fix(mgb): fix attribute check compatibility when profiling and read_from_cache in fast run

GitOrigin-RevId: b865d467b0

src/opr/impl/search_policy/algo_chooser.cpp

@@ -299,18 +299,13 @@ void AlgoChooser<Opr>::profile(ExeContext& ctx,
     RealTimer timer;
     for (auto algo : ctx.get_all_candidates()) {
         Maybe<AlgoChooserProfileCache::ResultEntry> cur_rst;
-        std::string msg = ssprintf("profiling %s algorithm %s %s",
-                                   ctx.mgb_opr()->dyn_typeinfo()->name,
-                                   algo.desc.name.c_str(), layouts_str.c_str());
+
         ImplExecutionPolicy policy;
         policy.algo = algo.desc;
-        ctx.construct_execution_policy(selected_strategy, policy);
-        if (ctx.get_workspace_size_bytes(policy) >= workspace_limit) {
-            continue;
-        }
+
+        //! check negative attribute : skip negative attribute
         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))) {
+        if (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 "
@@ -322,6 +317,15 @@ void AlgoChooser<Opr>::profile(ExeContext& ctx,
             continue;
         }
 
+        //! check workspace limit
+        ctx.construct_execution_policy(selected_strategy, policy);
+        if (ctx.get_workspace_size_bytes(policy) >= workspace_limit) {
+            continue;
+        }
+
+        std::string msg = ssprintf("profiling %s algorithm %s %s",
+                                   ctx.mgb_opr()->dyn_typeinfo()->name,
+                                   algo.desc.name.c_str(), layouts_str.c_str());
         timer.reset();
         MGB_TRY { cur_rst = ctx.profile_single_algo(policy, cur_timeout); }
         MGB_CATCH(std::exception & exc, {
@@ -350,11 +354,11 @@ void AlgoChooser<Opr>::profile(ExeContext& ctx,
         prof_rst.push_back(rst);
     }
     std::string msg = ssprintf(
-            "no usable %s algorithm %s with attribute(%s) and without "
-            "attribute(%s)",
+            "no usable %s algorithm %s without attribute(%s) or could not meet "
+            "workspace limite requirement(%zu)",
             ctx.mgb_opr()->dyn_typeinfo()->name, layouts_str.c_str(),
-            Algorithm::attribute_str(target_attr.first).c_str(),
-            Algorithm::attribute_str(target_attr.second).c_str());
+            Algorithm::attribute_str(target_attr.second).c_str(),
+            workspace_limit);
     mgb_assert(!prof_rst.empty(), "%s", msg.c_str());
 
     FixedTensorLayouts origin_layouts = ctx.layouts();
@@ -544,6 +548,7 @@ AlgoChooser<Opr>::ExeContext::get_profile_result_from_cache(
         return {};
 
     auto target_attr = extract_algo_attribute(selected_strategy);
+    bool skip_by_negative = false;
     for (auto&& i : prof) {
         auto attr_of_algo =
                 static_cast<megdnn::Algorithm::Attribute>(i.attribute);
@@ -552,26 +557,36 @@ AlgoChooser<Opr>::ExeContext::get_profile_result_from_cache(
                  (attr_of_algo & target_attr.first));
         bool contain_attr_any_negative =
                 static_cast<bool>(attr_of_algo & target_attr.second);
-        if (contain_attr_all_positive && !contain_attr_any_negative) {
-            auto iter = algo_map.find(i.algo);
-            mgb_assert(iter != algo_map.end(),
-                       "algorithm %s exists in "
-                       "profiling result but not in algo_map; please "
-                       "report this "
-                       "bug; opr: %s{%s}, layouts: %s ",
-                       i.algo.c_str(), m_base_mgb_opr->cname(),
-                       m_base_mgb_opr->dyn_typeinfo()->name,
-                       format_fixlayouts<Opr>(m_layouts, arity_in, arity_out)
-                               .c_str());
-            return iter->second;
+        if (contain_attr_all_positive) {
+            if (!contain_attr_any_negative) {
+                auto iter = algo_map.find(i.algo);
+                mgb_assert(
+                        iter != algo_map.end(),
+                        "algorithm %s exists in profiling result but not in "
+                        "algo_map; please report this bug; opr: %s{%s}, "
+                        "layouts: %s ",
+                        i.algo.c_str(), m_base_mgb_opr->cname(),
+                        m_base_mgb_opr->dyn_typeinfo()->name,
+                        format_fixlayouts<Opr>(m_layouts, arity_in, arity_out)
+                                .c_str());
+                return iter->second;
+            } else {
+                skip_by_negative = true;
+            }
         }
     }
 
-    mgb_log_error(
-            "algos read from cache could not satisfy attribute with %s and "
-            "without %s",
-            Algorithm::attribute_str(target_attr.first).c_str(),
-            Algorithm::attribute_str(target_attr.second).c_str());
+    if (skip_by_negative) {
+        mgb_log_error(
+                "No usable algo. Only navie algos are available, but negative "
+                "stategy is %s.",
+                Algorithm::attribute_str(target_attr.second).c_str());
+    } else {
+        mgb_log_error(
+                "No usable algo. algos read from cache could not satisfy "
+                "attribute with %s",
+                Algorithm::attribute_str(target_attr.first).c_str());
+    }
 
     mgb_trap();
     MIDOUT_E

src/opr/test/dnn/convolution.cpp

@@ -356,14 +356,7 @@ TEST(TestOprDNN, ConvBiasExePolicy) {
     auto orig_impl = PersistentCache::set_impl(
             std::make_shared<InMemoryPersistentCache>());
 
-#if MGB_ENABLE_FASTRUN
-    for (auto strategy :
-         SmallVector<S>{S::PROFILE, S::HEURISTIC, S::PROFILE | S::REPRODUCIBLE,
-                        S::PROFILE | S::HEURISTIC}) {
-#else
-    for (auto strategy :
-         SmallVector<S>{S : HEURISTIC, S::PROFILE | S::HEURISTIC}) {
-#endif
+    auto run = [&](S strategy) {
         auto graph = ComputingGraph::make();
         HostTensorGenerator<> gen;
 
@@ -378,10 +371,8 @@ TEST(TestOprDNN, ConvBiasExePolicy) {
         auto x = mkvar("x", {20, 50, 50, 16}, dtype::QuantizedS8(2.5f));
         auto w = mkvar("w", {24, 3, 3, 16}, dtype::QuantizedS8(2.5f));
         auto bias = mkvar("bias", {1, 1, 1, 24}, dtype::QuantizedS32(6.25f));
-
         param.nonlineMode = Param::NonlineMode::RELU;
         param.format = Param::Format::NHWC;
-
         Policy policy;
         policy.strategy = strategy;
 
@@ -391,10 +382,21 @@ TEST(TestOprDNN, ConvBiasExePolicy) {
         HostTensorND host_y;
         auto func = graph->compile({make_callback_copy(conv_bias, host_y)});
         func->execute();
-
         //! set a new cache
         PersistentCache::set_impl(std::make_shared<InMemoryPersistentCache>());
+    };
+
+#if MGB_ENABLE_FASTRUN
+    for (auto strategy :
+         SmallVector<S>{S::PROFILE, S::HEURISTIC, S::PROFILE | S::REPRODUCIBLE,
+                        S::PROFILE | S::HEURISTIC}) {
+#else
+    for (auto strategy :
+         SmallVector<S>{S : HEURISTIC, S::PROFILE | S::HEURISTIC}) {
+#endif
+        run(strategy);
     }
+    ASSERT_THROW(run(S::OPTIMIZED | S::PROFILE), MegBrainError);
     PersistentCache::set_impl(orig_impl);
 }