【PIR Dist Op Reg No.1】 reg push_sparse_v2

paddle/fluid/ir_adaptor/translator/op_compat_gen.py

@@ -164,6 +164,9 @@ def insert_new_mutable_attributes(
         "atol_tensor": "TolTensor",
         "out": "Out",
     }
+    op_arg_name_mappings['push_sparse_v2'].update(
+        {"out_grad_in": "Out@GRAD", "out_grad_out": "Out@GRAD"}
+    )
 
     op_name_normailzer_template = env.get_template("op_compat_info.cc.j2")
     with open(output_source_file, 'wt') as f:

paddle/fluid/pir/dialect/op_generator/ops_api_gen.py

@@ -142,6 +142,7 @@
     'uniform_random_batch_size_like',
     'c_reduce_min',
     'c_reduce_min_',
+    'push_sparse_v2',
 ]
 
 

paddle/fluid/pir/dialect/operator/ir/ops.yaml

@@ -968,6 +968,17 @@
     func : prod
   backward : prod_grad
 
+- op : push_sparse_v2
+  args : (Tensor[] ids, Tensor[] w, Tensor[] out_grad_in, int embeddingdim = 11, int tableid = 0, str accessorclass = "", str ctrlabelname = "", int paddingid = 0, bool scalesparsegrad = true, str[] inputnames = {}, bool is_distributed = true)
+  output : Tensor[](out_grad_out){out_grad_in.size()}
+  infer_meta :
+    func : UnchangedInferMeta
+    param : [out_grad_in]
+  kernel :
+    func : push_sparse_v2
+    data_type : out_grad_in
+  inplace: (out_grad_in -> out_grad_out)
+
 - op : randint
   args : (int low, int high, IntArray shape, DataType dtype=DataType::INT64, Place place={})
   output : Tensor(out)

paddle/fluid/pir/dialect/operator/utils/utils.cc

@@ -62,7 +62,8 @@ const std::unordered_set<std::string> LegacyOpList = {
     SoftReluGradOp::name(),
     NceOp::name(),
     NceGradOp::name(),
-    CReduceMinOp::name()};
+    CReduceMinOp::name(),
+    PushSparseV2Op::name()};
 
 const std::unordered_set<std::string> OneDNNLegacyOpList = {};
 enum class AttrType {

paddle/phi/api/yaml/op_compat.yaml

@@ -2441,6 +2441,14 @@
   outputs :
     out : Out
 
+- op : push_sparse_v2
+  inputs :
+    { x : Ids, W : w}
+  outputs :
+    out : Out
+  extra :
+    attrs : [int embeddingdim = 11, int tableid = 0, str accessorclass = "", str ctrlabelname = "", int paddingid = 0, bool scalesparsegrad = true, 'str[] inputnames = {}', bool is_distributed = true]
+
 - op : put_along_axis
   backward : put_along_axis_grad
   inputs :

test/ir/pir/translator/CMakeLists.txt

@@ -4,7 +4,8 @@ file(
   "test_*.py")
 string(REPLACE ".py" "" TEST_INTERP_CASES "${TEST_INTERP_CASES}")
 
-set(DISTRIBUTED_OP_TRANSLATOR_TEST test_c_reduce_min_translator)
+set(DISTRIBUTED_OP_TRANSLATION_TEST test_c_reduce_min_translate)
+list(APPEND DISTRIBUTED_OP_TRANSLATION_TEST test_push_sparse_v2_translate)
 
 if(NOT WITH_DISTRIBUTE)
   list(REMOVE_ITEM TEST_INTERP_CASES ${DISTRIBUTED_OP_TRANSLATOR_TEST})

test/ir/pir/translator/test_push_sparse_v2_translator.py

@@ -0,0 +1,52 @@
+# Copyright (c) 2023 PaddlePaddle Authors. All Rights Reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+import unittest
+
+import test_op_translator
+
+import paddle
+from paddle.base.layer_helper import LayerHelper
+
+
+class TestPushSparseV2OpTranslator(test_op_translator.TestOpTranslator):
+    def append_op(self):
+        self.op_type = "push_sparse_v2"
+        ids = paddle.ones(shape=(100, 2, 3), dtype='float32')
+        w = paddle.ones(shape=(100, 2, 3), dtype='float32')
+        out = paddle.ones(shape=(100, 2, 3), dtype='float32')
+        attrs = {
+            'embeddingdim': 11,
+            'tableid': 0,
+            'accessorclass': "",
+            'ctrlabelname': "",
+            'paddingid': 0,
+            'scalesparsegrad': True,
+            'inputnames': [],
+            'is_distributed': True,
+        }
+        helper = LayerHelper(self.op_type)
+        helper.append_op(
+            type=self.op_type,
+            inputs={"Ids": ids, "W": w},
+            outputs={"Out": out},
+            attrs=attrs,
+        )
+
+    def test_translator(self):
+        self.check()
+
+
+if __name__ == "__main__":
+    unittest.main()