PaddlePaddle · luotao1 · Apr 10, 2024 · Apr 10, 2024
diff --git a/paddle/cinn/ir/schedule/schedule_base.cc b/paddle/cinn/ir/schedule/schedule_base.cc
@@ -105,7 +105,7 @@ void ScheduleBase::Broadcast(const std::string& block_name,
   }
   std::vector<Expr> all_loops = this->GetLoops(block_name);
   if (axes[0] >= all_loops.size()) {
-    throw std::runtime_error("axes execeed loop size");
+    throw std::runtime_error("axes exceed loop size");
   }
 
   // Get Last loop
@@ -150,14 +150,14 @@ void ScheduleBase::Broadcast(const std::string& block_name,
     auto stride = Expr(1);
     auto in_offset = Expr(0);
 
-    std::set<int> brodacast_set(info.broadcast_axes.begin(),
+    std::set<int> broadcast_set(info.broadcast_axes.begin(),
                                 info.broadcast_axes.end());
     for (int i = all_loops.size() - 1; i >= 0; --i) {
       auto loop_temp = all_loops[i].As<ir::For>();
       offset = offset + loop_temp->loop_var * stride;
 
       stride = stride * loop_temp->extent;
-      if (!brodacast_set.count(i)) {
+      if (!broadcast_set.count(i)) {
         in_offset = in_offset + loop_temp->loop_var * stride;
       }
     }

diff --git a/paddle/cinn/pybind/frontend.cc b/paddle/cinn/pybind/frontend.cc
@@ -937,7 +937,7 @@ void BindFrontend(pybind11::module *m) {
       .def("get_cinn_name",
            [](PaddleModelConvertor &self, const std::string &paddle_name) {
              CHECK(self.var_model_to_program_map().count(paddle_name))
-                 << "Cannot find variabel " << paddle_name
+                 << "Cannot find variable " << paddle_name
                  << " in CINN! Please check.";
              return self.var_model_to_program_map().at(paddle_name);
            });

diff --git a/paddle/fluid/distributed/fleet_executor/compute_interceptor.cc b/paddle/fluid/distributed/fleet_executor/compute_interceptor.cc
@@ -39,7 +39,7 @@ void ComputeInterceptor::PrepareDeps() {
     for (int64_t i = 0; i < node_->max_run_times(); ++i) {
       ready_size_map.emplace(i, 0);
     }
-    in_readys_.emplace(up.first, std::make_pair(up.second, ready_size_map));
+    in_readies_.emplace(up.first, std::make_pair(up.second, ready_size_map));
   }
   for (auto down : downstream) {
     out_buffs_.emplace(down.first, std::make_pair(down.second, 0));
@@ -106,11 +106,11 @@ InterceptorMessage ComputeInterceptor::PrepareVarsMsg() {
 }
 
 void ComputeInterceptor::IncreaseReady(int64_t up_id, int64_t scope_id) {
-  auto it = in_readys_.find(up_id);
+  auto it = in_readies_.find(up_id);
   PADDLE_ENFORCE_NE(it,
-                    in_readys_.end(),
+                    in_readies_.end(),
                     platform::errors::NotFound(
-                        "Cannot find upstream=%lld in in_readys.", up_id));
+                        "Cannot find upstream=%lld in in_readies.", up_id));
 
   auto max_ready_size = it->second.first;
   const auto& ready_scope_map = it->second.second;
@@ -171,7 +171,7 @@ bool ComputeInterceptor::IsInputReady() {
   for (int64_t i = start_micro_step; i < start_micro_step + num_micro_step;
        ++i) {
     bool flag = true;
-    for (auto& ins : in_readys_) {
+    for (auto& ins : in_readies_) {
       auto ready_size_map = ins.second.second;
       flag = flag && (ready_size_map.at(i) != 0);
     }
@@ -268,7 +268,7 @@ void ComputeInterceptor::SendDataReadyToDownStream() {
 }
 
 void ComputeInterceptor::ReplyCompletedToUpStream() {
-  for (auto& ins : in_readys_) {
+  for (auto& ins : in_readies_) {
     auto up_id = ins.first;
     auto ready_size = ins.second.second.at(cur_scope_id_);
     ready_size -= 1;

diff --git a/paddle/fluid/distributed/fleet_executor/compute_interceptor.h b/paddle/fluid/distributed/fleet_executor/compute_interceptor.h
@@ -41,7 +41,7 @@ class ComputeInterceptor : public Interceptor {
 
   // upstream_id-->(max_ready_size, scope-->ready_size)
   std::map<int64_t, std::pair<int64_t, std::map<int64_t, int64_t>>>
-      in_readys_{};
+      in_readies_{};
   // downstream_id-->(max_buffer_size, used_size)
   std::map<int64_t, std::pair<int64_t, int64_t>> out_buffs_{};
 

diff --git a/paddle/fluid/eager/auto_code_generator/CMakeLists.txt b/paddle/fluid/eager/auto_code_generator/CMakeLists.txt
@@ -1,6 +1,6 @@
 add_subdirectory(generator)
 
-set(EAGER_GENERETOR_DEPS
+set(EAGER_GENERATOR_DEPS
     ${GLOB_OP_LIB}
     ${GLOB_OPERATOR_DEPS}
     pybind
@@ -13,12 +13,12 @@ set(EAGER_GENERETOR_DEPS
     imperative_flag)
 
 if(WITH_CUSTOM_DEVICE)
-  set(EAGER_GENERETOR_DEPS ${EAGER_GENERETOR_DEPS}
+  set(EAGER_GENERATOR_DEPS ${EAGER_GENERATOR_DEPS}
                            custom_device_common_op_registry)
 endif()
 
 add_executable(eager_generator eager_generator.cc)
-target_link_libraries(eager_generator ${EAGER_GENERETOR_DEPS})
+target_link_libraries(eager_generator ${EAGER_GENERATOR_DEPS})
 
 get_property(os_dependency_modules GLOBAL PROPERTY OS_DEPENDENCY_MODULES)
 target_link_libraries(eager_generator ${os_dependency_modules})

diff --git a/paddle/fluid/eager/auto_code_generator/generator/eager_gen.py b/paddle/fluid/eager/auto_code_generator/generator/eager_gen.py
@@ -292,7 +292,7 @@ class {} : public egr::GradNodeBase {{
 
   // Forward API Call
 {}
-  // Log memory infomation
+  // Log memory information
 {}
   // Check NaN and Inf if needed
 {}
@@ -346,7 +346,7 @@ class {} : public egr::GradNodeBase {{
 {}
   // Forward API Call
 {}
-  // Log memory infomation
+  // Log memory information
 {}
   // Check NaN and Inf if needed
 {}
@@ -538,8 +538,8 @@ class {} : public egr::GradNodeBase {{
 """
 
 TYPE_PROMOTION_LOGIC_TEMPLATE = """   if (phi::NeedTypePromotion({x}.dtype(), {y}.dtype())) {{
-    VLOG(5) << "got different data type, run type protmotion automatically.";
-    LOG_FIRST_N(WARNING, 1) << "got different data type, run type protmotion automatically, this may cause data type been changed.";
+    VLOG(5) << "got different data type, run type promotion automatically.";
+    LOG_FIRST_N(WARNING, 1) << "got different data type, run type promotion automatically, this may cause data type been changed.";
     {op_name}
     auto promotion_type = phi::GetPromoteDtype(op_name, {x}.dtype(), {y}.dtype());
 

diff --git a/paddle/fluid/operators/controlflow/depend_op.cc b/paddle/fluid/operators/controlflow/depend_op.cc
@@ -51,7 +51,7 @@ class DependOp : public framework::OperatorBase {
     PADDLE_ENFORCE_EQ(x_name,
                       out_name,
                       platform::errors::PreconditionNotMet(
-                          "Input(X) and Output(Out) varibale should be the "
+                          "Input(X) and Output(Out) variable should be the "
                           "same, but got Input is %s and Output is %s.",
                           x_name,
                           out_name));

diff --git a/paddle/fluid/pir/dialect/operator/ir/ops.yaml b/paddle/fluid/pir/dialect/operator/ir/ops.yaml
@@ -1,7 +1,7 @@
 # The operators included in this file are:
 # 1) Operators defined only in PIR, dynamic graphs do not exist;
 # 2) The definitions of static graphs and dynamic graphs are inconsistent, but the final definition plan has not yet been clarified.
-# After the definition is clearly defined, migrate to paddle /fluid/pir/dialect/operator/ir/update_ops.yaml or paddle/phi/api/yaml/ops.yaml
+# After the definition is clearly defined, migrate to paddle/fluid/pir/dialect/operator/ir/update_ops.yaml or paddle/phi/api/yaml/ops.yaml
 
 - op : adadelta_
   args : (Tensor param, Tensor grad, Tensor avg_squared_grad, Tensor avg_squared_update, Tensor learning_rate, Tensor master_param, float rho, float epsilon, bool multi_precision)

diff --git a/paddle/phi/api/profiler/device_tracer.cc b/paddle/phi/api/profiler/device_tracer.cc
@@ -834,7 +834,7 @@ uint32_t GetCurSystemThreadId() {
   return id;
 }
 
-void RecoreCurThreadId(uint64_t id) {
+void RecordCurThreadId(uint64_t id) {
   std::lock_guard<std::mutex> lock(system_thread_id_map_mutex);
   auto gid = GetCurSystemThreadId();
   system_thread_id_map[gid] = id;

diff --git a/paddle/phi/api/profiler/device_tracer.h b/paddle/phi/api/profiler/device_tracer.h
@@ -162,5 +162,5 @@ void ClearCurBlock();
 int BlockDepth();
 
 // Set current thread id, so we can map the system thread id to thread id.
-void RecoreCurThreadId(uint64_t id);
+void RecordCurThreadId(uint64_t id);
 }  // namespace phi
diff --git a/paddle/phi/api/profiler/profiler_helper.h b/paddle/phi/api/profiler/profiler_helper.h
@@ -73,7 +73,7 @@ inline EventList<Event> &GetEventList() {
     ProfilerHelper::g_thread_id = ProfilerHelper::g_next_thread_id++;
     ProfilerHelper::g_all_event_lists.emplace_front(
         ProfilerHelper::g_event_list);
-    RecoreCurThreadId(ProfilerHelper::g_thread_id);
+    RecordCurThreadId(ProfilerHelper::g_thread_id);
   }
   return *ProfilerHelper::g_event_list;
 }

diff --git a/paddle/pir/src/dialect/shape/utils/dim_expr_util.cc b/paddle/pir/src/dialect/shape/utils/dim_expr_util.cc
@@ -589,12 +589,12 @@ ConstRational MulConstRational(const ConstRational& lhs,
   const auto [lhs_num, lhs_dem] = lhs;
   const auto [rhs_num, rhs_dem] = rhs;
   // Crossing is correct.
-  const auto [simplifed_lhs_num, simplifed_rhs_dem] =
+  const auto [simplified_lhs_num, simplified_rhs_dem] =
       SimplifiedConstRational(lhs_num, rhs_dem);
-  const auto [simplifed_rhs_num, simplifed_lhs_dem] =
+  const auto [simplified_rhs_num, simplified_lhs_dem] =
       SimplifiedConstRational(rhs_num, lhs_dem);
-  return ConstRational{simplifed_lhs_num * simplifed_rhs_num,
-                       simplifed_lhs_dem * simplifed_rhs_dem};
+  return ConstRational{simplified_lhs_num * simplified_rhs_num,
+                       simplified_lhs_dem * simplified_rhs_dem};
 }
 
 template <>

diff --git a/python/paddle/incubate/distributed/fleet/parameter_server/distribute_transpiler/__init__.py b/python/paddle/incubate/distributed/fleet/parameter_server/distribute_transpiler/__init__.py
@@ -144,7 +144,7 @@ def get_sparse_attrs():
 
                 if len(dist_varnames) != 0:
                     raise ValueError(
-                        "GeoStrategy can not support large scale embeding now, please use paddle.static.nn.embedding"
+                        "GeoStrategy can not support large scale embedding now, please use paddle.static.nn.embedding"
                     )
 
                 init_attrs = []

diff --git a/python/paddle/incubate/distributed/utils/io/dist_save.py b/python/paddle/incubate/distributed/utils/io/dist_save.py
@@ -156,7 +156,7 @@ def save(state_dict, path, **configs):
             paddle.save(gathered_state_dict, path, **configs)
     except:
         raise RuntimeError(
-            f'''Saving failed. Follwing are some suggestions:
+            f'''Saving failed. Following are some suggestions:
     1) pass the param max_grouped_size to turn the grouped size smaller (current value of max_grouped_size is {max_size})
     2) if sharding stage is 1, use paddle.save rather than paddle.distributed.save
     3) Concat the developers

diff --git a/python/paddle/incubate/optimizer/pipeline.py b/python/paddle/incubate/optimizer/pipeline.py
@@ -481,13 +481,13 @@ def _get_op_device_attr(self, op):
         if device:
             assert device[0:3] == 'gpu', (
                 "Now, only gpu devices are "
-                "supported in pipeline parallemism."
+                "supported in pipeline parallelism."
             )
         return device
 
     def _add_op_device_attr_for_op(self, op, idx, block):
         """
-        Add op_device attrribute for ops that have not that attribute set.
+        Add op_device attribute for ops that have not that attribute set.
         We use "gpu:all" to represent the op should be put on all
         sub-programs, such as lr-related ops. Note that: "gpu:all"
         is only used by pipeline as an indicator.