Refine error msg in paddle/fluid/framework/details [part 1] (#25631)

* refine error msg in var_handle.h, test=develop

* refine all_reduce_op_handle

* fix some error msg

* refine variable_visitor

* refine threaded_ssa_graph_executor

* refine inplace related files

* refine executor related files

* refine fetch_op_handle.cc

* fix bug

* follow comments

paddle/fluid/framework/details/all_reduce_op_handle.cc

@@ -12,7 +12,9 @@
 // See the License for the specific language governing permissions and
 // limitations under the License.
 #include "paddle/fluid/framework/details/all_reduce_op_handle.h"
+
 #include <algorithm>
+
 #include "paddle/fluid/framework/details/container_cast.h"
 #include "paddle/fluid/framework/details/reduce_and_gather.h"
 #include "paddle/fluid/framework/details/variable_visitor.h"
@@ -34,14 +36,24 @@ AllReduceOpHandle::AllReduceOpHandle(ir::Node *node,
                                      const std::vector<platform::Place> &places,
                                      const platform::NCCLCommunicator *ctxs)
     : NCCLOpHandleBase(node, places, ctxs), local_scopes_(local_scopes) {
-  PADDLE_ENFORCE_EQ(places_.size(), local_scopes_.size());
+  PADDLE_ENFORCE_EQ(places_.size(), local_scopes_.size(),
+                    platform::errors::InvalidArgument(
+                        "The number of places and the number of local scopes "
+                        "should be equal, but got number of places is %d and "
+                        "number of local scopes is %d.",
+                        places_.size(), local_scopes_.size()));
 }
 #else
 AllReduceOpHandle::AllReduceOpHandle(ir::Node *node,
                                      const std::vector<Scope *> &local_scopes,
                                      const std::vector<platform::Place> &places)
     : OpHandleBase(node), local_scopes_(local_scopes), places_(places) {
-  PADDLE_ENFORCE_EQ(places_.size(), local_scopes_.size());
+  PADDLE_ENFORCE_EQ(places_.size(), local_scopes_.size(),
+                    platform::errors::InvalidArgument(
+                        "The number of places and the number of local scopes "
+                        "should be equal, but got number of places is %d and "
+                        "number of local scopes is %d.",
+                        places_.size(), local_scopes_.size()));
 }
 #endif
 
@@ -60,13 +72,25 @@ void AllReduceOpHandle::AllReduceImpl(
     const std::vector<VarHandle *> &in_var_handles,
     const std::vector<VarHandle *> &out_var_handles) {
   size_t num_places = places_.size();
-  PADDLE_ENFORCE_EQ(
-      in_var_handles.size(), num_places,
-      "The NoDummyInputSize should be equal to the number of places.");
+  PADDLE_ENFORCE_EQ(in_var_handles.size(), num_places,
+                    platform::errors::InvalidArgument(
+                        "The NoDummyInputSize should be equal "
+                        "to the number of places, but got NoDummyInputSize is "
+                        "%d and the number of place is %d.",
+                        in_var_handles.size(), num_places));
   PADDLE_ENFORCE_EQ(
       in_var_handles.size(), out_var_handles.size(),
-      "The NoDummyInputSize and NoDummyOutputSize should be equal.");
-  PADDLE_ENFORCE_EQ(local_exec_scopes_.size(), num_places);
+      platform::errors::InvalidArgument(
+          "The NoDummyInputSize and NoDummyOutputSize should be "
+          "equal, but got NoDummyInputSize is %d and NoDummyOutputSize is %d.",
+          in_var_handles.size(), out_var_handles.size()));
+  PADDLE_ENFORCE_EQ(
+      local_exec_scopes_.size(), num_places,
+      platform::errors::InvalidArgument(
+          "The number of local scopes should be equal "
+          "to the number of places, but got the number of local scopes is "
+          "%d and the number of place is %d.",
+          in_var_handles.size(), num_places));
 
   std::vector<const void *> lod_tensor_data;
   std::vector<platform::Place> places;
@@ -78,23 +102,36 @@ void AllReduceOpHandle::AllReduceImpl(
   for (size_t i = 0; i < local_exec_scopes_.size(); ++i) {
     auto &local_scope = local_exec_scopes_[i];
     auto var = local_scope->FindVar(in_var_handles[i]->name());
-    PADDLE_ENFORCE_NOT_NULL(var, "%s is not found int scope.",
-                            in_var_handles[i]->name());
+    PADDLE_ENFORCE_NOT_NULL(var, platform::errors::NotFound(
+                                     "Variable %s is not found in local scope.",
+                                     in_var_handles[i]->name()));
     auto &lod_tensor = var->Get<LoDTensor>();
 
     if (i == 0) {
       numel = static_cast<int64_t>(lod_tensor.numel());
       // only enforce place0, we will enforce other palce numel == place0 numel
       PADDLE_ENFORCE_GT(
-          numel, 0, platform::errors::InvalidArgument(
-                        "The numel of tensos=[%s] must > 0. But now numel=[%d]",
-                        in_var_handles[i]->name(), numel));
+          numel, 0,
+          platform::errors::PreconditionNotMet(
+              "The numel of tensor %s should be > 0, but got numel is %d.",
+              in_var_handles[i]->name(), numel));
       dtype = lod_tensor.type();
       is_gpu_place = platform::is_gpu_place(lod_tensor.place());
     }
-    PADDLE_ENFORCE_EQ(numel, static_cast<int64_t>(lod_tensor.numel()));
-    PADDLE_ENFORCE_EQ(dtype, lod_tensor.type());
-    PADDLE_ENFORCE_EQ(is_gpu_place, platform::is_gpu_place(lod_tensor.place()));
+    PADDLE_ENFORCE_EQ(
+        numel, static_cast<int64_t>(lod_tensor.numel()),
+        platform::errors::PreconditionNotMet(
+            "The size of tensors of the same variable in different local "
+            "scopes should be equal."));
+    PADDLE_ENFORCE_EQ(
+        dtype, lod_tensor.type(),
+        platform::errors::PreconditionNotMet(
+            "The dtype of tensors of the same variable in different local "
+            "scopes should be equal."));
+    PADDLE_ENFORCE_EQ(is_gpu_place, platform::is_gpu_place(lod_tensor.place()),
+                      platform::errors::PreconditionNotMet(
+                          "The place type of tensors of the same variable "
+                          "in different local scopes should be equal."));
 
     lod_tensor_data.emplace_back(lod_tensor.data<void>());
     places.emplace_back(lod_tensor.place());
@@ -102,8 +139,12 @@ void AllReduceOpHandle::AllReduceImpl(
     VLOG(10) << "place:" << i << ", input_name:" << in_var_handles[i]->name()
              << ", out_name:" << out_var_handles[i]->name();
 
-    PADDLE_ENFORCE_EQ(in_var_handles[i]->name(), out_var_handles[i]->name(),
-                      "The name of input and output should be equal.");
+    PADDLE_ENFORCE_EQ(
+        in_var_handles[i]->name(), out_var_handles[i]->name(),
+        platform::errors::InvalidArgument(
+            "The name of input and output of all_reduce op should be equal, "
+            "but got input is %s and output is %s.",
+            in_var_handles[i]->name(), out_var_handles[i]->name()));
   }
 
   std::vector<std::string> grad_var_names;
@@ -122,7 +163,9 @@ void AllReduceOpHandle::AllReduceFunc(
     const std::vector<std::string> &out_var_names) {
   if (is_gpu_place(places[0])) {
 #if defined(PADDLE_WITH_NCCL)
-    PADDLE_ENFORCE_NOT_NULL(nccl_ctxs_, "nccl_ctxs should not be nullptr.");
+    PADDLE_ENFORCE_NOT_NULL(nccl_ctxs_,
+                            platform::errors::InvalidArgument(
+                                "The nccl context should not be NULL."));
     ncclDataType_t nccl_dtype = platform::ToNCCLDataType(dtype);
     std::vector<std::function<void()>> all_reduce_calls;
     for (size_t i = 0; i < local_exec_scopes_.size(); ++i) {
@@ -134,7 +177,8 @@ void AllReduceOpHandle::AllReduceFunc(
     }
     NCCLAllReduceFunc(all_reduce_calls);
 #else
-    PADDLE_THROW("Not compiled with CUDA.");
+    PADDLE_THROW(
+        platform::errors::PreconditionNotMet("Not compiled with CUDA."));
 #endif
   } else {  // Special handle CPU only Operator's gradient. Like CRF
     auto &trg = *local_exec_scopes_[0]

paddle/fluid/framework/details/async_ssa_graph_executor.cc

@@ -89,8 +89,19 @@ AsyncSSAGraphExecutor::AsyncSSAGraphExecutor(
       places_(std::move(places)),
       graphs_(std::move(graphs)) {
   VLOG(3) << "build AsyncSSAGraphExecutor";
-  PADDLE_ENFORCE_EQ(places_.size(), local_scopes_.size());
-  PADDLE_ENFORCE_EQ(local_scopes_.size(), local_exec_scopes_.size());
+  PADDLE_ENFORCE_EQ(places_.size(), local_scopes_.size(),
+                    platform::errors::InvalidArgument(
+                        "The number of places and the number of local scopes "
+                        "should be equal, but got number of places is %d and "
+                        "number of local scopes is %d.",
+                        places_.size(), local_scopes_.size()));
+  PADDLE_ENFORCE_EQ(
+      local_scopes_.size(), local_exec_scopes_.size(),
+      platform::errors::InvalidArgument(
+          "The number of local scopes and the number of local execution scopes "
+          "should be equal, but got number of local scopes is %d and "
+          "number of local execution scopes is %d.",
+          local_scopes_.size(), local_exec_scopes_.size()));
 
   // set the correct size of thread pool to each device.
   strategy_.num_threads_ = strategy_.num_threads_ < places_.size()

paddle/fluid/framework/details/fast_threaded_ssa_graph_executor.cc

@@ -12,12 +12,14 @@
 // See the License for the specific language governing permissions and
 // limitations under the License.
 #include "paddle/fluid/framework/details/fast_threaded_ssa_graph_executor.h"
+
 #include <deque>
 #include <memory>
 #include <string>
 #include <unordered_map>
 #include <unordered_set>
 #include <vector>
+
 #include "paddle/fluid/framework/details/computation_op_handle.h"
 #include "paddle/fluid/framework/details/fetch_async_op_handle.h"
 #include "paddle/fluid/framework/details/multi_devices_helper.h"
@@ -48,7 +50,9 @@ FastThreadedSSAGraphExecutor::FastThreadedSSAGraphExecutor(
       bootstrap_ops_.emplace_back(op);
     }
   }
-  PADDLE_ENFORCE_GT(op_deps_.size(), 0, "The graph doesn't have operators.");
+  PADDLE_ENFORCE_GT(op_deps_.size(), 0,
+                    platform::errors::PreconditionNotMet(
+                        "The graph doesn't have operators."));
   PrepareAtomicOpDeps();
 }
 

paddle/fluid/framework/details/fetch_op_handle.cc

@@ -13,9 +13,11 @@
 // limitations under the License.
 
 #include "paddle/fluid/framework/details/fetch_op_handle.h"
+
 #include <string>
 #include <utility>
 #include <vector>
+
 #include "paddle/fluid/platform/profiler.h"
 
 namespace paddle {
@@ -138,8 +140,10 @@ void FetchOpHandle::RunImpl() {
     auto *var_handle = static_cast<VarHandle *>(inputs_[i]);
     auto &scope = scopes.at(var_handle->scope_idx());
     auto *var = scope->FindVar(var_handle->name());
-    PADDLE_ENFORCE_NOT_NULL(var, "Cannot find variable %s in execution scope",
-                            var_handle->name());
+    PADDLE_ENFORCE_NOT_NULL(
+        var,
+        platform::errors::NotFound(
+            "Cannot find variable %s in execution scope.", var_handle->name()));
 
     if (var->IsType<LoDTensor>()) {
       auto &t = var->Get<framework::LoDTensor>();

paddle/fluid/framework/details/parallel_ssa_graph_executor.cc

@@ -13,9 +13,11 @@
 // limitations under the License.
 
 #include "paddle/fluid/framework/details/parallel_ssa_graph_executor.h"
+
 #include <algorithm>
 #include <memory>
 #include <utility>
+
 #include "paddle/fluid/framework/ir/graph_helper.h"
 
 namespace paddle {
@@ -104,7 +106,12 @@ ParallelSSAGraphExecutor::ParallelSSAGraphExecutor(
       places_(places),
       graphs_(std::move(graphs)),
       feed_status_(places.size(), FeedStatus::kNone) {
-  PADDLE_ENFORCE_EQ(places_.size(), local_scopes_.size());
+  PADDLE_ENFORCE_EQ(places_.size(), local_scopes_.size(),
+                    platform::errors::InvalidArgument(
+                        "The number of places and the number of local scopes "
+                        "should be equal, but got number of places is %d and "
+                        "number of local scopes is %d.",
+                        places_.size(), local_scopes_.size()));
 
   PADDLE_ENFORCE_EQ(places_.size(), graphs_.size(),
                     platform::errors::InvalidArgument(

paddle/fluid/framework/details/scope_buffered_ssa_graph_executor.cc

@@ -13,10 +13,12 @@
 // limitations under the License.
 
 #include "paddle/fluid/framework/details/scope_buffered_ssa_graph_executor.h"
+
 #include <stdexcept>
 #include <string>
 #include <utility>
 #include <vector>
+
 #include "paddle/fluid/framework/details/multi_devices_helper.h"
 #include "paddle/fluid/framework/op_registry.h"
 #include "paddle/fluid/framework/variable_helper.h"
@@ -37,7 +39,13 @@ ScopeBufferedSSAGraphExecutor::ScopeBufferedSSAGraphExecutor(
       var_infos_(std::move(var_infos)),
       places_(std::move(places)),
       scope_monitor_(places_, local_exec_scopes_) {
-  PADDLE_ENFORCE_EQ(local_scopes_.size(), local_exec_scopes_.size());
+  PADDLE_ENFORCE_EQ(
+      local_scopes_.size(), local_exec_scopes_.size(),
+      platform::errors::InvalidArgument(
+          "The number of local scopes and the number of local execution scopes "
+          "should be equal, but got number of local scopes is %d and "
+          "number of local execution scopes is %d.",
+          local_scopes_.size(), local_exec_scopes_.size()));
   PrepareLocalExeScopes();
 }
 

paddle/fluid/framework/details/share_tensor_buffer_functor.cc

@@ -13,9 +13,11 @@
 // limitations under the License.
 
 #include "paddle/fluid/framework/details/share_tensor_buffer_functor.h"
+
 #include <string>
 #include <unordered_map>
 #include <unordered_set>
+
 #include "paddle/fluid/framework/lod_tensor.h"
 #include "paddle/fluid/framework/selected_rows.h"
 #include "paddle/fluid/platform/enforce.h"
@@ -29,7 +31,8 @@ static inline const Tensor &GetTensorFromVar(const Variable *var) {
   if (var->IsType<LoDTensor>()) {
     return var->Get<LoDTensor>();
   } else {
-    PADDLE_THROW("Variable must be type of LoDTensor");
+    PADDLE_THROW(platform::errors::InvalidArgument(
+        "Variable must be type of LoDTensor."));
   }
 }
 
@@ -37,7 +40,8 @@ static inline Tensor *GetMutableTensorFromVar(Variable *var) {
   if (var->IsType<LoDTensor>()) {
     return var->GetMutable<LoDTensor>();
   } else {
-    PADDLE_THROW("Variable must be type of LoDTensor");
+    PADDLE_THROW(platform::errors::InvalidArgument(
+        "Variable must be type of LoDTensor."));
   }
 }
 
@@ -50,7 +54,12 @@ ShareTensorBufferFunctor::ShareTensorBufferFunctor(
       op_type_(op_type),
       in_var_infos_(in_var_infos),
       out_var_names_(out_var_names) {
-  PADDLE_ENFORCE_EQ(in_var_infos_.size(), out_var_names_.size());
+  PADDLE_ENFORCE_EQ(in_var_infos_.size(), out_var_names_.size(),
+                    platform::errors::PreconditionNotMet(
+                        "The number of input variables and output variables "
+                        "should be equal, but got number of input variables is "
+                        "%d and number of output variables is %d.",
+                        in_var_infos_.size(), out_var_names_.size()));
   for (size_t i = 0; i < in_var_infos_.size(); ++i) {
     AddReuseVarPair(in_var_infos_[i], out_var_names_[i]);
   }
@@ -67,32 +76,59 @@ ShareTensorBufferFunctor::ReusedVars() const {
 
 void ShareTensorBufferFunctor::AddReuseVarPair(
     const ir::MemOptVarInfo *in_var_info, const std::string &out_var_name) {
-  PADDLE_ENFORCE_NOT_NULL(in_var_info, "in_var_info cannot be nullptr");
+  PADDLE_ENFORCE_NOT_NULL(
+      in_var_info,
+      platform::errors::InvalidArgument(
+          "The input variables to be inplaced should not be NULL."));
   PADDLE_ENFORCE_NE(in_var_info->Name(), out_var_name,
-                    "in/out cannot have same name: %s", out_var_name);
+                    platform::errors::InvalidArgument(
+                        "The input variable and output variable to be inplaced "
+                        "cannot have the same name: %s.",
+                        out_var_name));
   in_var_infos_.emplace_back(in_var_info);
   out_var_names_.emplace_back(out_var_name);
 }
 
 void ShareTensorBufferFunctor::CallOnce() {
-  PADDLE_ENFORCE(in_out_vars_.empty(), "in_out_vars_ must be initialized here");
+  PADDLE_ENFORCE(in_out_vars_.empty(),
+                 platform::errors::InvalidArgument(
+                     "The input-output variable pairs to be "
+                     "inplaced should be initialized here."));
   for (size_t i = 0; i < in_var_infos_.size(); ++i) {
     auto *in_var = exec_scope_->FindVar(in_var_infos_[i]->Name());
     auto *out_var = exec_scope_->FindVar(out_var_names_[i]);
-    PADDLE_ENFORCE_NOT_NULL(in_var);
-    PADDLE_ENFORCE_NOT_NULL(out_var);
-    PADDLE_ENFORCE_NE(in_var, out_var);
+    PADDLE_ENFORCE_NOT_NULL(
+        in_var, platform::errors::NotFound(
+                    "The input variable(%s)to be inplaced should not be NULL.",
+                    in_var_infos_[i]->Name()));
+    PADDLE_ENFORCE_NOT_NULL(
+        out_var,
+        platform::errors::NotFound(
+            "The output variable(%s) to be inplaced should not be NULL.",
+            out_var_names_[i]));
+    PADDLE_ENFORCE_NE(
+        in_var, out_var,
+        platform::errors::PreconditionNotMet(
+            "The input variable and output variable to be inplaced "
+            "cannot be the same variable(%s).",
+            out_var_names_[i]));
     in_out_vars_.emplace_back(in_var, out_var);
   }
 }
 
 void ShareTensorBufferFunctor::operator()(Scope *exec_scope) {
   if (!exec_scope_) {
-    PADDLE_ENFORCE_NOT_NULL(exec_scope);
+    PADDLE_ENFORCE_NOT_NULL(exec_scope,
+                            platform::errors::InvalidArgument(
+                                "The given execution scope should not be NULL "
+                                "if the cached scope is NULL."));
     exec_scope_ = exec_scope;
     CallOnce();
   } else {
-    PADDLE_ENFORCE(exec_scope_ == exec_scope, "Scope must be the same");
+    PADDLE_ENFORCE_EQ(exec_scope_, exec_scope,
+                      platform::errors::InvalidArgument(
+                          "The given execution scope and the cached execution "
+                          "scope should be the same."));
   }
 
   for (size_t i = 0; i < in_var_infos_.size(); ++i) {

paddle/fluid/framework/details/share_tensor_buffer_op_handle.cc

@@ -13,8 +13,10 @@
 // limitations under the License.
 
 #include "paddle/fluid/framework/details/share_tensor_buffer_op_handle.h"
+
 #include <string>
 #include <unordered_set>
+
 #include "paddle/fluid/framework/ir/memory_optimize_pass/memory_optimization_var_info.h"
 #include "paddle/fluid/framework/lod_tensor.h"
 #include "paddle/fluid/framework/scope.h"
@@ -32,17 +34,25 @@ ComputationOpHandle *GetUniquePendingComputationOpHandle(
     for (ir::Node *pending_op : out_var->outputs) {
       auto &op = pending_op->Wrapper<OpHandleBase>();
       auto *compute_op = dynamic_cast<ComputationOpHandle *>(&op);
-      PADDLE_ENFORCE_NOT_NULL(compute_op);
+      PADDLE_ENFORCE_NOT_NULL(
+          compute_op,
+          platform::errors::PreconditionNotMet(
+              "The pending OpHandle should be ComputationOpHandle."));
 
       if (result_op == nullptr) {
         result_op = compute_op;
       } else {
-        PADDLE_ENFORCE_EQ(result_op, compute_op);
+        PADDLE_ENFORCE_EQ(
+            result_op, compute_op,
+            platform::errors::PreconditionNotMet(
+                "The pending OpHandle should be the unique one."));
       }
     }
   }
 
-  PADDLE_ENFORCE_NOT_NULL(result_op);
+  PADDLE_ENFORCE_NOT_NULL(result_op,
+                          platform::errors::PreconditionNotMet(
+                              "The pending OpHandle should not be NULL."));
   return result_op;
 }
 

paddle/fluid/framework/details/ssa_graph_executor.cc

@@ -13,6 +13,7 @@
 // limitations under the License.
 
 #include "paddle/fluid/framework/details/ssa_graph_executor.h"
+
 #include "paddle/fluid/framework/details/fetch_async_op_handle.h"
 
 namespace paddle {
@@ -27,8 +28,9 @@ void ClearFetchOp(ir::Graph* graph, std::vector<OpHandleBase*>* fetch_ops) {
     PADDLE_ENFORCE_EQ(dynamic_cast<FetchOpHandle*>(op) != nullptr ||
                           dynamic_cast<FetchAsyncOpHandle*>(op) != nullptr,
                       true,
-                      "The input ops of ClearFetchOp function should be "
-                      "FetchOpHandle or FetchAsyncOpHandle.");
+                      platform::errors::PreconditionNotMet(
+                          "The input ops of ClearFetchOp function should be "
+                          "FetchOpHandle or FetchAsyncOpHandle."));
     for (auto& out_var : op->Node()->outputs) {
       graph->RemoveNode(out_var);
     }

paddle/fluid/framework/details/threaded_ssa_graph_executor.cc

@@ -13,6 +13,7 @@
 // limitations under the License.
 
 #include "paddle/fluid/framework/details/threaded_ssa_graph_executor.h"
+
 #include "paddle/fluid/framework/ir/graph_helper.h"
 #include "paddle/fluid/platform/profiler.h"
 
@@ -138,7 +139,10 @@ inline FetchResultType ThreadedSSAGraphExecutor::RunImpl(
         }
       }
     }
-    PADDLE_ENFORCE(ready_ops.empty());
+    PADDLE_ENFORCE_EQ(
+        ready_ops.empty(), true,
+        platform::errors::Fatal("After the execution of computation graph, "
+                                "there are unexecuted operators left."));
   }
 
   // Wait FetchOps.
@@ -165,9 +169,8 @@ void ThreadedSSAGraphExecutor::InsertFetchOps(
     FetchResultType *fetch_data, bool return_merged) {
   std::unordered_map<std::string, std::vector<VarHandleBase *>> fetched_vars;
   std::unordered_set<VarHandleBase *> local_ready_vars;
-  std::unordered_set<std::string> fetch_tensor_set(fetch_tensors.begin(),
-                                                   fetch_tensors.end());
-  for (auto &fetch_var_name : fetch_tensor_set) {
+
+  for (auto &fetch_var_name : fetch_tensors) {
     for (auto &var_map : graph_->Get<details::GraphVars>(details::kGraphVars)) {
       auto it = var_map.find(fetch_var_name);
       if (it != var_map.end()) {
@@ -231,7 +234,11 @@ void ThreadedSSAGraphExecutor::InsertFetchOps(
       ready_ops->insert(static_cast<OpHandleBase *>(op));
     }
   }
-  PADDLE_ENFORCE_EQ(local_ready_vars.size(), 0);
+  PADDLE_ENFORCE_EQ(
+      local_ready_vars.size(), 0,
+      platform::errors::Fatal(
+          "The number of ready variables should be 0, but got %d.",
+          local_ready_vars.size()));
 }
 
 void ThreadedSSAGraphExecutor::InsertPendingOp(
@@ -277,7 +284,9 @@ void ThreadedSSAGraphExecutor::PrepareOpDeps() {
     }
   }
   op_deps_->num_ops_ = ready_ops.size() + pending_ops.size();
-  PADDLE_ENFORCE_GT(op_deps_->num_ops_, 0, "The graph doesn't have operators.");
+  PADDLE_ENFORCE_GT(
+      op_deps_->num_ops_, 0,
+      platform::errors::InvalidArgument("The graph doesn't have operators."));
 
   for (auto ready_var : ready_vars) {
     pending_vars.erase(ready_var);

paddle/fluid/framework/details/threaded_ssa_graph_executor.h

@@ -14,6 +14,8 @@
 
 #pragma once
 
+#include <ThreadPool.h>  // ThreadPool in thrird party
+
 #include <deque>
 #include <functional>
 #include <list>
@@ -24,8 +26,6 @@
 #include <utility>
 #include <vector>
 
-#include <ThreadPool.h>  // ThreadPool in thrird party
-
 #include "paddle/fluid/framework/blocking_queue.h"
 #include "paddle/fluid/framework/details/exception_holder.h"
 #include "paddle/fluid/framework/details/execution_strategy.h"

paddle/fluid/framework/details/var_handle.h

@@ -54,8 +54,10 @@ struct VarHandleBase {
 
   void AddOutput(OpHandleBase* out, ir::Node* node) {
     if (pending_ops_.find(out) == pending_ops_.end()) {
-      PADDLE_ENFORCE(out != nullptr, "The output of %s should not be nullptr",
-                     this->Node()->Name());
+      PADDLE_ENFORCE_NOT_NULL(out,
+                              platform::errors::InvalidArgument(
+                                  "The output added to VarHandle %s is NULL.",
+                                  this->Node()->Name()));
       pending_ops_.insert(out);
       node_->outputs.push_back(node);
     }
@@ -120,7 +122,10 @@ struct VarHandle : public VarHandleBase {
   bool HasEvent() { return has_event_; }
 
   const cudaEvent_t& GetEvent() {
-    PADDLE_ENFORCE(HasEvent(), "The event is not set.");
+    PADDLE_ENFORCE_EQ(
+        HasEvent(), true,
+        platform::errors::PreconditionNotMet(
+            "The cuda event is not set, maybe InitCUDA() is not called."));
     return event_;
   }
 

paddle/fluid/framework/details/variable_visitor.cc

@@ -13,6 +13,7 @@
 // limitations under the License.
 
 #include "paddle/fluid/framework/details/variable_visitor.h"
+
 #include "paddle/fluid/framework/selected_rows.h"
 namespace paddle {
 namespace framework {
@@ -24,7 +25,9 @@ static void VisitVariable(Variable* var, Func* func) {
   } else if (var->IsType<SelectedRows>()) {
     (*func)(var->GetMutable<SelectedRows>());
   } else {
-    PADDLE_THROW("Not supported type %s", ToTypeName(var->Type()));
+    PADDLE_THROW(platform::errors::Unimplemented(
+        "VisitVariable is not supported for type %s.",
+        ToTypeName(var->Type())));
   }
 }
 
@@ -35,7 +38,8 @@ static void VisitVariable(const Variable& var, Func* func) {
   } else if (var.IsType<SelectedRows>()) {
     (*func)(var.Get<SelectedRows>());
   } else {
-    PADDLE_THROW("Not supported type %s", ToTypeName(var.Type()));
+    PADDLE_THROW(platform::errors::Unimplemented(
+        "VisitVariable is not supported for type %s.", ToTypeName(var.Type())));
   }
 }
 
@@ -50,7 +54,8 @@ struct TensorVisitor {
 
   template <typename T>
   void operator()() {
-    PADDLE_THROW("Not Support to get LoDTensor from %s", typeid(T).name());
+    PADDLE_THROW(platform::errors::Unimplemented(
+        "Getting tensor from type %s is not supported.", typeid(T).name()));
   }
 };
 
@@ -78,8 +83,8 @@ struct ShareDimsAndLoDVisitor {
 
   template <typename T>
   void operator()(const T&) {
-    PADDLE_ENFORCE("ShareDimsAndLoD is not supported by type %s",
-                   typeid(T).name());
+    PADDLE_THROW(platform::errors::Unimplemented(
+        "ShareDimsAndLoD is not supported for type %s.", typeid(T).name()));
   }
 };
 
@@ -89,42 +94,54 @@ void VariableVisitor::ShareDimsAndLoD(const Variable& src, Variable* trg) {
 }
 
 struct EnforceShapeAndDTypeEQVisitor {
-  const Variable* trg_;
+  const Variable* dst_;
 
   void operator()(const LoDTensor& src) {
-    auto& tensor = trg_->Get<LoDTensor>();
-    PADDLE_ENFORCE_EQ(
-        src.place().which(), tensor.place().which(),
-        "The Places of the two Variable must be all on CPU or all on GPU.");
+    auto& tensor = dst_->Get<LoDTensor>();
+    PADDLE_ENFORCE_EQ(src.place().which(), tensor.place().which(),
+                      platform::errors::PreconditionNotMet(
+                          "The place type of the two variables is not equal."));
     PADDLE_ENFORCE_EQ(src.type(), tensor.type(),
-                      "The dtype of the two Variable is not equal.");
-    PADDLE_ENFORCE_EQ(src.dims(), tensor.dims(),
-                      "The dims of the two Variable is not equal.");
+                      platform::errors::PreconditionNotMet(
+                          "The dtype of the two variables is not equal."));
+    PADDLE_ENFORCE_EQ(
+        src.dims(), tensor.dims(),
+        platform::errors::PreconditionNotMet(
+            "The layout of the two variables' tensors is not equal."));
     PADDLE_ENFORCE_EQ(src.lod(), tensor.lod(),
-                      "The lod of the two Variable is not equal.");
-    PADDLE_ENFORCE_EQ(src.layout(), tensor.layout(),
-                      "The layout of the two Variable's tensor is not equal.");
+                      platform::errors::PreconditionNotMet(
+                          "The lod of the two variable is not equal."));
+    PADDLE_ENFORCE_EQ(
+        src.layout(), tensor.layout(),
+        platform::errors::PreconditionNotMet(
+            "The layout of the two variables' tensors tensor is not equal."));
   }
 
   void operator()(const SelectedRows& src) {
-    auto& selected_rows = trg_->Get<SelectedRows>();
-    PADDLE_ENFORCE_EQ(
-        src.place().which(), selected_rows.place().which(),
-        "The Places of the two Variable must be all on CPU or all on GPU.");
+    auto& selected_rows = dst_->Get<SelectedRows>();
+    PADDLE_ENFORCE_EQ(src.place().which(), selected_rows.place().which(),
+                      platform::errors::PreconditionNotMet(
+                          "The place type of the two variables is not equal."));
     PADDLE_ENFORCE_EQ(src.value().type(), selected_rows.value().type(),
-                      "The dtype of the two Variable is not equal.");
-    PADDLE_ENFORCE_EQ(src.value().layout(), selected_rows.value().layout(),
-                      "The layout of the two Variable's tensor is not equal.");
+                      platform::errors::PreconditionNotMet(
+                          "The dtype of the two variables is not equal."));
+    PADDLE_ENFORCE_EQ(
+        src.value().layout(), selected_rows.value().layout(),
+        platform::errors::PreconditionNotMet(
+            "The layout of the two variables' tensors is not equal."));
     PADDLE_ENFORCE_EQ(src.height(), selected_rows.height(),
-                      "The height of the two Variable is not equal.");
+                      platform::errors::PreconditionNotMet(
+                          "The height of the two variables is not equal."));
     PADDLE_ENFORCE_EQ(src.GetCompleteDims(), selected_rows.GetCompleteDims(),
-                      "The dims of the two Variable is not equal.");
+                      platform::errors::PreconditionNotMet(
+                          "The dims of the two variables is not equal."));
   }
 
   template <typename T>
   void operator()(const T&) {
-    PADDLE_ENFORCE("EnforceShapeAndDTypeEQ is not supported by type %s",
-                   typeid(T).name());
+    PADDLE_THROW(platform::errors::Unimplemented(
+        "EnforceShapeAndDTypeEQ is not supported for type %s.",
+        typeid(T).name()));
   }
 };