Remove mojo/public/cpp/bindings/map.h.

Convert all callers to use base::flat_map in the first place, instead of
using std::map and then converting them. Fix link errors along the way.

Change-Id: I34bd7b2c42cfb5cdcd68d4e0880b82633b989697
Reviewed-on: https://chromium-review.googlesource.com/c/chromium/src/+/1892437Reviewed-by: Ahmed Fakhry <afakhry@chromium.org>
Reviewed-by: Oksana Zhuravlova <oksamyt@chromium.org>
Reviewed-by: Jenny Zhang <jennyz@chromium.org>
Commit-Queue: Lei Zhang <thestig@chromium.org>
Cr-Commit-Position: refs/heads/master@{#712876}

ash/test/ash_test_base.cc

@@ -40,7 +40,6 @@
 #include "chromeos/dbus/power/fake_power_manager_client.h"
 #include "components/account_id/account_id.h"
 #include "components/user_manager/user_names.h"
-#include "mojo/public/cpp/bindings/map.h"
 #include "ui/aura/client/aura_constants.h"
 #include "ui/aura/client/window_parenting_client.h"
 #include "ui/aura/env.h"

chrome/browser/chromeos/power/ml/smart_dim/ml_service_client.cc

@@ -4,11 +4,14 @@
 
 #include "chrome/browser/chromeos/power/ml/smart_dim/ml_service_client.h"
 
+#include <string>
+#include <utility>
+
 #include "base/bind.h"
+#include "base/containers/flat_map.h"
 #include "base/feature_list.h"
 #include "base/memory/weak_ptr.h"
 #include "base/metrics/histogram_macros.h"
-#include "base/threading/thread.h"
 #include "base/time/time.h"
 #include "chrome/browser/chromeos/power/ml/smart_dim/model_impl.h"
 #include "chromeos/constants/chromeos_features.h"
@@ -16,7 +19,6 @@
 #include "chromeos/services/machine_learning/public/mojom/graph_executor.mojom.h"
 #include "chromeos/services/machine_learning/public/mojom/model.mojom.h"
 #include "chromeos/services/machine_learning/public/mojom/tensor.mojom.h"
-#include "mojo/public/cpp/bindings/map.h"
 #include "mojo/public/cpp/bindings/remote.h"
 
 using ::chromeos::machine_learning::mojom::BuiltinModelId;
@@ -169,7 +171,7 @@ void MlServiceClientImpl::DoInference(
   InitMlServiceHandlesIfNeeded();
 
   // Prepare the input tensor.
-  std::map<std::string, TensorPtr> inputs;
+  base::flat_map<std::string, TensorPtr> inputs;
   auto tensor = Tensor::New();
   tensor->shape = Int64List::New();
   tensor->shape->value = std::vector<int64_t>({1, features.size()});
@@ -182,7 +184,7 @@ void MlServiceClientImpl::DoInference(
   std::vector<std::string> outputs({std::string("output")});
 
   executor_->Execute(
-      mojo::MapToFlatMap(std::move(inputs)), std::move(outputs),
+      std::move(inputs), std::move(outputs),
       base::BindOnce(&MlServiceClientImpl::ExecuteCallback,
                      weak_factory_.GetWeakPtr(), get_prediction_callback,
                      std::move(decision_callback)));

chrome/browser/chromeos/power/ml/smart_dim/ml_service_client.h

@@ -5,7 +5,7 @@
 #ifndef CHROME_BROWSER_CHROMEOS_POWER_ML_SMART_DIM_ML_SERVICE_CLIENT_H_
 #define CHROME_BROWSER_CHROMEOS_POWER_ML_SMART_DIM_ML_SERVICE_CLIENT_H_
 
-#include <utility>
+#include <memory>
 #include <vector>
 
 #include "base/callback.h"
@@ -20,8 +20,7 @@ namespace ml {
 // inference on inputs provided by the caller.
 class MlServiceClient {
  public:
-  MlServiceClient() = default;
-  virtual ~MlServiceClient() {}
+  virtual ~MlServiceClient() = default;
 
   // Sends an input vector to the ML service to run inference on. It also
   // provides a |decision_callback| to the Mojo service which will be run

chrome/browser/ui/app_list/search/search_result_ranker/ml_app_rank_provider.cc

-// Copyright (c) 2019 The Chromium Authors. All rights reserved.
+// Copyright 2019 The Chromium Authors. All rights reserved.
 // Use of this source code is governed by a BSD-style license that can be
 // found in the LICENSE file.
 
 #include "chrome/browser/ui/app_list/search/search_result_ranker/ml_app_rank_provider.h"
 
+#include <utility>
+
 #include "base/bind.h"
 #include "base/callback.h"
 #include "base/location.h"
@@ -21,7 +23,6 @@
 #include "components/crx_file/id_util.h"
 #include "content/public/browser/browser_task_traits.h"
 #include "content/public/browser/browser_thread.h"
-#include "mojo/public/cpp/bindings/map.h"
 #include "ui/base/resource/resource_bundle.h"
 
 using ::chromeos::machine_learning::mojom::BuiltinModelId;
@@ -76,15 +77,15 @@ bool LoadExamplePreprocessorConfig(
 
 // Perform the inference given the |features| and |app_id| of an app.
 // Posts |callback| to |task_runner| to perform the actual inference.
-void DoInference(
-    const std::string& app_id,
-    const std::vector<float>& features,
-    scoped_refptr<base::SequencedTaskRunner> task_runner,
-    const base::RepeatingCallback<void(std::map<std::string, TensorPtr> inputs,
-                                       const std::vector<std::string> outputs,
-                                       const std::string app_id)> callback) {
+void DoInference(const std::string& app_id,
+                 const std::vector<float>& features,
+                 scoped_refptr<base::SequencedTaskRunner> task_runner,
+                 const base::RepeatingCallback<
+                     void(base::flat_map<std::string, TensorPtr> inputs,
+                          const std::vector<std::string> outputs,
+                          const std::string app_id)> callback) {
   // Prepare the input tensor.
-  std::map<std::string, TensorPtr> inputs;
+  base::flat_map<std::string, TensorPtr> inputs;
   auto tensor = Tensor::New();
   tensor->shape = Int64List::New();
   tensor->shape->value = std::vector<int64_t>({1, features.size()});
@@ -104,10 +105,10 @@ void DoInference(
 // Returns true on success.
 bool RankerExampleToVectorizedFeatures(
     const assist_ranker::ExamplePreprocessorConfig& preprocessor_config,
-    assist_ranker::RankerExample& example,
+    assist_ranker::RankerExample* example,
     std::vector<float>* vectorized_features) {
   int preprocessor_error = assist_ranker::ExamplePreprocessor::Process(
-      preprocessor_config, &example, true);
+      preprocessor_config, example, true);
   // kNoFeatureIndexFound can occur normally (e.g., when the app URL
   // isn't known to the model or a rarely seen enum value is used).
   if (preprocessor_error != assist_ranker::ExamplePreprocessor::kSuccess &&
@@ -118,7 +119,7 @@ bool RankerExampleToVectorizedFeatures(
   }
 
   const auto& extracted_features =
-      example.features()
+      example->features()
           .at(assist_ranker::ExamplePreprocessor::kVectorizedFeatureDefaultName)
           .float_list()
           .float_value();
@@ -137,9 +138,10 @@ void CreateRankingsImpl(
     int all_clicks_last_hour,
     int all_clicks_last_24_hours,
     scoped_refptr<base::SequencedTaskRunner> task_runner,
-    const base::RepeatingCallback<void(std::map<std::string, TensorPtr> inputs,
-                                       const std::vector<std::string> outputs,
-                                       const std::string app_id)>& callback) {
+    const base::RepeatingCallback<
+        void(base::flat_map<std::string, TensorPtr> inputs,
+             const std::vector<std::string> outputs,
+             const std::string app_id)>& callback) {
   const base::Time now(base::Time::Now());
   const int hour = HourOfDay(now);
   const int day = DayOfWeek(now);
@@ -156,7 +158,7 @@ void CreateRankingsImpl(
                             total_hours, day, hour, all_clicks_last_hour,
                             all_clicks_last_24_hours));
     std::vector<float> vectorized_features;
-    if (RankerExampleToVectorizedFeatures(preprocessor_config, example,
+    if (RankerExampleToVectorizedFeatures(preprocessor_config, &example,
                                           &vectorized_features)) {
       DoInference(app.first, vectorized_features, task_runner, callback);
     }
@@ -283,12 +285,13 @@ std::map<std::string, float> MlAppRankProvider::RetrieveRankings() {
   return ranking_map_;
 }
 
-void MlAppRankProvider::RunExecutor(std::map<std::string, TensorPtr> inputs,
-                                    const std::vector<std::string> outputs,
-                                    const std::string app_id) {
+void MlAppRankProvider::RunExecutor(
+    base::flat_map<std::string, TensorPtr> inputs,
+    const std::vector<std::string> outputs,
+    const std::string app_id) {
   DCHECK_CALLED_ON_VALID_SEQUENCE(creation_sequence_checker_);
   BindGraphExecutorIfNeeded();
-  executor_->Execute(mojo::MapToFlatMap(std::move(inputs)), std::move(outputs),
+  executor_->Execute(std::move(inputs), std::move(outputs),
                      base::BindOnce(&MlAppRankProvider::ExecuteCallback,
                                     base::Unretained(this), app_id));
 }

chrome/browser/ui/app_list/search/search_result_ranker/ml_app_rank_provider.h

@@ -7,9 +7,9 @@
 
 #include <map>
 #include <string>
-#include <utility>
 #include <vector>
 
+#include "base/containers/flat_map.h"
 #include "base/macros.h"
 #include "base/memory/weak_ptr.h"
 #include "base/optional.h"
@@ -62,8 +62,8 @@ class MlAppRankProvider {
  private:
   // Execute the |executor_| on the creation thread.
   void RunExecutor(
-      std::map<std::string, ::chromeos::machine_learning::mojom::TensorPtr>
-          inputs,
+      base::flat_map<std::string,
+                     ::chromeos::machine_learning::mojom::TensorPtr> inputs,
       std::vector<std::string> outputs,
       std::string app_id);
 

chrome/browser/ui/app_list/search/search_result_ranker/search_ranking_event_logger.cc

@@ -4,9 +4,10 @@
 
 #include "chrome/browser/ui/app_list/search/search_result_ranker/search_ranking_event_logger.h"
 
-#include <cmath>
+#include <utility>
 
 #include "ash/public/cpp/app_list/app_list_types.h"
+#include "base/containers/flat_map.h"
 #include "base/metrics/histogram_macros.h"
 #include "base/strings/stringprintf.h"
 #include "base/strings/utf_string_conversions.h"
@@ -20,7 +21,6 @@
 #include "components/assist_ranker/example_preprocessing.h"
 #include "components/crx_file/id_util.h"
 #include "components/omnibox/browser/autocomplete_match_type.h"
-#include "mojo/public/cpp/bindings/map.h"
 #include "services/metrics/public/cpp/metrics_utils.h"
 #include "services/metrics/public/cpp/ukm_builders.h"
 #include "ui/base/resource/resource_bundle.h"
@@ -51,7 +51,7 @@ constexpr base::TimeDelta kDelayForHistoryService =
 // exponent used for counts that are not seconds is 1.15 (via
 // ukm::GetExponentialBucketMinForCounts1000). The first value skipped by
 // bucketing is 10.
-constexpr float kBucketExponentForSeconds = 1.045;
+constexpr float kBucketExponentForSeconds = 1.045f;
 
 // The UMA histogram that logs the error occurs in inference code.
 constexpr char kInferenceError[] = "Apps.AppList.AggregatedSearchRankerError";
@@ -313,7 +313,7 @@ void SearchRankingEventLogger::PopulateSearchRankingItem(
     }
   }
 
-  if (event_info->last_launch != base::nullopt) {
+  if (event_info->last_launch.has_value()) {
     base::Time last_launch = event_info->last_launch.value();
     base::Time::Exploded last_launch_exploded;
     last_launch.LocalExplode(&last_launch_exploded);
@@ -576,7 +576,7 @@ void SearchRankingEventLogger::DoInference(const std::vector<float>& features,
   BindGraphExecutorIfNeeded();
 
   // Prepare the input tensor.
-  std::map<std::string, TensorPtr> inputs;
+  base::flat_map<std::string, TensorPtr> inputs;
   auto tensor = Tensor::New();
   tensor->shape = Int64List::New();
   tensor->shape->value = std::vector<int64_t>({1, features.size()});
@@ -588,7 +588,7 @@ void SearchRankingEventLogger::DoInference(const std::vector<float>& features,
 
   const std::vector<std::string> outputs({std::string("output")});
   // Execute
-  executor_->Execute(mojo::MapToFlatMap(std::move(inputs)), std::move(outputs),
+  executor_->Execute(std::move(inputs), std::move(outputs),
                      base::BindOnce(&SearchRankingEventLogger::ExecuteCallback,
                                     weak_factory_.GetWeakPtr(), id));
 }

chrome/browser/ui/app_list/search/search_result_ranker/search_ranking_event_logger.h

@@ -6,8 +6,8 @@
 #define CHROME_BROWSER_UI_APP_LIST_SEARCH_SEARCH_RESULT_RANKER_SEARCH_RANKING_EVENT_LOGGER_H_
 
 #include <map>
+#include <memory>
 #include <string>
-#include <utility>
 #include <vector>
 
 #include "ash/public/cpp/app_list/app_list_types.h"

mojo/public/cpp/bindings/BUILD.gn

@@ -88,7 +88,6 @@ component("bindings_base") {
     "lib/validation_errors.h",
     "lib/validation_util.cc",
     "lib/validation_util.h",
-    "map.h",
     "map_data_view.h",
     "map_traits.h",
     "map_traits_flat_map.h",

mojo/public/cpp/bindings/map.h

-// Copyright 2014 The Chromium Authors. All rights reserved.
-// Use of this source code is governed by a BSD-style license that can be
-// found in the LICENSE file.
-
-#ifndef MOJO_PUBLIC_CPP_BINDINGS_MAP_H_
-#define MOJO_PUBLIC_CPP_BINDINGS_MAP_H_
-
-#include <map>
-#include <utility>
-
-#include "base/containers/flat_map.h"
-
-namespace mojo {
-
-// TODO(yzshen): These conversion functions should be removed and callsites
-// should be revisited and changed to use the same map type.
-template <typename Key, typename Value>
-base::flat_map<Key, Value> MapToFlatMap(const std::map<Key, Value>& input) {
-  return base::flat_map<Key, Value>(input.begin(), input.end());
-}
-
-template <typename Key, typename Value>
-base::flat_map<Key, Value> MapToFlatMap(std::map<Key, Value>&& input) {
-  return base::flat_map<Key, Value>(std::make_move_iterator(input.begin()),
-                                    std::make_move_iterator(input.end()));
-}
-
-template <typename Key, typename Value>
-std::map<Key, Value> FlatMapToMap(const base::flat_map<Key, Value>& input) {
-  return std::map<Key, Value>(input.begin(), input.end());
-}
-
-template <typename Key, typename Value>
-std::map<Key, Value> FlatMapToMap(base::flat_map<Key, Value>&& input) {
-  return std::map<Key, Value>(std::make_move_iterator(input.begin()),
-                              std::make_move_iterator(input.end()));
-}
-
-}  // namespace mojo
-
-#endif  // MOJO_PUBLIC_CPP_BINDINGS_MAP_H_