/*
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* Copyright (C) 2018 The Android Open Source Project
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*
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* Licensed under the Apache License, Version 2.0 (the "License");
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* you may not use this file except in compliance with the License.
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* You may obtain a copy of the License at
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*
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* http://www.apache.org/licenses/LICENSE-2.0
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*
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* Unless required by applicable law or agreed to in writing, software
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* distributed under the License is distributed on an "AS IS" BASIS,
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* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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* See the License for the specific language governing permissions and
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* limitations under the License.
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*/
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#include "actions/lua-actions.h"
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#include <map>
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#include <string>
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#include "actions/test_utils.h"
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#include "actions/types.h"
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#include "utils/tflite-model-executor.h"
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#include "gmock/gmock.h"
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#include "gtest/gtest.h"
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namespace libtextclassifier3 {
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namespace {
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MATCHER_P2(IsAction, type, response_text, "") {
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return testing::Value(arg.type, type) &&
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testing::Value(arg.response_text, response_text);
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}
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MATCHER_P(IsActionType, type, "") { return testing::Value(arg.type, type); }
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TEST(LuaActions, SimpleAction) {
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Conversation conversation;
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const std::string test_snippet = R"(
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return {{ type = "test_action" }}
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)";
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std::vector<ActionSuggestion> actions;
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EXPECT_TRUE(LuaActionsSuggestions::CreateLuaActionsSuggestions(
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test_snippet, conversation,
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/*model_executor=*/nullptr,
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/*model_spec=*/nullptr,
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/*interpreter=*/nullptr,
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/*actions_entity_data_schema=*/nullptr,
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/*annotations_entity_data_schema=*/nullptr)
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->SuggestActions(&actions));
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EXPECT_THAT(actions,
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testing::ElementsAreArray({IsActionType("test_action")}));
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}
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TEST(LuaActions, ConversationActions) {
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Conversation conversation;
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conversation.messages.push_back({/*user_id=*/0, "hello there!"});
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conversation.messages.push_back({/*user_id=*/1, "general kenobi!"});
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const std::string test_snippet = R"(
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local actions = {}
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for i, message in pairs(messages) do
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if i < #messages then
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if message.text == "hello there!" and
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messages[i+1].text == "general kenobi!" then
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table.insert(actions, {
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type = "text_reply",
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response_text = "you are a bold one!"
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})
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end
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if message.text == "i am the senate!" and
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messages[i+1].text == "not yet!" then
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table.insert(actions, {
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type = "text_reply",
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response_text = "it's treason then"
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})
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end
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end
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end
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return actions;
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)";
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std::vector<ActionSuggestion> actions;
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EXPECT_TRUE(LuaActionsSuggestions::CreateLuaActionsSuggestions(
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test_snippet, conversation,
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/*model_executor=*/nullptr,
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/*model_spec=*/nullptr,
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/*interpreter=*/nullptr,
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/*actions_entity_data_schema=*/nullptr,
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/*annotations_entity_data_schema=*/nullptr)
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->SuggestActions(&actions));
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EXPECT_THAT(actions, testing::ElementsAreArray(
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{IsAction("text_reply", "you are a bold one!")}));
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}
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TEST(LuaActions, SimpleModelAction) {
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Conversation conversation;
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const std::string test_snippet = R"(
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if #model.actions_scores == 0 then
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return {{ type = "test_action" }}
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end
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return {}
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)";
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std::vector<ActionSuggestion> actions;
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EXPECT_TRUE(LuaActionsSuggestions::CreateLuaActionsSuggestions(
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test_snippet, conversation,
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/*model_executor=*/nullptr,
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/*model_spec=*/nullptr,
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/*interpreter=*/nullptr,
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/*actions_entity_data_schema=*/nullptr,
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/*annotations_entity_data_schema=*/nullptr)
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->SuggestActions(&actions));
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EXPECT_THAT(actions,
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testing::ElementsAreArray({IsActionType("test_action")}));
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}
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TEST(LuaActions, AnnotationActions) {
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AnnotatedSpan annotation;
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annotation.span = {11, 15};
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annotation.classification = {ClassificationResult("address", 1.0)};
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Conversation conversation = {{{/*user_id=*/1, "are you at home?",
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/*reference_time_ms_utc=*/0,
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/*reference_timezone=*/"Europe/Zurich",
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/*annotations=*/{annotation},
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/*locales=*/"en"}}};
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const std::string test_snippet = R"(
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local actions = {}
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local last_message = messages[#messages]
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for i, annotation in pairs(last_message.annotation) do
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if #annotation.classification > 0 then
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if annotation.classification[1].collection == "address" then
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local text = string.sub(last_message.text,
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annotation.span["begin"] + 1,
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annotation.span["end"])
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table.insert(actions, {
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type = "text_reply",
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response_text = "i am at " .. text,
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annotation = {{
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name = "location",
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span = {
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text = text
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},
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entity = annotation.classification[1]
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}},
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})
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end
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end
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end
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return actions;
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)";
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std::vector<ActionSuggestion> actions;
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EXPECT_TRUE(LuaActionsSuggestions::CreateLuaActionsSuggestions(
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test_snippet, conversation,
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/*model_executor=*/nullptr,
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/*model_spec=*/nullptr,
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/*interpreter=*/nullptr,
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/*actions_entity_data_schema=*/nullptr,
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/*annotations_entity_data_schema=*/nullptr)
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->SuggestActions(&actions));
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EXPECT_THAT(actions, testing::ElementsAreArray(
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{IsAction("text_reply", "i am at home")}));
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EXPECT_EQ("address", actions[0].annotations[0].entity.collection);
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}
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TEST(LuaActions, EntityData) {
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std::string test_schema = TestEntityDataSchema();
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Conversation conversation = {{{/*user_id=*/1, "hello there"}}};
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const std::string test_snippet = R"(
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return {{
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type = "test",
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entity = {
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greeting = "hello",
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location = "there",
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person = "Kenobi",
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},
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}};
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)";
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std::vector<ActionSuggestion> actions;
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EXPECT_TRUE(LuaActionsSuggestions::CreateLuaActionsSuggestions(
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test_snippet, conversation,
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/*model_executor=*/nullptr,
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/*model_spec=*/nullptr,
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/*interpreter=*/nullptr,
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/*actions_entity_data_schema=*/
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flatbuffers::GetRoot<reflection::Schema>(test_schema.data()),
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/*annotations_entity_data_schema=*/nullptr)
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->SuggestActions(&actions));
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EXPECT_THAT(actions, testing::SizeIs(1));
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EXPECT_EQ("test", actions.front().type);
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const flatbuffers::Table* entity =
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flatbuffers::GetAnyRoot(reinterpret_cast<const unsigned char*>(
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actions.front().serialized_entity_data.data()));
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EXPECT_EQ(entity->GetPointer<const flatbuffers::String*>(/*field=*/4)->str(),
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"hello");
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EXPECT_EQ(entity->GetPointer<const flatbuffers::String*>(/*field=*/6)->str(),
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"there");
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EXPECT_EQ(entity->GetPointer<const flatbuffers::String*>(/*field=*/8)->str(),
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"Kenobi");
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}
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} // namespace
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} // namespace libtextclassifier3
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