Merge branch 'core_opt_choose_kernel' of https://github.com/Xreki/Paddle into...

Merge branch 'core_opt_choose_kernel' of https://github.com/Xreki/Paddle into core_opt_choose_kernel

paddle/fluid/framework/operator.cc

@@ -880,50 +880,23 @@ void OperatorWithKernel::RunImpl(const Scope& scope,
   platform::DeviceContextPool& pool = platform::DeviceContextPool::Instance();
   auto* dev_ctx = pool.Get(place);
 
-  // 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(
-        "There are no kernels which are registered in the %s operator.", type_);
-  }
-
-  OpKernelMap& kernels = kernels_iter->second;
-
-  auto expected_kernel_key = this->GetExpectedKernelType(
-      ExecutionContext(*this, scope, *dev_ctx, ctx, nullptr));
-  VLOG(3) << "expected_kernel_key:" << expected_kernel_key;
-
-  auto kernel_iter = kernels.find(expected_kernel_key);
-#ifdef PADDLE_WITH_MKLDNN
-  // workaround for missing MKLDNN kernel when FLAGS_use_mkldnn env var is set
-  if (kernel_iter == kernels.end() &&
-      expected_kernel_key.library_type_ == LibraryType::kMKLDNN) {
-    VLOG(3) << "missing MKLDNN kernel: fallbacking to PLAIN one";
-    expected_kernel_key.library_type_ = LibraryType::kPlain;
-    expected_kernel_key.data_layout_ = DataLayout::kAnyLayout;
-    kernel_iter = kernels.find(expected_kernel_key);
-  }
-#endif
-  if (kernel_iter == kernels.end()) {
-    PADDLE_THROW("op %s does not have kernel for %s", type_,
-                 KernelTypeToString(expected_kernel_key));
+  if (!kernel_type_) {
+    ChooseKernel(ctx, scope, place);
   }
 
-  std::vector<KernelConfig>* kernel_configs =
-      GetKernelConfig(expected_kernel_key);
+  std::vector<KernelConfig>* kernel_configs = GetKernelConfig(*kernel_type_);
 
   // do data transformScope &transfer_scope;
   std::vector<std::string> transfered_inplace_vars;
   auto* transfer_scope =
-      PrepareData(scope, expected_kernel_key, &transfered_inplace_vars, &ctx);
+      PrepareData(scope, *kernel_type_, &transfered_inplace_vars, &ctx);
 
   // exec scope is the scope that kernel actually executed on.
   const Scope& exec_scope =
       (transfer_scope == nullptr ? scope : *transfer_scope);
 
-  if (!(expected_kernel_key.place_ == dev_ctx->GetPlace())) {
-    dev_ctx = pool.Get(expected_kernel_key.place_);
+  if (!(kernel_type_->place_ == dev_ctx->GetPlace())) {
+    dev_ctx = pool.Get(kernel_type_->place_);
   }
 
   if (!HasAttr(kAllKernelsMustComputeRuntimeShape)) {
@@ -932,7 +905,7 @@ void OperatorWithKernel::RunImpl(const Scope& scope,
   }
   // TODO(panyx0718): ExecutionContext should only depend on RuntimeContext
   // not Scope. Imperative mode only pass inputs and get outputs.
-  kernel_iter->second(
+  (*kernel_func_)(
       ExecutionContext(*this, exec_scope, *dev_ctx, ctx, kernel_configs));
 
   if (!transfered_inplace_vars.empty()) {
@@ -959,6 +932,46 @@ void OperatorWithKernel::RunImpl(const Scope& scope,
   }
 }
 
+void OperatorWithKernel::ChooseKernel(const RuntimeContext& ctx,
+                                      const Scope& scope,
+                                      const platform::Place& place) const {
+  platform::DeviceContextPool& pool = platform::DeviceContextPool::Instance();
+  auto* dev_ctx = pool.Get(place);
+
+  // 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(
+        "There are no kernels which are registered in the %s operator.", type_);
+  }
+
+  OpKernelMap& kernels = kernels_iter->second;
+
+  auto expected_kernel_key = this->GetExpectedKernelType(
+      ExecutionContext(*this, scope, *dev_ctx, ctx, nullptr));
+  VLOG(3) << "expected_kernel_key:" << expected_kernel_key;
+
+  auto kernel_iter = kernels.find(expected_kernel_key);
+#ifdef PADDLE_WITH_MKLDNN
+  // workaround for missing MKLDNN kernel when FLAGS_use_mkldnn env var is set
+  if (kernel_iter == kernels.end() &&
+      expected_kernel_key.library_type_ == LibraryType::kMKLDNN) {
+    VLOG(3) << "missing MKLDNN kernel: fallbacking to PLAIN one";
+    expected_kernel_key.library_type_ = LibraryType::kPlain;
+    expected_kernel_key.data_layout_ = DataLayout::kAnyLayout;
+    kernel_iter = kernels.find(expected_kernel_key);
+  }
+#endif
+  if (kernel_iter == kernels.end()) {
+    PADDLE_THROW("op %s does not have kernel for %s", type_,
+                 KernelTypeToString(expected_kernel_key));
+  }
+
+  kernel_type_.reset(new OpKernelType(expected_kernel_key));
+  kernel_func_.reset(new OpKernelFunc(kernel_iter->second));
+}
+
 void OperatorWithKernel::TransferInplaceVarsBack(
     const Scope& scope, const std::vector<std::string>& inplace_vars,
     const Scope& transfer_scope) const {

paddle/fluid/framework/operator.h

@@ -472,8 +472,13 @@ class OperatorWithKernel : public OperatorBase {
                                const std::vector<std::string>& inplace_vars,
                                const Scope& exec_scope) const;
 
+  void ChooseKernel(const RuntimeContext& ctx, const Scope& scope,
+                    const platform::Place& place) const;
+
  protected:
   mutable OpKernelConfigsMap kernel_configs_map_;
+  mutable std::unique_ptr<OpKernelType> kernel_type_;
+  mutable std::unique_ptr<OpKernelFunc> kernel_func_;
 };
 
 extern bool OpSupportGPU(const std::string& op_type);