Merge pull request #107 from Yanghello/truncate3

add compile option for truncate3

CMakeLists.txt

@@ -61,6 +61,8 @@ option(USE_AES_NI "Compile with AES NI" ON)
 
 option(USE_OPENMP "Compile with OpenMP" ON)
 
+option(USE_ABY3_TRUNC1 "Compile with ABY3 truncate 1 algorithm" OFF)
+
 ########################### the project build part ###############################
 message(STATUS "Using paddlepaddle installation of ${paddle_version}")
 message(STATUS "paddlepaddle include directory: ${PADDLE_INCLUDE}")
@@ -84,6 +86,10 @@ if (USE_OPENMP)
     find_package(OpenMP REQUIRED)
 endif(USE_OPENMP)
 
+if (USE_ABY3_TRUNC1)
+    add_compile_definitions(USE_ABY3_TRUNC1)
+endif(USE_ABY3_TRUNC1)
+
 add_subdirectory(core/privc3)
 add_subdirectory(core/paddlefl_mpc/mpc_protocol)
 add_subdirectory(core/paddlefl_mpc/operators)

core/privc3/fixedpoint_tensor.h

@@ -191,6 +191,9 @@ public:
     void max_pooling(FixedPointTensor* ret,
                      BooleanTensor<T>* pos = nullptr) const;
 
+    static void truncate(const FixedPointTensor* op, FixedPointTensor* ret,
+                        size_t scaling_factor);
+
 private:
 
     static inline std::shared_ptr<CircuitContext> aby3_ctx() {
@@ -201,9 +204,6 @@ private:
         return paddle::mpc::ContextHolder::tensor_factory();
     }
 
-    static void truncate(const FixedPointTensor* op, FixedPointTensor* ret,
-                          size_t scaling_factor);
-
     template<typename MulFunc>
     static void mul_trunc(const FixedPointTensor<T, N>* lhs,
                           const FixedPointTensor<T, N>* rhs,

core/privc3/fixedpoint_tensor_imp.h

@@ -21,7 +21,6 @@
 #include "prng.h"
 
 namespace aby3 {
-
 template<typename T, size_t N>
 FixedPointTensor<T, N>::FixedPointTensor(TensorAdapter<T>* share_tensor[2]) {
     // TODO: check tensors' shapes
@@ -166,6 +165,7 @@ void FixedPointTensor<T, N>::mul(const FixedPointTensor<T, N>* rhs,
     mul_trunc(this, rhs, ret, &TensorAdapter<T>::mul);
 }
 
+#ifdef USE_ABY3_TRUNC1 //use aby3 trunc1
 template<typename T, size_t N>
 void FixedPointTensor<T, N>::truncate(const FixedPointTensor<T, N>* op,
                                        FixedPointTensor<T, N>* ret,
@@ -208,7 +208,20 @@ void FixedPointTensor<T, N>::truncate(const FixedPointTensor<T, N>* op,
     return;
 }
 
-// Protocol. `truncate3`
+#else // use truncate3
+
+// Protocol. `truncate3` (illustrated for data type T = int64_t)
+// motivation:
+// truncates in aby3 may cause msb error with small probability
+// the reason is that before rishft op, its masked value e.g., x' - r' may overflow in int64_t
+// so that, in `truncate3`, we limit r' in (-2^62, 2^62) to avoid the problem.
+
+// notice:
+// when r' is contrainted in (-2^62, 2^62),
+// the SD (statistical distance) of x' - r' between this
+// and r' in Z_{2^64} is equal to |X| / (2^63 + |X|)
+
+// detail protocol:
 // P2 randomly generates r' \in (-2^62, 2^62), randomly generates r'_0, r_0, r_1 in Z_{2^64},
 // P2 compute r'_1 = r' - r'_0, r_2 = r'/2^N - r_0 - r_1, let x2 = r_2
 // P2 send r_0, r'_0 to P0, send r_1, r'_1 to P1
@@ -217,7 +230,7 @@ void FixedPointTensor<T, N>::truncate(const FixedPointTensor<T, N>* op,
 // P0 set x0 = r_0
 // P0, P1, P2 invoke reshare() with inputs x0, x1, x2 respectively.
 template<typename T, size_t N>
-void FixedPointTensor<T, N>::truncate3(const FixedPointTensor<T, N>* op,
+void FixedPointTensor<T, N>::truncate(const FixedPointTensor<T, N>* op,
                                        FixedPointTensor<T, N>* ret,
                                        size_t scaling_factor) {
     if (scaling_factor == 0) {
@@ -231,23 +244,9 @@ void FixedPointTensor<T, N>::truncate3(const FixedPointTensor<T, N>* op,
             temp.emplace_back(
                 tensor_factory()->template create<T>(op->shape()));
         }
-        // r',  contraint in (-2^62, 2^62)
-        // notice : when r' is contrainted in (-2^62, 2^62),
-        // the SD (statistical distance) of x - r' between this
-        // and r' in Z_{2^64} is equal to |X| / (2^63 + |X|)
-        // according to http://yuyu.hk/files/ho2.pdf
+        // r'
         aby3_ctx()->template gen_random_private(*temp[0]);
-        int64_t contraint_upper = ~((uint64_t) 1 << 62);
-        int64_t contraint_low = (uint64_t) 1 << 62;
-        std::for_each(temp[0]->data(), temp[0]->data() + temp[0]->numel(),
-                      [&contraint_upper, &contraint_low] (T& a) {
-                          // contraint -2^62 < a < 2^62
-                          if (a >= 0) {
-                              a &= contraint_upper;
-                          } else {
-                              a |= contraint_low;
-                          }
-                      });
+        temp[0]->rshift(1, temp[0].get());
 
         //r'_0, r'_1
         aby3_ctx()->template gen_random_private(*temp[1]);
@@ -307,6 +306,7 @@ void FixedPointTensor<T, N>::truncate3(const FixedPointTensor<T, N>* op,
     tensor_carry_in->scaling_factor() = N;
     ret->add(tensor_carry_in.get(), ret);
 }
+#endif //USE_ABY3_TRUNC1
 
 template<typename T, size_t N>
 template<typename MulFunc>
@@ -345,7 +345,7 @@ void FixedPointTensor<T, N>::mul_trunc(const FixedPointTensor<T, N>* lhs,
     temp->copy(ret_no_trunc->_share[0]);
     reshare(temp.get(), ret_no_trunc->_share[1]);
 
-    truncate3(ret_no_trunc.get(), ret, N);
+    truncate(ret_no_trunc.get(), ret, N);
 }
 
 template<typename T, size_t N>
@@ -360,7 +360,7 @@ void FixedPointTensor<T, N>::mul(const TensorAdapter<T>* rhs,
 
     _share[0]->mul(rhs, temp->_share[0]);
     _share[1]->mul(rhs, temp->_share[1]);
-    truncate3(temp.get(), ret, rhs->scaling_factor());
+    truncate(temp.get(), ret, rhs->scaling_factor());
 }
 
 template<typename T, size_t N>
@@ -404,7 +404,7 @@ void FixedPointTensor<T, N>::mat_mul(const TensorAdapter<T>* rhs,
                                      FixedPointTensor<T, N>* ret) const {
     _share[0]->mat_mul(rhs, ret->_share[0]);
     _share[1]->mat_mul(rhs, ret->_share[1]);
-    truncate3(ret, ret, rhs->scaling_factor());
+    truncate(ret, ret, rhs->scaling_factor());
 }
 
 template< typename T, size_t N>
@@ -831,7 +831,7 @@ void FixedPointTensor<T, N>::long_div(const FixedPointTensor<T, N>* rhs,
     }
 
     for (size_t i = 1; i <= N; ++i) {
-        truncate3(&abs_rhs, &sub_rhs, i);
+        truncate(&abs_rhs, &sub_rhs, i);
         abs_lhs.gt(&sub_rhs, &cmp_res);
         cmp_res.mul(&sub_rhs, &sub_rhs);
         cmp_res.lshift(N - i, &cmp_res);
@@ -1184,7 +1184,7 @@ void FixedPointTensor<T, N>::inverse_square_root(const FixedPointTensor* op,
     std::shared_ptr<FixedPointTensor<T, N>> x2 =
         std::make_shared<FixedPointTensor<T, N>>(temp[2].get(), temp[3].get());
     // x2 = 0.5 * op
-    truncate3(op, x2.get(), 1);
+    truncate(op, x2.get(), 1);
 
     assign_to_tensor(y->mutable_share(0), (T)(x0 * pow(2, N)));
     assign_to_tensor(y->mutable_share(1), (T)(x0 * pow(2, N)));

core/privc3/fixedpoint_tensor_test.cc

@@ -1267,6 +1267,7 @@ TEST_F(FixedTensorTest, mulfixed) {
     EXPECT_TRUE(test_fixedt_check_tensor_eq(out0.get(), &result));
 }
 
+#ifndef USE_ABY3_TRUNC1 //use aby3 trunc1
 TEST_F(FixedTensorTest, mulfixed_multi_times) {
 
     std::vector<size_t> shape = {100000, 1};
@@ -1327,6 +1328,7 @@ TEST_F(FixedTensorTest, mulfixed_multi_times) {
     EXPECT_TRUE(test_fixedt_check_tensor_eq(out1.get(), out2.get()));
     EXPECT_TRUE(test_fixedt_check_tensor_eq(out0.get(), &result));
 }
+#endif
 
 TEST_F(FixedTensorTest, mulfixed_overflow) {
 
@@ -3435,4 +3437,124 @@ TEST_F(FixedTensorTest, inv_sqrt_test) {
 
 }
 
+#ifdef USE_ABY3_TRUNC1 //use aby3 trunc1
+TEST_F(FixedTensorTest, truncate1_msb_incorrect) {
+    std::vector<size_t> shape = { 1 };
+    std::shared_ptr<TensorAdapter<int64_t>> sl[3] = { gen(shape), gen(shape), gen(shape) };
+    std::shared_ptr<TensorAdapter<int64_t>> sout[6] = { gen(shape), gen(shape), gen(shape),
+                                                        gen(shape), gen(shape), gen(shape)};
+    // lhs = 6 = 1 + 2 + 3, share before truncate
+    // zero share 0 = (1 << 62) + (1 << 62) - (1 << 63)
+    sl[0]->data()[0] = ((int64_t) 3 << 32) - ((uint64_t) 1 << 63);
+    sl[1]->data()[0] = ((int64_t) 2 << 32) + ((int64_t) 1 << 62);
+    sl[2]->data()[0] = ((int64_t) 1 << 32) + ((int64_t) 1 << 62);
+
+    auto pr = gen(shape);
+
+    // rhs = 15
+    pr->data()[0] = 6 << 16;
+    pr->scaling_factor() = 16;
+    Fix64N16 fl0(sl[0].get(), sl[1].get());
+    Fix64N16 fl1(sl[1].get(), sl[2].get());
+    Fix64N16 fl2(sl[2].get(), sl[0].get());
+    Fix64N16 fout0(sout[0].get(), sout[1].get());
+    Fix64N16 fout1(sout[2].get(), sout[3].get());
+    Fix64N16 fout2(sout[4].get(), sout[5].get());
+
+    auto p = gen(shape);
+
+    _t[0] = std::thread(
+        [&] () {
+        g_ctx_holder::template run_with_context(
+            _exec_ctx.get(), _mpc_ctx[0], [&](){
+                Fix64N16::truncate(&fl0, &fout0, 16);
+                fout0.reveal_to_one(0, p.get());
+            });
+        }
+    );
+    _t[1] = std::thread(
+        [&] () {
+        g_ctx_holder::template run_with_context(
+            _exec_ctx.get(), _mpc_ctx[1], [&](){
+                Fix64N16::truncate(&fl1, &fout1, 16);
+                fout1.reveal_to_one(0, nullptr);
+            });
+        }
+    );
+    _t[2] = std::thread(
+        [&] () {
+        g_ctx_holder::template run_with_context(
+            _exec_ctx.get(), _mpc_ctx[2], [&](){
+                Fix64N16::truncate(&fl2, &fout2, 16);
+                fout2.reveal_to_one(0, nullptr);
+            });
+        }
+    );
+    for (auto &t: _t) {
+        t.join();
+    }
+    // failed: result is not close to 6
+    EXPECT_GT(std::abs((p->data()[0] >> 16) - 6), 1000);
+}
+
+#else
+TEST_F(FixedTensorTest, truncate3_msb_correct) {
+    std::vector<size_t> shape = { 1 };
+    std::shared_ptr<TensorAdapter<int64_t>> sl[3] = { gen(shape), gen(shape), gen(shape) };
+    std::shared_ptr<TensorAdapter<int64_t>> sout[6] = { gen(shape), gen(shape), gen(shape),
+                                                        gen(shape), gen(shape), gen(shape)};
+    // lhs = 6 = 1 + 2 + 3, share before truncate
+    // zero share 0 = (1 << 62) + (1 << 62) - (1 << 63)
+    sl[0]->data()[0] = ((int64_t) 3 << 32) - ((uint64_t) 1 << 63);
+    sl[1]->data()[0] = ((int64_t) 2 << 32) + ((int64_t) 1 << 62);
+    sl[2]->data()[0] = ((int64_t) 1 << 32) + ((int64_t) 1 << 62);
+
+    auto pr = gen(shape);
+
+    // rhs = 15
+    pr->data()[0] = 6 << 16;
+    pr->scaling_factor() = 16;
+    Fix64N16 fl0(sl[0].get(), sl[1].get());
+    Fix64N16 fl1(sl[1].get(), sl[2].get());
+    Fix64N16 fl2(sl[2].get(), sl[0].get());
+    Fix64N16 fout0(sout[0].get(), sout[1].get());
+    Fix64N16 fout1(sout[2].get(), sout[3].get());
+    Fix64N16 fout2(sout[4].get(), sout[5].get());
+
+    auto p = gen(shape);
+
+    _t[0] = std::thread(
+        [&] () {
+        g_ctx_holder::template run_with_context(
+            _exec_ctx.get(), _mpc_ctx[0], [&](){
+                Fix64N16::truncate(&fl0, &fout0, 16);
+                fout0.reveal_to_one(0, p.get());
+            });
+        }
+    );
+    _t[1] = std::thread(
+        [&] () {
+        g_ctx_holder::template run_with_context(
+            _exec_ctx.get(), _mpc_ctx[1], [&](){
+                Fix64N16::truncate(&fl1, &fout1, 16);
+                fout1.reveal_to_one(0, nullptr);
+            });
+        }
+    );
+    _t[2] = std::thread(
+        [&] () {
+        g_ctx_holder::template run_with_context(
+            _exec_ctx.get(), _mpc_ctx[2], [&](){
+                Fix64N16::truncate(&fl2, &fout2, 16);
+                fout2.reveal_to_one(0, nullptr);
+            });
+        }
+    );
+    for (auto &t: _t) {
+        t.join();
+    }
+    EXPECT_EQ((p->data()[0] >> 16), 6);
+}
+#endif
+
 } // namespace aby3