to_program = {"default": main_program.desc}
-                plan = core.Plan([default_job], type_to_program)
-                new_exe = core.StandaloneExecutor(place, plan, new_scope)
+        _ = paddle.fluid.core.translate_newirprogram(main_program.desc)
 
 
 class TestAssignValueOpTranscriber(unittest.TestCase):
@@ -90,10 +81,7 @@ class TestAssignValueOpTranscriber(unittest.TestCase):
                     stop_gradient=False,
                 )
 
-                default_job = core.Job("default")
-                type_to_program = {"default": main_program.desc}
-                plan = core.Plan([default_job], type_to_program)
-                new_exe = core.StandaloneExecutor(place, plan, new_scope)
+        _ = paddle.fluid.core.translate_newirprogram(main_program.desc)
 
 
 class TestRnnOpTranscriber(unittest.TestCase):
@@ -110,10 +98,29 @@ class TestRnnOpTranscriber(unittest.TestCase):
                 cell = paddle.nn.SimpleRNNCell(16, 32)
                 y, h = cell(x, prev_h)
 
-                default_job = core.Job("default")
-                type_to_program = {"default": main_program.desc}
-                plan = core.Plan([default_job], type_to_program)
-                new_exe = core.StandaloneExecutor(place, plan, new_scope)
+        _ = paddle.fluid.core.translate_newirprogram(main_program.desc)
+
+
+class TestEmptyVarTranslate(unittest.TestCase):
+    def test_op(self):
+        place = core.Place()
+        place.set_place(paddle.CPUPlace())
+        new_scope = paddle.static.Scope()
+        main_program = paddle.static.Program()
+        with paddle.static.scope_guard(new_scope):
+            with paddle.static.program_guard(main_program):
+                x1 = paddle.rand(shape=[3, 3], dtype="float32")
+                x1.stop_gradient = False
+                weight = paddle.full(
+                    shape=[3, 3], fill_value="0.5", dtype="float32"
+                )
+                y = paddle.nn.functional.linear(x1, weight)
+                y.stop_gradient = True
+                out1 = paddle.concat(x=[x1, y], axis=1)
+                out2 = paddle.mean(out1)
+                sgd_optimizer = paddle.optimizer.SGD(learning_rate=0.1)
+                sgd_optimizer.minimize(out2)
+        _ = paddle.fluid.core.translate_newirprogram(main_program.desc)
 
 
 class TestOneHotOpTranscriber(unittest.TestCase):