Refine error msg in paddle/fluid/framework/details [part 2] (#27429)

* refine broadcast_op_handle

* refine some error messages

* refine some files

* fix bug

* fix bug

* fix bug

* follow comments

* follow comments

paddle/fluid/framework/details/all_reduce_op_handle.cc

@@ -76,7 +76,7 @@ void AllReduceOpHandle::AllReduceImpl(
                     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.",
+                        "%d and the number of places is %d.",
                         in_var_handles.size(), num_places));
   PADDLE_ENFORCE_EQ(
       in_var_handles.size(), out_var_handles.size(),
@@ -89,7 +89,7 @@ void AllReduceOpHandle::AllReduceImpl(
       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.",
+          "%d and the number of places is %d.",
           in_var_handles.size(), num_places));
 
   std::vector<const void *> lod_tensor_data;

paddle/fluid/framework/details/broadcast_op_handle.cc

@@ -13,6 +13,7 @@
 // limitations under the License.
 
 #include "paddle/fluid/framework/details/broadcast_op_handle.h"
+
 #include "paddle/fluid/framework/details/container_cast.h"
 #include "paddle/fluid/framework/details/variable_visitor.h"
 #include "paddle/fluid/platform/profiler.h"
@@ -31,10 +32,15 @@ void BroadcastOpHandle::RunImpl() {
   auto out_var_handles = DynamicCast<VarHandle>(outputs_);
 
   PADDLE_ENFORCE_EQ(in_var_handles.size(), 1UL,
-                    "The number of input should be one.");
-  PADDLE_ENFORCE_EQ(
-      out_var_handles.size(), places_.size(),
-      "The number of output should equal to the number of places.");
+                    platform::errors::PreconditionNotMet(
+                        "The number of inputs should be 1, but got %d.",
+                        in_var_handles.size()));
+  PADDLE_ENFORCE_EQ(out_var_handles.size(), places_.size(),
+                    platform::errors::PreconditionNotMet(
+                        "The number of outputs and the number of places should "
+                        "be equal, but got the number of outputs is %d and the "
+                        "number of places is %d.",
+                        out_var_handles.size(), places_.size()));
 
   VarHandle *in_var_handle = in_var_handles[0];
 
@@ -47,7 +53,9 @@ void BroadcastOpHandle::BroadcastOneVar(
     const std::vector<Scope *> &var_scopes) {
   auto *in_var =
       var_scopes.at(in_var_handle.scope_idx())->FindVar(in_var_handle.name());
-  PADDLE_ENFORCE_NOT_NULL(in_var);
+  PADDLE_ENFORCE_NOT_NULL(
+      in_var, platform::errors::NotFound("Variable %s is not found in scopes.",
+                                         in_var_handle.name()));
   Tensor &in_tensor = VariableVisitor::GetMutableTensor(in_var);
   if (UNLIKELY(!in_tensor.IsInitialized())) {
     VLOG(3) << "in var " << in_var_handle.name() << "not inited, return!";
@@ -103,7 +111,7 @@ void BroadcastOpHandle::BroadcastOneVar(
 
       broadcast_calls.emplace_back(
           [send_recv_buffer, numel, type, root_id, &nccl_ctx] {
-            PADDLE_ENFORCE(platform::dynload::ncclBcast(
+            PADDLE_ENFORCE_CUDA_SUCCESS(platform::dynload::ncclBcast(
                 send_recv_buffer, numel, static_cast<ncclDataType_t>(type),
                 root_id, nccl_ctx.comm_, nccl_ctx.stream()));
           });
@@ -131,7 +139,8 @@ void BroadcastOpHandle::BroadcastOneVar(
       nccl_ctxs_->DevCtx(p)->Wait();
     }
 #else
-    PADDLE_THROW("CUDA is not enabled.");
+    PADDLE_THROW(
+        platform::errors::PreconditionNotMet("Not compiled with NCLL."));
 #endif
   }
 }
@@ -154,10 +163,13 @@ void BroadcastOpHandle::InitOutputValue(
     auto t_out_p = out_var_handle->place();
     auto *out_var = var_scopes.at(out_var_handle->scope_idx())
                         ->FindVar(out_var_handle->name());
-    PADDLE_ENFORCE_NOT_NULL(out_var);
+    PADDLE_ENFORCE_NOT_NULL(out_var, platform::errors::NotFound(
+                                         "Variable %s is not found in scopes.",
+                                         out_var_handle->name()));
     if (is_gpu_place(in_tensor.place())) {
-      PADDLE_ENFORCE(platform::is_gpu_place(t_out_p),
-                     "Places of input and output must be all on GPU.");
+      PADDLE_ENFORCE_EQ(platform::is_gpu_place(t_out_p), true,
+                        platform::errors::PreconditionNotMet(
+                            "Places of input and output must be all on GPU."));
     } else {
       t_out_p = platform::CPUPlace();
     }

paddle/fluid/framework/details/broadcast_op_handle_test.h

@@ -79,7 +79,8 @@ struct TestBroadcastOpHandle {
       }
       nccl_ctxs_.reset(new platform::NCCLContextMap(place_list_));
 #else
-      PADDLE_THROW("CUDA is not support.");
+      PADDLE_THROW(
+          platform::errors::PreconditionNotMet("Not compiled with NCLL."));
 #endif
     } else {
       int count = 8;
@@ -113,7 +114,8 @@ struct TestBroadcastOpHandle {
       op_handle_ = new BroadcastOpHandle(nodes_.back().get(), local_scopes_,
                                          place_list_, nccl_ctxs_.get());
 #else
-      PADDLE_THROW("CUDA is not support.");
+      PADDLE_THROW(
+          platform::errors::PreconditionNotMet("Not compiled with NCLL."));
 #endif
     } else {
 #if defined(PADDLE_WITH_NCCL)
@@ -171,7 +173,9 @@ struct TestBroadcastOpHandle {
                                    float val_scalar = 0.0) {
     auto var = param_scopes_[input_scope_idx]->FindVar(varname);
 
-    PADDLE_ENFORCE_NOT_NULL(var);
+    PADDLE_ENFORCE_NOT_NULL(
+        var, platform::errors::NotFound("Variable %s is not found in scope.",
+                                        varname));
     auto lod_tensor = var->GetMutable<f::LoDTensor>();
     std::vector<float> send_vector(static_cast<size_t>(f::product(kDims)));
     for (size_t k = 0; k < send_vector.size(); ++k) {
@@ -194,7 +198,9 @@ struct TestBroadcastOpHandle {
     }
 
     auto var = param_scopes_[input_scope_idx]->FindVar(varname);
-    PADDLE_ENFORCE_NOT_NULL(var);
+    PADDLE_ENFORCE_NOT_NULL(
+        var, platform::errors::NotFound("Variable %s is not found in scope.",
+                                        varname));
     auto selected_rows = var->GetMutable<f::SelectedRows>();
     auto value = selected_rows->mutable_value();
     value->mutable_data<float>(kDims, place_list_[input_scope_idx]);
@@ -211,13 +217,24 @@ struct TestBroadcastOpHandle {
                          const std::vector<float>& send_vector,
                          const std::vector<int64_t>& rows, int height) {
     auto var = param_scopes_[input_scope_idx]->FindVar(varname);
-    PADDLE_ENFORCE_NOT_NULL(var);
+    PADDLE_ENFORCE_NOT_NULL(
+        var, platform::errors::NotFound("Variable %s is not found in scope.",
+                                        varname));
     auto& selected_rows = var->Get<f::SelectedRows>();
     auto rt = selected_rows.value();
-    PADDLE_ENFORCE_EQ(selected_rows.height(), height, "height is not equal.");
+    PADDLE_ENFORCE_EQ(selected_rows.height(), height,
+                      platform::errors::InvalidArgument(
+                          "The height of SelectedRows is not equal to "
+                          "the expected, expect %d, but got %ld.",
+                          height, selected_rows.height()));
 
     for (size_t k = 0; k < selected_rows.rows().size(); ++k) {
-      PADDLE_ENFORCE_EQ(selected_rows.rows()[k], rows[k]);
+      PADDLE_ENFORCE_EQ(
+          selected_rows.rows()[k], rows[k],
+          platform::errors::InvalidArgument(
+              "The item at position %zu of rows of SelectedRows "
+              "is not equal to the expected, expect %ld, but got %ld.",
+              k, rows[k], selected_rows.rows()[k]));
     }
 
     p::CPUPlace cpu_place;
@@ -235,9 +252,15 @@ struct TestBroadcastOpHandle {
                       framework::Scope* scope) {
     p::CPUPlace cpu_place;
     auto var = scope->FindVar(varname);
-    PADDLE_ENFORCE_NOT_NULL(var);
+    PADDLE_ENFORCE_NOT_NULL(
+        var, platform::errors::NotFound("Variable %s is not found in scope.",
+                                        varname));
     auto tensor = var->Get<f::LoDTensor>();
-    PADDLE_ENFORCE_EQ(tensor.lod(), lod, "lod is not equal.");
+    PADDLE_ENFORCE_EQ(tensor.lod(), lod,
+                      platform::errors::InvalidArgument(
+                          "The LoD of tensor is not equal to "
+                          "the expected, expect %s, but got %s.",
+                          lod, tensor.lod()));
     f::Tensor result_tensor;
     f::TensorCopySync(tensor, cpu_place, &result_tensor);
     float* ct = result_tensor.mutable_data<float>(cpu_place);

paddle/fluid/framework/details/build_strategy.cc

@@ -235,7 +235,8 @@ class ParallelExecutorPassBuilder : public ir::PassBuilder {
               AppendPass("reduce_mode_multi_devices_pass").get();
           break;
         default:
-          PADDLE_THROW("Unknown reduce strategy.");
+          PADDLE_THROW(
+              platform::errors::Unimplemented("Unknown reduce strategy."));
       }
     }
     multi_devices_pass->SetNotOwned<const BuildStrategy>("strategy",

paddle/fluid/framework/details/eager_deletion_op_handle.cc

@@ -12,11 +12,12 @@
 // See the License for the specific language governing permissions and
 // limitations under the License.
 
+#include "paddle/fluid/framework/details/eager_deletion_op_handle.h"
+
 #include <memory>
 #include <unordered_set>
 #include <utility>
 
-#include "paddle/fluid/framework/details/eager_deletion_op_handle.h"
 #include "paddle/fluid/framework/ir/memory_optimize_pass/memory_optimization_var_info.h"
 #include "paddle/fluid/framework/lod_tensor_array.h"
 #include "paddle/fluid/framework/scope.h"
@@ -47,15 +48,19 @@ EagerDeletionOpHandle::EagerDeletionOpHandle(
     if (dynamic_cast<StreamGarbageCollector *>(gc_)) {
       platform::CUDADeviceGuard guard(
           BOOST_GET_CONST(platform::CUDAPlace, place).device);
-      PADDLE_ENFORCE(cudaEventCreateWithFlags(&event_, cudaEventDisableTiming));
-      PADDLE_ENFORCE_NOT_NULL(event_);
+      PADDLE_ENFORCE_CUDA_SUCCESS(
+          cudaEventCreateWithFlags(&event_, cudaEventDisableTiming));
+      PADDLE_ENFORCE_NOT_NULL(event_, platform::errors::InvalidArgument(
+                                          "The cuda envet created is NULL."));
     }
   }
 #endif
-  PADDLE_ENFORCE_NE(vars.empty(), true, platform::errors::InvalidArgument(
-                                            "Variable names are empty."));
+  PADDLE_ENFORCE_NE(vars.empty(), true,
+                    platform::errors::InvalidArgument(
+                        "The variables to be deleted are empty."));
   for (auto *var : var_infos_) {
-    PADDLE_ENFORCE_NOT_NULL(var);
+    PADDLE_ENFORCE_NOT_NULL(var, platform::errors::InvalidArgument(
+                                     "The memory optimization info is NULL."));
   }
 }
 
@@ -64,7 +69,7 @@ EagerDeletionOpHandle::~EagerDeletionOpHandle() {
   if (event_) {
     auto gpu_place = BOOST_GET_CONST(platform::CUDAPlace, dev_ctx_->GetPlace());
     platform::CUDADeviceGuard guard(gpu_place.device);
-    PADDLE_ENFORCE(cudaEventDestroy(event_));
+    PADDLE_ENFORCE_CUDA_SUCCESS(cudaEventDestroy(event_));
   }
 #endif
 }
@@ -78,12 +83,17 @@ void EagerDeletionOpHandle::InitCUDA() {
 }
 
 void EagerDeletionOpHandle::CallOnce() {
-  PADDLE_ENFORCE(vars_.empty(), "vars_ must be initialized here");
+  PADDLE_ENFORCE_EQ(
+      vars_.empty(), true,
+      platform::errors::InvalidArgument(
+          "The variables to be deleted should be initialized here."));
   Scope *exec_scope = local_exec_scopes_[0];
   for (auto *var_info : var_infos_) {
     auto *var = exec_scope->FindVar(var_info->Name());
-    PADDLE_ENFORCE_NOT_NULL(var, "Variable %s should not be nullptr",
-                            var_info->Name());
+    PADDLE_ENFORCE_NOT_NULL(
+        var, platform::errors::NotFound(
+                 "The variable(%s) to be inplaced is not found in scope.",
+                 var_info->Name()));
     vars_.emplace_back(var);
   }
 }
@@ -119,8 +129,9 @@ void EagerDeletionOpHandle::RunImpl() {
         garbages.emplace_back(t.MoveMemoryHolder());
       }
     } else {
-      PADDLE_THROW("Type %s of %s is not supported eager deletion",
-                   framework::ToTypeName(var->Type()), var_info->Name());
+      PADDLE_THROW(platform::errors::Unimplemented(
+          "The variable(%s) of type %s is not supported in eager deletion.",
+          framework::ToTypeName(var->Type()), var_info->Name()));
     }
   }
 
@@ -137,8 +148,9 @@ void EagerDeletionOpHandle::ClearGarbages(
     auto callback_stream =
         reinterpret_cast<StreamGarbageCollector *>(gc_)->stream();
     auto callback_func = [=]() {
-      PADDLE_ENFORCE(cudaEventRecord(event_, compute_stream));
-      PADDLE_ENFORCE(cudaStreamWaitEvent(callback_stream, event_, 0));
+      PADDLE_ENFORCE_CUDA_SUCCESS(cudaEventRecord(event_, compute_stream));
+      PADDLE_ENFORCE_CUDA_SUCCESS(
+          cudaStreamWaitEvent(callback_stream, event_, 0));
     };
     gc_->Add(std::move(*garbages), callback_func);
   } else {

paddle/fluid/framework/details/fused_all_reduce_op_handle.cc

@@ -12,8 +12,10 @@
 // See the License for the specific language governing permissions and
 // limitations under the License.
 #include "paddle/fluid/framework/details/fused_all_reduce_op_handle.h"
+
 #include <algorithm>
 #include <utility>
+
 #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"
@@ -56,10 +58,20 @@ void FusedAllReduceOpHandle::RunImpl() {
   size_t place_num = places_.size();
   PADDLE_ENFORCE_EQ(
       in_var_handles.size(), place_num * num_of_all_reduce_,
-      "The NoDummyInputSize should be equal to the number of places.");
+      platform::errors::PreconditionNotMet(
+          "The number of input variable handles should be equal to the number "
+          "of places plus the number of all reduce handles, "
+          "but got the number of input variable handles is %d, the "
+          "number of places is %d, and the number of all reduce handles "
+          "is %d.",
+          in_var_handles.size(), place_num, num_of_all_reduce_));
   PADDLE_ENFORCE_EQ(
       in_var_handles.size(), out_var_handles.size(),
-      "The NoDummyInputSize and NoDummyOutputSize should be equal.");
+      platform::errors::PreconditionNotMet(
+          "The number of input variable handles should be equal to the number "
+          "of output variable handles, but got the number of input variable "
+          "handles is %d, and the number of  output variable handles is %d.",
+          in_var_handles.size(), out_var_handles.size()));
 
   // Note: some gradient op doesn't have CUDAKernel, so the gradients of
   // those op are in CPUPlace, in this case, the all reduce should not be fused.
@@ -106,7 +118,13 @@ void FusedAllReduceOpHandle::FusedAllReduceFunc(
       dtype = ele_dtype;
     }
 
-    PADDLE_ENFORCE_EQ(ele_dtype, dtype);
+    PADDLE_ENFORCE_EQ(
+        ele_dtype, dtype,
+        platform::errors::InvalidArgument(
+            "The DataType of grad tensors of fused_all_reduce_op_handle  "
+            "must be consistent. The current dtype is %s, but the "
+            "previous dtype is %s.",
+            DataTypeToString(ele_dtype), DataTypeToString(dtype)));
 
     // Check whether the address space is contiguous.
     std::sort(
@@ -130,16 +148,29 @@ void FusedAllReduceOpHandle::FusedAllReduceFunc(
           "input[%d] address: 0X%02x. The offset: %d",
           k - 1, g_tensor.at(k - 1).first, cur_address, g_tensor.at(k).first, k,
           next_address, k, infer_next_address, offset);
-      PADDLE_ENFORCE_EQ(infer_next_address, next_address,
-                        "The address is not consistent.");
+      PADDLE_ENFORCE_EQ(
+          infer_next_address, next_address,
+          platform::errors::InvalidArgument(
+              "The infered address of the next tensor should be equal to the "
+              "real address of the next tensor. But got infered address is %p "
+              "and real address is %p.",
+              infer_next_address, next_address));
     }
   }
 
   if (!FLAGS_skip_fused_all_reduce_check) {
     for (size_t scope_idx = 0; scope_idx < place_num; ++scope_idx) {
       for (size_t j = 1; j < num_of_all_reduce_; ++j) {
-        PADDLE_ENFORCE_EQ(grads_tensor.at(0).at(j).first,
-                          grads_tensor.at(scope_idx).at(j).first);
+        PADDLE_ENFORCE_EQ(
+            grads_tensor.at(0).at(j).first,
+            grads_tensor.at(scope_idx).at(j).first,
+            platform::errors::InvalidArgument(
+                "The variable name of grad tensors of "
+                "fused_all_reduce_op_handle  "
+                "must be consistent. The current name is %s, but the "
+                "previous name is %s.",
+                grads_tensor.at(0).at(j).first,
+                grads_tensor.at(scope_idx).at(j).first));
       }
     }
   }
@@ -167,7 +198,9 @@ bool FusedAllReduceOpHandle::InputIsInDifferentPlace(
     for (size_t j = 0; j < in_var_handles.size(); j += place_num) {
       auto var_name = in_var_handles[j]->name();
       auto var = local_scope->FindVar(var_name);
-      PADDLE_ENFORCE_NOT_NULL(var, "%s is not found in local scope.", var_name);
+      PADDLE_ENFORCE_NOT_NULL(
+          var, platform::errors::NotFound(
+                   "The variable '%s' is not found in local scope.", var_name));
       auto &lod_tensor = var->Get<LoDTensor>();
       if (!is_same_place(lod_tensor.place(), places_.at(scope_idx))) {
         return true;
@@ -185,14 +218,24 @@ void FusedAllReduceOpHandle::GetGradLoDTensor(
   size_t place_num = places_.size();
   for (size_t j = 0; j < in_var_handles.size(); j += place_num) {
     auto var_name = in_var_handles[j]->name();
-    PADDLE_ENFORCE_EQ(var_name, out_var_handles[j]->name());
+    PADDLE_ENFORCE_EQ(
+        var_name, out_var_handles[j]->name(),
+        platform::errors::InvalidArgument(
+            "The name of input variable should be equal "
+            "to the name of output variable. But got the name of input "
+            "variable is %s and the name of output variable is %s.",
+            var_name, out_var_handles[j]->name()));
     auto var = local_scope->FindVar(var_name);
-    PADDLE_ENFORCE_NOT_NULL(var, "%s is not found in local scope.", var_name);
+    PADDLE_ENFORCE_NOT_NULL(
+        var, platform::errors::NotFound(
+                 "The variable '%s' is not found in local scope.", var_name));
     auto &lod_tensor = var->Get<LoDTensor>();
 
     PADDLE_ENFORCE_EQ(
         platform::is_same_place(lod_tensor.place(), places_.at(scope_idx)),
-        true, "%s(%d) is not in the right place.", var_name, scope_idx);
+        true, platform::errors::InvalidArgument(
+                  "The variable '%s' at scope %d is not in the right place.",
+                  var_name, scope_idx));
     grad_tensor->emplace_back(std::make_pair(var_name, &lod_tensor));
   }
 }
@@ -204,16 +247,26 @@ void FusedAllReduceOpHandle::GetDTypeAndNumel(
   size_t size_of_dtype = 0;
   for (size_t i = 0; i < grad_tensor.size(); ++i) {
     // Get dtype
-    auto ele_type = grad_tensor.at(i).second->type();
+    auto ele_dtype = grad_tensor.at(i).second->type();
     if (i == 0) {
-      *dtype = ele_type;
-      size_of_dtype = framework::SizeOfType(ele_type);
+      *dtype = ele_dtype;
+      size_of_dtype = framework::SizeOfType(ele_dtype);
     }
-    PADDLE_ENFORCE_EQ(ele_type, *dtype);
+    PADDLE_ENFORCE_EQ(
+        ele_dtype, *dtype,
+        platform::errors::InvalidArgument(
+            "The DataType of grad tensors of fused_all_reduce_op_handle  "
+            "must be consistent. The current dtype is %s, but the "
+            "previous dtype is %s.",
+            DataTypeToString(ele_dtype), DataTypeToString(*dtype)));
 
     // Get element number
     int64_t len = grad_tensor.at(i).second->numel();
-    PADDLE_ENFORCE_GT(len, 0);
+    PADDLE_ENFORCE_GT(
+        len, 0, platform::errors::InvalidArgument(
+                    "The size of grad tensors of fused_all_reduce_op_handle  "
+                    "must be > 0, but got %d.",
+                    len));
     *numel +=
         platform::Alignment(len * size_of_dtype, places_[0]) / size_of_dtype;
   }

paddle/fluid/framework/details/fused_broadcast_op_handle.cc

@@ -13,6 +13,7 @@
 // limitations under the License.
 
 #include "paddle/fluid/framework/details/fused_broadcast_op_handle.h"
+
 #include "paddle/fluid/framework/details/container_cast.h"
 #include "paddle/fluid/framework/details/variable_visitor.h"
 #include "paddle/fluid/platform/profiler.h"
@@ -32,7 +33,15 @@ void FusedBroadcastOpHandle::RunImpl() {
   WaitInputVarGenerated();
 
   size_t place_num = places_.size();
-  PADDLE_ENFORCE_EQ(in_var_handles.size() * place_num, out_var_handles.size());
+  PADDLE_ENFORCE_EQ(
+      in_var_handles.size() * place_num, out_var_handles.size(),
+      platform::errors::PreconditionNotMet(
+          "The number of input variable handles plus the number "
+          "of places should be equal to the number of output variable handles, "
+          "but got the number of input variable handles is %d, the "
+          "number of places is %d, and the number of output variable handles "
+          "is %d.",
+          in_var_handles.size(), place_num, out_var_handles.size()));
 
   for (size_t i = 0; i < in_var_handles.size(); ++i) {
     BroadcastOneVar(

paddle/fluid/framework/details/fused_broadcast_op_handle_test.cc

@@ -13,8 +13,10 @@
 // limitations under the License.
 
 #include "paddle/fluid/framework/details/fused_broadcast_op_handle.h"
+
 #include <memory>
 #include <unordered_map>
+
 #include "gtest/gtest.h"
 #include "paddle/fluid/framework/details/broadcast_op_handle_test.h"
 #include "paddle/fluid/framework/details/op_handle_base.h"
@@ -58,7 +60,8 @@ struct TestFusedBroadcastOpHandle : TestBroadcastOpHandle {
       op_handle_ = new FusedBroadcastOpHandle(
           nodes_.back().get(), local_scopes_, place_list_, nccl_ctxs_.get());
 #else
-      PADDLE_THROW("CUDA is not supported.");
+      PADDLE_THROW(
+          platform::errors::PreconditionNotMet("Not compiled with CUDA."));
 #endif
     } else {
 #if defined(PADDLE_WITH_NCCL)

paddle/fluid/framework/details/gather_op_handle.cc

@@ -13,6 +13,7 @@
 // limitations under the License.
 
 #include "paddle/fluid/framework/details/gather_op_handle.h"
+
 #include "paddle/fluid/framework/details/container_cast.h"
 #include "paddle/fluid/framework/details/variable_visitor.h"
 
@@ -32,13 +33,20 @@ void GatherOpHandle::RunImpl() {
 
   PADDLE_ENFORCE_EQ(
       in_var_handles.size(), places_.size(),
-      "The number of output should equal to the number of places.");
+      platform::errors::InvalidArgument(
+          "The number of input variables should be equal "
+          "to the number of places, but got the number of input variables is "
+          "%d and the number of places is %d.",
+          in_var_handles.size(), places_.size()));
 
   VarHandle *out_var_handle;
   {
     auto out_var_handles = DynamicCast<VarHandle>(this->Outputs());
-    PADDLE_ENFORCE_EQ(out_var_handles.size(), 1,
-                      "The number of output should be one.");
+    PADDLE_ENFORCE_EQ(
+        out_var_handles.size(), 1,
+        platform::errors::InvalidArgument(
+            "The number of output variables should be 1, but got %d.",
+            out_var_handles.size()));
     out_var_handle = out_var_handles.front();
   }
 
@@ -47,10 +55,14 @@ void GatherOpHandle::RunImpl() {
   auto in_0_handle = in_var_handles[0];
   auto pre_in_var =
       var_scopes.at(in_0_handle->scope_idx())->FindVar(in_0_handle->name());
-  PADDLE_ENFORCE_NOT_NULL(pre_in_var);
+  PADDLE_ENFORCE_NOT_NULL(
+      pre_in_var,
+      platform::errors::NotFound("The variable '%s' is not found in the scope.",
+                                 in_0_handle->name()));
 
-  PADDLE_ENFORCE(pre_in_var->IsType<framework::SelectedRows>(),
-                 "Currently, gather_op only can gather SelectedRows.");
+  PADDLE_ENFORCE_EQ(pre_in_var->IsType<framework::SelectedRows>(), true,
+                    platform::errors::Unimplemented(
+                        "Currently, gather_op only supports SelectedRows."));
 
   // Wait input done, this Wait is asynchronous operation
   WaitInputVarGenerated();
@@ -63,7 +75,10 @@ void GatherOpHandle::RunImpl() {
   for (auto *in_handle : in_var_handles) {
     auto *in_var =
         var_scopes.at(in_handle->scope_idx())->FindVar(in_handle->name());
-    PADDLE_ENFORCE_NOT_NULL(in_var);
+    PADDLE_ENFORCE_NOT_NULL(
+        in_var,
+        platform::errors::NotFound(
+            "The variable '%s' is not found in the scope.", in_handle->name()));
     VariableVisitor::EnforceShapeAndDTypeEQ(*in_var, *pre_in_var);
 
     auto &in_sr_value = in_var->Get<framework::SelectedRows>();
@@ -76,15 +91,19 @@ void GatherOpHandle::RunImpl() {
   // NOTE: The Places of all input tensor must be all on CPU or all on GPU.
   platform::Place t_out_p = out_var_handle->place();
   if (platform::is_gpu_place(pre_in_value.place())) {
-    PADDLE_ENFORCE(platform::is_gpu_place(t_out_p),
-                   "Places of input and output must be all on GPU.");
+    PADDLE_ENFORCE_EQ(platform::is_gpu_place(t_out_p), true,
+                      platform::errors::PreconditionNotMet(
+                          "Places of input and output must be all on GPU."));
   } else {
     t_out_p = platform::CPUPlace();
   }
 
   auto out_var = var_scopes.at(out_var_handle->scope_idx())
                      ->FindVar(out_var_handle->name());
-  PADDLE_ENFORCE_NOT_NULL(out_var);
+  PADDLE_ENFORCE_NOT_NULL(
+      out_var,
+      platform::errors::NotFound("The variable '%s' is not found in the scope.",
+                                 out_var_handle->name()));
   auto out_value = out_var->GetMutable<framework::SelectedRows>();
   out_value->set_height(pre_in_value.height());
   out_value->set_rows(out_rows);

paddle/fluid/framework/details/gather_op_handle_test.cc

@@ -13,8 +13,10 @@
 // limitations under the License.
 
 #include "paddle/fluid/framework/details/gather_op_handle.h"
+
 #include <memory>
 #include <unordered_map>
+
 #include "gtest/gtest.h"
 
 namespace paddle {
@@ -60,7 +62,8 @@ struct TestGatherOpHandle {
         ctxs_.emplace_back(new p::CUDADeviceContext(p));
       }
 #else
-      PADDLE_THROW("CUDA is not support.");
+      PADDLE_THROW(
+          platform::errors::PreconditionNotMet("Not compiled with CUDA."));
 #endif
     } else {
       int count = 8;
@@ -141,7 +144,9 @@ struct TestGatherOpHandle {
     for (size_t input_scope_idx = 0; input_scope_idx < gpu_list_.size();
          ++input_scope_idx) {
       auto in_var = param_scopes_.at(input_scope_idx)->FindVar("input");
-      PADDLE_ENFORCE_NOT_NULL(in_var);
+      PADDLE_ENFORCE_NOT_NULL(
+          in_var, platform::errors::NotFound(
+                      "The variable '%s' is not found in the scope.", "input"));
       auto in_selected_rows = in_var->GetMutable<f::SelectedRows>();
       auto value = in_selected_rows->mutable_value();
       value->mutable_data<float>(kDims, gpu_list_[input_scope_idx]);
@@ -155,7 +160,9 @@ struct TestGatherOpHandle {
     }
 
     auto out_var = param_scopes_.at(output_scope_idx)->FindVar("out");
-    PADDLE_ENFORCE_NOT_NULL(out_var);
+    PADDLE_ENFORCE_NOT_NULL(
+        out_var, platform::errors::NotFound(
+                     "The variable '%s' is not found in the scope.", "out"));
     auto out_selected_rows = out_var->GetMutable<f::SelectedRows>();
 
     auto in_var = param_scopes_.at(output_scope_idx)->FindVar("input");
@@ -173,9 +180,19 @@ struct TestGatherOpHandle {
     auto& out_select_rows = out_var->Get<f::SelectedRows>();
     auto rt = out_select_rows.value();
 
-    PADDLE_ENFORCE_EQ(out_select_rows.height(), height, "height is not equal.");
+    PADDLE_ENFORCE_EQ(out_select_rows.height(), height,
+                      platform::errors::InvalidArgument(
+                          "The height of SelectedRows is not equal to "
+                          "the expected, expect %d, but got %d.",
+                          height, out_select_rows.height()));
+
     for (size_t k = 0; k < out_select_rows.rows().size(); ++k) {
-      PADDLE_ENFORCE_EQ(out_select_rows.rows()[k], rows[k % rows.size()]);
+      PADDLE_ENFORCE_EQ(
+          out_select_rows.rows()[k], rows[k % rows.size()],
+          platform::errors::InvalidArgument(
+              "The item at position %d of rows of SelectedRows is not equal to "
+              "the expected, expect %d, but got %d.",
+              k, rows[k % rows.size()], out_select_rows.rows()[k]));
     }
 
     f::Tensor result_tensor;
@@ -207,6 +224,7 @@ TEST(GatherTester, TestGPUGatherTestSelectedRows) {
   test_op.TestGatherSelectedRows(input_scope_idx);
 }
 #endif
+
 }  // namespace details
 }  // namespace framework
 }  // namespace paddle

paddle/fluid/framework/details/nccl_op_handle.h

@@ -46,14 +46,17 @@ class NCCLOpHandleBase : public OpHandleBase {
   }
   virtual ~NCCLOpHandleBase() {
     for (auto& ev : inter_events_) {
-      PADDLE_ENFORCE(cudaEventDestroy(ev.second));
+      PADDLE_ENFORCE_CUDA_SUCCESS(cudaEventDestroy(ev.second));
     }
     for (auto& ev : exter_events_) {
-      PADDLE_ENFORCE(cudaEventDestroy(ev.second));
+      PADDLE_ENFORCE_CUDA_SUCCESS(cudaEventDestroy(ev.second));
     }
   }
   void SetRunEnv(int run_order, bool use_hierarchical_allreduce) {
-    PADDLE_ENFORCE(run_order >= 0, "run_order must >= 0");
+    PADDLE_ENFORCE_GE(
+        run_order, 0,
+        platform::errors::InvalidArgument(
+            "The argument run_order must be >= 0, but got %d.", run_order));
     run_order_ = run_order;
     use_hierarchical_allreduce_ = use_hierarchical_allreduce;
 
@@ -74,8 +77,11 @@ class NCCLOpHandleBase : public OpHandleBase {
       return;
     }
 
-    PADDLE_ENFORCE(places_.size() == 1,
-                   "HierarchicalAllReduce run one proc with one card mode.");
+    PADDLE_ENFORCE_EQ(places_.size(), 1,
+                      platform::errors::InvalidArgument(
+                          "HierarchicalAllReduce can only run "
+                          "one proccess with one card mode, but got %d cards.",
+                          places_.size()));
 
     for (auto& p : places_) {
       auto ctxs = nccl_ctxs_->GetHierarchicalInterCtx(run_order);
@@ -88,11 +94,11 @@ class NCCLOpHandleBase : public OpHandleBase {
         continue;
       }
 
-      PADDLE_ENFORCE(cudaSetDevice(dev_id));
-      PADDLE_ENFORCE(cudaEventCreateWithFlags(&inter_events_[dev_id],
-                                              cudaEventDisableTiming));
-      PADDLE_ENFORCE(cudaEventCreateWithFlags(&exter_events_[dev_id],
-                                              cudaEventDisableTiming));
+      PADDLE_ENFORCE_CUDA_SUCCESS(cudaSetDevice(dev_id));
+      PADDLE_ENFORCE_CUDA_SUCCESS(cudaEventCreateWithFlags(
+          &inter_events_[dev_id], cudaEventDisableTiming));
+      PADDLE_ENFORCE_CUDA_SUCCESS(cudaEventCreateWithFlags(
+          &exter_events_[dev_id], cudaEventDisableTiming));
       VLOG(10) << "Create events on dev_id:" << dev_id
                << ", inter_event:" << &inter_events_[dev_id]
                << ", exter_event:" << &exter_events_[dev_id];
@@ -102,7 +108,10 @@ class NCCLOpHandleBase : public OpHandleBase {
   void FlatNCCLAllReduce(platform::Place place, const void* sendbuff,
                          void* recvbuff, size_t count, ncclDataType_t datatype,
                          ncclRedOp_t op) {
-    PADDLE_ENFORCE(run_order_ >= 0, "run_order must > 0");
+    PADDLE_ENFORCE_GE(
+        run_order_, 0,
+        platform::errors::InvalidArgument(
+            "The argument run_order_ must be >= 0, but got %d.", run_order_));
     auto flat_nccl_ctxs = nccl_ctxs_->GetFlatCtx(run_order_);
     int dev_id = BOOST_GET_CONST(platform::CUDAPlace, place).device;
     auto& nccl_ctx = flat_nccl_ctxs->at(dev_id);
@@ -113,14 +122,17 @@ class NCCLOpHandleBase : public OpHandleBase {
              << ", dev_id:" << dev_id << ", dtype:" << datatype
              << ", place:" << place;
 
-    PADDLE_ENFORCE(platform::dynload::ncclAllReduce(
+    PADDLE_ENFORCE_CUDA_SUCCESS(platform::dynload::ncclAllReduce(
         sendbuff, recvbuff, count, datatype, op, comm, stream));
   }
 
   void NCCLAllReduce(platform::Place place, const void* sendbuff,
                      void* recvbuff, size_t count, ncclDataType_t datatype,
                      ncclRedOp_t op) {
-    PADDLE_ENFORCE(run_order_ >= 0, "run_order must > 0");
+    PADDLE_ENFORCE_GE(
+        run_order_, 0,
+        platform::errors::InvalidArgument(
+            "The argument run_order_ must be >= 0, but got %d.", run_order_));
     if (!use_hierarchical_allreduce_) {
       FlatNCCLAllReduce(place, sendbuff, recvbuff, count, datatype, op);
       return;
@@ -132,7 +144,10 @@ class NCCLOpHandleBase : public OpHandleBase {
   void HierarchicalAllReduce(platform::Place place, const void* sendbuff,
                              void* recvbuff, size_t count,
                              ncclDataType_t datatype, ncclRedOp_t op) {
-    PADDLE_ENFORCE(run_order_ >= 0, "run_order must > 0");
+    PADDLE_ENFORCE_GE(
+        run_order_, 0,
+        platform::errors::InvalidArgument(
+            "The argument run_order_ must be >= 0, but got %d.", run_order_));
     InterReduce(place, sendbuff, recvbuff, count, datatype, op);
     // When a trainer is not in exter allreduce ring
     // they need not to call this.
@@ -157,14 +172,13 @@ class NCCLOpHandleBase : public OpHandleBase {
              << ", dtype:" << datatype << ", place:" << place
              << ", stream:" << stream;
 
-    PADDLE_ENFORCE(platform::dynload::ncclReduce(
+    PADDLE_ENFORCE_CUDA_SUCCESS(platform::dynload::ncclReduce(
         sendbuff, recvbuff, count, datatype, ncclSum, 0, comm, stream));
 
     cudaEventRecord(inter_events_.at(dev_id), stream);
 
     if (FLAGS_sync_nccl_allreduce) {
-      PADDLE_ENFORCE(cudaStreamSynchronize(stream),
-                     "sync HierarchicalAllReduce inter stream error");
+      PADDLE_ENFORCE_CUDA_SUCCESS(cudaStreamSynchronize(stream));
     }
   }
 
@@ -172,7 +186,9 @@ class NCCLOpHandleBase : public OpHandleBase {
                       void* recvbuff, size_t count, ncclDataType_t datatype,
                       ncclRedOp_t op) {
     auto nccl_ctxs = nccl_ctxs_->GetHierarchicalExterCtx(run_order_);
-    PADDLE_ENFORCE(nccl_ctxs_, "can't get exter %d nccl_ctxs", run_order_);
+    PADDLE_ENFORCE_NOT_NULL(
+        nccl_ctxs_, platform::errors::NotFound(
+                        "Can't get exter %d nccl contexts.", run_order_));
     int dev_id = BOOST_GET_CONST(platform::CUDAPlace, place).device;
     auto& nccl_ctx = nccl_ctxs->at(dev_id);
     auto stream = nccl_ctx.stream();
@@ -185,14 +201,13 @@ class NCCLOpHandleBase : public OpHandleBase {
 
     cudaStreamWaitEvent(stream, inter_events_.at(dev_id), 0);
 
-    PADDLE_ENFORCE(platform::dynload::ncclAllReduce(
+    PADDLE_ENFORCE_CUDA_SUCCESS(platform::dynload::ncclAllReduce(
         sendbuff, recvbuff, count, datatype, op, comm, stream));
 
     cudaEventRecord(exter_events_.at(dev_id), stream);
 
     if (FLAGS_sync_nccl_allreduce) {
-      PADDLE_ENFORCE(cudaStreamSynchronize(stream),
-                     "sync HierarchicalAllReduce exter stream error");
+      PADDLE_ENFORCE_CUDA_SUCCESS(cudaStreamSynchronize(stream));
     }
   }
 
@@ -210,8 +225,8 @@ class NCCLOpHandleBase : public OpHandleBase {
              << ", stream:" << stream;
 
     cudaStreamWaitEvent(stream, exter_events_.at(dev_id), 0);
-    PADDLE_ENFORCE(platform::dynload::ncclBcast(sendbuff, count, datatype, 0,
-                                                comm, stream));
+    PADDLE_ENFORCE_CUDA_SUCCESS(platform::dynload::ncclBcast(
+        sendbuff, count, datatype, 0, comm, stream));
   }
 
  protected:

paddle/fluid/framework/details/op_handle_base.cc

@@ -47,8 +47,8 @@ void OpHandleBase::InitCUDA() {
 #ifdef PADDLE_WITH_CUDA
   for (auto &p : dev_ctxes_) {
     int dev_id = BOOST_GET_CONST(platform::CUDAPlace, p.first).device;
-    PADDLE_ENFORCE(cudaSetDevice(dev_id));
-    PADDLE_ENFORCE(
+    PADDLE_ENFORCE_CUDA_SUCCESS(cudaSetDevice(dev_id));
+    PADDLE_ENFORCE_CUDA_SUCCESS(
         cudaEventCreateWithFlags(&events_[dev_id], cudaEventDisableTiming));
   }
   if (IsMultiDeviceTransfer() && dev_ctxes_.size() > 0) {
@@ -62,17 +62,22 @@ void OpHandleBase::InitCUDA() {
       }
     }
   } else {
-    PADDLE_ENFORCE_EQ(dev_ctxes_.size(), 1UL,
-                      "%s should have only one dev_ctx.", Name());
+    PADDLE_ENFORCE_EQ(
+        dev_ctxes_.size(), 1UL,
+        platform::errors::InvalidArgument(
+            "Operator %s should have only one dev_ctx, but got %d.", Name(),
+            dev_ctxes_.size()));
     auto &place = dev_ctxes_.begin()->first;
     int dev_id = BOOST_GET_CONST(platform::CUDAPlace, place).device;
     for (auto &out_var : outputs_) {
       auto *out_var_handle = dynamic_cast<VarHandle *>(out_var);
       if (out_var_handle) {
-        PADDLE_ENFORCE(platform::is_same_place(place, out_var_handle->place()),
+        PADDLE_ENFORCE_EQ(
+            platform::is_same_place(place, out_var_handle->place()), true,
+            platform::errors::InvalidArgument(
                 "The place of output(%s) is not consistent with the "
                 "place of current op(%s).",
-                       out_var_handle->Name(), Name());
+                out_var_handle->Name(), Name()));
         out_var_handle->SetGenerateEvent(events_.at(dev_id));
       }
     }
@@ -86,7 +91,10 @@ void OpHandleBase::Run(bool use_cuda) {
     InitCUDA();
   }
 #else
-  PADDLE_ENFORCE(!use_cuda);
+  PADDLE_ENFORCE_EQ(use_cuda, false,
+                    platform::errors::InvalidArgument(
+                        "Argument use_cuda should be false when Paddle is not "
+                        "compiled with CUDA."));
 #endif
 
   // skip running current op, used with inplace_addto_op_pass
@@ -100,17 +108,20 @@ void OpHandleBase::Run(bool use_cuda) {
 
 void OpHandleBase::RecordWaitEventOnCtx(platform::DeviceContext *waited_ctx) {
 #ifdef PADDLE_WITH_CUDA
-  PADDLE_ENFORCE_NOT_NULL(waited_ctx);
+  PADDLE_ENFORCE_NOT_NULL(waited_ctx, platform::errors::InvalidArgument(
+                                          "Argument waited_ctx is NULL."));
   if (platform::is_cpu_place(waited_ctx->GetPlace()) || events_.empty()) {
     for (auto &dev_ctx : dev_ctxes_) {
-      PADDLE_ENFORCE_NOT_NULL(dev_ctx.second);
+      PADDLE_ENFORCE_NOT_NULL(
+          dev_ctx.second,
+          platform::errors::InvalidArgument("The device context is NULL."));
       dev_ctx.second->Wait();
     }
   } else {
     auto stream =
         static_cast<platform::CUDADeviceContext *>(waited_ctx)->stream();
     for (auto &ev : events_) {
-      PADDLE_ENFORCE(cudaStreamWaitEvent(stream, ev.second, 0));
+      PADDLE_ENFORCE_CUDA_SUCCESS(cudaStreamWaitEvent(stream, ev.second, 0));
     }
   }
 #else
@@ -145,10 +156,11 @@ void OpHandleBase::WaitInputVarGenerated() {
           auto stream =
               static_cast<platform::CUDADeviceContext *>(dev_ctxes_.at(place))
                   ->stream();
-          PADDLE_ENFORCE(
+          PADDLE_ENFORCE_CUDA_SUCCESS(
               cudaStreamWaitEvent(stream, in_var_handle->GetEvent(), 0));
 #else
-          PADDLE_THROW("Doesn't compile the GPU.");
+          PADDLE_THROW(
+              platform::errors::PreconditionNotMet("Not compiled with CUDA."));
 #endif
         }
         // There are nothing to do when the place is CPUPlace.
@@ -169,10 +181,11 @@ void OpHandleBase::WaitInputVarGenerated(const platform::Place &place) {
           auto stream = static_cast<platform::CUDADeviceContext *>(
                             dev_ctxes_.at(in_var_handle->place()))
                             ->stream();
-          PADDLE_ENFORCE(
+          PADDLE_ENFORCE_CUDA_SUCCESS(
               cudaStreamWaitEvent(stream, in_var_handle->GetEvent(), 0));
 #else
-          PADDLE_THROW("Doesn't compile the GPU.");
+          PADDLE_THROW(
+              platform::errors::PreconditionNotMet("Not compiled with CUDA."));
 #endif
         }
         // There are nothing to do when the place is CPUPlace.
@@ -242,7 +255,9 @@ void OpHandleBase::SetLocalExecScopes(
   auto scopes = GetLocalScopes();
   for (auto *scope : scopes) {
     auto iter = scope_map.find(scope);
-    PADDLE_ENFORCE(iter != scope_map.end(), "Local scope not found");
+    PADDLE_ENFORCE_NE(
+        iter, scope_map.end(),
+        platform::errors::NotFound("Local scope not found in scope map."));
     local_exec_scopes_.emplace_back(iter->second);
   }
 }

paddle/fluid/framework/details/op_registry.h

@@ -21,6 +21,7 @@ limitations under the License. */
 #include <unordered_map>
 #include <unordered_set>
 #include <vector>
+
 #include "paddle/fluid/framework/grad_op_desc_maker.h"
 #include "paddle/fluid/framework/inplace_op_inference.h"
 #include "paddle/fluid/framework/no_need_buffer_vars_inference.h"
@@ -186,19 +187,20 @@ struct OpInfoFiller<T, kOpProtoAndCheckerMaker> {
   void operator()(const char* op_type, OpInfo* info) const {
     PADDLE_ENFORCE_EQ(info->proto_, nullptr,
                       platform::errors::AlreadyExists(
-                          "OpProto of %s has been registered", op_type));
+                          "OpProto of %s has been registered.", op_type));
     PADDLE_ENFORCE_EQ(info->checker_, nullptr,
                       platform::errors::AlreadyExists(
-                          "OpAttrChecker of %s has been registered", op_type));
+                          "OpAttrChecker of %s has been registered.", op_type));
     info->proto_ = new proto::OpProto;
     info->checker_ = new OpAttrChecker();
     T maker;
     maker(info->proto_, info->checker_);
     info->proto_->set_type(op_type);
-    PADDLE_ENFORCE(
-        info->proto_->IsInitialized(),
-        "Fail to initialize %s's OpProto, because %s is not initialized",
-        op_type, info->proto_->InitializationErrorString());
+    PADDLE_ENFORCE_EQ(
+        info->proto_->IsInitialized(), true,
+        platform::errors::PreconditionNotMet(
+            "Fail to initialize %s's OpProto, because %s is not initialized.",
+            op_type, info->proto_->InitializationErrorString()));
   }
 };
 

paddle/fluid/framework/details/reduce_and_gather.h

@@ -16,6 +16,7 @@
 #include <algorithm>
 #include <map>
 #include <vector>
+
 #include "paddle/fluid/framework/details/reduce_and_gather.h"
 #include "paddle/fluid/framework/lod_tensor.h"
 #include "paddle/fluid/framework/selected_rows.h"
@@ -32,9 +33,13 @@ struct ReduceLoDTensor {
 
   template <typename T>
   void apply() const {
-    PADDLE_ENFORCE(!src_tensors_.empty());
+    PADDLE_ENFORCE_NE(src_tensors_.empty(), true,
+                      platform::errors::InvalidArgument(
+                          "The number of tensors to be reduced is 0."));
     auto &t0 = *src_tensors_[0];
-    PADDLE_ENFORCE_NE(t0.numel(), 0);
+    PADDLE_ENFORCE_NE(t0.numel(), 0,
+                      platform::errors::InvalidArgument(
+                          "The size of first tensor to be reduced is 0."));
 
     dst_tensor_.Resize(t0.dims());
     T *dst = dst_tensor_.mutable_data<T>(platform::CPUPlace());
@@ -45,8 +50,19 @@ struct ReduceLoDTensor {
         continue;
       }
 
-      PADDLE_ENFORCE_EQ(t.dims(), t0.dims());
-      PADDLE_ENFORCE_EQ(t.type(), t0.type());
+      PADDLE_ENFORCE_EQ(t.dims(), t0.dims(),
+                        platform::errors::InvalidArgument(
+                            "The shape of tensors to be reduced must be "
+                            "consistent. The shape of current tensor is %s, "
+                            "but the shape of the first tensor is %s.",
+                            t.dims(), t0.dims()));
+
+      PADDLE_ENFORCE_EQ(t.type(), t0.type(),
+                        platform::errors::InvalidArgument(
+                            "The type of tensors to be reduced must be "
+                            "consistent. The type of current tensor is %s, "
+                            "but the type of the first tensor is %s.",
+                            t.type(), t0.type()));
       std::transform(t.data<T>(), t.data<T>() + t.numel(), dst, dst,
                      [](T a, T b) -> T { return a + b; });
     }
@@ -88,7 +104,9 @@ struct GatherLocalSelectedRowsFunctor {
         in_places_(in_places),
         out_place_(out_place),
         dst_selected_rows_(dst_selected_rows) {
-    PADDLE_ENFORCE_EQ(src_selected_rows.empty(), false);
+    PADDLE_ENFORCE_NE(src_selected_rows.empty(), true,
+                      platform::errors::InvalidArgument(
+                          "The number of selected_rows to be gathered is 0."));
 
     std::vector<int64_t> out_rows;
 

paddle/fluid/framework/details/reduce_op_handle.cc

@@ -13,7 +13,9 @@
 // limitations under the License.
 
 #include "paddle/fluid/framework/details/reduce_op_handle.h"
+
 #include <memory>
+
 #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"
@@ -116,8 +118,15 @@ void ReduceOpHandle::GatherSelectedRows(
   merged_dev_ctx->Wait();
   scope->EraseVars(std::vector<std::string>{gathered_var_name});
 
-  PADDLE_ENFORCE(client->Gather(vars, &remote, *merged_dev_ctx, scope));
-  PADDLE_ENFORCE(remote.size() == vars.size());
+  PADDLE_ENFORCE_EQ(
+      client->Gather(vars, &remote, *merged_dev_ctx, scope), true,
+      platform::errors::PreconditionNotMet("Gather SelectedRows failed."));
+  PADDLE_ENFORCE_EQ(remote.size(), vars.size(),
+                    platform::errors::PreconditionNotMet(
+                        "The number of remotes should be equal to the number "
+                        "of variables to be gathered, but got the number of "
+                        "remotes is %d and the number of variables is %d.",
+                        remote.size(), vars.size()));
 
   // 4. merged local selected rows.
   std::vector<const SelectedRows *> all;
@@ -151,14 +160,19 @@ void ReduceOpHandle::RunImpl() {
 
   PADDLE_ENFORCE_EQ(
       in_var_handles.size(), places_.size(),
-      "The number of output should equal to the number of places.");
+      platform::errors::InvalidArgument(
+          "The number of inputs should equal to the number of places, but got "
+          "the number of inputs is %d and the number of places is %d.",
+          in_var_handles.size(), places_.size()));
 
   VarHandle *out_var_handle;
   {
     auto out_var_handles = DynamicCast<VarHandle>(outputs_);
 
     PADDLE_ENFORCE_EQ(out_var_handles.size(), 1UL,
-                      "The number of output should be one.");
+                      platform::errors::InvalidArgument(
+                          "The number of output should be one, but got %d.",
+                          out_var_handles.size()));
     out_var_handle = out_var_handles.front();
   }
 
@@ -168,7 +182,10 @@ void ReduceOpHandle::RunImpl() {
 
   auto pre_in_var =
       var_scopes.at(in_0_handle->scope_idx())->FindVar(in_0_handle->name());
-  PADDLE_ENFORCE_NOT_NULL(pre_in_var);
+
+  PADDLE_ENFORCE_NOT_NULL(pre_in_var, platform::errors::NotFound(
+                                          "Variable %s is not found in scope.",
+                                          in_0_handle->name()));
 
   // NOTE: The Places of all input tensor must be all on CPU or all on GPU.
   std::vector<platform::Place> in_places;  // used to get dev_ctx
@@ -176,21 +193,29 @@ void ReduceOpHandle::RunImpl() {
     in_places.emplace_back(in_handle->place());
     auto in_var =
         var_scopes.at(in_handle->scope_idx())->FindVar(in_handle->name());
-    PADDLE_ENFORCE_NOT_NULL(in_var);
+
+    PADDLE_ENFORCE_NOT_NULL(
+        in_var, platform::errors::NotFound("Variable %s is not found in scope.",
+                                           in_handle->name()));
+
     VariableVisitor::EnforceShapeAndDTypeEQ(*pre_in_var, *in_var);
   }
 
   auto out_var = var_scopes.at(out_var_handle->scope_idx())
                      ->FindVar(out_var_handle->name());
-  PADDLE_ENFORCE_NOT_NULL(out_var);
+
+  PADDLE_ENFORCE_NOT_NULL(
+      out_var, platform::errors::NotFound("Variable %s is not found in scope.",
+                                          out_var_handle->name()));
 
   // NOTE: The tensors' Place of input and output must be all on GPU or all on
   // CPU.
   auto in_p = VariableVisitor::GetMutableTensor(pre_in_var).place();
   platform::Place t_out_p;
   if (platform::is_gpu_place(in_p)) {
-    PADDLE_ENFORCE(platform::is_gpu_place(out_var_handle->place()),
-                   "Places of input and output must be all on GPU.");
+    PADDLE_ENFORCE_EQ(platform::is_gpu_place(out_var_handle->place()), true,
+                      platform::errors::PreconditionNotMet(
+                          "Places of input and output must be all on GPU."));
     t_out_p = out_var_handle->place();
   } else {
     t_out_p = platform::CPUPlace();
@@ -229,7 +254,10 @@ void ReduceOpHandle::RunImpl() {
             in_selected_rows, in_places, dev_ctxes_, out_var_handle, t_out_p,
             out_var->GetMutable<framework::SelectedRows>());
       } else {
-        PADDLE_THROW("only support double or float when gather SelectedRows");
+        PADDLE_THROW(platform::errors::Unimplemented(
+            "Only support double or float when gather SelectedRows, but got "
+            "%s.",
+            framework::DataTypeToString(in_selected_rows[0]->value().type())));
       }
 #endif
     });
@@ -292,7 +320,7 @@ void ReduceOpHandle::RunImpl() {
         size_t numel = static_cast<size_t>(lod_tensor.numel());
         all_reduce_calls.emplace_back(
             [buffer, recvbuffer, type, numel, root_id, &nccl_ctx] {
-              PADDLE_ENFORCE(platform::dynload::ncclReduce(
+              PADDLE_ENFORCE_CUDA_SUCCESS(platform::dynload::ncclReduce(
                   buffer, recvbuffer, numel, static_cast<ncclDataType_t>(type),
                   ncclSum, root_id, nccl_ctx.comm_, nccl_ctx.stream()));
             });
@@ -306,10 +334,13 @@ void ReduceOpHandle::RunImpl() {
         }
       });
 #else
-      PADDLE_THROW("CUDA is not enabled.");
+      PADDLE_THROW(
+          platform::errors::PreconditionNotMet("Not compiled with CUDA."));
 #endif
     } else {
-      PADDLE_THROW("Place should be CPUPlace or CUDAPlace.");
+      PADDLE_THROW(platform::errors::InvalidArgument(
+          "The place of tensor should be CPUPlace or CUDAPlace, but got %s.",
+          lod_tensors[0]->place()));
     }
   }
 }

paddle/fluid/framework/details/reduce_op_handle_test.cc

@@ -13,7 +13,9 @@
 // limitations under the License.
 
 #include "paddle/fluid/framework/details/reduce_op_handle.h"
+
 #include <unordered_map>
+
 #include "gtest/gtest.h"
 #include "paddle/fluid/platform/device_context.h"
 
@@ -69,7 +71,8 @@ struct TestReduceOpHandle {
       }
       nccl_ctxs_.reset(new platform::NCCLContextMap(gpu_list_));
 #else
-      PADDLE_THROW("CUDA is not support.");
+      PADDLE_THROW(
+          platform::errors::PreconditionNotMet("Not compiled with NCLL."));
 #endif
     } else {
       int count = 8;
@@ -103,7 +106,8 @@ struct TestReduceOpHandle {
       op_handle_.reset(new ReduceOpHandle(nodes.back().get(), local_scopes_,
                                           gpu_list_, nccl_ctxs_.get()));
 #else
-      PADDLE_THROW("CUDA is not support.");
+      PADDLE_THROW(
+          platform::errors::PreconditionNotMet("Not compiled with NCLL."));
 #endif
     } else {
 #if defined(PADDLE_WITH_NCCL)
@@ -164,7 +168,10 @@ struct TestReduceOpHandle {
     for (size_t input_scope_idx = 0; input_scope_idx < gpu_list_.size();
          ++input_scope_idx) {
       auto in_var = param_scopes_[input_scope_idx]->FindVar("input");
-      PADDLE_ENFORCE_NOT_NULL(in_var);
+
+      PADDLE_ENFORCE_NOT_NULL(
+          in_var, platform::errors::NotFound(
+                      "Variable %s is not found in scope.", "input"));
       auto in_selected_rows = in_var->GetMutable<f::SelectedRows>();
       auto value = in_selected_rows->mutable_value();
       value->mutable_data<float>(kDims, gpu_list_[input_scope_idx]);
@@ -178,7 +185,9 @@ struct TestReduceOpHandle {
     }
 
     auto out_var = param_scopes_[output_scope_idx]->FindVar("out");
-    PADDLE_ENFORCE_NOT_NULL(out_var);
+    PADDLE_ENFORCE_NOT_NULL(out_var,
+                            platform::errors::NotFound(
+                                "Variable %s is not found in scope.", "out"));
     auto out_selected_rows = out_var->GetMutable<f::SelectedRows>();
 
     auto in_var = param_scopes_[output_scope_idx]->FindVar("input");
@@ -196,9 +205,18 @@ struct TestReduceOpHandle {
     auto &out_select_rows = out_var->Get<f::SelectedRows>();
     auto rt = out_select_rows.value();
 
-    PADDLE_ENFORCE_EQ(out_select_rows.height(), height, "height is not equal.");
+    PADDLE_ENFORCE_EQ(out_select_rows.height(), height,
+                      platform::errors::InvalidArgument(
+                          "The height of SelectedRows is not equal to "
+                          "the expected, expect %d, but got %d.",
+                          height, out_select_rows.height()));
     for (size_t k = 0; k < out_select_rows.rows().size(); ++k) {
-      PADDLE_ENFORCE_EQ(out_select_rows.rows()[k], rows[k % rows.size()]);
+      PADDLE_ENFORCE_EQ(
+          out_select_rows.rows()[k], rows[k % rows.size()],
+          platform::errors::InvalidArgument(
+              "The item at position %d of rows of SelectedRows is not equal to "
+              "the expected, expect %d, but got %d.",
+              k, rows[k % rows.size()], out_select_rows.rows()[k]));
     }
 
     f::Tensor result_tensor;
@@ -208,7 +226,7 @@ struct TestReduceOpHandle {
     for (int64_t j = 0; j < f::product(result_tensor.dims()); ++j) {
       ASSERT_NEAR(ct[j], send_vector[j % send_vector.size()], 1e-5);
     }
-  }
+  }  // namespace details
 
   void TestReduceLodTensors(size_t output_scope_idx) {
     std::vector<float> send_vector(static_cast<size_t>(f::product(kDims)));
@@ -220,7 +238,9 @@ struct TestReduceOpHandle {
     for (size_t input_scope_idx = 0; input_scope_idx < gpu_list_.size();
          ++input_scope_idx) {
       auto in_var = param_scopes_[input_scope_idx]->FindVar("input");
-      PADDLE_ENFORCE_NOT_NULL(in_var);
+      PADDLE_ENFORCE_NOT_NULL(
+          in_var, platform::errors::NotFound(
+                      "Variable %s is not found in scope.", "input"));
       auto in_lod_tensor = in_var->GetMutable<f::LoDTensor>();
       in_lod_tensor->mutable_data<float>(kDims, gpu_list_[input_scope_idx]);
       in_lod_tensor->set_lod(lod);
@@ -230,7 +250,9 @@ struct TestReduceOpHandle {
     }
 
     auto out_var = param_scopes_[output_scope_idx]->FindVar("out");
-    PADDLE_ENFORCE_NOT_NULL(out_var);
+    PADDLE_ENFORCE_NOT_NULL(out_var,
+                            platform::errors::NotFound(
+                                "Variable %s is not found in scope.", "out"));
     auto out_lodtensor = out_var->GetMutable<f::LoDTensor>();
 
     auto in_var = param_scopes_[output_scope_idx]->FindVar("input");
@@ -254,7 +276,7 @@ struct TestReduceOpHandle {
       ASSERT_NEAR(ct[j], send_vector[j] * gpu_list_.size(), 1e-5);
     }
   }
-};
+};  // namespace details
 
 TEST(ReduceTester, TestCPUReduceTestSelectedRows) {
   TestReduceOpHandle test_op;

paddle/fluid/framework/details/share_tensor_buffer_functor.cc

@@ -111,12 +111,11 @@ void ShareTensorBufferFunctor::CallOnce() {
     auto *out_var = exec_scope_->FindVar(out_var_names_[i]);
     PADDLE_ENFORCE_NOT_NULL(
         in_var, platform::errors::NotFound(
-                    "The input variable(%s)to be inplaced should not be NULL.",
+                    "The variable(%s) to be inplaced is not found in scope.",
                     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, platform::errors::NotFound(
+                     "The variable(%s) to be inplaced is not found in scope.",
                      out_var_names_[i]));
     PADDLE_ENFORCE_NE(
         in_var, out_var,

paddle/fluid/framework/details/sparse_all_reduce_op_handle.cc

@@ -12,8 +12,10 @@
 // See the License for the specific language governing permissions and
 // limitations under the License.
 #include "paddle/fluid/framework/details/sparse_all_reduce_op_handle.h"
+
 #include <algorithm>
 #include <utility>
+
 #include "dgc/dgc.h"
 #include "paddle/fluid/framework/details/container_cast.h"
 #include "paddle/fluid/framework/details/reduce_and_gather.h"
@@ -38,18 +40,23 @@ SparseAllReduceOpHandle::SparseAllReduceOpHandle(
       is_encoded_(is_encoded),
       nranks_(nranks) {
   // TODO(gongwb) :polish them!
-  PADDLE_ENFORCE_EQ(is_encoded, true);
+  PADDLE_ENFORCE_EQ(is_encoded, true, platform::errors::InvalidArgument(
+                                          "The argument is_encoded is false."));
   VLOG(1) << "Use dgc allreduce mode"
           << ", nranks:" << nranks_;
 
-  PADDLE_ENFORCE_GT(local_scopes_.size(), 0);
+  PADDLE_ENFORCE_GT(local_scopes_.size(), 0,
+                    platform::errors::PreconditionNotMet(
+                        "The number of local scope should be > 0, but got %zu.",
+                        local_scopes_.size()));
   auto nranks_name = g_dgc_nranks;
   for (size_t i = 0; i < local_scopes_.size(); ++i) {
     auto *local_scope = local_scopes_[i];
     auto nranks_var = local_scope->FindVar(nranks_name);
-    if (nranks_var == nullptr) {
-      PADDLE_THROW("not find nranks_var:%s", nranks_name);
-    }
+
+    PADDLE_ENFORCE_NOT_NULL(
+        nranks_var, platform::errors::NotFound(
+                        "Variable %s is not found in scope.", nranks_name));
 
     float *dgc_nranks = nranks_var->GetMutable<LoDTensor>()->data<float>();
     *dgc_nranks = nranks;
@@ -64,10 +71,18 @@ void SparseAllReduceOpHandle::RunImplEncoded() {
   auto out_var_handles = DynamicCast<VarHandle>(this->Outputs());
   PADDLE_ENFORCE_EQ(
       in_var_handles.size(), places_.size(),
-      "The NoDummyInputSize should be equal to the number of places.");
+      platform::errors::PreconditionNotMet(
+          "The number of input variables should be equal to the number of "
+          "places, but got the number of input variables is %zu and the the "
+          "number of places is %zu.",
+          in_var_handles.size(), places_.size()));
   PADDLE_ENFORCE_EQ(
       in_var_handles.size(), out_var_handles.size(),
-      "The NoDummyInputSize and NoDummyOutputSize should be equal.");
+      platform::errors::PreconditionNotMet(
+          "The number of input variables should be equal to the number of "
+          "output variables, but got the number of input variables is %zu and "
+          "the the number of output variables is %zu.",
+          in_var_handles.size(), out_var_handles.size()));
 
   std::vector<const LoDTensor *> ins;
   std::vector<LoDTensor *> gathers;
@@ -80,14 +95,17 @@ void SparseAllReduceOpHandle::RunImplEncoded() {
 
     auto encode_var_name = original_name + g_dgc_encoded;
     auto *in_var = local_scope->FindVar(encode_var_name);
-    PADDLE_ENFORCE_NOT_NULL(in_var, "%s should not be null", encode_var_name);
+    PADDLE_ENFORCE_NOT_NULL(
+        in_var, platform::errors::NotFound("Variable %s is not found in scope.",
+                                           encode_var_name));
     auto &in = in_var->Get<LoDTensor>();
     ins.emplace_back(&in);
 
     auto gather_var_name = original_name + g_dgc_gather;
     auto *gather_var = local_scope->FindVar(gather_var_name);
-    PADDLE_ENFORCE_NOT_NULL(gather_var, "%s should not be null",
-                            gather_var_name);
+    PADDLE_ENFORCE_NOT_NULL(
+        gather_var, platform::errors::NotFound(
+                        "Variable %s is not found in scope.", gather_var));
     auto *gather = gather_var->GetMutable<LoDTensor>();
     gathers.emplace_back(gather);
 
@@ -100,14 +118,26 @@ void SparseAllReduceOpHandle::RunImplEncoded() {
     }
   }
 
-  PADDLE_ENFORCE(platform::is_gpu_place(ins[0]->place()));
-  PADDLE_ENFORCE(platform::is_gpu_place(outs[0]->place()));
-  PADDLE_ENFORCE(nccl_ctxs_, "nccl_ctxs should not be nullptr.");
+  PADDLE_ENFORCE_EQ(
+      platform::is_gpu_place(ins[0]->place()), true,
+      platform::errors::InvalidArgument(
+          "The place of input variable should be CUDAPlace, but got %s.",
+          ins[0]->place()));
+  PADDLE_ENFORCE_EQ(
+      platform::is_gpu_place(outs[0]->place()), true,
+      platform::errors::InvalidArgument(
+          "The place of input variable should be CUDAPlace, but got %s.",
+          outs[0]->place()));
+  PADDLE_ENFORCE_NOT_NULL(nccl_ctxs_, platform::errors::PreconditionNotMet(
+                                          "The nccl contexts are NULL."));
 
   int dtype = -1;
   size_t in_numel = 0;
   size_t out_numel = 0;
-  PADDLE_ENFORCE(nranks_ > 1);
+  PADDLE_ENFORCE_GT(
+      nranks_, 1,
+      platform::errors::PreconditionNotMet(
+          "The number of ranks should be > 1, but got %d.", nranks_));
   std::vector<std::function<void()>> all_gather_calls;
   std::vector<std::function<void()>> sparse_reduce_calls;
 
@@ -123,8 +153,16 @@ void SparseAllReduceOpHandle::RunImplEncoded() {
 
     dtype = (dtype == -1) ? platform::ToNCCLDataType(in.type()) : dtype;
     in_numel = (in_numel == 0) ? static_cast<size_t>(in.numel()) : in_numel;
-    PADDLE_ENFORCE(in_numel % 2 == 0);
-    PADDLE_ENFORCE(in_numel / 2 == static_cast<size_t>(k));
+    PADDLE_ENFORCE_EQ(in_numel % 2, 0,
+                      platform::errors::InvalidArgument(
+                          "The number of elements of input variable should be "
+                          "even, but got %zu.",
+                          in_numel));
+    PADDLE_ENFORCE_EQ(in_numel / 2, static_cast<size_t>(k),
+                      platform::errors::InvalidArgument(
+                          "The number of elements of input variable should be "
+                          "even, but got %zu.",
+                          in_numel));
     out_numel = (out_numel == 0) ? static_cast<size_t>(out.numel()) : out_numel;
 
     int dev_id = BOOST_GET_CONST(platform::CUDAPlace, place).device;
@@ -154,7 +192,8 @@ void SparseAllReduceOpHandle::RunImplEncoded() {
       PADDLE_ENFORCE_EQ(paddle::communication::dgc::sparseReduce(
                             gather_buff, k, out_tensor_buf,
                             static_cast<int>(out_numel), nranks_, stream),
-                        true);
+                        true, platform::errors::Unavailable(
+                                  "Calling sparseReduce() failed."));
     });
   }
 
@@ -187,11 +226,16 @@ void SparseAllReduceOpHandle::SparseAllReduceFunc(
 int SparseAllReduceOpHandle::GetKValue(const std::string &grad_name) {
   auto original_name = paddle::framework::GradOriginalVarName(grad_name);
   auto var_name = original_name + g_dgc_k;
-  PADDLE_ENFORCE(local_scopes_.size() > 0);
+  PADDLE_ENFORCE_GT(local_scopes_.size(), 0,
+                    platform::errors::PreconditionNotMet(
+                        "The number of local scope should be > 0, but got %zu.",
+                        local_scopes_.size()));
 
   auto *scope = local_exec_scopes_[0];
   auto var = scope->FindVar(var_name);
-  PADDLE_ENFORCE_NOT_NULL(var);
+  PADDLE_ENFORCE_NOT_NULL(
+      var, platform::errors::NotFound("Variable %s is not found in scope.",
+                                      var_name));
   auto tensor = var->Get<LoDTensor>().data<float>();
   return *tensor;
 }
@@ -202,15 +246,22 @@ bool SparseAllReduceOpHandle::IsEncoded() {
   }
   auto counter_name = g_dgc_counter_name;
   auto step_name = g_dgc_rampup_begin_step;
-  PADDLE_ENFORCE(local_scopes_.size() > 0);
+
+  PADDLE_ENFORCE_GT(local_scopes_.size(), 0,
+                    platform::errors::PreconditionNotMet(
+                        "The number of local scope should be > 0, but got %zu.",
+                        local_scopes_.size()));
 
   auto *local_scope = local_exec_scopes_[0];
   auto count_var = local_scope->FindVar(counter_name);
   auto step_var = local_scope->FindVar(step_name);
-  if (count_var == nullptr || step_var == nullptr) {
-    PADDLE_THROW("not find count_var:%s or step_var:%s", counter_name,
-                 step_var);
-  }
+
+  PADDLE_ENFORCE_NOT_NULL(
+      count_var, platform::errors::NotFound(
+                     "Variable %s is not found in scope.", counter_name));
+  PADDLE_ENFORCE_NOT_NULL(
+      step_var, platform::errors::NotFound("Variable %s is not found in scope.",
+                                           step_var));
 
   float count = *count_var->Get<LoDTensor>().data<float>();
   float step = *step_var->Get<LoDTensor>().data<float>();