Extract InferShape to many cc files

paddle/framework/CMakeLists.txt

@@ -24,9 +24,10 @@ cc_test(program_desc_test SRCS program_desc_test.cc DEPS proto_desc)
 cc_library(op_proto_maker SRCS op_proto_maker.cc DEPS framework_proto attribute)
 cc_test(op_proto_maker_test SRCS op_proto_maker_test.cc DEPS op_proto_maker)
 cc_library(op_info SRCS op_info.cc DEPS attribute framework_proto)
-cc_library(operator SRCS operator.cc DEPS op_info device_context tensor scope glog)
+cc_library(shape_inference SRCS shape_inference.cc DEPS ddim attribute)
+cc_library(operator SRCS operator.cc DEPS op_info device_context tensor scope glog shape_inference)
 cc_test(operator_test SRCS operator_test.cc DEPS operator op_registry)
-cc_library(proto_desc SRCS var_desc.cc op_desc.cc block_desc.cc program_desc.cc DEPS attribute ddim op_info operator glog)
+cc_library(proto_desc SRCS var_desc.cc op_desc.cc block_desc.cc program_desc.cc DEPS shape_inference op_info operator glog)
 
 cc_library(op_registry SRCS op_registry.cc DEPS op_proto_maker op_info operator glog proto_desc)
 cc_test(op_registry_test SRCS op_registry_test.cc DEPS op_registry)

paddle/framework/op_desc.cc

@@ -16,15 +16,51 @@ limitations under the License. */
 #include <functional>
 #include <mutex>
 #include <unordered_map>
+#include "glog/logging.h"
 #include "paddle/framework/block_desc.h"
 #include "paddle/framework/operator.h"
 #include "paddle/framework/program_desc.h"
-
-#include "glog/logging.h"
+#include "paddle/framework/shape_inference.h"
 
 namespace paddle {
 namespace framework {
 
+class OpDescBind;
+class BlockDescBind;
+class CompileTimeInferShapeContext : public InferShapeContext {
+ public:
+  CompileTimeInferShapeContext(const OpDescBind &op,
+                               const BlockDescBind &block);
+
+  bool HasInput(const std::string &name) const override;
+
+  bool HasOutput(const std::string &name) const override;
+
+  bool HasInputs(const std::string &name) const override;
+
+  bool HasOutputs(const std::string &name) const override;
+
+  DDim GetInputDim(const std::string &name) const override;
+
+  void SetOutputDim(const std::string &name, const DDim &dim) override;
+
+  AttrReader Attrs() const override;
+
+  const std::vector<std::string> &Inputs(
+      const std::string &name) const override;
+
+  const std::vector<std::string> &Outputs(
+      const std::string &name) const override;
+
+ private:
+  DDim GetDim(const std::string &name) const override;
+
+  void SetDim(const std::string &name, const DDim &dim) override;
+
+  const OpDescBind &op_;
+  const BlockDescBind &block_;
+};
+
 OpDescBind::OpDescBind(const std::string &type, const VariableNameMap &inputs,
                        const VariableNameMap &outputs,
                        const AttributeMap &attrs) {
@@ -288,5 +324,97 @@ void OpDescBind::InferVarType(BlockDescBind *block) const {
   }
 }
 
+CompileTimeInferShapeContext::CompileTimeInferShapeContext(
+    const OpDescBind &op, const BlockDescBind &block)
+    : op_(op), block_(block) {}
+
+bool CompileTimeInferShapeContext::HasInput(const std::string &name) const {
+  const std::vector<std::string> &input_names = op_.Input(name);
+  auto length = input_names.size();
+  if (length == 0) {
+    return false;
+  }
+  PADDLE_ENFORCE_EQ(length, 1UL,
+                    "Input(%s) should have only one value, "
+                    "but it have %d now",
+                    name, length);
+  return block_.HasVarRecursive(input_names[0]);
+}
+
+bool CompileTimeInferShapeContext::HasOutput(const std::string &name) const {
+  const std::vector<std::string> &output_names = op_.Output(name);
+  auto length = output_names.size();
+  if (length == 0) {
+    return false;
+  }
+  PADDLE_ENFORCE_EQ(length, 1UL,
+                    "Output(%s) should have only one value, "
+                    "but it have %d now",
+                    name, length);
+  return block_.HasVarRecursive(output_names[0]);
+}
+
+bool CompileTimeInferShapeContext::HasInputs(const std::string &name) const {
+  const std::vector<std::string> &input_names = op_.Input(name);
+  if (input_names.empty()) {
+    return false;
+  }
+  for (auto &input : input_names) {
+    if (!block_.HasVarRecursive(input)) return false;
+  }
+  return true;
+}
+
+bool CompileTimeInferShapeContext::HasOutputs(const std::string &name) const {
+  const std::vector<std::string> &output_names = op_.Output(name);
+  if (output_names.empty()) {
+    return false;
+  }
+  for (auto &output : output_names) {
+    if (!block_.HasVarRecursive(output)) return false;
+  }
+  return true;
+}
+
+DDim CompileTimeInferShapeContext::GetInputDim(const std::string &name) const {
+  std::vector<DDim> ddims = GetInputsDim(name);
+  auto length = ddims.size();
+  PADDLE_ENFORCE_EQ(length, 1UL,
+                    "Input(%s) should have 1 value, "
+                    "but it has %d now",
+                    name, length);
+  return ddims[0];
+}
+
+void CompileTimeInferShapeContext::SetOutputDim(const std::string &name,
+                                                const DDim &dim) {
+  SetOutputsDim(name, {dim});
+}
+
+AttrReader CompileTimeInferShapeContext::Attrs() const {
+  return AttrReader(op_.GetAttrMap());
+}
+
+const std::vector<std::string> &CompileTimeInferShapeContext::Inputs(
+    const std::string &name) const {
+  return op_.Input(name);
+}
+
+const std::vector<std::string> &CompileTimeInferShapeContext::Outputs(
+    const std::string &name) const {
+  return op_.Output(name);
+}
+
+DDim CompileTimeInferShapeContext::GetDim(const std::string &name) const {
+  auto var = block_.FindVarRecursive(name);
+  PADDLE_ENFORCE(var != nullptr, "Cannot find variable %s", name);
+  return framework::make_ddim(var->Shape());
+}
+
+void CompileTimeInferShapeContext::SetDim(const std::string &name,
+                                          const DDim &dim) {
+  block_.FindVarRecursive(name)->SetShape(framework::vectorize(dim));
+}
+
 }  // namespace framework
 }  // namespace paddle

paddle/framework/op_registry.h

@@ -29,6 +29,7 @@ limitations under the License. */
 #include "paddle/framework/op_desc.h"
 #include "paddle/framework/operator.h"
 #include "paddle/framework/scope.h"
+#include "paddle/framework/shape_inference.h"
 
 namespace paddle {
 namespace framework {

paddle/framework/operator.cc

@@ -15,6 +15,7 @@ limitations under the License. */
 #include "paddle/framework/operator.h"
 #include <algorithm>
 #include <atomic>
+#include "paddle/framework/shape_inference.h"
 
 namespace paddle {
 namespace framework {
@@ -273,5 +274,136 @@ bool OpSupportGPU(const std::string& op_type) {
   return false;
 }
 
+class RuntimeInferShapeContext : public InferShapeContext {
+ public:
+  RuntimeInferShapeContext(const OperatorBase& op, const Scope& scope)
+      : op_(op), scope_(scope) {}
+
+  bool HasInput(const std::string& name) const override {
+    auto& ins = Inputs(name);
+    size_t length = ins.size();
+    if (length == 0) {
+      return false;
+    }
+    PADDLE_ENFORCE_EQ(length, 1UL, "Input %s should have more than one inputs",
+                      name);
+    auto ipt = ins[0];
+    auto* var = ipt == kEmptyVarName ? nullptr : scope_.FindVar(ipt);
+    return var != nullptr;
+  }
+
+  bool HasOutput(const std::string& name) const override {
+    auto& outs = Outputs(name);
+    size_t length = outs.size();
+    if (length == 0) {
+      return false;
+    }
+    PADDLE_ENFORCE_EQ(length, 1UL, "Output %s should have more than one inputs",
+                      name);
+    auto ipt = outs[0];
+    auto* var = ipt == kEmptyVarName ? nullptr : scope_.FindVar(ipt);
+    return var != nullptr;
+  }
+
+  bool HasInputs(const std::string& name) const override {
+    auto inputs = op_.Inputs(name);
+    if (inputs.empty()) {
+      return false;
+    }
+    for (auto& input : inputs) {
+      if (scope_.FindVar(input) == nullptr) {
+        return false;
+      }
+    }
+    return true;
+  }
+
+  bool HasOutputs(const std::string& name) const override {
+    auto outputs = op_.Outputs(name);
+    if (outputs.empty()) {
+      return false;
+    }
+    for (auto& output : outputs) {
+      if (scope_.FindVar(output) == nullptr) {
+        return false;
+      }
+    }
+    return true;
+  }
+
+  DDim GetInputDim(const std::string& name) const override {
+    return GetDim(op_.Input(name));
+  }
+
+  void SetOutputDim(const std::string& name, const DDim& dim) override {
+    SetDim(op_.Output(name), dim);
+  }
+
+  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);
+  }
+
+ private:
+  DDim GetDim(const std::string& name) const override {
+    Variable* var = scope_.FindVar(name);
+    if (var->IsType<LoDTensor>()) {
+      return var->Get<LoDTensor>().dims();
+    } else if (var->IsType<SelectedRows>()) {
+      return var->Get<SelectedRows>().GetCompleteDims();
+    } else {
+      PADDLE_THROW("Variable type must be LoDTensor/SelectedRows.");
+    }
+  }
+
+  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 type must be LoDTensor/SelectedRows.");
+    }
+  }
+
+  const OperatorBase& op_;
+  const Scope& scope_;
+};
+
+void OperatorWithKernel::Run(const Scope& scope,
+                             const platform::DeviceContext& dev_ctx) const {
+  VLOG(3) << "Running operator " << this->Type();
+  RuntimeInferShapeContext infer_shape_ctx(*this, scope);
+  this->InferShape(&infer_shape_ctx);
+
+  ExecutionContext ctx(*this, scope, dev_ctx);
+
+  // check if op[type] has kernel registered.
+  auto& all_op_kernels = AllOpKernels();
+  auto kernels_iter = all_op_kernels.find(type_);
+  if (kernels_iter == all_op_kernels.end()) {
+    PADDLE_THROW("op[%s] has no kernel", type_);
+  }
+
+  // check if op[type] have kernel for kernel_key
+  OpKernelMap& kernels = kernels_iter->second;
+  auto kernel_key = OpKernelKey(IndicateDataType(ctx), dev_ctx);
+  auto kernel_iter = kernels.find(kernel_key);
+
+  if (kernel_iter == kernels.end()) {
+    PADDLE_THROW("op[%s] has no kernel with kernel_key[%s]", type_, kernel_key);
+  }
+
+  kernel_iter->second->Compute(ctx);
+}
+
 }  // namespace framework
 }  // namespace paddle