Move input_size check into RunTime phrase of gru_unit_op and refine error message (#24776)

* Add IsRuntime judgement in GRUUnit test=develop

* add IsRuntime judgement is GradOp test=develop

* Refine Error Message of SelecteInput/Output test=develop

* refine Error Message of RNNMemoryHelperOp test=develop

paddle/fluid/operators/gru_unit_op.cc

@@ -25,19 +25,14 @@ class GRUUnitOp : public framework::OperatorWithKernel {
   using framework::OperatorWithKernel::OperatorWithKernel;
 
   void InferShape(framework::InferShapeContext* ctx) const override {
-    PADDLE_ENFORCE(ctx->HasInput("Input"),
-                   "Input(%s) of GRUUnitOp should not be null.", "Input");
-    PADDLE_ENFORCE(ctx->HasInput("HiddenPrev"),
-                   "Input(%s) of GRUUnitOp should not be null.", "HiddenPrev");
-    PADDLE_ENFORCE(ctx->HasInput("Weight"),
-                   "Input(%s) of GRUUnitOp should not be null.", "Weight");
-    PADDLE_ENFORCE(ctx->HasOutput("Gate"),
-                   "Output(%s) of GRUUnitOp should not be null.", "Gate");
-    PADDLE_ENFORCE(ctx->HasOutput("ResetHiddenPrev"),
-                   "Output(%s) of GRUUnitOp should not be null.",
-                   "ResetHiddenPrev");
-    PADDLE_ENFORCE(ctx->HasOutput("Hidden"),
-                   "Output(%s) of GRUUnitOp should not be null.", "Hidden");
+    OP_INOUT_CHECK(ctx->HasInput("Input"), "Input", "Input", "GRUUnit");
+    OP_INOUT_CHECK(ctx->HasInput("HiddenPrev"), "Input", "HiddenPrev",
+                   "GRUUnit");
+    OP_INOUT_CHECK(ctx->HasInput("Weight"), "Input", "Weight", "GRUUnit");
+    OP_INOUT_CHECK(ctx->HasOutput("Gate"), "Output", "Gate", "GRUUnit");
+    OP_INOUT_CHECK(ctx->HasOutput("ResetHiddenPrev"), "Output",
+                   "ResetHiddenPrev", "GRUUnit");
+    OP_INOUT_CHECK(ctx->HasOutput("Hidden"), "Output", "Hidden", "GRUUnit");
     auto input_dims = ctx->GetInputDim("Input");
     auto hidden_prev_dims = ctx->GetInputDim("HiddenPrev");
     auto weight_dims = ctx->GetInputDim("Weight");
@@ -46,23 +41,45 @@ class GRUUnitOp : public framework::OperatorWithKernel {
     int frame_size = hidden_prev_dims[1];
     int weight_height = weight_dims[0];
     int weight_width = weight_dims[1];
-    PADDLE_ENFORCE_EQ(
-        input_size, frame_size * 3,
-        "The input_size must be 3 times of frame_size in GRUUnitOp.");
+    if (ctx->IsRuntime() || input_size >= 0) {
+      PADDLE_ENFORCE_EQ(input_size, frame_size * 3,
+                        platform::errors::InvalidArgument(
+                            "The second dimension of Input(Input) must be 3 "
+                            "times of frame_size in GRUUnitOp, but received %d "
+                            "(Input) vs %d (frame_size).",
+                            input_size, frame_size));
+    }
     PADDLE_ENFORCE_EQ(
         weight_height, frame_size,
-        "The shape of Weight matrix must be [frame_size, frame_size * 3].");
+        platform::errors::InvalidArgument(
+            "The shape of Input(Weight) matrix must be [frame_size, frame_size "
+            "* 3] in GRUUnitOp, but received [%d, %d] (Weight) vs [%d, %d] "
+            "(frame_size).",
+            weight_height, weight_width, frame_size, frame_size * 3));
     PADDLE_ENFORCE_EQ(
         weight_width, frame_size * 3,
-        "The shape of Weight matrix must be [frame_size, frame_size * 3].");
+        platform::errors::InvalidArgument(
+            "The shape of Input(Weight) matrix must be [frame_size, frame_size "
+            "* 3] in GRUUnitOp, but received [%d, %d] (Weight) vs [%d, %d] "
+            "(frame_size).",
+            weight_height, weight_width, frame_size, frame_size * 3));
+
     if (ctx->HasInput("Bias")) {
       auto bias_dims = ctx->GetInputDim("Bias");
       int bias_height = bias_dims[0];
       int bias_width = bias_dims[1];
-      PADDLE_ENFORCE_EQ(bias_height, 1,
-                        "The shape of Bias must be [1, frame_size * 3].");
-      PADDLE_ENFORCE_EQ(bias_width, frame_size * 3,
-                        "The shape of Bias must be [1, frame_size * 3].");
+      PADDLE_ENFORCE_EQ(
+          bias_height, 1,
+          platform::errors::InvalidArgument(
+              "The shape of Bias must be [1, frame_size * 3], but received "
+              "[%d, %d] (Bias) vs [1, %d] (frame_size * 3).",
+              bias_height, bias_width, frame_size * 3));
+      PADDLE_ENFORCE_EQ(
+          bias_width, frame_size * 3,
+          platform::errors::InvalidArgument(
+              "The shape of Bias must be [1, frame_size * 3], but received "
+              "[%d, %d] (Bias) vs [1, %d] (frame_size * 3).",
+              bias_height, bias_width, frame_size * 3));
     }
     ctx->SetOutputDim("Gate", {batch_size, frame_size * 3});
     ctx->SetOutputDim("ResetHiddenPrev", {batch_size, frame_size});
@@ -143,21 +160,16 @@ class GRUUnitGradOp : public framework::OperatorWithKernel {
   using framework::OperatorWithKernel::OperatorWithKernel;
 
   void InferShape(framework::InferShapeContext* ctx) const override {
-    PADDLE_ENFORCE(ctx->HasInput("Input"),
-                   "Input(%s) of GRUUnitGradOp should not be null.", "Input");
-    PADDLE_ENFORCE(ctx->HasInput("HiddenPrev"),
-                   "Input(%s) of GRUUnitGradOp should not be null.",
-                   "HiddenPrev");
-    PADDLE_ENFORCE(ctx->HasInput("Weight"),
-                   "Input(%s) of GRUUnitGradOp should not be null.", "Weight");
-    PADDLE_ENFORCE(ctx->HasInput("Gate"),
-                   "Input(%s) of GRUUnitGradOp should not be null.", "Gate");
-    PADDLE_ENFORCE(ctx->HasInput("ResetHiddenPrev"),
-                   "Input(%s) of GRUUnitGradOp should not be null.",
-                   "ResetHiddenPrev");
-    PADDLE_ENFORCE(ctx->HasInput(framework::GradVarName("Hidden")),
-                   "Input(%s@GRAD) of GRUUnitGradOp should not be null.",
-                   "Hidden");
+    OP_INOUT_CHECK(ctx->HasInput("Input"), "Input", "Input", "GRUUnitGrad");
+    OP_INOUT_CHECK(ctx->HasInput("HiddenPrev"), "Input", "HiddenPrev",
+                   "GRUUnitGrad");
+    OP_INOUT_CHECK(ctx->HasInput("Weight"), "Input", "Weight", "GRUUnitGrad");
+    OP_INOUT_CHECK(ctx->HasInput("Gate"), "Input", "Gate", "GRUUnitGrad");
+    OP_INOUT_CHECK(ctx->HasInput("ResetHiddenPrev"), "Input", "ResetHiddenPrev",
+                   "GRUUnitGrad");
+    OP_INOUT_CHECK(ctx->HasInput(framework::GradVarName("Hidden")), "Input",
+                   "Hidden@GRAD", "GRUUnitGrad");
+
     auto input_dims = ctx->GetInputDim("Input");
     auto hidden_prev_dims = ctx->GetInputDim("HiddenPrev");
     auto weight_dims = ctx->GetInputDim("Weight");
@@ -166,23 +178,46 @@ class GRUUnitGradOp : public framework::OperatorWithKernel {
     int frame_size = hidden_prev_dims[1];
     int weight_height = weight_dims[0];
     int weight_width = weight_dims[1];
+    if (ctx->IsRuntime() || input_size >= 0) {
       PADDLE_ENFORCE_EQ(
           input_size, frame_size * 3,
-        "The input_size must be 3 times of frame_size in GRUUnitOp.");
+          platform::errors::InvalidArgument(
+              "The second dimension of Input(Input) must be 3 "
+              "times of frame_size in GRUUnitGradOp, but received %d "
+              "(Input) vs %d (frame_size).",
+              input_size, frame_size));
+    }
     PADDLE_ENFORCE_EQ(
         weight_height, frame_size,
-        "The shape of Weight matrix must be [frame_size, frame_size * 3].");
+        platform::errors::InvalidArgument(
+            "The shape of Input(Weight) matrix must be [frame_size, frame_size "
+            "* 3] in GRUUnitGradOp, but received [%d, %d] (Weight) vs [%d, %d] "
+            "(frame_size).",
+            weight_height, weight_width, frame_size, frame_size * 3));
     PADDLE_ENFORCE_EQ(
         weight_width, frame_size * 3,
-        "The shape of Weight matrix must be [frame_size, frame_size * 3].");
+        platform::errors::InvalidArgument(
+            "The shape of Input(Weight) matrix must be [frame_size, frame_size "
+            "* 3] in GRUUnitGradOp, but received [%d, %d] (Weight) vs [%d, %d] "
+            "(frame_size).",
+            weight_height, weight_width, frame_size, frame_size * 3));
     if (ctx->HasInput("Bias")) {
       auto bias_dims = ctx->GetInputDim("Bias");
       int bias_height = bias_dims[0];
       int bias_width = bias_dims[1];
-      PADDLE_ENFORCE_EQ(bias_height, 1,
-                        "The shape of Bias must be [1, frame_size * 3].");
-      PADDLE_ENFORCE_EQ(bias_width, frame_size * 3,
-                        "The shape of Bias must be [1, frame_size * 3].");
+
+      PADDLE_ENFORCE_EQ(
+          bias_height, 1,
+          platform::errors::InvalidArgument(
+              "The shape of Bias must be [1, frame_size * 3], but received "
+              "[%d, %d] (Bias) vs [1, %d] (frame_size * 3).",
+              bias_height, bias_width, frame_size * 3));
+      PADDLE_ENFORCE_EQ(
+          bias_width, frame_size * 3,
+          platform::errors::InvalidArgument(
+              "The shape of Bias must be [1, frame_size * 3], but received "
+              "[%d, %d] (Bias) vs [1, %d] (frame_size * 3).",
+              bias_height, bias_width, frame_size * 3));
       auto bias_grad_name = framework::GradVarName("Bias");
       if (ctx->HasOutput(bias_grad_name))
         ctx->SetOutputDim(bias_grad_name, bias_dims);

paddle/fluid/operators/rnn_memory_helper_op.cc

@@ -30,15 +30,15 @@ class RNNMemoryHelperOp : public framework::OperatorBase {
                const platform::Place &dev_place) const override {
     auto mem_var_name = Input("X");
     auto *mem_var = scope.FindVar(mem_var_name);
-    PADDLE_ENFORCE(mem_var != nullptr,
-                   "Cannot find mem_var in scope, mem_var_name is %s",
-                   mem_var_name);
+    PADDLE_ENFORCE_NOT_NULL(
+        mem_var, platform::errors::NotFound("Cannot find mem_var: %s in scope.",
+                                            mem_var_name));
 
     auto out_name = this->Output("Out");
     auto *out_var = scope.FindVar(out_name);
-    PADDLE_ENFORCE(out_var != nullptr,
-                   "Cannot find out_var in scope, out_var_name is %s",
-                   out_name);
+    PADDLE_ENFORCE_NOT_NULL(
+        out_var, platform::errors::NotFound("Cannot find out_var: %s in scope.",
+                                            out_name));
 
     platform::DeviceContextPool &pool = platform::DeviceContextPool::Instance();
     auto &dev_ctx = *pool.Get(dev_place);
@@ -53,10 +53,9 @@ class RNNMemoryHelperOp : public framework::OperatorBase {
 class RNNMemoryHelperOpShapeInference : public framework::InferShapeBase {
  public:
   void operator()(framework::InferShapeContext *ctx) const override {
-    PADDLE_ENFORCE(ctx->HasInput("X"),
-                   "Input(X) of rnn_memory_helper op should not be null.");
-    PADDLE_ENFORCE(ctx->HasOutput("Out"),
-                   "Output of rnn_memory_helper op should not be null.");
+    OP_INOUT_CHECK(ctx->HasInput("X"), "Input", "X", "RNNMemoryHelper");
+    OP_INOUT_CHECK(ctx->HasOutput("Out"), "Output", "Out", "RNNMemoryHelper");
+
     ctx->ShareDim("X", /*->*/ "Out");
     ctx->ShareLoD("X", /*->*/ "Out");
   }
@@ -91,10 +90,10 @@ class RNNMemoryHelperGradOp : public framework::OperatorBase {
 
     auto in_grad_var_name = Output(framework::GradVarName("X"));
     auto *in_grad_var = scope.FindVar(in_grad_var_name);
-
-    PADDLE_ENFORCE(in_grad_var != nullptr,
-                   "Cannot find in_grad_var in scope, name is %s",
-                   in_grad_var_name);
+    PADDLE_ENFORCE_NOT_NULL(
+        in_grad_var,
+        platform::errors::NotFound("Cannot find in_grad_var: %s in scope.",
+                                   in_grad_var_name));
 
     platform::DeviceContextPool &pool = platform::DeviceContextPool::Instance();
     auto &dev_ctx = *pool.Get(dev_place);
@@ -143,11 +142,9 @@ class RNNMemoryHelperGradOpShapeInference : public framework::InferShapeBase {
  public:
   void operator()(framework::InferShapeContext *ctx) const override {
     auto x_grad_name = framework::GradVarName("X");
-    PADDLE_ENFORCE(ctx->HasOutput(x_grad_name),
-                   "Gradient of Input(X) in rnn_memory_helper_grad of should "
-                   "not be null.");
-    PADDLE_ENFORCE(ctx->HasInput("X"),
-                   "Input(X) of rnn_memory_helper_grad of should not be null.");
+    OP_INOUT_CHECK(ctx->HasInput("X"), "Input", "X", "RNNMemoryHelperGrad");
+    OP_INOUT_CHECK(ctx->HasOutput(x_grad_name), "Output", x_grad_name,
+                   "RNNMemoryHelperGrad");
     ctx->SetOutputDim(x_grad_name, ctx->GetInputDim("X"));
     ctx->ShareLoD("X", /*->*/ x_grad_name);
   }

paddle/fluid/operators/select_input_op.cc

@@ -80,12 +80,9 @@ specifying the output branchi.
 class SelectInputInferShape : public framework::InferShapeBase {
  public:
   void operator()(framework::InferShapeContext *context) const override {
-    PADDLE_ENFORCE_EQ(context->HasInputs("X"), true,
-                      "SelectInputOp must have input X.");
-    PADDLE_ENFORCE_EQ(context->HasInput("Mask"), true,
-                      "SelectInputOp must have input Mask.");
-    PADDLE_ENFORCE_EQ(context->HasOutput("Out"), true,
-                      "SelectInputOp must have output Out.");
+    OP_INOUT_CHECK(context->HasInputs("X"), "Input", "X", "SelectInput");
+    OP_INOUT_CHECK(context->HasInput("Mask"), "Input", "Mask", "SelectInput");
+    OP_INOUT_CHECK(context->HasOutput("Out"), "Output", "Out", "SelectInput");
   }
 };
 

paddle/fluid/operators/select_output_op.cc

@@ -78,12 +78,9 @@ specify which output branch should copy the input.
 class SelectOutputInferShape : public framework::InferShapeBase {
  public:
   void operator()(framework::InferShapeContext *context) const override {
-    PADDLE_ENFORCE_EQ(context->HasInput("X"), true,
-                      "SelectOutputOp must have input X.");
-    PADDLE_ENFORCE_EQ(context->HasInput("Mask"), true,
-                      "SelectOutputOp must have input Mask.");
-    PADDLE_ENFORCE_EQ(context->HasOutputs("Out"), true,
-                      "SelectOutputOp must have output Out.");
+    OP_INOUT_CHECK(context->HasInput("X"), "Input", "X", "SelectOutput");
+    OP_INOUT_CHECK(context->HasInput("Mask"), "Input", "Mask", "SelectOutput");
+    OP_INOUT_CHECK(context->HasOutputs("Out"), "Output", "Out", "SelectOutput");
   }
 };