PaddlePaddle
diff --git a/‎paddle/fluid/operators/generator/type_mapping.py
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+3-3Lines changed: 3 additions & 3 deletions b/‎paddle/fluid/operators/generator/type_mapping.py
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+3-3Lines changed: 3 additions & 3 deletions
diff --git a/‎paddle/fluid/pir/dialect/op_generator/api_gen.py
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+12-10Lines changed: 12 additions & 10 deletions b/‎paddle/fluid/pir/dialect/op_generator/api_gen.py
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+12-10Lines changed: 12 additions & 10 deletions
diff --git a/‎paddle/fluid/pir/dialect/op_generator/op_build_gen.py
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+1Lines changed: 1 addition & 0 deletions b/‎paddle/fluid/pir/dialect/op_generator/op_build_gen.py
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+1Lines changed: 1 addition & 0 deletions
diff --git a/‎paddle/fluid/pir/dialect/op_generator/op_gen.py
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+1-1Lines changed: 1 addition & 1 deletion b/‎paddle/fluid/pir/dialect/op_generator/op_gen.py
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+1-1Lines changed: 1 addition & 1 deletion
diff --git a/‎paddle/fluid/pir/dialect/operator/ir/manual_api.cc
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+19Lines changed: 19 additions & 0 deletions b/‎paddle/fluid/pir/dialect/operator/ir/manual_api.cc
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+19Lines changed: 19 additions & 0 deletions
diff --git a/‎paddle/fluid/pir/dialect/operator/ir/manual_api.h
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+13Lines changed: 13 additions & 0 deletions b/‎paddle/fluid/pir/dialect/operator/ir/manual_api.h
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+13Lines changed: 13 additions & 0 deletions
diff --git a/‎paddle/fluid/primitive/backend/manual/manual_backend.h
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+8-1Lines changed: 8 additions & 1 deletion b/‎paddle/fluid/primitive/backend/manual/manual_backend.h
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+8-1Lines changed: 8 additions & 1 deletion
diff --git a/‎paddle/fluid/primitive/backend/manual/manual_static_backend.cc
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+17Lines changed: 17 additions & 0 deletions b/‎paddle/fluid/primitive/backend/manual/manual_static_backend.cc
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+17Lines changed: 17 additions & 0 deletions
@@ -48,7 +48,7 @@
     'int64_t[]': 'const std::vector<int64_t>&',
     'float[]': 'const std::vector<float>&',
     'double[]': 'const std::vector<double>&',
-    'str[]': 'const std::vector<<std::string>&',
+    'str[]': 'const std::vector<std::string>&',
 }
 
 opmaker_attr_types_map = {
@@ -86,8 +86,8 @@
 }
 
 optional_output_type_map = {
-    'Tensor': 'const paddle::optional<Tensor>&',
-    'Tensor[]': 'const paddle::optional<std::vector<Tensor>>&',
+    'Tensor': 'const paddle::optional<Tensor>',
+    'Tensor[]': 'const paddle::optional<std::vector<Tensor>>',
 }
 
 # ------------------------------ phi attr ------------------------------
 
@@ -197,7 +197,9 @@ def _is_optional_input(self, op_info, input_name):
             return True
         return False
 
-    def _is_optinonal_output(self, op_info, output_name):
+    def _is_optional_output(self, op_info, op_name, output_name):
+        if op_name.endswith(('_grad', '_grad_')):
+            return False
         inplace_map = op_info.inplace_map
         input_optional_list = op_info.input_optional_list
         input_name_list = op_info.input_name_list
@@ -271,7 +273,7 @@ def _gen_api_args(
         )
         return (inputs + ', ' + attrs).strip(', ')
 
-    def _gen_ret_type(self, op_info):
+    def _gen_ret_type(self, op_info, op_name):
         name_list = op_info.output_name_list
         type_list = op_info.output_type_list
         intermediate_list = op_info.output_intermediate_list
@@ -285,15 +287,15 @@ def _gen_ret_type(self, op_info):
             ):
                 if intermediate == 'true':
                     continue
-                if self._is_optinonal_output(op_info, name):
+                if self._is_optional_output(op_info, op_name, name):
                     ret.append(OPTIONAL_OUTPUT_TYPE_MAP[type])
                 else:
                     ret.append(OUTPUT_TYPE_MAP[type])
             return 'std::tuple<{}>'.format(', '.join(ret))
         elif output_num == 1:
             index = intermediate_list.index('false')
             name = name_list[index]
-            if self._is_optinonal_output(op_info, name):
+            if self._is_optional_output(op_info, op_name, name):
                 return OPTIONAL_OUTPUT_TYPE_MAP[type_list[index]]
             else:
                 return OUTPUT_TYPE_MAP[type_list[index]]
@@ -304,7 +306,7 @@ def _gen_one_declare(
         self, op_info, op_name, is_mutable_attr, is_vector_mutable_attr
     ):
         return API_DECLARE_TEMPLATE.format(
-            ret_type=self._gen_ret_type(op_info),
+            ret_type=self._gen_ret_type(op_info, op_name),
             api_name=op_name,
             args=self._gen_api_args(
                 op_info, True, is_mutable_attr, is_vector_mutable_attr
@@ -367,7 +369,7 @@ def _gen_handle_optional_outputs(self, op_info, op_name):
         ):
             if intermediate == 'true':
                 continue
-            if self._is_optinonal_output(op_info, name):
+            if self._is_optional_output(op_info, op_name, name):
                 if VECTOR_TYPE in type:
                     ret += OPTIONAL_VECTOR_OPRESULT_OUTPUT_TEMPLATE.format(
                         name=name,
@@ -461,7 +463,7 @@ def _gen_compute_op(
             op_inst_name,
         )
 
-    def _gen_out_split_and_ret_list(self, op_info, op_inst_name):
+    def _gen_out_split_and_ret_list(self, op_info, op_name, op_inst_name):
         name_list = op_info.output_name_list
         type_list = op_info.output_type_list
         intermediate_list = op_info.output_intermediate_list
@@ -480,7 +482,7 @@ def _gen_out_split_and_ret_list(self, op_info, op_inst_name):
         ):
             if intermediate == 'true':
                 continue
-            if self._is_optinonal_output(op_info, name):
+            if self._is_optional_output(op_info, op_name, name):
                 ret_list.append(f'optional_{name}')
             elif VECTOR_TYPE in type:
                 split_op_name = f'{name}_split_op'
@@ -503,7 +505,7 @@ def _gen_return_result(self, ret_list):
     def _gen_one_impl(
         self, op_info, op_name, is_mutable_attr, is_vector_mutable_attr
     ):
-        ret_type = self._gen_ret_type(op_info)
+        ret_type = self._gen_ret_type(op_info, op_name)
         in_combine, in_combine_op_list = self._gen_in_combine(
             op_info, is_mutable_attr, is_vector_mutable_attr
         )
@@ -514,7 +516,7 @@ def _gen_one_impl(
             compute_op += f' (void){op_inst_name};'
 
         out_split, ret_list = self._gen_out_split_and_ret_list(
-            op_info, op_inst_name
+            op_info, op_name, op_inst_name
         )
 
         ret = API_IMPL_TEMPLATE.format(
 
@@ -144,6 +144,7 @@ def GenBuildInputArgsStr(
     'int': 'phi::DataType::INT32',
     'int64_t': 'phi::DataType::INT64',
     'float': 'phi::DataType::FLOAT32',
+    'double': 'phi::DataType::FLOAT64',
     'std::vector<int64_t>': 'phi::DataType::INT64',
     'const std::vector<int64_t>&': 'phi::DataType::INT64',
     'bool': 'phi::DataType::BOOL',
 
@@ -477,7 +477,7 @@ def parse_mutable_attribute(self):
                     if (self.op_compat_item['op'] == "isclose") or (
                         self.op_compat_item['op'] == "allclose"
                     ):
-                        data_type = "float"
+                        data_type = "double"
                     mutable_attribute_type_list.append(
                         [
                             "paddle::dialect::ScalarAttribute",
 
@@ -100,5 +100,24 @@ pir::OpResult split_with_num_grad(const std::vector<pir::Value>& out_grad,
           out_grad_combine_op.out(), axis);
   return split_grad_op.result(0);
 }
+
+pir::OpResult ones(const std::vector<int64_t>& shape,
+                   phi::DataType dtype,
+                   const Place& place) {
+  return paddle::dialect::full(shape, 1, dtype, place);
+}
+
+pir::OpResult ones_like(pir::Value x_,
+                        phi::DataType dtype,
+                        const Place& place) {
+  return paddle::dialect::full_like(x_, 1, dtype, place);
+}
+
+pir::OpResult zeros(const std::vector<int64_t>& shape,
+                    phi::DataType dtype,
+                    const Place& place) {
+  return paddle::dialect::full(shape, 0, dtype, place);
+}
+
 }  // namespace dialect
 }  // namespace paddle
@@ -47,5 +47,18 @@ pir::OpResult split_with_num_grad(const std::vector<pir::Value>& out_grad,
 
 pir::OpResult split_with_num_grad(const std::vector<pir::Value>& out_grad,
                                   const pir::Value& axis);
+
+pir::OpResult ones(const std::vector<int64_t>& shape,
+                   phi::DataType dtype = phi::DataType::FLOAT32,
+                   const Place& place = phi::CPUPlace());
+
+pir::OpResult ones_like(pir::Value x_,
+                        phi::DataType dtype = phi::DataType::UNDEFINED,
+                        const Place& place = {});
+
+pir::OpResult zeros(const std::vector<int64_t>& shape,
+                    phi::DataType dtype = phi::DataType::FLOAT32,
+                    const Place& place = phi::CPUPlace());
+
 }  // namespace dialect
 }  // namespace paddle
@@ -24,14 +24,21 @@ namespace primitive {
 namespace backend {
 
 using Tensor = paddle::Tensor;
-using Scalar = paddle::experimental::Scalar;
+using Scalar = phi::Scalar;
 using IntArray = paddle::experimental::IntArray;
 using DataType = phi::DataType;
 
 template <typename T>
 std::vector<Tensor> add_n_grad(const std::vector<Tensor>& x,
                                const Tensor& out_grad);
 
+template <typename T>
+Tensor embedding_grad(const Tensor& x,
+                      const Tensor& weight,
+                      const Tensor& out_grad,
+                      int64_t padding_idx = -1,
+                      bool sparse = false);
+
 }  // namespace backend
 }  // namespace primitive
 }  // namespace paddle
@@ -45,6 +45,23 @@ std::vector<Tensor> add_n_grad<LazyTensor>(const std::vector<Tensor>& x,
   return x_grad;
 }
 
+template <>
+Tensor embedding_grad<LazyTensor>(const Tensor& x,
+                                  const Tensor& weight,
+                                  const Tensor& out_grad,
+                                  int64_t padding_idx,
+                                  bool sparse) {
+  pir::Value x_res = std::static_pointer_cast<LazyTensor>(x.impl())->value();
+  pir::Value weight_res =
+      std::static_pointer_cast<LazyTensor>(weight.impl())->value();
+  pir::Value out_grad_res =
+      std::static_pointer_cast<LazyTensor>(out_grad.impl())->value();
+  auto op_res = paddle::dialect::embedding_grad(
+      x_res, weight_res, out_grad_res, padding_idx, sparse);
+  Tensor out(std::make_shared<LazyTensor>(op_res));
+  return out;
+}
+
 }  // namespace backend
 }  // namespace primitive
 }  // namespace paddle
Original file line number	Diff line number	Diff line change
`@@ -48,7 +48,7 @@`
`48`	`48`	`'int64_t[]': 'const std::vector<int64_t>&',`
`49`	`49`	`'float[]': 'const std::vector<float>&',`
`50`	`50`	`'double[]': 'const std::vector<double>&',`
`51`		`- 'str[]': 'const std::vector<<std::string>&',`
	`51`	`+ 'str[]': 'const std::vector<std::string>&',`
`52`	`52`	`}`
`53`	`53`
`54`	`54`	`opmaker_attr_types_map = {`
`@@ -86,8 +86,8 @@`
`86`	`86`	`}`
`87`	`87`
`88`	`88`	`optional_output_type_map = {`
`89`		`- 'Tensor': 'const paddle::optional<Tensor>&',`
`90`		`- 'Tensor[]': 'const paddle::optional<std::vector<Tensor>>&',`
	`89`	`+ 'Tensor': 'const paddle::optional<Tensor>',`
	`90`	`+ 'Tensor[]': 'const paddle::optional<std::vector<Tensor>>',`
`91`	`91`	`}`
`92`	`92`
`93`	`93`	`# ------------------------------ phi attr ------------------------------`
Original file line number	Diff line number	Diff line change
`@@ -477,7 +477,7 @@ def parse_mutable_attribute(self):`
`477`	`477`	`if (self.op_compat_item['op'] == "isclose") or (`
`478`	`478`	`self.op_compat_item['op'] == "allclose"`
`479`	`479`	`):`
`480`		`- data_type = "float"`
	`480`	`+ data_type = "double"`
`481`	`481`	`mutable_attribute_type_list.append(`
`482`	`482`	`[`
`483`	`483`	`"paddle::dialect::ScalarAttribute",`