add UT for fuse

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

@@ -15,6 +15,8 @@
 from __future__ import print_function
 
 import unittest
+import numpy as np
+
 import paddle.fluid as fluid
 import paddle.fluid.core as core
 
@@ -27,8 +29,11 @@ class TestLookupTableFuseOp(unittest.TestCase):
             self.check_with_place(place)
 
     def check_with_place(self, place):
-        scope = core.Scope()
-        program = fluid.Program()
+        scope = fluid.global_scope()
+        init_program = fluid.Program()
+
+        lr = scope.var("LearningRate")
+        lr.get_tensor().set([0.01], place)
 
         ids = [i for i in range(100)]
         out = scope.var("output")
@@ -41,13 +46,13 @@ class TestLookupTableFuseOp(unittest.TestCase):
             "embedding_2.block0:Param:8:0:embedding_2@GRAD.block0:embedding_2.block0,kSparseIDs@embedding_2.block0:uniform_random&0&-0.5&0.5:none"
         )
 
-        program.global_block().append_op(
+        init_program.global_block().append_op(
             type="lookup_sparse_table_init",
             inputs=None,
             outputs=None,
             attrs={"large_scale_metas": metas})
 
-        program.global_block().append_op(
+        init_program.global_block().append_op(
             type="lookup_sparse_table_read",
             inputs={"Ids": ids},
             outputs={"Out": out},
@@ -57,7 +62,7 @@ class TestLookupTableFuseOp(unittest.TestCase):
                 "value_names": ["Param", "Moment1", "Moment2"],
             })
 
-        program.global_block().append_op(
+        init_program.global_block().append_op(
             type="lookup_sparse_table_read",
             inputs={"Ids": ids},
             outputs={"Out": out},
@@ -68,7 +73,43 @@ class TestLookupTableFuseOp(unittest.TestCase):
             })
 
         executor = fluid.Executor(fluid.CPUPlace())
-        executor.run(program)
+        executor.run(init_program)
+
+        training_program = fluid.Program()
+
+        rows = [0, 1, 2, 3, 4, 5, 6]
+        row_numel = 7
+
+        w_selected_rows = scope.var('W').get_selected_rows()
+        w_selected_rows.set_height(len(rows))
+        w_selected_rows.set_rows(rows)
+        w_array = np.ones((len(rows), row_numel)).astype("float32")
+        for i in range(len(rows)):
+            w_array[i] *= i
+        w_tensor = w_selected_rows.get_tensor()
+        w_tensor.set(w_array, place)
+
+        training_program.global_block().append_op(
+            type="lookup_sparse_table_fuse_adam",
+            inputs={"Grad": ids,
+                    "LearningRate": lr},
+            outputs={"Out": out},
+            attrs={
+                "is_entry": False,
+                "tablename": "embedding_1.block0",
+                "value_names": ["Param", "Moment1", "Moment2"],
+            })
+
+        training_program.global_block().append_op(
+            type="lookup_sparse_table_fuse_sgd",
+            inputs={"Grad": ids,
+                    "LearningRate": lr},
+            outputs={"Out": out},
+            attrs={
+                "is_entry": False,
+                "tablename": "embedding_2.block0",
+                "value_names": ["Param"],
+            })
 
 
 if __name__ == "__main__":