refactor(mgb): move algo's name from info to desc and delete some algo's unnecessary param() method

GitOrigin-RevId: 144ff547d1

dnn/include/megdnn/oprs/base.h

@@ -136,16 +136,16 @@ public:
             uint32_t type = INVALID_ALGO_TYPE;
             //! serialized param of the algo type
             std::string param;
+            //! algorithm name
+            std::string name;
             bool valid() const { return type != INVALID_ALGO_TYPE; }
             void reset() { type = INVALID_ALGO_TYPE; }
 
             bool operator==(const Desc& rhs) const {
                 return handle_type == rhs.handle_type && type == rhs.type &&
-                       param == rhs.param;
+                       param == rhs.param && name == rhs.name;
             }
         } desc;
-        //! algorithm name
-        std::string name;
         Attribute attribute;
         bool valid() const { return desc.valid(); }
         void reset() { desc.reset(); }
@@ -178,12 +178,12 @@ public:
     static std::string attribute_str(const Attribute& attr);
 
     Handle::HandleType handle_type() const { return m_handle_type; }
+
+    Info::Desc desc() const { return {handle_type(), type(), param(), name()}; }
     Info info() const {
-        return {{handle_type(), type(), param()}, name(), attribute()};
+        return {desc(), attribute()};
     }
 
-    Info::Desc desc() const { return {handle_type(), type(), param()}; }
-
     template <typename T>
     static void serialize_write_pod(const T& val, std::string& result) {
         static_assert(std::is_trivially_copyable<T>::value,

dnn/src/common/algo_base.h

@@ -116,8 +116,10 @@ struct hash<megdnn::detail::Algorithm::Info::Desc> {
             const megdnn::detail::Algorithm::Info::Desc& desc) const {
         return megdnn::hash_combine<size_t>(
                 megdnn::hash_combine<size_t>(
-                        std::hash<std::string>()(desc.param),
-                        std::hash<uint32_t>()(desc.type)),
+                        std::hash<std::string>()(desc.name),
+                        megdnn::hash_combine<size_t>(
+                                std::hash<std::string>()(desc.param),
+                                std::hash<uint32_t>()(desc.type))),
                 std::hash<uint32_t>()(static_cast<uint32_t>(desc.handle_type)));
     }
 };

dnn/src/cuda/conv_bias/algo.h

@@ -439,12 +439,6 @@ public:
                                  TensorLayout& dst_pg, TensorLayout& bias_pg);
     MEGDNN_DECL_ALGO_TYPE(CUDA_GROUP_CONV_GENERAL)
 
-    std::string param() const override {
-        std::string ret;
-        serialize_write_pod(m_impl->name(), ret);
-        return ret;
-    }
-
 private:
     WorkspaceBundle get_workspace_bundle(void* ptr, const SizeArgs& args) const;
     AlgoBase* m_impl;

dnn/src/cuda/convolution/backward_data/algo.h

@@ -237,12 +237,6 @@ public:
         }
         return ret;
     }
-
-    std::string param() const override {
-        std::string ret;
-        serialize_write_pod(m_impl->name(), ret);
-        return ret;
-    }
 };
 
 class ConvolutionBackwardDataImpl::AlgoInt8NCHW4DotProdImplicitGemm final

dnn/src/cuda/convolution/backward_filter/algo.h

@@ -222,12 +222,6 @@ public:
         }
         return ret;
     }
-
-    std::string param() const override {
-        std::string ret;
-        serialize_write_pod(m_impl->name(), ret);
-        return ret;
-    }
 };
 
 class ConvolutionBackwardFilterImpl::AlgoPack : NonCopyableObj {

dnn/src/cuda/convolution3d/backward_data/algo.h

@@ -174,14 +174,8 @@ public:
     }
 
     MEGDNN_DECL_ALGO_TYPE(CUDA_GROUP_CONV_GENERAL)
-    std::string param() const override {
-        std::string ret;
-        serialize_write_pod(m_impl->name(), ret);
-        return ret;
-    }
 };
 
-
 class Convolution3DBackwardDataImpl::AlgoPack : NonCopyableObj {
     // defined in cudnn.cpp
     void fill_cudnn_algos();

dnn/src/cuda/convolution3d/backward_filter/algo.h

@@ -183,11 +183,6 @@ public:
                                  TensorLayout& diff_pg);
 
     MEGDNN_DECL_ALGO_TYPE(CUDA_GROUP_CONV_GENERAL)
-    std::string param() const override {
-        std::string ret;
-        serialize_write_pod(m_impl->name(), ret);
-        return ret;
-    }
 };
 
 class Convolution3DBackwardFilterImpl::AlgoPack : NonCopyableObj {

dnn/src/cuda/convolution3d/forward/algo.h

@@ -135,11 +135,6 @@ public:
     static void modify_size_args(SizeArgs& args, TensorLayout& src_pg,
                                  TensorLayout& dst_pg);
     MEGDNN_DECL_ALGO_TYPE(CUDA_GROUP_CONV_GENERAL)
-    std::string param() const override {
-        std::string ret;
-        serialize_write_pod(m_impl->name(), ret);
-        return ret;
-    }
 };
 
 class Convolution3DForwardImpl::AlgoCUDNN final : public AlgoBase {

dnn/src/fallback/conv_bias/algos.h

@@ -65,11 +65,6 @@ public:
         return {AlgoDataType::FLOAT32, AlgoCategory::WINOGRAD};
     }
     MEGDNN_DECL_ALGO_TYPE(FB_WINOGRAD_F32)
-    std::string param() const override {
-        std::string ret;
-        serialize_write_pod(m_matmul_algo->name(), ret);
-        return ret;
-    }
 
 private:
     MatrixMulImpl::AlgoBase* m_matmul_algo;
@@ -101,11 +96,6 @@ public:
         return {AlgoDataType::FLOAT32, AlgoCategory::WINOGRAD};
     }
     MEGDNN_DECL_ALGO_TYPE(FB_WINOGRAD_4X4_F32)
-    std::string param() const override {
-        std::string ret;
-        serialize_write_pod(m_matmul_algo->name(), ret);
-        return ret;
-    }
 
 private:
     MatrixMulImpl::AlgoBase* m_matmul_algo;
@@ -137,11 +127,6 @@ public:
         return {AlgoDataType::QINT8X8X32, AlgoCategory::WINOGRAD};
     }
     MEGDNN_DECL_ALGO_TYPE(FB_WINOGRAD_QS8)
-    std::string param() const override {
-        std::string ret;
-        serialize_write_pod(m_matmul_algo->name(), ret);
-        return ret;
-    }
 
 private:
     MatrixMulImpl::AlgoBase* m_matmul_algo;
@@ -173,11 +158,6 @@ public:
         return {AlgoDataType::QINT8X8X32, AlgoCategory::WINOGRAD};
     }
     MEGDNN_DECL_ALGO_TYPE(FB_WINOGRAD_8X8_QS8)
-    std::string param() const override {
-        std::string ret;
-        serialize_write_pod(m_matmul_algo->name(), ret);
-        return ret;
-    }
 
 private:
     MatrixMulImpl::AlgoBase* m_matmul_algo;

dnn/src/fallback/conv_bias/common.h

@@ -157,7 +157,6 @@ using BiasMode = ConvBiasForward::BiasMode;
     }                                                                          \
     std::string param() const override {                                       \
         std::string ret;                                                       \
-        serialize_write_pod(m_matmul_algo->name(), ret);                       \
         serialize_write_pod(m_tile_size, ret);                                 \
         return ret;                                                            \
     }                                                                          \

dnn/src/fallback/conv_bias/conv1x1/algos.h

@@ -62,10 +62,9 @@ public:
         return {m_matmul_algo->matmul_description().algo_type.data_type,
                 AlgoCategory::IM2COL};
     }
-    MEGDNN_DECL_ALGO_TYPE(FB_WINOGRAD_8X8_QS8)
+    MEGDNN_DECL_ALGO_TYPE(FB_CONV1x1)
     std::string param() const override {
         std::string ret;
-        serialize_write_pod(m_matmul_algo->name(), ret);
         serialize_write_pod(m_oc_block_size, ret);
         return ret;
     }

dnn/src/fallback/conv_bias/im2col/algos.h

@@ -74,7 +74,6 @@ public:
 
     std::string param() const override {
         std::string ret;
-        serialize_write_pod(m_matmul_algo->name(), ret);
         serialize_write_pod(m_ohw_tile_size, ret);
         return ret;
     }

dnn/src/fallback/convolution/algos.h

@@ -155,12 +155,6 @@ public:
     //! select matmul to the highest preference
     bool is_preferred(const NCBKernSizeParam& param) const override;
 
-    std::string param() const override {
-        std::string ret;
-        serialize_write_pod(m_algorithm->name(), ret);
-        return ret;
-    }
-
     static ConvBiasImpl::NCBKernSizeParam init_conv_bias_param(
             const NCBKernSizeParam& param);
 

dnn/test/common/benchmarker.h

@@ -380,13 +380,13 @@ float algo_benchmark(Benchmarker<Opr, T>& benchmark, TensorLayoutArray layouts,
     float min_used = std::numeric_limits<float>::max();
     bool execed = false;
     for (auto i : algos) {
-        if (std::regex_match(i.name,
+        if (std::regex_match(i.desc.name,
                              std::regex("(" + algo_base + ")(.*)"))) {
             opr->execution_policy().algo = i.desc;
             auto used = benchmark.exec(layouts);
             min_used = std::min(min_used, used);
-            printf("run algo: %s used: %f ms min_used: %f ms\n", i.name.c_str(),
-                   used, min_used);
+            printf("run algo: %s used: %f ms min_used: %f ms\n",
+                   i.desc.name.c_str(), used, min_used);
             execed = true;
         }
     }

dnn/test/common/checker.h

@@ -482,7 +482,7 @@ public:
              AlgoProxy<Opr, OprTrait<Opr>::arity>::get_all_algorithms_info(
                      opr.get(), layouts)) {
             if (std::regex_match(
-                        algo_info.name,
+                        algo_info.desc.name,
                         std::regex("(" + policy_name.name + ")(.*)"))) {
                 ret.algo = algo_info.desc;
             } else {
@@ -495,7 +495,7 @@ public:
             if (sub_items.size() != policy_name.sub_policy_names.size()) {
                 printf("Invalid sub_policy_names in %s, expected %zu but got "
                        "%zu\n",
-                       algo_info.name.c_str(), sub_items.size(),
+                       algo_info.desc.name.c_str(), sub_items.size(),
                        policy_name.sub_policy_names.size());
                 return {};
             }
@@ -528,7 +528,7 @@ public:
             auto algo =
                     OprAlgoProxy::get_algorithm_info_heuristic(opr, layouts);
             ASSERT_STREQ(opr->get_algorithm_from_desc(m_policy.algo)->name(),
-                         algo.name.c_str());
+                         algo.desc.name.c_str());
         } else {
             opr->execution_policy() = m_policy;
         }

dnn/test/common/convolution.cpp

@@ -629,11 +629,10 @@ Checker<Convolution> checker(handle);
             out_type = inp_type;
         }
 
-        checker
-            .set_dtype(0, inp_type)
-            .set_dtype(1, inp_type)
-            .set_dtype(2, out_type)
-            .set_param(param);
+        checker.set_dtype(0, inp_type)
+                .set_dtype(1, inp_type)
+                .set_dtype(2, out_type)
+                .set_param(param);
         auto opr = checker.opr();
         opr->param() = param;
         std::string param_str;
@@ -642,7 +641,8 @@ Checker<Convolution> checker(handle);
         oly.dtype = out_type;
         opr->deduce_layout(ily, fly, oly);
         int channel_start = 1;
-        if (format) channel_start = 3;
+        if (format)
+            channel_start = 3;
         float scale = 1.0f / sqrt(fshp[channel_start] * FH * FW);
         UniformFloatRNG rng(scale, 2 * scale);
         checker.set_rng(0, &rng).set_rng(1, &rng);
@@ -653,11 +653,11 @@ Checker<Convolution> checker(handle);
             construct_sub_execution_policy_heuristic<ConvolutionForward>(
                     opr->execution_policy(), {ily, fly, oly}, param_str,
                     opr->handle());
-            checker
-                .set_epsilon(eps_getter(dtype == 1, 0, algo.name.c_str()))
-                .execs({ishp, fshp, {}});
+            checker.set_epsilon(
+                           eps_getter(dtype == 1, 0, algo.desc.name.c_str()))
+                    .execs({ishp, fshp, {}});
             opr->execution_policy() = {};
-            ASSERT_TRUE(checker.prev_succ()) << errmsg(algo.name.c_str());
+            ASSERT_TRUE(checker.prev_succ()) << errmsg(algo.desc.name.c_str());
         }
 
         if (test_backward) {
@@ -671,7 +671,7 @@ Checker<Convolution> checker(handle);
             opr->param() = param;
             std::string param_str;
             Algorithm::serialize_write_pod(opr->param(), param_str);
-            for (auto algo: opr->get_all_algorithms_info(fly, oly, ily)) {
+            for (auto algo : opr->get_all_algorithms_info(fly, oly, ily)) {
                 used_algos_bwd_data.insert(algo.desc);
                 opr->execution_policy().algo = algo.desc;
                 construct_sub_execution_policy_heuristic<
@@ -679,26 +679,26 @@ Checker<Convolution> checker(handle);
                                                  {fly, oly, ily}, param_str,
                                                  opr->handle());
                 checker_bwd_data
-                    .set_epsilon(eps_getter(dtype == 1, 1, algo.name.c_str()))
-                    .execl({fly, oly, ily});
+                        .set_epsilon(eps_getter(dtype == 1, 1,
+                                                algo.desc.name.c_str()))
+                        .execl({fly, oly, ily});
                 opr->execution_policy() = {};
-                ASSERT_TRUE(checker_bwd_data.prev_succ()) <<
-                    errmsg(algo.name.c_str());
+                ASSERT_TRUE(checker_bwd_data.prev_succ())
+                        << errmsg(algo.desc.name.c_str());
             }
         }
         if (test_backward) {
             // backward filter
-            checker_bwd_filter
-                .set_dtype(0, inp_type)
-                .set_dtype(1, out_type)
-                .set_dtype(2, inp_type)
-                .set_param(param);
+            checker_bwd_filter.set_dtype(0, inp_type)
+                    .set_dtype(1, out_type)
+                    .set_dtype(2, inp_type)
+                    .set_param(param);
 
             auto opr = checker_bwd_filter.opr();
             opr->param() = param;
             std::string param_str;
             Algorithm::serialize_write_pod(opr->param(), param_str);
-            for (auto algo: opr->get_all_algorithms_info(ily, oly, fly)) {
+            for (auto algo : opr->get_all_algorithms_info(ily, oly, fly)) {
                 used_algos_bwd_flt.insert(algo.desc);
                 opr->execution_policy().algo = algo.desc;
                 construct_sub_execution_policy_heuristic<
@@ -706,11 +706,12 @@ Checker<Convolution> checker(handle);
                                                    {ily, oly, fly}, param_str,
                                                    opr->handle());
                 checker_bwd_filter
-                    .set_epsilon(eps_getter(dtype == 1, 2, algo.name.c_str()))
-                    .execl({ily, oly, fly});
+                        .set_epsilon(eps_getter(dtype == 1, 2,
+                                                algo.desc.name.c_str()))
+                        .execl({ily, oly, fly});
                 opr->execution_policy() = {};
-                ASSERT_TRUE(checker_bwd_filter.prev_succ()) <<
-                    errmsg(algo.name.c_str());
+                ASSERT_TRUE(checker_bwd_filter.prev_succ())
+                        << errmsg(algo.desc.name.c_str());
             }
         }
     }

dnn/test/common/opr_proxy.h

@@ -400,7 +400,7 @@ struct OprProxyProfilingBase
             megcoreSynchronize(opr->handle()->megcore_computing_handle());
             timer.stop();
             megdnn_log("%.3fms %s", timer.get_time_in_us() / 1e3,
-                       algo.name.c_str());
+                       algo.desc.name.c_str());
             if (min_time > timer.get_time_in_us()) {
                 min_time = timer.get_time_in_us();
                 best_algo = algo.desc;
@@ -522,7 +522,7 @@ struct OprWeightPreprocessProxyImpl : public OprProxyProfilingBase<Opr> {
                 megcoreSynchronize(opr->handle()->megcore_computing_handle());
                 timer.stop();
                 printf("%.3fms %s\n", timer.get_time_in_us() / 1e3,
-                       algo.name.c_str());
+                       algo.desc.name.c_str());
                 if (min_time > timer.get_time_in_us()) {
                     min_time = timer.get_time_in_us();
                     Base::target_execution_policy.algo = algo.desc;

dnn/test/cuda/cutlass_matmul.cpp

@@ -88,7 +88,7 @@ void test_multibatchsize(
                          A_tensor.layout(), B_tensor.layout(),
                          C_tensor.layout())) {
                 if (std::regex_match(
-                            i.name.c_str(),
+                            i.desc.name.c_str(),
                             std::regex("(" + std::string(algo) + ")(.*)"))) {
                     opr_reference->execution_policy().algo = i.desc;
                     break;
@@ -117,7 +117,7 @@ void test_multibatchsize(
                          A_tensor_prime.layout(), B_tensor.layout(),
                          C_tensor_batch.layout())) {
                 if (std::regex_match(
-                            i.name.c_str(),
+                            i.desc.name.c_str(),
                             std::regex("(" + std::string(algo) + ")(.*)"))) {
                     opr_reference->execution_policy().algo = i.desc;
                     break;

src/opr/impl/search_policy/algo_chooser.cpp

@@ -318,7 +318,7 @@ void AlgoChooser<Opr>::profile(ExeContext& ctx,
         Maybe<AlgoChooserProfileCache::ResultEntry> cur_rst;
         std::string msg = ssprintf("profiling %s algorithm %s %s",
                                    ctx.mgb_opr()->dyn_typeinfo()->name,
-                                   algo.name.c_str(), layouts_str.c_str());
+                                   algo.desc.name.c_str(), layouts_str.c_str());
         ImplExecutionPolicy policy;
         policy.algo = algo.desc;
         ctx.construct_execution_policy(selected_strategy, policy);
@@ -327,12 +327,12 @@ void AlgoChooser<Opr>::profile(ExeContext& ctx,
         }
         auto palgo = ctx.megdnn_opr()->get_algorithm_from_desc(policy.algo);
         if (!(palgo->contain_attribute_all(target_attr.first) &&
-            !palgo->contain_attribute_any(target_attr.second))) {
+              !palgo->contain_attribute_any(target_attr.second))) {
             mgb_log_debug(
                     "skip algo %s with attribute(%s), which is not match the "
                     "profile strategy required contain attribute(%s) and not "
                     "contain attribute(%s).",
-                    algo.name.c_str(),
+                    algo.desc.name.c_str(),
                     Algorithm::attribute_str(palgo->attribute()).c_str(),
                     Algorithm::attribute_str(target_attr.first).c_str(),
                     Algorithm::attribute_str(target_attr.second).c_str());
@@ -552,8 +552,8 @@ AlgoChooser<Opr>::ExeContext::get_profile_result_from_cache(
     auto&& prof = rst.val();
     std::unordered_map<std::string, ImplAlgo> algo_map;
     for (auto i : get_all_candidates()) {
-        auto ins = algo_map.emplace(i.name.c_str(), i);
-        mgb_assert(ins.second, "duplicated algo name: %s", i.name.c_str());
+        auto ins = algo_map.emplace(i.desc.name.c_str(), i);
+        mgb_assert(ins.second, "duplicated algo name: %s", i.desc.name.c_str());
     }
 
     if (prof.empty())

src/opr/impl/search_policy/profiler.cpp

@@ -41,8 +41,11 @@ std::string serialize_policy(const megdnn::ExecutionPolicy& policy) {
     megdnn::Algorithm::serialize_write_pod(policy.algo.handle_type, ret);
     megdnn::Algorithm::serialize_write_pod(policy.algo.type, ret);
     uint32_t param_size = policy.algo.param.size();
+    uint32_t name_size = policy.algo.name.size();
     megdnn::Algorithm::serialize_write_pod<uint32_t>(param_size, ret);
+    megdnn::Algorithm::serialize_write_pod<uint32_t>(name_size, ret);
     ret += policy.algo.param;
+    ret += policy.algo.name;
 
     //! serialize sub_policy
     uint32_t size = policy.sub_policy.size();
@@ -64,11 +67,17 @@ megdnn::ExecutionPolicy deserialize_policy(const char* buf, uint32_t size,
     cb(ret.algo.type, uint32_t);
 
     uint32_t param_size = 0;
+    uint32_t name_size = 0;
     cb(param_size, uint32_t);
+    cb(name_size, uint32_t);
     if (param_size > 0) {
         ret.algo.param = std::string(buf + offset, param_size);
         offset += param_size;
     }
+    if (name_size > 0) {
+        ret.algo.name = std::string(buf + offset, name_size);
+        offset += name_size;
+    }
 
     uint32_t nr_policy = 0;
     cb(nr_policy, uint32_t);