Merge pull request #14387 from jacquesqiao/lookup_sparse_table_add_test_mode

Lookup sparse table add test mode

paddle/fluid/framework/selected_rows.cc

@@ -63,6 +63,26 @@ struct TensorCopyVisitor {
   int64_t size_;
 };
 
+struct TensorFillVisitor {
+  TensorFillVisitor(framework::Tensor* dst, int64_t dst_offset, int64_t size,
+                    float value)
+      : dst_(dst), dst_offset_(dst_offset), size_(size) {}
+
+  template <typename T>
+  void apply() const {
+    // TODO(qiao): support other place
+    platform::CPUPlace cpu;
+    auto* tensor_data = dst_->mutable_data<T>(cpu);
+    auto* start = tensor_data + dst_offset_;
+    auto* end = start + size_;
+    std::fill(start, end, static_cast<T>(0.0));
+  }
+
+  framework::Tensor* dst_;
+  int64_t dst_offset_;
+  int64_t size_;
+};
+
 void SerializeToStream(std::ostream& os, const SelectedRows& selected_rows,
                        const platform::DeviceContext& dev_ctx) {
   {  // the 1st field, uint32_t version
@@ -120,7 +140,17 @@ bool SelectedRows::HasKey(int64_t key) const {
                                                                    : true;
 }
 
-int64_t SelectedRows::AutoGrownIndex(int64_t key, bool auto_grown) {
+int64_t SelectedRows::AutoGrownIndex(int64_t key, bool auto_grown,
+                                     bool is_test) {
+  if (is_test) {
+    auto iter = id_to_index_.find(key);
+    if (iter == id_to_index_.end()) {
+      return -1;
+    } else {
+      return iter->second;
+    }
+  }
+
   rwlock_->RDLock();
   auto iter = id_to_index_.find(key);
   if (iter == id_to_index_.end()) {
@@ -172,7 +202,7 @@ void SelectedRows::SyncIndex() {
 }
 
 void SelectedRows::Get(const framework::Tensor& ids, framework::Tensor* value,
-                       bool auto_grown) {
+                       bool auto_grown, bool is_test) {
   PADDLE_ENFORCE(value->IsInitialized(),
                  "The value tensor should be initialized.");
   if (ids.numel() == 0) {
@@ -183,11 +213,19 @@ void SelectedRows::Get(const framework::Tensor& ids, framework::Tensor* value,
                       "output tensor should have the same shape with table "
                       "except the dims[0].");
     for (int i = 0; i < ids.numel(); ++i) {
-      int64_t index = AutoGrownIndex(ids.data<int64_t>()[i], auto_grown);
-      framework::VisitDataType(
-          framework::ToDataType(value_->type()),
-          TensorCopyVisitor(value, i * value_width, *value_.get(),
-                            index * value_width, value_width));
+      auto id = ids.data<int64_t>()[i];
+      int64_t index = AutoGrownIndex(id, auto_grown, is_test);
+      if (index < 0) {
+        VLOG(5) << "id " << id << " not in the table, return 0";
+        framework::VisitDataType(
+            framework::ToDataType(value_->type()),
+            TensorFillVisitor(value, i * value_width, value_width, 0.0));
+      } else {
+        framework::VisitDataType(
+            framework::ToDataType(value_->type()),
+            TensorCopyVisitor(value, i * value_width, *value_.get(),
+                              index * value_width, value_width));
+      }
     }
   }
 }

paddle/fluid/framework/selected_rows.h

@@ -105,7 +105,7 @@ class SelectedRows {
    * the value
    */
   void Get(const framework::Tensor& ids, framework::Tensor* value,
-           bool auto_grown = false);
+           bool auto_grown = false, bool is_test = false);
 
   /*
    * @brief Get the index of the key from id_to_index_ map. If the key not
@@ -118,7 +118,7 @@ class SelectedRows {
    *
    * @return index of the key.
    */
-  int64_t AutoGrownIndex(int64_t key, bool auto_grown);
+  int64_t AutoGrownIndex(int64_t key, bool auto_grown, bool is_test = false);
 
   void SyncIndex();
 

paddle/fluid/framework/selected_rows_test.cc

@@ -84,10 +84,14 @@ TEST(SelectedRows, SparseTable) {
       data[i * embedding_width + j] = static_cast<float>(i);
     }
   }
-  ASSERT_EQ(table.AutoGrownIndex(10, true), 0);
-  ASSERT_EQ(table.AutoGrownIndex(8, true), 1);
-  ASSERT_EQ(table.AutoGrownIndex(8, true), 1);
-  ASSERT_EQ(table.AutoGrownIndex(6, true), 2);
+  ASSERT_EQ(table.AutoGrownIndex(10, true, false), 0);
+  ASSERT_EQ(table.AutoGrownIndex(8, true, false), 1);
+  ASSERT_EQ(table.AutoGrownIndex(8, true, false), 1);
+  ASSERT_EQ(table.AutoGrownIndex(6, true, false), 2);
+  for (int64_t i = 11; i < 20; i++) {
+    ASSERT_EQ(table.AutoGrownIndex(i, true, true), -1);
+    ASSERT_TRUE(!table.HasKey(i));
+  }
   ASSERT_TRUE(table.HasKey(10));
   ASSERT_TRUE(table.HasKey(8));
   ASSERT_TRUE(table.HasKey(6));

paddle/fluid/operators/lookup_sparse_table_op.cc

@@ -45,6 +45,7 @@ class LookupSparseTableOp : public framework::OperatorBase {
     auto out_var = scope.FindVar(Output("Out"));
     auto w_var = scope.FindVar(Input("W"));
     auto ids_var = scope.FindVar(Input("Ids"));
+    auto is_test = Attr<bool>("is_test");
 
     PADDLE_ENFORCE(out_var->IsType<framework::LoDTensor>(),
                    "The type of Out var should be LodTensor.");
@@ -65,7 +66,7 @@ class LookupSparseTableOp : public framework::OperatorBase {
     PADDLE_ENFORCE_EQ(framework::ToDataType(w_t->value().type()),
                       framework::proto::VarType::FP32,
                       "The sparse table only support FP32");
-    w_t->Get(ids_t, out_t, true);
+    w_t->Get(ids_t, out_t, true, is_test);
   }
 };
 
@@ -91,6 +92,10 @@ class LookupSparseTableOpMaker : public framework::OpProtoAndCheckerMaker {
                   "(bool default false)"
                   "Whether create new value if for nonexistent key.")
         .SetDefault(true);
+    AddAttr<bool>("is_test",
+                  "In test mode, lookup_sparse_table will "
+                  "return a 0 for unknown id")
+        .SetDefault(false);
     AddComment(R"DOC(
 Lookup Sprase Tablel Operator.
 

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

@@ -80,6 +80,33 @@ class TestLookupSpraseTable(OpTest):
         assert (result_array2[3] == w_array[6]).all()
         assert (result_array2[4] == w_array[7]).all()
 
+        # create and run lookup_table operator
+        test_lookup_table = Operator(
+            "lookup_sparse_table",
+            W='W',
+            Ids='Ids',
+            Out='Out',
+            min=-5.0,
+            max=10.0,
+            seed=10,
+            is_test=True)
+
+        ids = scope.var("Ids").get_tensor()
+        unknown_id = [44, 22, 33]
+        ids_array2 = np.array([4, 2, 3, 7, 100000] + unknown_id).astype("int64")
+        ids.set(ids_array2, place)
+        test_lookup_table.run(scope, place)
+
+        result_array2 = np.array(out_tensor)
+        assert (result_array2[0] == w_array[5]).all()
+        assert (result_array2[1] == w_array[1]).all()
+        assert (result_array2[2] == w_array[2]).all()
+        assert (result_array2[3] == w_array[6]).all()
+        assert (result_array2[4] == w_array[7]).all()
+
+        for i in [5, 6, 7]:
+            assert np.all(result_array2[i] == 0)
+
     def test_w_is_selected_rows(self):
         places = [core.CPUPlace()]
         # currently only support CPU