Merge pull request #13346 from tensor-tang/refine/infershape

Refine/infershape

paddle/fluid/framework/operator.cc

@@ -464,35 +464,35 @@ class RuntimeInferShapeContext : public InferShapeContext {
       : op_(op), scope_(scope) {}
 
   bool HasInput(const std::string& name) const override {
-    if (!op_.HasInputs(name)) {
+    // has only one input
+    const auto& ins = op_.Inputs();
+    auto it = ins.find(name);
+    if (it == ins.end()) {
       return false;
     }
-    auto& ins = Inputs(name);
-    size_t length = ins.size();
-    if (length == 0) {
+    const auto& in = it->second;
+    if (in.size() == 0 || in[0] == kEmptyVarName) {
       return false;
     }
-    PADDLE_ENFORCE_EQ(length, 1UL,
+    PADDLE_ENFORCE_EQ(in.size(), 1UL,
                       "Input %s should not have more than one inputs", name);
-    auto ipt = ins[0];
-    auto* var = ipt == kEmptyVarName ? nullptr : scope_.FindVar(ipt);
-    return var != nullptr;
+    return scope_.FindVar(in[0]) != nullptr;
   }
 
   bool HasOutput(const std::string& name) const override {
-    if (!op_.HasOutputs(name)) {
+    // has only one output
+    const auto& outs = op_.Outputs();
+    auto it = outs.find(name);
+    if (it == outs.end()) {
       return false;
     }
-    auto& outs = Outputs(name);
-    size_t length = outs.size();
-    if (length == 0) {
+    const auto& out = it->second;
+    if (out.size() == 0 || out[0] == kEmptyVarName) {
       return false;
     }
-    PADDLE_ENFORCE_EQ(length, 1UL,
-                      "Output %s should not have more than one inputs", name);
-    auto ipt = outs[0];
-    auto* var = ipt == kEmptyVarName ? nullptr : scope_.FindVar(ipt);
-    return var != nullptr;
+    PADDLE_ENFORCE_EQ(out.size(), 1UL,
+                      "Output %s should not have more than one outputs", name);
+    return scope_.FindVar(out[0]) != nullptr;
   }
 
   bool HasInputs(const std::string& name) const override {

paddle/fluid/operators/attention_lstm_op.cc

@@ -24,28 +24,28 @@ namespace operators {
 
 void AttentionLSTMOp::InferShape(framework::InferShapeContext* ctx) const {
   PADDLE_ENFORCE(ctx->HasInput("X"),
-                 "Input(X) of AttentionLSTM should not be null.");
+                 "Assert only one Input(X) of AttentionLSTM.");
   PADDLE_ENFORCE(ctx->HasInput("C0"),
-                 "Input(C0) of AttentionLSTM should not be null.");
+                 "Assert only one Input(C0) of AttentionLSTM.");
   PADDLE_ENFORCE(ctx->HasInput("LSTMWeight"),
-                 "Input(LSTMWeight) of AttentionLSTM should not be null.");
+                 "Assert only one Input(LSTMWeight) of AttentionLSTM.");
   PADDLE_ENFORCE(ctx->HasInput("LSTMBias"),
-                 "Input(LSTMBias) of AttentionLSTM should not be null.");
+                 "Assert only one Input(LSTMBias) of AttentionLSTM.");
   PADDLE_ENFORCE(ctx->HasInput("AttentionWeight"),
-                 "Input(AttentionWeight) of AttentionLSTM should not be null.");
+                 "Assert only one Input(AttentionWeight) of AttentionLSTM.");
 
   PADDLE_ENFORCE(ctx->HasOutput("Hidden"),
-                 "Output(Hidden) of AttentionLSTM should not be null.");
+                 "Assert only one Output(Hidden) of AttentionLSTM.");
   PADDLE_ENFORCE(ctx->HasOutput("Cell"),
-                 "Output(Cell) of AttentionLSTM should not be null.");
+                 "Assert only one Output(Cell) of AttentionLSTM.");
   PADDLE_ENFORCE(ctx->HasOutput("AttentionedX"),
-                 "Output(AttentionedX) of AttentionLSTM should not be null.");
+                 "Assert only one Output(AttentionedX) of AttentionLSTM.");
   PADDLE_ENFORCE(ctx->HasOutput("AttentionFCOut"),
-                 "Output(AttentionFCOut) of AttentionLSTM should not be null.");
+                 "Assert only one Output(AttentionFCOut) of AttentionLSTM.");
   PADDLE_ENFORCE(ctx->HasOutput("LSTMX"),
-                 "Output(LSTMX) of AttentionLSTM should not be null.");
+                 "Assert only one Output(LSTMX) of AttentionLSTM.");
   PADDLE_ENFORCE(ctx->HasOutput("LSTMOUT"),
-                 "Output(LSTMOUT) of AttentionLSTM should not be null.");
+                 "Assert only one Output(LSTMOUT) of AttentionLSTM.");
 
   auto x_dims = ctx->GetInputDim("X");
   const int M = x_dims[1];

paddle/fluid/operators/fusion_gru_op.cc

@@ -25,14 +25,14 @@ namespace paddle {
 namespace operators {
 
 void FusionGRUOp::InferShape(framework::InferShapeContext* ctx) const {
-  PADDLE_ENFORCE(ctx->HasInput("X"), "Input(X) of GRU should not be null.");
+  PADDLE_ENFORCE(ctx->HasInput("X"), "Assert only one Input(X) of GRU.");
   PADDLE_ENFORCE(ctx->HasInput("WeightX"),
-                 "Input(WeightX) of GRU should not be null.");
+                 "Assert only one Input(WeightX) of GRU.");
   PADDLE_ENFORCE(ctx->HasInput("WeightH"),
-                 "Input(WeightH) of GRU should not be null.");
-  PADDLE_ENFORCE(ctx->HasOutput("XX"), "Output(XX) of GRU should not be null.");
+                 "Assert only one Input(WeightH) of GRU.");
+  PADDLE_ENFORCE(ctx->HasOutput("XX"), "Assert only one Output(XX) of GRU.");
   PADDLE_ENFORCE(ctx->HasOutput("Hidden"),
-                 "Output(Hidden) of GRU should not be null.");
+                 "Assert only one Output(Hidden) of GRU.");
 
   auto x_dims = ctx->GetInputDim("X");
   PADDLE_ENFORCE_EQ(x_dims.size(), 2, "Input(X)'s rank must be 2.");
@@ -80,11 +80,11 @@ void FusionGRUOp::InferShape(framework::InferShapeContext* ctx) const {
   } else {
     xx_width = x_dims[1] > wx_dims[1] ? wx_dims[1] : x_dims[1];
     PADDLE_ENFORCE(ctx->HasOutput("ReorderedH0"),
-                   "Output(ReorderedH0) of GRU should not be null.");
+                   "Assert only one Output(ReorderedH0) of GRU.");
     PADDLE_ENFORCE(ctx->HasOutput("BatchedInput"),
-                   "Output(BatchedInput) of GRU should not be null.");
+                   "Assert only one Output(BatchedInput) of GRU.");
     PADDLE_ENFORCE(ctx->HasOutput("BatchedOut"),
-                   "Output(BatchedOut) of GRU should not be null.");
+                   "Assert only one Output(BatchedOut) of GRU.");
     ctx->SetOutputDim("BatchedInput", {x_dims[0], wx_dims[1]});
     ctx->SetOutputDim("BatchedOut", out_dims);
   }

paddle/fluid/operators/fusion_lstm_op.cc

@@ -24,20 +24,17 @@ namespace paddle {
 namespace operators {
 
 void FusionLSTMOp::InferShape(framework::InferShapeContext* ctx) const {
-  PADDLE_ENFORCE(ctx->HasInput("X"), "Input(X) of LSTM should not be null.");
+  PADDLE_ENFORCE(ctx->HasInput("X"), "Assert only one Input(X) of LSTM.");
   PADDLE_ENFORCE(ctx->HasInput("WeightX"),
-                 "Input(WeightX) of LSTM should not be null.");
+                 "Assert only one Input(WeightX) of LSTM.");
   PADDLE_ENFORCE(ctx->HasInput("WeightH"),
-                 "Input(WeightH) of LSTM should not be null.");
-  PADDLE_ENFORCE(ctx->HasInput("Bias"),
-                 "Input(Bias) of LSTM should not be null.");
-
-  PADDLE_ENFORCE(ctx->HasOutput("XX"),
-                 "Output(XX) of LSTM should not be null.");
+                 "Assert only one Input(WeightH) of LSTM.");
+  PADDLE_ENFORCE(ctx->HasInput("Bias"), "Assert only one Input(Bias) of LSTM.");
+  PADDLE_ENFORCE(ctx->HasOutput("XX"), "Assert only one Output(XX) of LSTM.");
   PADDLE_ENFORCE(ctx->HasOutput("Hidden"),
-                 "Output(Hidden) of LSTM should not be null.");
+                 "Assert only one Output(Hidden) of LSTM.");
   PADDLE_ENFORCE(ctx->HasOutput("Cell"),
-                 "Output(Cell) of LSTM should not be null.");
+                 "Assert only one Output(Cell) of LSTM.");
 
   auto x_dims = ctx->GetInputDim("X");
   PADDLE_ENFORCE_EQ(x_dims.size(), 2, "Input(X)'s rank must be 2.");
@@ -96,15 +93,15 @@ void FusionLSTMOp::InferShape(framework::InferShapeContext* ctx) const {
   } else {
     xx_width = x_dims[1] > wx_dims[1] ? wx_dims[1] : x_dims[1];
     PADDLE_ENFORCE(ctx->HasOutput("BatchedInput"),
-                   "Output(BatchedInput) of LSTM should not be null.");
+                   "Assert only one Output(BatchedInput) of LSTM.");
     PADDLE_ENFORCE(ctx->HasOutput("BatchedHidden"),
-                   "Output(BatchedHidden) of LSTM should not be null.");
+                   "Assert only one Output(BatchedHidden) of LSTM.");
     PADDLE_ENFORCE(ctx->HasOutput("BatchedCell"),
-                   "Output(BatchedCell) of LSTM should not be null.");
+                   "Assert only one Output(BatchedCell) of LSTM.");
     PADDLE_ENFORCE(ctx->HasOutput("ReorderedH0"),
-                   "Output(ReorderedH0) of LSTM should not be null.");
+                   "Assert only one Output(ReorderedH0) of LSTM");
     PADDLE_ENFORCE(ctx->HasOutput("ReorderedC0"),
-                   "Output(ReorderedC0) of LSTM should not be null.");
+                   "Assert only one Output(ReorderedC0) of LSTM.");
     ctx->SetOutputDim("BatchedInput", {x_dims[0], wx_dims[1]});
     ctx->SetOutputDim("BatchedHidden", out_dims);
     ctx->SetOutputDim("BatchedCell", out_dims);