【Prim】Refactor prim flags system

paddle/fluid/eager/auto_code_generator/generator/eager_gen.py

@@ -1841,7 +1841,7 @@ def GenerateHigherOrderNodeCreationCode(self):
 
         if is_composite_grad_api and next_grad_node_creation_str != '':
             next_grad_node_creation_str = f"""
- if (!paddle::prim::PrimCommonUtils::IsPrimEnabled()) {{
+ if (!paddle::prim::PrimCommonUtils::IsBwdPrimEnabled()) {{
     {next_grad_node_creation_str}
  }}
   """
@@ -2261,7 +2261,7 @@ def GenerateNodeDefinition(
         # TODO(Ruting):using composite only when we don't have backward kernel in the future.
         elif is_composite_grad_api:
             grad_function_call_str = f"""
-  if (paddle::prim::PrimCommonUtils::IsPrimEnabled()) {{
+  if (paddle::prim::PrimCommonUtils::IsBwdPrimEnabled()) {{
   {indent}{composite_grad_api_namespace}{composite_grad_api_name}{composite_template_name}({composite_grad_api_args_str});
   VLOG(4) << "Composite api {composite_grad_api_name} is called ";
   }}else{{

paddle/fluid/prim/api/generated/prim_api/static_prim_api.cc

@@ -12,6 +12,7 @@
 // See the License for the specific language governing permissions and
 // limitations under the License.
 
+#include <string.h>
 #include <memory>
 #include <sstream>
 #include <string>
@@ -166,7 +167,16 @@ Tensor full<DescTensor>(const IntArray& shape,
       phi::errors::InvalidArgument(
           "We only support float32/float16 for full, but we got data type: %s",
           phi::DataTypeToString(dtype)));
-  op->SetAttr("value", value.to<float>());
+  if (dtype == phi::DataType::FLOAT32) {
+    op->SetAttr("value", value.to<float>());
+  } else if (dtype == phi::DataType::FLOAT64) {
+    op->SetAttr("str_value", std::to_string(value.to<double>()));
+  } else if (dtype == phi::DataType::FLOAT16) {
+    op->SetAttr("str_value", std::to_string(value.to<float>()));
+  } else {
+    PADDLE_THROW(phi::errors::Unimplemented(
+        "We only support float64/float32/float16 for full"));
+  }
   op->SetAttr("dtype", paddle::framework::TransToProtoVarType(dtype));
   op->SetOutput(
       "Out", {std::static_pointer_cast<prim::DescTensor>(out.impl())->Name()});

paddle/fluid/prim/api/manual/backward/composite_backward_api.h

@@ -192,7 +192,7 @@ void divide_grad(const Tensor& x,
   }  // indicate we will compute dy
   if (dx) {
     // dx = (1/y) * dout
-    auto one_tensor = full<T>(phi::vectorize(y.dims()), 1.0);
+    auto one_tensor = full<T>(phi::vectorize(y.dims()), 1.0, y.dtype());
     auto tmp0 = divide<T>(one_tensor, y);
     auto dx_res = multiply<T>(tmp0, out_grad);
     if (y.dims() != x.dims()) {

paddle/fluid/prim/tests/test_eager_prim.cc

@@ -68,16 +68,16 @@ TEST(EagerPrim, TanhBackwardTest) {
   paddle::experimental::Tensor out0 = tanh_ad_func(tensor0);
   std::vector<paddle::experimental::Tensor> outs0 = {out0};
   // Disable prim
-  PrimCommonUtils::SetPrimEnabled(false);
-  ASSERT_FALSE(PrimCommonUtils::IsPrimEnabled());
+  PrimCommonUtils::SetBwdPrimEnabled(false);
+  ASSERT_FALSE(PrimCommonUtils::IsBwdPrimEnabled());
   // 4. Run Backward
   egr::Backward(outs0, {}, false);
 
   paddle::experimental::Tensor out1 = tanh_ad_func(tensor1);
   std::vector<paddle::experimental::Tensor> outs1 = {out1};
   // Disable prim
-  PrimCommonUtils::SetPrimEnabled(true);
-  ASSERT_TRUE(PrimCommonUtils::IsPrimEnabled());
+  PrimCommonUtils::SetBwdPrimEnabled(true);
+  ASSERT_TRUE(PrimCommonUtils::IsBwdPrimEnabled());
   // 4. Run Backward
   ::egr::Backward(outs1, {}, false);
   VLOG(7)
@@ -99,10 +99,10 @@ TEST(EagerPrim, TanhBackwardTest) {
 }
 
 TEST(EagerPrim, TestFlags) {
-  PrimCommonUtils::SetPrimEnabled(true);
-  ASSERT_TRUE(PrimCommonUtils::IsPrimEnabled());
-  PrimCommonUtils::SetPrimEnabled(false);
-  ASSERT_FALSE(PrimCommonUtils::IsPrimEnabled());
+  PrimCommonUtils::SetBwdPrimEnabled(true);
+  ASSERT_TRUE(PrimCommonUtils::IsBwdPrimEnabled());
+  PrimCommonUtils::SetBwdPrimEnabled(false);
+  ASSERT_FALSE(PrimCommonUtils::IsBwdPrimEnabled());
 }
 
 }  // namespace prim

paddle/fluid/prim/tests/test_static_prim.cc

@@ -341,10 +341,10 @@ TEST(StaticCompositeGradMaker, TestMutiOutputMethod) {
 }
 
 TEST(StaticPrim, TestFlags) {
-  PrimCommonUtils::SetPrimEnabled(true);
-  ASSERT_TRUE(PrimCommonUtils::IsPrimEnabled());
-  PrimCommonUtils::SetPrimEnabled(false);
-  ASSERT_FALSE(PrimCommonUtils::IsPrimEnabled());
+  PrimCommonUtils::SetBwdPrimEnabled(true);
+  ASSERT_TRUE(PrimCommonUtils::IsBwdPrimEnabled());
+  PrimCommonUtils::SetBwdPrimEnabled(false);
+  ASSERT_FALSE(PrimCommonUtils::IsBwdPrimEnabled());
 }
 
 }  // namespace prim

paddle/fluid/prim/utils/static/static_global_utils.cc

@@ -18,6 +18,7 @@ namespace paddle {
 namespace prim {
 StaticCompositeContext* StaticCompositeContext::static_composite_context_ =
     new StaticCompositeContext();
-thread_local bool StaticCompositeContext::enable_prim_ = false;
+thread_local bool StaticCompositeContext::enable_bwd_prim_ = false;
+thread_local bool StaticCompositeContext::enable_fwd_prim_ = false;
 }  // namespace prim
 }  // namespace paddle

paddle/fluid/prim/utils/static/static_global_utils.h

@@ -56,17 +56,27 @@ class StaticCompositeContext {
     return generator_->Generate(key);
   }
 
-  void SetPrimEnabled(bool enable_prim) { enable_prim_ = enable_prim; }
+  void SetBwdPrimEnabled(bool enable_prim) { enable_bwd_prim_ = enable_prim; }
 
-  bool IsPrimEnabled() { return enable_prim_; }
+  bool IsBwdPrimEnabled() { return enable_bwd_prim_; }
+
+  void SetFwdPrimEnabled(bool enable_prim) { enable_fwd_prim_ = enable_prim; }
+
+  bool IsFwdPrimEnabled() { return enable_fwd_prim_; }
+
+  void SetAllPrimEnabled(bool enable_prim) {
+    enable_fwd_prim_ = enable_prim;
+    enable_bwd_prim_ = enable_prim;
+  }
 
  private:
   StaticCompositeContext()
       : current_block_desc_(nullptr), generator_(new UniqueNameGenerator()) {}
 
   framework::BlockDesc* current_block_desc_;
   std::unique_ptr<UniqueNameGenerator> generator_;
-  static thread_local bool enable_prim_;
+  static thread_local bool enable_bwd_prim_;
+  static thread_local bool enable_fwd_prim_;
   static StaticCompositeContext* static_composite_context_;
   DISABLE_COPY_AND_ASSIGN(StaticCompositeContext);
 };

paddle/fluid/prim/utils/utils.cc

@@ -19,12 +19,24 @@
 PADDLE_DEFINE_EXPORTED_bool(prim_enabled, false, "enable_prim or not");
 namespace paddle {
 namespace prim {
-bool PrimCommonUtils::IsPrimEnabled() {
-  return StaticCompositeContext::Instance().IsPrimEnabled();
+bool PrimCommonUtils::IsBwdPrimEnabled() {
+  return StaticCompositeContext::Instance().IsBwdPrimEnabled();
 }
 
-void PrimCommonUtils::SetPrimEnabled(bool enable_prim) {
-  return StaticCompositeContext::Instance().SetPrimEnabled(enable_prim);
+void PrimCommonUtils::SetBwdPrimEnabled(bool enable_prim) {
+  return StaticCompositeContext::Instance().SetBwdPrimEnabled(enable_prim);
+}
+
+bool PrimCommonUtils::IsFwdPrimEnabled() {
+  return StaticCompositeContext::Instance().IsFwdPrimEnabled();
+}
+
+void PrimCommonUtils::SetFwdPrimEnabled(bool enable_prim) {
+  return StaticCompositeContext::Instance().SetFwdPrimEnabled(enable_prim);
+}
+
+void PrimCommonUtils::SetAllPrimEnabled(bool enable_prim) {
+  return StaticCompositeContext::Instance().SetAllPrimEnabled(enable_prim);
 }
 }  // namespace prim
 }  // namespace paddle

paddle/fluid/prim/utils/utils.h

@@ -18,8 +18,11 @@ namespace paddle {
 namespace prim {
 class PrimCommonUtils {
  public:
-  static bool IsPrimEnabled();
-  static void SetPrimEnabled(bool enabled);
+  static bool IsBwdPrimEnabled();
+  static void SetBwdPrimEnabled(bool enabled);
+  static bool IsFwdPrimEnabled();
+  static void SetFwdPrimEnabled(bool enabled);
+  static void SetAllPrimEnabled(bool enabled);
 };
 }  // namespace prim
 }  // namespace paddle

paddle/fluid/pybind/pybind.cc

@@ -660,8 +660,16 @@ PYBIND11_MODULE(libpaddle, m) {
         return oss.str();
       });
 
-  m.def("set_prim_enabled", &paddle::prim::PrimCommonUtils::SetPrimEnabled);
-  m.def("is_prim_enabled", &paddle::prim::PrimCommonUtils::IsPrimEnabled);
+  m.def("__set_bwd_prim_enabled",
+        &paddle::prim::PrimCommonUtils::SetBwdPrimEnabled);
+  m.def("_is_bwd_prim_enabled",
+        &paddle::prim::PrimCommonUtils::IsBwdPrimEnabled);
+  m.def("__set_fwd_prim_enabled",
+        &paddle::prim::PrimCommonUtils::SetFwdPrimEnabled);
+  m.def("_is_fwd_prim_enabled",
+        &paddle::prim::PrimCommonUtils::IsFwdPrimEnabled);
+  m.def("__set_all_prim_enabled",
+        &paddle::prim::PrimCommonUtils::SetAllPrimEnabled);
   m.def("set_num_threads", &platform::SetNumThreads);
 
   m.def("disable_signal_handler", &DisableSignalHandler);
@@ -1264,8 +1272,9 @@ All parameter, weight, gradient are variables in Paddle.
           // priority of GradCompOpMaker is less than GradCompMaker for better
           // performance.
           std::vector<std::unique_ptr<OpDesc>> grad_op_descs;
-          if (paddle::prim::PrimCommonUtils::IsPrimEnabled()) {
+          if (paddle::prim::PrimCommonUtils::IsBwdPrimEnabled()) {
             if (grad_comp_op_maker != nullptr) {
+              VLOG(3) << "Runing composite fun for " << op_desc.Type();
               grad_op_descs = grad_comp_op_maker(op_desc,
                                                  no_grad_set,
                                                  &grad_to_var,

paddle/phi/api/yaml/legacy_backward.yaml

@@ -42,7 +42,7 @@
   kernel :
     func : add_grad
   no_need_buffer : x, y
-  composite : add_grad(Tensor x, Tensor y, Tensor out_grad, int axis)
+  composite : add_grad(x, y, out_grad, axis)
   backward : add_double_grad
   inplace : (out_grad -> x_grad)
 
@@ -390,7 +390,7 @@
     param : [x, y]
   kernel :
     func : divide_grad
-  composite : divide_grad(Tensor x, Tensor y, Tensor out, Tensor out_grad, int axis = -1)
+  composite : divide_grad(x, y, out, out_grad, -1)
   backward : divide_double_grad
 
 - backward_op : dropout_grad
@@ -1319,7 +1319,7 @@
   kernel :
     func : subtract_grad
   no_need_buffer : x, y
-  composite : subtract_grad(Tensor x, Tensor y, Tensor out_grad, int axis)
+  composite : subtract_grad(x, y, out_grad, axis)
   backward : subtract_double_grad
   inplace : (out_grad -> x_grad)
 

python/paddle/fluid/backward.py

@@ -1493,14 +1493,15 @@ def update_distop_context(
 
     # remove some backward ops
     # TODO(Jiabin): Support this in prime later, it will prune add_grad, fix this problem
-    if not core.is_prim_enabled():
+    if not core._is_bwd_prim_enabled():
         not_need_ops = _find_not_need_ops(
             grad_op_descs, ops, input_grad_names_set
         )
-
         grad_op_descs = [
             op_desc for op_desc in grad_op_descs if op_desc not in not_need_ops
         ]
+    else:
+        logging.debug("Runing backward composite and disable find_not_need_ops")
 
     # append op_desc in grad_op_descs to target_block
     op_role_attr_name = core.op_proto_and_checker_maker.kOpRoleAttrName()