fix(mgb): fix spell error

GitOrigin-RevId: acae00e0a54daf5a18a775bcf8bb5d2469f337cb

dnn/src/x86/conv_bias/opr_impl.cpp

@@ -185,7 +185,7 @@ SmallVector<AlgoCategory> ConvBiasImpl::suggest_algo_category_order(
     }
     //! conv1x1
     im2col_prefer |= (FH == 1 && FW == 1);
-    //! x86 8x8x16 not optmized, so it will use fallback im2col+matmul
+    //! x86 8x8x16 not optimized, so it will use fallback im2col+matmul
     if (param.deduce_algo_data_type() == AlgoDataType::INT8X8X16) {
         im2col_prefer = true;
     }

imperative/python/megengine/functional/debug_param.py

@@ -40,7 +40,7 @@ def set_execution_strategy(option):
         * HEURISTIC uses heuristic to choose the fastest algorithm.
         * PROFILE runs possible algorithms on real device to find the best one.
         * REPRODUCIBLE uses the algorithms that is reproducible.
-        * OPTMIZED uses the algorithms that is optimized.
+        * OPTIMIZED uses the algorithms that is optimized.
 
         The default strategy is HEURISTIC, this options can be combined to
         form a combination option, e.g. PROFILE | REPRODUCIBLE

imperative/python/src/graph_rt.cpp

@@ -271,7 +271,7 @@ void init_graph_rt(py::module m) {
                 {"HEURISTIC", [&]() { stg = _AlgoStrategy::HEURISTIC; }},
                 {"PROFILE", [&]() { stg = _AlgoStrategy::PROFILE; }},
                 {"REPRODUCIBLE", [&]() { stg = _AlgoStrategy::REPRODUCIBLE; }},
-                {"OPTMIZED", [&]() { stg = _AlgoStrategy::OPTMIZED; }},
+                {"OPTIMIZED", [&]() { stg = _AlgoStrategy::OPTIMIZED; }},
         };
         auto it = m.find(strategy);
         mgb_assert(it != m.end(), "Invalid strategy string!");

sdk/load-and-run/src/mgblar.cpp

@@ -709,7 +709,7 @@ void run_test_st(Args &env) {
             strategy = S::PROFILE;
         }
     } else if (env.use_fast_run) {
-        strategy = S::PROFILE | S::OPTMIZED;
+        strategy = S::PROFILE | S::OPTIMIZED;
     } else if (env.reproducible) {
         strategy = S::HEURISTIC | S::REPRODUCIBLE;
     }

src/gopt/test/inference.cpp

@@ -1756,8 +1756,8 @@ TEST(TestGoptInference, FastProfileCache) {
     using S = opr::Convolution::ExecutionPolicy::Strategy;
     ASSERT_EQ(S::HEURISTIC, conv.execution_policy_transient().strategy);
     gopt::modify_opr_algo_strategy_inplace({z + 2.3f},
-                                           S::PROFILE | S::OPTMIZED);
-    ASSERT_EQ(S::PROFILE | S::OPTMIZED, conv.execution_policy().strategy);
+                                           S::PROFILE | S::OPTIMIZED);
+    ASSERT_EQ(S::PROFILE | S::OPTIMIZED, conv.execution_policy().strategy);
 }
 
 TEST(TestGoptInference, AlgoWorkspaceLimit) {

src/opr/impl/search_policy/algo_chooser.cpp

@@ -287,7 +287,7 @@ extract_algo_attribute_from_execution_strategy(
     if (strategy & ExecutionStrategy::REPRODUCIBLE) {
         ret.first |= AlgoAttribute::REPRODUCIBLE;
     }
-    if (strategy & ExecutionStrategy::OPTMIZED) {
+    if (strategy & ExecutionStrategy::OPTIMIZED) {
         ret.second |= AlgoAttribute::NAIVE;
     }
     return ret;

src/opr/test/dnn/convolution.cpp

@@ -357,7 +357,7 @@ TEST(TestOprDNN, ConvBiasExePolicy) {
 #if MGB_ENABLE_FASTRUN
     for (auto strategy :
          SmallVector<S>{S::PROFILE, S::HEURISTIC, S::PROFILE | S::REPRODUCIBLE,
-          S::PROFILE | S::HEURISTIC, S::PROFILE | S::OPTMIZED}) {
+          S::PROFILE | S::HEURISTIC, S::PROFILE | S::OPTIMIZED}) {
 #else
     for (auto strategy :
          SmallVector<S>{S : HEURISTIC, S::PROFILE | S::HEURISTIC}) {
@@ -444,7 +444,7 @@ TEST(TestOprDNN, ConvolutionExePolicy) {
 #if MGB_ENABLE_FASTRUN
     for (auto strategy :
          SmallVector<S>{S::PROFILE, S::HEURISTIC, S::PROFILE | S::REPRODUCIBLE,
-          S::PROFILE | S::HEURISTIC, S::PROFILE | S::OPTMIZED}) {
+          S::PROFILE | S::HEURISTIC, S::PROFILE | S::OPTIMIZED}) {
 #else
     for (auto strategy :
          SmallVector<S>{S : HEURISTIC, S::PROFILE | S::HEURISTIC}) {
@@ -1717,7 +1717,7 @@ TEST(TestOprDNN, LocalShareForwardExecPolicy) {
 #if MGB_ENABLE_FASTRUN
     for (auto strategy :
          SmallVector<S>{S::PROFILE, S::HEURISTIC, S::PROFILE | S::REPRODUCIBLE,
-          S::PROFILE | S::HEURISTIC, S::PROFILE | S::OPTMIZED}) {
+          S::PROFILE | S::HEURISTIC, S::PROFILE | S::OPTIMIZED}) {
 #else
     for (auto strategy :
          SmallVector<S>{S : HEURISTIC, S::PROFILE | S::HEURISTIC}) {
@@ -1828,7 +1828,7 @@ TEST(TestOprDNN, DeformableConvForward) {
 #if MGB_ENABLE_FASTRUN
     for (auto strategy :
          SmallVector<S>{S::PROFILE, S::HEURISTIC, S::PROFILE | S::REPRODUCIBLE,
-          S::PROFILE | S::HEURISTIC, S::PROFILE | S::OPTMIZED}) {
+          S::PROFILE | S::HEURISTIC, S::PROFILE | S::OPTIMIZED}) {
 #else
     for (auto strategy :
          SmallVector<S>{S : HEURISTIC, S::PROFILE | S::HEURISTIC}) {
@@ -1997,7 +1997,7 @@ TEST(TestOprDNN, BatchConvBiasForward) {
 #if MGB_ENABLE_FASTRUN
     for (auto strategy :
          SmallVector<S>{S::PROFILE, S::HEURISTIC, S::PROFILE | S::REPRODUCIBLE,
-          S::PROFILE | S::HEURISTIC, S::PROFILE | S::OPTMIZED}) {
+          S::PROFILE | S::HEURISTIC, S::PROFILE | S::OPTIMIZED}) {
 #else
     for (auto strategy :
          SmallVector<S>{S : HEURISTIC, S::PROFILE | S::HEURISTIC}) {

tools/param_defs/mgb_opr_param_defs.py

@@ -41,12 +41,13 @@ pdef('PersistentOutputStorage').add_fields(
           Doc('REPRODUCIBLE',
               'when profile or heuristic algo selection it require the algos'
               'must be reproducible'),
-          Doc('OPTMIZED',
+          Doc('OPTIMIZED',
               'profile require algos are optmized to achieve fast-profile'),
           default=('HEURISTIC',),
           member_alias=[(('HEURISTIC', 'REPRODUCIBLE'), 'HEURISTIC_REPRODUCIBLE'),
                         (('PROFILE', 'REPRODUCIBLE'), 'PROFILE_REPRODUCIBLE'),
                         (('PROFILE', 'HEURISTIC'), 'PROFILE_HEURISTIC'),
+                        (('OPTIMIZED',), 'OPTMIZED'),
                         ]).
  add_fields('uint64',
             Doc('workspace_limit', 'workspace limit in bytes'),