feat: Privacy Preserving Learning

.github/workflows/build_vw_privacy_activation.yml

@@ -0,0 +1,24 @@
+name: Linux / C++ - VW with privacy activation
+
+on:
+  push:
+    branches:
+      - master
+      - 'releases/**'
+  pull_request:
+    branches:
+      - '*'
+
+jobs:
+  check:
+    container:
+      image: vowpalwabbit/ubuntu1804-build:latest
+    runs-on: ubuntu-latest
+    steps:
+      - uses: actions/checkout@v1
+      - name: Build VW with privacy activation
+        shell: bash
+        run: ./.scripts/linux/build-privacy_activation.sh
+      - name: Test VW with privacy activation
+        shell: bash
+        run: ./.scripts/linux/test-privacy_activation.sh

.scripts/linux/build-privacy_activation.sh

@@ -0,0 +1,11 @@
+#!/bin/bash
+set -e
+set -x
+
+SCRIPT_DIR="$(cd "$(dirname "$0")" && pwd)"
+REPO_DIR=$SCRIPT_DIR/../../
+cd $REPO_DIR
+
+rm -rf build
+cmake -S . -B build -G Ninja -DCMAKE_BUILD_TYPE=Debug -DWARNINGS=OFF -DBUILD_PRIVACY_ACTIVATION=On -DBUILD_JAVA=Off -DBUILD_PYTHON=Off -DBUILD_TESTS=On -DBUILD_FLATBUFFERS=Off
+cmake --build build --target vw-bin vw-unit-test.out

.scripts/linux/test-privacy_activation.sh

@@ -0,0 +1,13 @@
+#!/bin/bash
+set -e
+set -x
+
+SCRIPT_DIR="$(cd "$(dirname "$0")" && pwd)"
+REPO_DIR=$SCRIPT_DIR/../../
+cd $REPO_DIR
+
+cd test
+python3 run_tests.py -f --skip_spanning_tree_tests -j $(nproc) --test_spec privacy_activation.vwtest.json
+
+cd ../build
+./test/unit_test/vw-unit-test.out --run_test=test_feature_is_activated*,test_feature_not_activated*,test_feature_could_be_activated_but_feature_not_initialized*

CMakeLists.txt

@@ -99,6 +99,7 @@ option(RAPIDJSON_SYS_DEP "Override using the submodule for RapidJSON dependency.
 option(FMT_SYS_DEP "Override using the submodule for FMT dependency. Instead will use find_package" OFF)
 option(SPDLOG_SYS_DEP "Override using the submodule for spdlog dependency. Instead will use find_package" OFF)
 option(BUILD_FLATBUFFERS "Build flatbuffers" OFF)
+option(BUILD_PRIVACY_ACTIVATION "Enable privacy activation feature" OFF)
 
 string(TOUPPER "${CMAKE_BUILD_TYPE}" CONFIG)
 

test/CMakeLists.txt

@@ -26,4 +26,13 @@ if(NOT WIN32)
     COMMAND python3 run_tests.py --ignore_dirty --test_spec ${CMAKE_CURRENT_SOURCE_DIR}/slow.vwtest.json
     WORKING_DIRECTORY ${CMAKE_CURRENT_SOURCE_DIR}
   )
+
+  if(BUILD_PRIVACY_ACTIVATION)
+    add_test(
+      NAME privacy_activation_tests
+
+      COMMAND python3 run_tests.py --ignore_dirty --test_spec ${CMAKE_CURRENT_SOURCE_DIR}/privacy_activation.vwtest.json
+      WORKING_DIRECTORY ${CMAKE_CURRENT_SOURCE_DIR}
+    )
+  endif()
 endif()

test/benchmarks/standalone/benchmark_text_input.cc

@@ -51,7 +51,7 @@ static void benchmark_cb_adf_learn(benchmark::State& state, int feature_count)
 {
   auto vw = VW::initialize("--cb_explore_adf --epsilon 0.1 --quiet -q ::", nullptr, false, nullptr, nullptr);
   multi_ex examples;
-  examples.push_back(VW::read_example(*vw, std::string("shared | s_1 s_2")));
+  examples.push_back(VW::read_example(*vw, std::string("shared tag1| s_1 s_2")));
   examples.push_back(VW::read_example(*vw, get_x_string_fts(feature_count)));
   examples.push_back(VW::read_example(*vw, get_x_string_fts_no_label(feature_count)));
   examples.push_back(VW::read_example(*vw, get_x_string_fts_no_label(feature_count)));
@@ -65,6 +65,27 @@ static void benchmark_cb_adf_learn(benchmark::State& state, int feature_count)
   VW::finish(*vw);
 }
 
+#ifdef PRIVACY_ACTIVATION
+static void benchmark_cb_adf_learn_privacy_preserving(benchmark::State& state, int feature_count)
+{
+  auto vw = VW::initialize(
+      "--privacy_activation --cb_explore_adf --epsilon 0.1 --quiet -q ::", nullptr, false, nullptr, nullptr);
+  multi_ex examples;
+  examples.push_back(VW::read_example(*vw, std::string("shared tag1| s_1 s_2")));
+  examples.push_back(VW::read_example(*vw, get_x_string_fts(feature_count)));
+  examples.push_back(VW::read_example(*vw, get_x_string_fts_no_label(feature_count)));
+  examples.push_back(VW::read_example(*vw, get_x_string_fts_no_label(feature_count)));
+
+  for (auto _ : state)
+  {
+    vw->learn(examples);
+    benchmark::ClobberMemory();
+  }
+  vw->finish_example(examples);
+  VW::finish(*vw);
+}
+#endif
+
 static void benchmark_ccb_adf_learn(benchmark::State& state, std::string feature_string)
 {
   auto vw = VW::initialize("--ccb_explore_adf --quiet", nullptr, false, nullptr, nullptr);
@@ -225,6 +246,11 @@ BENCHMARK_CAPTURE(benchmark_ccb_adf_learn, many_features, "a b c d e f g h i j k
 BENCHMARK_CAPTURE(benchmark_cb_adf_learn, few_features, 2);
 BENCHMARK_CAPTURE(benchmark_cb_adf_learn, many_features, 120);
 
+#ifdef PRIVACY_ACTIVATION
+BENCHMARK_CAPTURE(benchmark_cb_adf_learn_privacy_preserving, few_features, 2);
+BENCHMARK_CAPTURE(benchmark_cb_adf_learn_privacy_preserving, many_features, 120);
+#endif
+
 BENCHMARK_CAPTURE(benchmark_multi, cb_adf_no_namespaces, gen_cb_examples(100, 7, 3, 6, 1, 4, 14, 2, false),
     "--cb_explore_adf --quiet");
 BENCHMARK_CAPTURE(benchmark_multi, cb_adf_diff_char_no_interactions, gen_cb_examples(100, 7, 3, 6, 3, 4, 14, 2, false),

test/pred-sets/ref/readable_model_privacy.txt

@@ -0,0 +1,15 @@
+Version 8.11.0
+Id 
+Min label:0
+Max label:1
+bits:18
+lda:0
+0 ngram:
+0 skip:
+options: --cb_adf --cb_explore_adf --cb_max_cost 1 --cb_min_cost 0 --cb_type mtr --cbify 2 --csoaa_ldf multiline --csoaa_rank
+Checksum: 2467443617
+event_sum 31
+action_sum 62
+:0
+Constant:116060:0.115805
+impression:236580:0.0376027

test/pred-sets/ref/readable_model_privacy_no_tags.txt

@@ -0,0 +1,13 @@
+Version 8.11.0
+Id 
+Min label:0
+Max label:1
+bits:18
+lda:0
+0 ngram:
+0 skip:
+options: --cb_adf --cb_explore_adf --cb_max_cost 1 --cb_min_cost 0 --cb_type mtr --cbify 2 --csoaa_ldf multiline --csoaa_rank
+Checksum: 2467443617
+event_sum 31
+action_sum 62
+:0

test/privacy_activation.vwtest.json

@@ -0,0 +1,26 @@
+[
+    {
+        "id": 1,
+        "desc": "test privacy_activation command line argument",
+        "vw_command": "--privacy_activation -d train-sets/privacy_dataset --invert_hash readable_model_privacy.txt --cbify 2 --cb_adf",
+        "diff_files": {
+            "stderr": "train-sets/ref/privacy_dataset.stderr",
+            "readable_model_privacy.txt": "pred-sets/ref/readable_model_privacy.txt"
+        },
+        "input_files": [
+            "train-sets/privacy_dataset"
+        ]
+    },
+    {
+        "id": 2,
+        "desc": "test privacy_activation command line argument with no tags input",
+        "vw_command": "--privacy_activation -d train-sets/privacy_dataset_no_tags --invert_hash readable_model_privacy_no_tags.txt --cbify 2 --cb_adf",
+        "diff_files": {
+            "stderr": "train-sets/ref/privacy_no_tags.stderr",
+            "readable_model_privacy_no_tags.txt": "pred-sets/ref/readable_model_privacy_no_tags.txt"
+        },
+        "input_files": [
+            "train-sets/privacy_dataset_no_tags"
+        ]
+    }
+]

test/train-sets/privacy_dataset

@@ -0,0 +1,31 @@
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test/train-sets/privacy_dataset_no_tags

@@ -0,0 +1,31 @@
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test/train-sets/ref/privacy_dataset.stderr

@@ -0,0 +1,24 @@
+Num weight bits = 18
+learning rate = 0.5
+initial_t = 0
+power_t = 0.5
+using no cache
+Reading datafile = train-sets/privacy_dataset
+num sources = 1
+Enabled reductions: gd, scorer-identity, csoaa_ldf-rank, cb_adf, cb_explore_adf_greedy, shared_feature_merger, cbify-adf
+Input label = multiclass
+Output pred = multiclass
+average  since         example        example  current  current  current
+loss     last          counter         weight    label  predict features
+0.000000 0.000000            1            1.0        1        1       11
+0.000000 0.000000            2            2.0        2        2       11
+0.000000 0.000000            4            4.0        2        2       11
+0.125000 0.250000            8            8.0        1        1       11
+0.187500 0.250000           16           16.0        1        1       11
+
+finished run
+number of examples = 31
+weighted example sum = 31.000000
+weighted label sum = 0.000000
+average loss = 0.193548
+total feature number = 341

test/train-sets/ref/privacy_no_tags.stderr

@@ -0,0 +1,24 @@
+Num weight bits = 18
+learning rate = 0.5
+initial_t = 0
+power_t = 0.5
+using no cache
+Reading datafile = train-sets/privacy_dataset_no_tags
+num sources = 1
+Enabled reductions: gd, scorer-identity, csoaa_ldf-rank, cb_adf, cb_explore_adf_greedy, shared_feature_merger, cbify-adf
+Input label = multiclass
+Output pred = multiclass
+average  since         example        example  current  current  current
+loss     last          counter         weight    label  predict features
+0.000000 0.000000            1            1.0        1        1       11
+0.000000 0.000000            2            2.0        2        2       11
+0.250000 0.500000            4            4.0        1        2       11
+0.375000 0.500000            8            8.0        1        1       11
+0.500000 0.625000           16           16.0        1        2       11
+
+finished run
+number of examples = 31
+weighted example sum = 31.000000
+weighted label sum = 0.000000
+average loss = 0.322581
+total feature number = 341