Cherry-pick PR41720, support no_need_buffer in eager_fluid state (#41720) (#41956)

* support no_need_buffer in eager_fluid state

* change no_need_buffer info from fwd_info to bwd_info

* fix CI fail, gru_unit donnot use no_need_buffer

* fix conflict between no_need_buffer and dispensable

* use tensor.define in dispensable

* solve conflict

* solve conflict

paddle/fluid/eager/auto_code_generator/eager_generator.cc

@@ -217,6 +217,13 @@ class GradNodeGenerationInfo {
       return &grad_attrs_;
     }
 
+    const std::unordered_set<std::string>& GetNoNeedBufferInputs() const {
+      return no_need_buffer_ins_;
+    }
+    std::unordered_set<std::string>* GetMutableNoNeedBufferInputs() {
+      return &no_need_buffer_ins_;
+    }
+
    private:
     std::string op_base_type_;
     std::map<std::string, std::string> grad_outs_slotname_map_;
@@ -229,6 +236,7 @@ class GradNodeGenerationInfo {
              std::vector<std::shared_ptr<paddle::imperative::VariableWrapper>>>
         grad_outs_;
     paddle::framework::AttributeMap grad_attrs_;
+    std::unordered_set<std::string> no_need_buffer_ins_;
   };
 
  public:
@@ -958,6 +966,12 @@ static bool CollectGradInformationFromOpInfo(
         VLOG(6) << "GradOuts Name: " << it.first;
       }
     }
+
+    auto& inferer = op_base.Info().NoNeedBufferVarsInferer();
+    if (inferer && !special_no_need_buffer_op_set.count(op_type)) {
+      *(*op_base_infos)[index].GetMutableNoNeedBufferInputs() =
+          inferer(g_ins, g_outs, *op_base_grad_attrs);
+    }
   }
 
   /* ------ Slot Name Matching ---- */
@@ -1129,11 +1143,14 @@ static std::string GenerateGradNodeCreationContent(
   for (const auto& iter : op_base_infos) {
     const std::map<std::string, std::string>& grad_ins_fwd_slotname_map =
         iter.GetGradInsFwdSlotnameMap();
+    const std::unordered_set<std::string>& no_need_buffer_ins =
+        iter.GetNoNeedBufferInputs();
     for (auto& kv : grad_ins_fwd_slotname_map) {
       const std::string& tensor_wrapper_name = kv.second;
       std::string full_reserved = "false";
       if (fwd_outputs_name_pos_map.find(tensor_wrapper_name) ==
-          fwd_outputs_name_pos_map.end()) {
+              fwd_outputs_name_pos_map.end() &&
+          !no_need_buffer_ins.count(tensor_wrapper_name)) {
         full_reserved = "true";
       }
       const char* SET_TENSOR_WRAPPER_TEMPLATE =
@@ -2064,7 +2081,7 @@ static std::string GenerateSingleOpBase(
         } else {
           const char* DISPENSABLE_GRAD_INS_FWD_CONTENT_TEMPLATE =
               "  auto %s = egr::EagerUtils::RecoverTensorWrapper(&this->%s);\n"
-              "  if(%s.initialized()) %s[\"%s\"] = "
+              "  if(%s.defined()) %s[\"%s\"] = "
               "     egr::EagerUtils::TrySyncToVars(%s);\n";
           generated_grad_function_body += paddle::string::Sprintf(
               DISPENSABLE_GRAD_INS_FWD_CONTENT_TEMPLATE, grad_input_name,
@@ -2190,7 +2207,7 @@ static std::string GenerateSingleOpBase(
                 grad_output_name, fwd_input_position);
           } else {
             const char* DISPENSABLE_GRAD_OUTS_FWD_CONTENT_TEMPLATE =
-                "  if(%s.initialized()) %s[\"%s\"] = "
+                "  if(%s.defined()) %s[\"%s\"] = "
                 "{std::make_shared<egr::EagerVariable>(egr::Controller::"
                 "Instance().GenerateUniqueName())};\n";
             generated_grad_function_body += paddle::string::Sprintf(
@@ -2532,6 +2549,8 @@ static std::string GenerateGradNodeHeaderContents(
   for (const auto& iter : op_base_infos) {
     const std::map<std::string, std::string>& grad_ins_fwd_slotname_map =
         iter.GetGradInsFwdSlotnameMap();
+    const std::unordered_set<std::string>& no_need_buffer_ins =
+        iter.GetNoNeedBufferInputs();
 
     for (const auto& kv : grad_ins_fwd_slotname_map) {
       const std::string& tensor_wrapper_name = kv.second;
@@ -2540,6 +2559,10 @@ static std::string GenerateGradNodeHeaderContents(
       std::string tensor_wrapper_arg_str;
       std::string tensor_wrapper_body_str;
       std::string full_reserved_str = "full_reserved";
+      std::string no_need_buffer_str = "false";
+      if (no_need_buffer_ins.count(tensor_wrapper_name)) {
+        no_need_buffer_str = "true";
+      }
       if (duplicable_tensors.count(tensor_wrapper_name)) {
         const char* ATTR_TENSOR_WRAPPER_ARG_TEMPLATE =
             "const std::vector<paddle::experimental::Tensor>& %s";
@@ -2553,12 +2576,12 @@ static std::string GenerateGradNodeHeaderContents(
 
         const char* SET_TENSOR_WRAPPER_BODY_TEMPLATE =
             "for(const auto& eager_tensor : %s) {\n"
-            "          %s.emplace_back( egr::TensorWrapper(eager_tensor, true "
-            "/*full_reserved*/) );\n"
+            "          %s.emplace_back( egr::TensorWrapper(eager_tensor, %s "
+            "/*full_reserved*/, %s) );\n"
             "      }\n";
         tensor_wrapper_body_str = paddle::string::Sprintf(
             SET_TENSOR_WRAPPER_BODY_TEMPLATE, tensor_wrapper_name,
-            struct_tensor_wrapper_name);
+            struct_tensor_wrapper_name, full_reserved_str, no_need_buffer_str);
 
         const char* CLEAR_TENSOR_WRAPPER_TEMPLATE =
             "for (auto tw: %s)   {\n"
@@ -2579,10 +2602,10 @@ static std::string GenerateGradNodeHeaderContents(
             TENSOR_WRAPPER_MEMBER_TEMPLATE, struct_tensor_wrapper_name);
 
         const char* SET_TENSOR_WRAPPER_BODY_TEMPLATE =
-            "%s = egr::TensorWrapper(%s, %s /*full_reserved*/);\n";
+            "%s = egr::TensorWrapper(%s, %s /*full_reserved*/, %s);\n";
         tensor_wrapper_body_str = paddle::string::Sprintf(
             SET_TENSOR_WRAPPER_BODY_TEMPLATE, struct_tensor_wrapper_name,
-            tensor_wrapper_name, full_reserved_str);
+            tensor_wrapper_name, full_reserved_str, no_need_buffer_str);
 
         const char* CLEAR_TENSOR_WRAPPER_TEMPLATE = "   %s.clear();\n";
         clear_tensor_wrappers_str += paddle::string::Sprintf(

paddle/fluid/pybind/op_function_generator.h

@@ -276,3 +276,11 @@ std::set<std::string> special_inplace_op_set = {
     "sum",     // `sum` op has duplicate input
     "assign",  // output of `assign` op is in `op_passing_outs_map`
 };
+
+// NOTE(pangyoki): Special no_need_buffer ops that are not supported in
+// temporary.
+// sequence_conv op will raise error to get no_need_buffer info during
+// compiling.
+std::set<std::string> special_no_need_buffer_op_set = {
+    "sequence_conv",
+};

python/paddle/fluid/tests/unittests/test_inplace.py

@@ -510,5 +510,19 @@ class TestContinuouslyInplace(unittest.TestCase):
         self.func_test_continuously_inplace()
 
 
+class TestGetitemBeforeInplace(unittest.TestCase):
+    def test_getitem_before_inplace(self):
+        with _test_eager_guard():
+            a = paddle.ones(shape=[4, 2, 3], dtype="float32")
+            a.stop_gradient = False
+            b = a**2
+            b[0] = 3
+            # getitem has no_need_buffer input
+            c = b[0:2]
+            loss = c.sum()
+            b[1] = 2
+            loss.backward()
+
+
 if __name__ == '__main__':
     unittest.main()