fix some errmsg report, in framework/ir/mkldnn (#25467)

* fix paddle/fluid/framework/ir/mkldnn/ error msg reoprt, test=develop

* modify error msg reoprt, about errortype, grammar, supplementary infor, test=develop

* modified some error descriptions, test=develop

paddle/fluid/framework/ir/mkldnn/conv_activation_mkldnn_fuse_pass.cc

@@ -22,7 +22,8 @@ namespace framework {
 namespace ir {
 
 void ConvActivationFusePass::ApplyImpl(ir::Graph* graph) const {
-  PADDLE_ENFORCE_NOT_NULL(graph, "graph cannot be nullptr.");
+  PADDLE_ENFORCE_NOT_NULL(
+      graph, platform::errors::InvalidArgument("Graph cannot be nullptr."));
   FusePassBase::Init("conv_activation_mkldnn_fuse", graph);
 
   GraphPatternDetector gpd;
@@ -75,7 +76,8 @@ void ConvActivationFusePass::ApplyImpl(ir::Graph* graph) const {
     GraphSafeRemoveNodes(graph, {activation, conv_out});
 
     PADDLE_ENFORCE_GT(subgraph.count(conv_input), 0UL,
-                      "subgraph has to contain conv_input node.");
+                      platform::errors::InvalidArgument(
+                          "Subgraph has to contain conv input node."));
     IR_NODE_LINK_TO(conv, activation_out);
     found_conv_activation_count++;
   };

paddle/fluid/framework/ir/mkldnn/conv_bias_mkldnn_fuse_pass.cc

@@ -26,7 +26,11 @@ namespace ir {
 template <typename BinaryOperation>
 LoDTensor tensor_apply_eltwise(const LoDTensor& vec_a, const LoDTensor& vec_b,
                                BinaryOperation f) {
-  PADDLE_ENFORCE_EQ(vec_a.dims(), vec_b.dims());
+  PADDLE_ENFORCE_EQ(vec_a.dims(), vec_b.dims(),
+                    platform::errors::InvalidArgument(
+                        "Input two tensors must have same shape, but they are "
+                        "different: %s, %s.",
+                        vec_a.dims(), vec_b.dims()));
   LoDTensor vec_y;
   vec_y.Resize(vec_a.dims());
   const float* a = vec_a.data<float>();
@@ -39,11 +43,13 @@ LoDTensor tensor_apply_eltwise(const LoDTensor& vec_a, const LoDTensor& vec_b,
 }
 
 void ConvBiasFusePass::ApplyImpl(ir::Graph* graph) const {
-  PADDLE_ENFORCE(graph);
+  PADDLE_ENFORCE_NOT_NULL(
+      graph, platform::errors::InvalidArgument("Graph cannot be nullptr."));
   FusePassBase::Init(name_scope_, graph);
 
   auto* scope = param_scope();
-  PADDLE_ENFORCE(scope);
+  PADDLE_ENFORCE_NOT_NULL(
+      scope, platform::errors::InvalidArgument("Scope cannot be nullptr."));
 
   GraphPatternDetector gpd;
   auto* conv_input =
@@ -68,7 +74,9 @@ void ConvBiasFusePass::ApplyImpl(ir::Graph* graph) const {
     // elementwise_add op
     GET_IR_NODE_FROM_SUBGRAPH(eltwise, eltwise, conv_bias_pattern);
 
-    PADDLE_ENFORCE(subgraph.count(conv_input));
+    PADDLE_ENFORCE_NE(
+        subgraph.count(conv_input), 0,
+        platform::errors::NotFound("Detector did not find conv input."));
 
     // check if fuse can be done and if MKL-DNN should be used
     FuseOptions fuse_option = FindFuseOption(*conv, *eltwise);
@@ -86,10 +94,16 @@ void ConvBiasFusePass::ApplyImpl(ir::Graph* graph) const {
     if (has_bias && conv->Op()->Input("Bias").size() > 0) {
       auto conv_bias_names = conv->Op()->Input("Bias");
       // add eltwise bias to existing conv bias
-      PADDLE_ENFORCE_EQ(conv_bias_names.size(), 1);
+      PADDLE_ENFORCE_EQ(conv_bias_names.size(), 1,
+                        platform::errors::NotFound("Can not find var Bias."));
       auto* conv_bias_var = scope->FindVar(conv_bias_names[0]);
       auto* conv_bias_tensor = conv_bias_var->GetMutable<LoDTensor>();
-      PADDLE_ENFORCE_EQ(conv_bias_tensor->dims(), eltwise_bias_tensor->dims());
+      PADDLE_ENFORCE_EQ(
+          conv_bias_tensor->dims(), eltwise_bias_tensor->dims(),
+          platform::errors::InvalidArgument(
+              "Conv bias tensor and eltwise bias tensor "
+              "must have same shape, but they are different: %s, %s.",
+              conv_bias_tensor->dims(), eltwise_bias_tensor->dims()));
       *conv_bias_tensor = tensor_apply_eltwise(
           *conv_bias_tensor, *eltwise_bias_tensor, std::plus<float>());
 

paddle/fluid/framework/ir/mkldnn/conv_concat_relu_mkldnn_fuse_pass.cc

@@ -39,7 +39,10 @@ void ConvConcatReLUFusePass::FindConcatWithConvs(
 
     for (auto node : concat_inputs) {
       auto prev_op_node = node->inputs;
-      PADDLE_ENFORCE_EQ(prev_op_node.size(), 1);
+      PADDLE_ENFORCE_EQ(prev_op_node.size(), 1,
+                        platform::errors::InvalidArgument(
+                            "Node(%s) input size(%d) must be 1.", node->Name(),
+                            prev_op_node.size()));
       auto* conv_op = prev_op_node[0];
       if (conv_op->Op()->Type() != "conv2d") return;
 
@@ -103,7 +106,8 @@ void ConvConcatReLUFusePass::FuseConvConcatReLU(
 }
 
 void ConvConcatReLUFusePass::ApplyImpl(ir::Graph* graph) const {
-  PADDLE_ENFORCE(graph);
+  PADDLE_ENFORCE_NOT_NULL(
+      graph, platform::errors::InvalidArgument("Graph cannot be nullptr."));
   FusePassBase::Init(name_scope_, graph);
 
   std::unordered_map<const Node*, int> concat_with_convs_counter;

paddle/fluid/framework/ir/mkldnn/cpu_quantize_pass.cc

@@ -68,9 +68,9 @@ void CPUQuantizePass::QuantizeInput(Graph* g, Node* op, Node* input,
   auto inputs = op->Op()->InputNames();
   bool name_found =
       std::find(inputs.begin(), inputs.end(), input_name) != inputs.end();
-  PADDLE_ENFORCE_EQ(
-      name_found, true,
-      platform::errors::InvalidArgument("%s isn't the input of the %s operator",
+  PADDLE_ENFORCE_EQ(name_found, true,
+                    platform::errors::InvalidArgument(
+                        "Var(%s) isn't the input of the %s operator.",
                         input_name, op->Op()->Type()));
   unsigned max = is_unsigned ? U8_MAX : S8_MAX;
   float scale = scale_to_one * max;
@@ -110,8 +110,14 @@ void CPUQuantizePass::QuantizeInputs(Graph* g, Node* op, std::string input_name,
                                      std::string scale_attr_name) const {
   auto inputs = op->inputs;
   auto output = op->outputs[0];
-  PADDLE_ENFORCE_GE(inputs.size(), 1);
-  PADDLE_ENFORCE_EQ(op->outputs.size(), 1);
+  PADDLE_ENFORCE_GE(inputs.size(), 1,
+                    platform::errors::InvalidArgument(
+                        "OP(%s)'s inputs(%d) must be equal or greater than 1.",
+                        op->Name(), inputs.size()));
+  PADDLE_ENFORCE_EQ(op->outputs.size(), 1,
+                    platform::errors::InvalidArgument(
+                        "OP(%s)'s outputs(%d) must be equal to 1.", op->Name(),
+                        op->outputs.size()));
 
   // create a quantize op desc prototype
   OpDesc q_desc;
@@ -159,8 +165,8 @@ void CPUQuantizePass::DequantizeOutput(Graph* g, Node* op, Node* output,
       std::find(outputs.begin(), outputs.end(), output_name) != outputs.end();
   PADDLE_ENFORCE_EQ(name_found, true,
                     platform::errors::InvalidArgument(
-                        "%s isn't the output of the %s operator", output_name,
-                        op->Op()->Type()));
+                        "Var(%s) isn't the output of the %s operator.",
+                        output_name, op->Op()->Type()));
   unsigned max = is_unsigned ? U8_MAX : S8_MAX;
   float scale = scale_to_one * max;
 
@@ -682,10 +688,12 @@ void CPUQuantizePass::QuantizeMatmul(Graph* graph) const {
     bool is_x_unsigned{false}, is_y_unsigned{false};
     auto input_x_scale = GetScaleValueForNode(matmul_in_x, &is_x_unsigned);
     auto input_y_scale = GetScaleValueForNode(matmul_in_y, &is_y_unsigned);
-    PADDLE_ENFORCE_EQ(
-        is_x_unsigned, is_y_unsigned,
+    PADDLE_ENFORCE_EQ(is_x_unsigned, is_y_unsigned,
                       platform::errors::InvalidArgument(
-            "Matmul inputs should have the same value of is_unsigned"));
+                          "Matmul inputs should have the same "
+                          "attribute of signed/unsigned, but they "
+                          "are different: x(%d), y(%d).",
+                          is_x_unsigned, is_y_unsigned));
     QuantizeInput(g, matmul_op, matmul_in_x, "X", input_x_scale, is_x_unsigned,
                   "Scale_x");
     QuantizeInput(g, matmul_op, matmul_in_y, "Y", input_y_scale, is_y_unsigned,
@@ -785,10 +793,12 @@ void CPUQuantizePass::QuantizeElementwiseAdd(Graph* graph) const {
 
 void CPUQuantizePass::ApplyImpl(ir::Graph* graph) const {
   VLOG(3) << "Quantizing the graph.";
-  PADDLE_ENFORCE(graph);
+  PADDLE_ENFORCE_NOT_NULL(
+      graph, platform::errors::InvalidArgument("Graph cannot be nullptr."));
   FusePassBase::Init(name_scope_, graph);
 
-  PADDLE_ENFORCE(param_scope());
+  PADDLE_ENFORCE_NOT_NULL(param_scope(), platform::errors::InvalidArgument(
+                                             "Scope cannot be nullptr."));
 
   QuantizeConv(graph, false /* with_residual_data */);
   QuantizeConv(graph, true /* with_residual_data */);

paddle/fluid/framework/ir/mkldnn/cpu_quantize_squash_pass.cc

@@ -75,7 +75,7 @@ void CPUQuantizeSquashPass::DequantQuantSquash(
         BOOST_GET_CONST(float, quant_op->Op()->GetAttr("Scale"));
     PADDLE_ENFORCE_NE(
         nodes_keep_counter->find(dequant_out), nodes_keep_counter->end(),
-        platform::errors::NotFound("The dequant output node is not found"));
+        platform::errors::NotFound("The dequant output node is not found."));
 
     // check if dequantize op should be kept or removed, decrease the counter
     bool keep_dequant = (*nodes_keep_counter)[dequant_out]-- > 1;
@@ -153,8 +153,9 @@ void CPUQuantizeSquashPass::OpRequantSquash(Graph* graph) const {
 
       PADDLE_ENFORCE_NE(
           any_op_output_name.empty(), true,
-          platform::errors::NotFound("Operator before requantize operator "
-                                     "should have requantize input as output"));
+          platform::errors::NotFound("Operator before requantize operator(%s) "
+                                     "should have requantize input as output.",
+                                     requant_in->Name()));
 
       float requant_scale_out =
           BOOST_GET_CONST(float, requant_op->Op()->GetAttr("Scale_out"));
@@ -195,10 +196,11 @@ void CPUQuantizeSquashPass::RequantOpSquash(Graph* graph) const {
         for (auto input_name : any_op->Op()->Input(name))
           if (input_name == requant_out->Name()) any_op_input_name = name;
 
-      PADDLE_ENFORCE_NE(
-          any_op_input_name.empty(), true,
-          platform::errors::NotFound("The operator after requantize operator "
-                                     "should have requantize output as input"));
+      PADDLE_ENFORCE_NE(any_op_input_name.empty(), true,
+                        platform::errors::NotFound(
+                            "The operator after requantize operator(%s) "
+                            "should have requantize output as input.",
+                            requant_out->Name()));
       float requant_scale_in =
           boost::get<float>(requant_op->Op()->GetAttr("Scale_in"));
 
@@ -206,11 +208,14 @@ void CPUQuantizeSquashPass::RequantOpSquash(Graph* graph) const {
       if (any_op->Op()->Type() == "matmul")
         scale_name = any_op_input_name == "X" ? "Scale_x" : "Scale_y";
 
-      PADDLE_ENFORCE_EQ(requant_op->Op()->GetAttrIfExists<float>("Scale_out"),
+      PADDLE_ENFORCE_EQ(
+          requant_op->Op()->GetAttrIfExists<float>("Scale_out"),
           any_op->Op()->GetAttrIfExists<float>(scale_name),
           platform::errors::InvalidArgument(
               "The operator after requantize should have input "
-                            "scale equal to requantize output scale"));
+              "scale(%f) equal to requantize output scale(%f).",
+              any_op->Op()->GetAttrIfExists<float>(scale_name),
+              requant_op->Op()->GetAttrIfExists<float>("Scale_out")));
       any_op->Op()->SetAttr(scale_name, requant_scale_in);
       any_op->Op()->SetInput(any_op_input_name,
                              std::vector<std::string>({requant_in->Name()}));
@@ -286,8 +291,9 @@ void CPUQuantizeSquashPass::MultipleQuantizeSquash(Graph* graph) const {
     auto* first_quant_out = first_quant_op->outputs[0];
     float scale = first_quant_op->Op()->GetAttrIfExists<float>("Scale");
 
-    PADDLE_ENFORCE_NE(scale, 0, platform::errors::InvalidArgument(
-                                    "Quantize scale should not be equal 0"));
+    PADDLE_ENFORCE_NE(scale, 0,
+                      platform::errors::InvalidArgument(
+                          "Quantize scale(%f) should not be equal 0.", scale));
 
     for (int iter = prev_out->outputs.size() - 1; iter >= 0; iter--) {
       auto quant_op = prev_out->outputs[iter];
@@ -304,8 +310,9 @@ void CPUQuantizeSquashPass::MultipleQuantizeSquash(Graph* graph) const {
 
         PADDLE_ENFORCE_NE(
             last_op_input_name.empty(), true,
-            platform::errors::NotFound("Operator after quantize operator "
-                                       "should has quantize output as input"));
+            platform::errors::NotFound("Operator after quantize operator(%s) "
+                                       "should has quantize output as input.",
+                                       quant_out->Name()));
         last_op->Op()->SetInput(
             last_op_input_name,
             std::vector<std::string>({first_quant_out->Name()}));
@@ -345,10 +352,12 @@ void CPUQuantizeSquashPass::DequantScaleSquash(Graph* graph) const {
 
       PADDLE_ENFORCE_GT(dequant_scale, 0.0f,
                         platform::errors::InvalidArgument(
-                            "Dequantize scale should have positive value"));
+                            "Dequantize scale(%f) should have positive value.",
+                            dequant_scale));
       PADDLE_ENFORCE_GT(scale_scale, 0.0f,
                         platform::errors::InvalidArgument(
-                            "Scale of scale op should have positive value"));
+                            "Scale(%f) of scale op should have positive value.",
+                            scale_scale));
 
       dequant_op->Op()->SetAttr("Scale", dequant_scale / scale_scale);
       dequant_op->Op()->SetOutput(
@@ -367,8 +376,8 @@ void CPUQuantizeSquashPass::DequantScaleSquash(Graph* graph) const {
 void CPUQuantizeSquashPass::ApplyImpl(ir::Graph* graph) const {
   PADDLE_ENFORCE_NOT_NULL(
       graph,
-      platform::errors::NotFound(
-          "The graph in function CPUQuantizeSquashPass::ApplyImpl is null"));
+      platform::errors::InvalidArgument(
+          "The graph in function CPUQuantizeSquashPass::ApplyImpl is null."));
   FusePassBase::Init("cpu_quantize_squash_pass", graph);
 
   std::unordered_map<const Node*, int> nodes_keep_counter;

paddle/fluid/framework/ir/mkldnn/cpu_quantize_squash_pass_tester.cc

@@ -57,7 +57,7 @@ void SetOp(ProgramDesc* prog, const std::string& type, const std::string& name,
     PADDLE_ENFORCE_EQ(inputs.size(), 2UL,
                       platform::errors::InvalidArgument(
                           "The fc inputs should contain input and weights, but "
-                          "now the size of inputs is %d",
+                          "now the size of inputs is %d.",
                           inputs.size()));
     op->SetInput("W", {inputs[1]});
     op->SetOutput("Out", outputs);

paddle/fluid/framework/ir/mkldnn/depthwise_conv_mkldnn_pass.cc

@@ -20,13 +20,16 @@ namespace framework {
 namespace ir {
 
 #define GET_NODE(id, pattern)                                     \
-  PADDLE_ENFORCE(subgraph.count(pattern.RetrieveNode(#id)), \
-                 "pattern has no Node called %s", #id);     \
+  PADDLE_ENFORCE_NE(subgraph.count(pattern.RetrieveNode(#id)), 0, \
+                    platform::errors::InvalidArgument(            \
+                        "Pattern has no Node called %s.", #id));  \
   auto* id = subgraph.at(pattern.RetrieveNode(#id));              \
-  PADDLE_ENFORCE_NOT_NULL(id, "subgraph has no node %s", #id);
+  PADDLE_ENFORCE_NOT_NULL(                                        \
+      id, platform::errors::InvalidArgument("Subgraph has no node %s.", #id));
 
 void DepthwiseConvMKLDNNPass::ApplyImpl(ir::Graph* graph) const {
-  PADDLE_ENFORCE(graph);
+  PADDLE_ENFORCE_NOT_NULL(
+      graph, platform::errors::InvalidArgument("Graph cannot be nullptr."));
   FusePassBase::Init("depthwise_conv_mkldnn_pass", graph);
   GraphPatternDetector gpd;
 

paddle/fluid/framework/ir/mkldnn/scale_matmul_fuse_pass.cc

@@ -46,12 +46,15 @@ void ScaleMatmulFusePass::ApplyImpl(ir::Graph* graph) const {
     if (scale_op->Op()->GetAttrIfExists<float>("bias") == 0.0) {
       auto matmul_alpha = matmul_op->Op()->GetAttrIfExists<float>("alpha");
       auto scale_scale = scale_op->Op()->GetAttrIfExists<float>("scale");
-      PADDLE_ENFORCE_GT(matmul_alpha, 0.0f,
+      PADDLE_ENFORCE_GT(
+          matmul_alpha, 0.0f,
           platform::errors::InvalidArgument(
-                            "Alpha of matmul op should have positive value"));
+              "Alpha(%f) of matmul op should have positive value.",
+              matmul_alpha));
       PADDLE_ENFORCE_GT(scale_scale, 0.0f,
                         platform::errors::InvalidArgument(
-                            "Scale of scale op should have positive value"));
+                            "Scale(%f) of scale op should have positive value.",
+                            scale_scale));
 
       std::string matmul_op_input_name;
       for (auto name : matmul_op->Op()->InputNames())
@@ -60,8 +63,9 @@ void ScaleMatmulFusePass::ApplyImpl(ir::Graph* graph) const {
 
       PADDLE_ENFORCE_NE(
           matmul_op_input_name.empty(), true,
-          platform::errors::NotFound("Operator after scale operator "
-                                     "should have scale output as input"));
+          platform::errors::NotFound("Operator after scale operator(%s) "
+                                     "should have scale output as input.",
+                                     scale_out->Name()));
       matmul_op->Op()->SetAttr("alpha", matmul_alpha * scale_scale);
       matmul_op->Op()->SetInput(matmul_op_input_name,
                                 std::vector<std::string>({scale_in->Name()}));