refine fusion gru infershape

Author: tensor-tang

paddle/fluid/operators/fusion_gru_op.cc

@@ -15,6 +15,7 @@ limitations under the License. */
 #include "paddle/fluid/operators/fusion_gru_op.h"
 #include <cstring>  // for memcpy
 #include <string>
+#include "paddle/fluid/framework/shape_runtime_infer.h"
 #include "paddle/fluid/operators/math/blas.h"
 #include "paddle/fluid/operators/math/cpu_vec.h"
 #include "paddle/fluid/operators/math/fc_compute.h"
@@ -25,14 +26,46 @@ 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("WeightX"),
-                 "Input(WeightX) of GRU should not be null.");
-  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.");
-  PADDLE_ENFORCE(ctx->HasOutput("Hidden"),
-                 "Output(Hidden) of GRU should not be null.");
+  auto* runtime_ctx = dynamic_cast<framework::RuntimeInferShapeContext*>(ctx);
+  if (runtime_ctx == nullptr) {
+    LOG(FATAL) << "Should have runtime infer context";
+  }
+  const auto& ins = runtime_ctx->OpBase().Inputs();
+  const auto& outs = runtime_ctx->OpBase().Outputs();
+  const auto& scope = runtime_ctx->InferScope();
+  const auto ins_end = ins.end();
+  const auto outs_end = outs.end();
+  auto fair_input = [&](const std::string& name) -> bool {
+    auto it = ins.find(name);
+    if (it == ins_end) {
+      return false;
+    }
+    const auto& in = it->second;
+    if (in.size() != 1 || in[0] == framework::kEmptyVarName) {
+      return false;
+    }
+    return scope.FindVar(in[0]) != nullptr;
+  };
+  auto fair_output = [&](const std::string& name) -> bool {
+    auto it = outs.find(name);
+    if (it == outs_end) {
+      return false;
+    }
+    const auto& out = it->second;
+    if (out.size() != 1 || out[0] == framework::kEmptyVarName) {
+      return false;
+    }
+    return scope.FindVar(out[0]) != nullptr;
+  };
+
+  PADDLE_ENFORCE(fair_input("X"), "Assert only one Input(X) of GRU.");
+  PADDLE_ENFORCE(fair_input("WeightX"),
+                 "Assert only one Input(WeightX) of GRU.");
+  PADDLE_ENFORCE(fair_input("WeightH"),
+                 "Assert only one Input(WeightH) of GRU.");
+  PADDLE_ENFORCE(fair_output("XX"), "Assert only one Output(XX) of GRU.");
+  PADDLE_ENFORCE(fair_output("Hidden"),
+                 "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.");
@@ -58,12 +91,12 @@ void FusionGRUOp::InferShape(framework::InferShapeContext* ctx) const {
                     "should be 3 * %d.",
                     frame_size);
 
-  if (ctx->HasInput("H0")) {
+  if (fair_input("H0")) {
     auto h0_dims = ctx->GetInputDim("H0");
     PADDLE_ENFORCE_EQ(h0_dims[1], frame_size,
                       "The width of H0 must be equal to frame_size.");
   }
-  if (ctx->HasInput("Bias")) {
+  if (fair_input("Bias")) {
     auto b_dims = ctx->GetInputDim("Bias");
     PADDLE_ENFORCE_EQ(b_dims.size(), 2, "The rank of Input(Bias) should be 2.");
     PADDLE_ENFORCE_EQ(b_dims[0], 1,
@@ -79,12 +112,12 @@ void FusionGRUOp::InferShape(framework::InferShapeContext* ctx) const {
     xx_width = wx_dims[1];
   } 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.");
-    PADDLE_ENFORCE(ctx->HasOutput("BatchedInput"),
-                   "Output(BatchedInput) of GRU should not be null.");
-    PADDLE_ENFORCE(ctx->HasOutput("BatchedOut"),
-                   "Output(BatchedOut) of GRU should not be null.");
+    PADDLE_ENFORCE(fair_output("ReorderedH0"),
+                   "Assert only one Output(ReorderedH0) of GRU.");
+    PADDLE_ENFORCE(fair_output("BatchedInput"),
+                   "Assert only one Output(BatchedInput) of GRU.");
+    PADDLE_ENFORCE(fair_output("BatchedOut"),
+                   "Assert only one Output(BatchedOut) of GRU.");
     ctx->SetOutputDim("BatchedInput", {x_dims[0], wx_dims[1]});
     ctx->SetOutputDim("BatchedOut", out_dims);
   }