refine infershape hasinput and hasoutput

Author: tensor-tang

paddle/fluid/framework/operator.cc

@@ -21,7 +21,6 @@ limitations under the License. */
 #include "paddle/fluid/framework/lod_tensor.h"
 #include "paddle/fluid/framework/operator.h"
 #include "paddle/fluid/framework/shape_inference.h"
-#include "paddle/fluid/framework/shape_runtime_infer.h"
 #include "paddle/fluid/framework/var_type.h"
 #include "paddle/fluid/platform/profiler.h"
 
@@ -459,147 +458,184 @@ bool OpSupportGPU(const std::string& op_type) {
   return false;
 }
 
-bool RuntimeInferShapeContext::HasInput(const std::string& name) const {
-  if (!op_.HasInputs(name)) {
-    return false;
-  }
-  auto& ins = Inputs(name);
-  size_t length = ins.size();
-  if (length == 0) {
-    return false;
-  }
-  PADDLE_ENFORCE_EQ(length, 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;
-}
+class RuntimeInferShapeContext : public InferShapeContext {
+ public:
+  RuntimeInferShapeContext(const OperatorBase& op, const Scope& scope)
+      : op_(op), scope_(scope) {}
 
-bool RuntimeInferShapeContext::HasOutput(const std::string& name) const {
-  if (!op_.HasOutputs(name)) {
-    return false;
-  }
-  auto& outs = Outputs(name);
-  size_t length = outs.size();
-  if (length == 0) {
-    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;
-}
+  bool HasInput(const std::string& name) const override {
+    // has only one input
+    const auto& ins = op_.Inputs();
+    auto it = ins.find(name);
+    if (it == ins.end()) {
+      return false;
+    }
+    const auto& in = it->second;
 
-bool RuntimeInferShapeContext::HasInputs(const std::string& name) const {
-  if (!op_.HasInputs(name)) {
-    return false;
-  }
-  auto inputs = op_.Inputs(name);
-  if (inputs.empty()) {
-    return false;
-  }
-  for (auto& input : inputs) {
-    if (scope_.FindVar(input) == nullptr) {
+    if (in.size() != 1 || in[0] == kEmptyVarName) {
       return false;
     }
+    return scope_.FindVar(in[0]) != nullptr;
   }
-  return true;
-}
 
-bool RuntimeInferShapeContext::HasOutputs(const std::string& name) const {
-  if (!op_.HasOutputs(name)) {
-    return false;
+  bool HasOutput(const std::string& name) const override {
+    // has only one output
+    const auto& outs = op_.Outputs();
+    auto it = outs.find(name);
+    if (it == outs.end()) {
+      return false;
+    }
+    const auto& out = it->second;
+    if (out.size() != 1 || out[0] == kEmptyVarName) {
+      return false;
+    }
+    return scope_.FindVar(out[0]) != nullptr;
   }
-  auto outputs = op_.Outputs(name);
-  if (outputs.empty()) {
-    return false;
+
+  bool HasInputs(const std::string& name) const override {
+    if (!op_.HasInputs(name)) {
+      return false;
+    }
+    auto inputs = op_.Inputs(name);
+    if (inputs.empty()) {
+      return false;
+    }
+    for (auto& input : inputs) {
+      if (scope_.FindVar(input) == nullptr) {
+        return false;
+      }
+    }
+    return true;
   }
-  for (auto& output : outputs) {
-    if (scope_.FindVar(output) == nullptr) {
+
+  bool HasOutputs(const std::string& name) const override {
+    if (!op_.HasOutputs(name)) {
+      return false;
+    }
+    auto outputs = op_.Outputs(name);
+    if (outputs.empty()) {
       return false;
     }
+    for (auto& output : outputs) {
+      if (scope_.FindVar(output) == nullptr) {
+        return false;
+      }
+    }
+    return true;
   }
-  return true;
-}
 
-void RuntimeInferShapeContext::ShareLoD(const std::string& in,
-                                        const std::string& out, size_t i,
-                                        size_t j) const {
-  PADDLE_ENFORCE_LT(i, Inputs(in).size());
-  PADDLE_ENFORCE_LT(j, Outputs(out).size());
-  Variable* in_var = scope_.FindVar(Inputs(in)[i]);
-  Variable* out_var = scope_.FindVar(Outputs(out)[j]);
-  if (!in_var->IsType<LoDTensor>()) return;
-  PADDLE_ENFORCE(out_var->IsType<LoDTensor>(),
-                 "The %d-th output of Output(%s) must be LoDTensor.", j, out);
-  auto in_tensor = in_var->Get<LoDTensor>();
-  auto* out_tensor = out_var->GetMutable<LoDTensor>();
-  out_tensor->set_lod(in_tensor.lod());
+  AttrReader Attrs() const override { return AttrReader(op_.Attrs()); }
+
+  const std::vector<std::string>& Inputs(
+      const std::string& name) const override {
+    return op_.Inputs(name);
+  }
+
+  const std::vector<std::string>& Outputs(
+      const std::string& name) const override {
+    return op_.Outputs(name);
+  }
+
+  void ShareLoD(const std::string& in, const std::string& out, size_t i = 0,
+                size_t j = 0) const override {
+    PADDLE_ENFORCE_LT(i, Inputs(in).size());
+    PADDLE_ENFORCE_LT(j, Outputs(out).size());
+    Variable* in_var = scope_.FindVar(Inputs(in)[i]);
+    Variable* out_var = scope_.FindVar(Outputs(out)[j]);
+    if (!in_var->IsType<LoDTensor>()) return;
+    PADDLE_ENFORCE(out_var->IsType<LoDTensor>(),
+                   "The %d-th output of Output(%s) must be LoDTensor.", j, out);
+    auto in_tensor = in_var->Get<LoDTensor>();
+    auto* out_tensor = out_var->GetMutable<LoDTensor>();
+    out_tensor->set_lod(in_tensor.lod());
 
 // TODO(dzhwinter) : reuse ShareLoD in most operators.
 // Need to call ShareLayout explicitly in sequence related ops.
 // Shall we have a better method to shared info between in/out Tensor?
 #ifdef PADDLE_WITH_MKLDNN
-  // Fix me: ugly workaround below
-  // Correct solution:
-  //    set_layout() should NOT be called here (i.e. ShareLoD). Instead,
-  //    layout of output tensor should be set "manually" in Compute()
-  //    of each OPKernel. The reason layout should NOT be shared between
-  //    input and output "automatically" (now by InferShape()->ShareLoD())
-  //    is that layout transform may occur after InferShape().
-  // Workaround:
-  //    Skip set_layout() when input layout is kMKLDNN
-  //    This is to avoid kMKLDNN is populated wrongly into a non-MKLDNN
-  //    OPKernel. In all MKLDNN OPkernel, set_layout(kMKLDNN) should be called
-  //    in Compute()
-  if (in_tensor.layout() != DataLayout::kMKLDNN)
+    // Fix me: ugly workaround below
+    // Correct solution:
+    //    set_layout() should NOT be called here (i.e. ShareLoD). Instead,
+    //    layout of output tensor should be set "manually" in Compute()
+    //    of each OPKernel. The reason layout should NOT be shared between
+    //    input and output "automatically" (now by InferShape()->ShareLoD())
+    //    is that layout transform may occur after InferShape().
+    // Workaround:
+    //    Skip set_layout() when input layout is kMKLDNN
+    //    This is to avoid kMKLDNN is populated wrongly into a non-MKLDNN
+    //    OPKernel. In all MKLDNN OPkernel, set_layout(kMKLDNN) should be called
+    //    in Compute()
+    if (in_tensor.layout() != DataLayout::kMKLDNN)
 #endif
+      out_tensor->set_layout(in_tensor.layout());
+  }
+
+  void ShareLayout(const std::string& in, const std::string& out, size_t i = 0,
+                   size_t j = 0) const {
+    PADDLE_ENFORCE_LT(i, Inputs(in).size());
+    PADDLE_ENFORCE_LT(j, Outputs(out).size());
+    Variable* in_var = scope_.FindVar(Inputs(in)[i]);
+    Variable* out_var = scope_.FindVar(Outputs(out)[j]);
+    if (!in_var->IsType<LoDTensor>()) return;
+    PADDLE_ENFORCE(out_var->IsType<LoDTensor>(),
+                   "The %d-th output of Output(%s) must be LoDTensor.", j, out);
+    auto in_tensor = in_var->Get<LoDTensor>();
+    auto* out_tensor = out_var->GetMutable<LoDTensor>();
     out_tensor->set_layout(in_tensor.layout());
-}
+  }
 
-void RuntimeInferShapeContext::ShareLayout(const std::string& in,
-                                           const std::string& out, size_t i,
-                                           size_t j) const {
-  PADDLE_ENFORCE_LT(i, Inputs(in).size());
-  PADDLE_ENFORCE_LT(j, Outputs(out).size());
-  Variable* in_var = scope_.FindVar(Inputs(in)[i]);
-  Variable* out_var = scope_.FindVar(Outputs(out)[j]);
-  if (!in_var->IsType<LoDTensor>()) return;
-  PADDLE_ENFORCE(out_var->IsType<LoDTensor>(),
-                 "The %d-th output of Output(%s) must be LoDTensor.", j, out);
-  auto in_tensor = in_var->Get<LoDTensor>();
-  auto* out_tensor = out_var->GetMutable<LoDTensor>();
-  out_tensor->set_layout(in_tensor.layout());
-}
-
-DDim RuntimeInferShapeContext::GetDim(const std::string& name) const {
-  Variable* var = scope_.FindVar(name);
-  PADDLE_ENFORCE_NOT_NULL(var);
-  if (var->IsType<LoDTensor>()) {
-    return var->Get<LoDTensor>().dims();
-  } else if (var->IsType<SelectedRows>()) {
-    return var->Get<SelectedRows>().GetCompleteDims();
-  } else {
-    PADDLE_THROW(
-        "Only LoDTensor/SelectedRows support 'GetDim', but Variable %s's "
-        "type_id is %s.",
-        name, var->Type().name());
+  bool IsRuntime() const override { return true; }
+
+ protected:
+  DDim GetDim(const std::string& name) const override {
+    Variable* var = scope_.FindVar(name);
+    PADDLE_ENFORCE_NOT_NULL(var);
+    if (var->IsType<LoDTensor>()) {
+      return var->Get<LoDTensor>().dims();
+    } else if (var->IsType<SelectedRows>()) {
+      return var->Get<SelectedRows>().GetCompleteDims();
+    } else {
+      PADDLE_THROW(
+          "Only LoDTensor/SelectedRows support 'GetDim', but Variable %s's "
+          "type_id is %s.",
+          name, var->Type().name());
+    }
   }
-}
 
-void RuntimeInferShapeContext::SetDim(const std::string& name,
-                                      const DDim& dim) {
-  Variable* var = scope_.FindVar(name);
-  if (var->IsType<LoDTensor>()) {
-    var->GetMutable<LoDTensor>()->Resize(dim);
-  } else if (var->IsType<SelectedRows>()) {
-    var->GetMutable<SelectedRows>()->set_height(dim[0]);
-  } else {
-    PADDLE_THROW("Variable %s type_id %s, expect LoDTensor/SelectedRows.", name,
-                 var->Type().name());
+  std::vector<DDim> GetRepeatedDims(const std::string& name) const override {
+    PADDLE_THROW("Only compile time support this method");
   }
-}
+
+  void SetDim(const std::string& name, const DDim& dim) override {
+    Variable* var = scope_.FindVar(name);
+    if (var->IsType<LoDTensor>()) {
+      var->GetMutable<LoDTensor>()->Resize(dim);
+    } else if (var->IsType<SelectedRows>()) {
+      var->GetMutable<SelectedRows>()->set_height(dim[0]);
+    } else {
+      PADDLE_THROW("Variable %s type_id %s, expect LoDTensor/SelectedRows.",
+                   name, var->Type().name());
+    }
+  }
+
+  void SetRepeatedDims(const std::string& name,
+                       const std::vector<DDim>& dims) override {
+    PADDLE_THROW("Only compile time support this method");
+  }
+
+  proto::VarType::Type GetVarType(const std::string& name) const override {
+    auto* var = scope_.FindVar(name);
+    return ToVarType(var->Type());
+  }
+
+  InferShapeVarPtr GetVarPtr(const std::string& name) override {
+    return scope_.FindVar(name);
+  }
+
+ private:
+  const OperatorBase& op_;
+  const Scope& scope_;
+};
 
 static void CheckTensorNANOrInf(const std::string& name,
                                 const framework::Tensor& tensor) {