Add input2output pass

mindspore/ccsrc/pre_activate/ascend/ascend_backend_optimization.cc

@@ -94,6 +94,7 @@
 #include "pre_activate/ascend/ir_fission/split_fission.h"
 #include "pre_activate/ascend/format_type/modify_ops_attrs.h"
 #include "pre_activate/ascend/format_type/remove_no_use_reshape_op.h"
+#include "pre_activate/ascend/ir_fusion/add_input_to_output.h"
 #include "utils/context/ms_context.h"
 #include "utils/config_manager.h"
 #include "debug/anf_ir_dump.h"
@@ -259,6 +260,7 @@ void AscendBackendIRFusionOptimization(const std::shared_ptr<session::KernelGrap
     ir_fusion_pm->AddPass(std::make_shared<EraseVisitAttr>());
   }
   ir_fusion_pm->AddPass(std::make_shared<InsertMemcpyAsyncForHcclOp>());
+  ir_fusion_pm->AddPass(std::make_shared<AddInputToOutput>());
   optimizer->AddPassManager(ir_fusion_pm);
   (void)optimizer->Optimize(kernel_graph);
   kernel_graph->SetExecOrderByDefault();

mindspore/ccsrc/pre_activate/ascend/ascend_helper.h

@@ -70,6 +70,21 @@ class KernelQuery {
   }
 };
 using KernelQueryPtr = std::shared_ptr<KernelQuery>;
+
+class OpFinder {
+ public:
+  OpFinder() = default;
+  virtual ~OpFinder() = default;
+  virtual int GetOpRegisteredOutputNum(const std::string &op_name) {
+    auto op_info = kernel::OpLib::FindOp(op_name, kernel::kTBE);
+    if (op_info == nullptr) {
+      return -1;
+    }
+    return op_info->outputs_ptr().size();
+  }
+};
+using OpFinderPtr = std::shared_ptr<OpFinder>;
+
 void RefreshKernelBuildInfo(const std::string &input_format, const std::string &output_format,
                             const AnfNodePtr &trans_data, const std::vector<kernel::Axis> &reshape_type = {});
 

mindspore/ccsrc/pre_activate/ascend/ir_fusion/add_input_to_output.cc

@@ -0,0 +1,115 @@
+/**
+ * Copyright 2020 Huawei Technologies Co., Ltd
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+#include "pre_activate/ascend/ir_fusion/add_input_to_output.h"
+#include <vector>
+#include <algorithm>
+#include "pre_activate/ascend/ir_fusion/input_to_output_registry.h"
+#include "session/anf_runtime_algorithm.h"
+#include "kernel/oplib/oplib.h"
+
+namespace mindspore {
+namespace opt {
+namespace {
+void GetInputOrOutputNames(const CNodePtr &cnode, const std::string &attr_name, std::vector<std::string> *names_vec) {
+  MS_EXCEPTION_IF_NULL(names_vec);
+  auto primitive = AnfAlgo::GetCNodePrimitive(cnode);
+  MS_EXCEPTION_IF_NULL(primitive);
+  ValuePtr names_value = primitive->GetAttr(attr_name);
+  if (names_value == nullptr) {
+    return;
+  }
+  *names_vec = GetValue<std::vector<std::string>>(names_value);
+}
+
+void AddOutputs(const CNodePtr &cnode, const std::vector<size_t> &input_indices) {
+  MS_EXCEPTION_IF_NULL(cnode);
+  std::vector<std::string> input_names_vec;
+  GetInputOrOutputNames(cnode, kAttrInputNames, &input_names_vec);
+  std::vector<std::string> output_names_vec;
+  GetInputOrOutputNames(cnode, kAttrOutputNames, &output_names_vec);
+  AbstractBasePtrList abstract_list;
+  auto origin_abstract = cnode->abstract();
+  MS_EXCEPTION_IF_NULL(origin_abstract);
+  if (origin_abstract->isa<abstract::AbstractTuple>()) {
+    auto origin_abstract_tuple = dyn_cast<abstract::AbstractTuple>(origin_abstract);
+    MS_EXCEPTION_IF_NULL(origin_abstract_tuple);
+    AbstractBasePtrList origin_abstract_list = origin_abstract_tuple->elements();
+    (void)std::copy(origin_abstract_list.begin(), origin_abstract_list.end(), std::back_inserter(abstract_list));
+  } else {
+    abstract_list.emplace_back(origin_abstract);
+  }
+
+  for (size_t i = 0; i < input_indices.size(); ++i) {
+    size_t index = input_indices[i];
+    if (index + 1 >= cnode->inputs().size()) {
+      MS_LOG(INFO) << "The input index " << index << " for converting to output is out of range, "
+                   << "node: " << cnode->DebugString();
+      continue;
+    }
+    auto node_to_output = cnode->input(index + 1);
+    MS_EXCEPTION_IF_NULL(node_to_output);
+    abstract_list.emplace_back(node_to_output->abstract());
+    if (!input_names_vec.empty() && !output_names_vec.empty() && index < input_names_vec.size()) {
+      output_names_vec.emplace_back(input_names_vec[index]);
+    }
+  }
+  if (!output_names_vec.empty()) {
+    AnfAlgo::SetNodeAttr(kAttrOutputNames, MakeValue(output_names_vec), cnode);
+  }
+  auto abstract_tuple = std::make_shared<abstract::AbstractTuple>(abstract_list);
+  cnode->set_abstract(abstract_tuple);
+}
+}  // namespace
+
+const AnfNodePtr AddInputToOutput::Process(const FuncGraphPtr &func_graph, const AnfNodePtr &node,
+                                           const EquivPtr &) const {
+  if (node == nullptr || !AnfAlgo::IsRealCNodeKernel(node)) {
+    return nullptr;
+  }
+  auto cnode = node->cast<CNodePtr>();
+  MS_EXCEPTION_IF_NULL(cnode);
+  std::string op_name = AnfAlgo::GetCNodeName(cnode);
+  InputToOutputRegister reg;
+  if (!InputToOutputRegistry::Instance().GetRegisterByOpName(op_name, &reg)) {
+    return nullptr;
+  }
+  int output_num = op_finder_->GetOpRegisteredOutputNum(op_name);
+  // No need add output when it is not a tbe op.
+  if (output_num == -1) {
+    return nullptr;
+  }
+  // No need add output if the output num matches the registered output num for tbe.
+  if (AnfAlgo::GetOutputTensorNum(cnode) >= IntToSize(output_num)) {
+    return nullptr;
+  }
+  bool is_origin_tuple_output = AnfAlgo::IsTupleOutput(cnode);
+  AddOutputs(cnode, reg.input_indices());
+  // No need to create tuple_getitem if the origin output is a tuple because there has already been some tuple_getitems
+  // pointed to the outputs.
+  if (is_origin_tuple_output) {
+    return nullptr;
+  }
+  std::vector<AnfNodePtr> new_outputs;
+  auto new_abstract_tuple = dyn_cast<abstract::AbstractTuple>(cnode->abstract());
+  MS_EXCEPTION_IF_NULL(new_abstract_tuple);
+  CreateMultipleOutputsOfAnfNode(func_graph, cnode, new_abstract_tuple->size(), &new_outputs);
+  if (new_outputs.size() != new_abstract_tuple->size()) {
+    MS_LOG(EXCEPTION) << "Failed to create outputs of " << cnode->DebugString();
+  }
+  return new_outputs[0];
+}
+}  // namespace opt
+}  // namespace mindspore

mindspore/ccsrc/pre_activate/ascend/ir_fusion/add_input_to_output.h

@@ -0,0 +1,39 @@
+/**
+ * Copyright 2020 Huawei Technologies Co., Ltd
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+#ifndef MINDSPORE_CCSRC_PRE_ACTIVATE_ASCEND_IR_FUSION_ADD_INPUT_TO_OUTPUT_H_
+#define MINDSPORE_CCSRC_PRE_ACTIVATE_ASCEND_IR_FUSION_ADD_INPUT_TO_OUTPUT_H_
+
+#include <string>
+#include <memory>
+#include "pre_activate/common/optimizer.h"
+#include "pre_activate/ascend/ascend_helper.h"
+
+namespace mindspore {
+namespace opt {
+class AddInputToOutput : public PatternProcessPass {
+ public:
+  explicit AddInputToOutput(bool multigraph = true)
+      : PatternProcessPass("add_input_to_output", multigraph), op_finder_(std::make_shared<OpFinder>()) {}
+  ~AddInputToOutput() override = default;
+  const AnfNodePtr Process(const FuncGraphPtr &, const AnfNodePtr &, const EquivPtr &) const override;
+
+ private:
+  OpFinderPtr op_finder_;
+};
+}  // namespace opt
+}  // namespace mindspore
+
+#endif  // MINDSPORE_CCSRC_PRE_ACTIVATE_ASCEND_IR_FUSION_ADD_INPUT_TO_OUTPUT_H_

mindspore/ccsrc/pre_activate/ascend/ir_fusion/input_to_output_registry.cc

@@ -0,0 +1,122 @@
+/**
+ * Copyright 2020 Huawei Technologies Co., Ltd
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+#include "pre_activate/ascend/ir_fusion/input_to_output_registry.h"
+#include <utility>
+#include "utils/utils.h"
+#include "session/anf_runtime_algorithm.h"
+
+namespace mindspore {
+namespace opt {
+namespace {
+bool ApplyRMSPropPreCheck(const CNodePtr &node) {
+  return !(AnfAlgo::GetPrevNodeOutputInferDataType(node, 0) != kNumberTypeFloat32);
+}
+
+bool FusedMulApplyMomentumPreCheck(const CNodePtr &node) {
+  TypeId data_type = AnfAlgo::GetPrevNodeOutputInferDataType(node, 0);
+  return !(data_type != kNumberTypeFloat32 && data_type != kNumberTypeFloat16);
+}
+
+bool SparseApplyRMSPropPreCheck(const CNodePtr &node) {
+  return !(AnfAlgo::GetPrevNodeOutputInferDataType(node, 0) != kNumberTypeFloat32);
+}
+
+bool ApplyAdagradV2PreCheck(const CNodePtr &node) {
+  TypeId data_type = AnfAlgo::GetPrevNodeOutputInferDataType(node, 0);
+  return !(data_type != kNumberTypeFloat32 && data_type != kNumberTypeFloat16);
+}
+
+bool ApplyKerasMomentumPreCheck(const CNodePtr &node) {
+  TypeId data_type = AnfAlgo::GetPrevNodeOutputInferDataType(node, 0);
+  return !(data_type != kNumberTypeFloat32 && data_type != kNumberTypeFloat16);
+}
+
+bool SparseApplyFtrlPreCheck(const CNodePtr &node) {
+  return !(AnfAlgo::GetPrevNodeOutputInferDataType(node, 0) != kNumberTypeFloat32);
+}
+
+bool SparseApplyFtrlV2PreCheck(const CNodePtr &node) {
+  return !(AnfAlgo::GetPrevNodeOutputInferDataType(node, 0) != kNumberTypeFloat32);
+}
+
+bool SparseApplyAdagradV2PreCheck(const CNodePtr &node) {
+  return !(AnfAlgo::GetPrevNodeOutputInferDataType(node, 0) != kNumberTypeFloat32);
+}
+
+bool SparseApplyAdadeltaPreCheck(const CNodePtr &node) {
+  return !(AnfAlgo::GetPrevNodeOutputInferDataType(node, 0) != kNumberTypeFloat32);
+}
+}  // namespace
+InputToOutputRegistry::InputToOutputRegistry() {
+  Register(kApplyRMSPropOpName, {1, 2}, ApplyRMSPropPreCheck);
+  Register(kFusedMulApplyMomentumOpName, {1}, FusedMulApplyMomentumPreCheck);
+  Register(kApplyAdagradOpName, {1});
+  Register(kApplyAdagradDAName, {1, 2});
+  Register(kApplyAdadeltaOpName, {1, 2});
+  Register(kApplyPowerSignOpName, {1});
+  Register(kApplyProximalAdagradOpName, {1});
+  Register(kApplyAdaMaxOpName, {1, 2});
+  Register(kApplyAdagradV2OpName, {1}, ApplyAdagradV2PreCheck);
+  Register(kApplyKerasMomentumOpName, {1}, ApplyKerasMomentumPreCheck);
+  Register(kSparseApplyFtrlOpName, {1, 2}, SparseApplyFtrlPreCheck);
+  Register(kSparseApplyFtrlV2OpName, {1, 2}, SparseApplyFtrlV2PreCheck);
+  Register(kSparseApplyAdagradV2OpName, {1}, SparseApplyAdagradV2PreCheck);
+  Register(kSparseApplyProximalAdagradOpName, {1});
+  Register(kSparseApplyAdagradOpName, {1});
+  Register(kApplyFtrlV2OpName, {1, 2});
+  Register(kApplyMomentumOpName, {1});
+  Register(kApplyFtrlOpName, {1, 2});
+  Register(kApplyAdamOpName, {1, 2});
+  Register(kApplyCenteredRMSPropOpName, {1, 2, 3});
+  Register(kApplyAddSignOpName, {1});
+  Register(kSparseApplyRMSPropOpName, {1, 2}, SparseApplyRMSPropPreCheck);
+  Register(kSparseApplyAdadeltaOpName, {1, 2}, SparseApplyAdadeltaPreCheck);
+  Register(kApplyAdamWithAmsgradOpName, {1, 2});
+}
+
+InputToOutputRegistry &InputToOutputRegistry::Instance() {
+  static InputToOutputRegistry instance;
+  return instance;
+}
+
+void InputToOutputRegistry::Register(const InputToOutputRegister &reg) {
+  auto op_name = reg.op_name();
+  if (op_input_to_output_map_.find(op_name) == op_input_to_output_map_.end()) {
+    (void)op_input_to_output_map_.insert(make_pair(op_name, reg));
+    MS_LOG(DEBUG) << op_name << " input2output register successfully!";
+  }
+}
+
+void InputToOutputRegistry::Register(const std::string &op_name, const std::vector<size_t> &input_indices,
+                                     const PreCheckFunc &pre_check_func) {
+  if (op_input_to_output_map_.find(op_name) == op_input_to_output_map_.end()) {
+    InputToOutputRegister reg(op_name, pre_check_func);
+    reg.set_input_indices(input_indices);
+    (void)op_input_to_output_map_.insert(make_pair(op_name, reg));
+    MS_LOG(DEBUG) << op_name << " input2output register successfully!";
+  }
+}
+
+bool InputToOutputRegistry::GetRegisterByOpName(const std::string &op_name, InputToOutputRegister *reg) const {
+  if (op_input_to_output_map_.find(op_name) != op_input_to_output_map_.end()) {
+    *reg = op_input_to_output_map_.at(op_name);
+    MS_LOG(DEBUG) << op_name << " input2output find in registry.";
+    return true;
+  }
+  return false;
+}
+}  // namespace opt
+}  // namespace mindspore

mindspore/ccsrc/pre_activate/ascend/ir_fusion/input_to_output_registry.h

@@ -0,0 +1,64 @@
+/**
+ * Copyright 2020 Huawei Technologies Co., Ltd
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+#ifndef MINDSPORE_CCSRC_PRE_ACTIVATE_IR_FUSION_INPUT_TO_OUTPUT_REGISTRY_H_
+#define MINDSPORE_CCSRC_PRE_ACTIVATE_IR_FUSION_INPUT_TO_OUTPUT_REGISTRY_H_
+#include <string>
+#include <unordered_map>
+#include <vector>
+#include <utility>
+#include "ir/anf.h"
+#include "common/utils.h"
+
+namespace mindspore {
+namespace opt {
+using PreCheckFunc = std::function<bool(const CNodePtr &node)>;
+class InputToOutputRegister {
+ public:
+  explicit InputToOutputRegister(
+    const std::string &op_name = "", const PreCheckFunc &pre_check_func = [](const CNodePtr &node) { return true; })
+      : op_name_(op_name), pre_check_func_(pre_check_func) {}
+  virtual ~InputToOutputRegister() = default;
+
+  void set_input_indices(const std::vector<size_t> &input_indices) { input_indices_ = input_indices; }
+
+  const std::vector<size_t> &input_indices() const { return input_indices_; }
+  const std::string &op_name() const { return op_name_; }
+
+ private:
+  std::string op_name_;
+  std::vector<size_t> input_indices_;
+  PreCheckFunc pre_check_func_;
+};
+
+class InputToOutputRegistry {
+ public:
+  static InputToOutputRegistry &Instance();
+  void Register(const InputToOutputRegister &reg);
+  void Register(
+    const std::string &op_name, const std::vector<size_t> &input_indices,
+    const PreCheckFunc &pre_check_func = [](const CNodePtr &node) { return true; });
+  bool GetRegisterByOpName(const std::string &op_name, InputToOutputRegister *reg) const;
+
+ private:
+  InputToOutputRegistry();
+  ~InputToOutputRegistry() = default;
+  DISABLE_COPY_AND_ASSIGN(InputToOutputRegistry)
+  std::unordered_map<std::string, InputToOutputRegister> op_input_to_output_map_;
+};
+}  // namespace opt
+}  // namespace mindspore
+
+#endif  // MINDSPORE_CCSRC_PRE_ACTIVATE_IR_FUSION_INPUT_TO_OUTPUT_REGISTRY_H_

mindspore/ccsrc/utils/utils.h

@@ -164,6 +164,15 @@ constexpr auto kStridedReadOpName = "StridedRead";
 constexpr auto kStridedWriteOpName = "StridedWrite";
 constexpr auto kFusedAdamWeightDecayName = "FusedAdamWeightDecay";
 constexpr auto kFusedAdamName = "FusedAdam";
+constexpr auto kApplyAdagradV2OpName = "ApplyAdagradV2";
+constexpr auto kSparseApplyAdagradV2OpName = "SparseApplyAdagradV2";
+constexpr auto kSparseApplyFtrlOpName = "SparseApplyFtrl";
+constexpr auto kSparseApplyFtrlV2OpName = "SparseApplyFtrlV2";
+constexpr auto kApplyKerasMomentumOpName = "ApplyKerasMomentum";
+constexpr auto kSparseApplyProximalAdagradOpName = "SparseApplyProximalAdagrad";
+constexpr auto kSparseApplyRMSPropOpName = "SparseApplyRMSProp";
+constexpr auto kSparseApplyAdadeltaOpName = "SparseApplyAdadelta";
+constexpr auto kApplyAdamWithAmsgradOpName = "ApplyAdamWithAmsgrad";
 
 // attr key name
 constexpr auto kAttrInputNames = "input_names";

tests/ut/cpp/pre_activate/ascend/ir_fusion/add_input_to_output_test.cc

@@ -0,0 +1,74 @@
+/**
+ * Copyright 2020 Huawei Technologies Co., Ltd
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+#include "common/backend_common_test.h"
+#include "common/py_func_graph_fetcher.h"
+#include "debug/anf_ir_dump.h"
+
+#define private public
+#define protected public
+#include "pre_activate/ascend/ir_fusion/add_input_to_output.h"
+#undef private
+#undef protected
+
+namespace mindspore {
+namespace opt {
+class TestHWAddInputToOutput : public BackendCommon {
+ public:
+  TestHWAddInputToOutput() : getPyFun_("gtest_input.pre_activate.add_input_to_output_test", true) {}
+  ~TestHWAddInputToOutput() override = default;
+
+ public:
+  UT::PyFuncGraphFetcher getPyFun_;
+};
+
+class MockOpFinder : public OpFinder {
+ public:
+  MockOpFinder() = default;
+  ~MockOpFinder() override = default;
+  int GetOpRegisteredOutputNum(const std::string &op_name) override { return 2; }
+};
+
+TEST_F(TestHWAddInputToOutput, test_add_input_to_output) {
+  FuncGraphPtr g = getPyFun_.CallAndParseRet("test_add_input_to_output", "before");
+  EXPECT_NE(g, nullptr);
+  std::vector<int> shp{2, 32, 224, 224};
+  auto x_abstract = std::make_shared<abstract::AbstractTensor>(kFloat32, shp);
+  AbstractBasePtrList args_spec_list;
+  for (size_t i = 0; i < 5; ++i) {
+    args_spec_list.push_back(x_abstract);
+  }
+  auto kg = GetKernelGraph(g, args_spec_list);
+  EXPECT_NE(kg, nullptr);
+  auto ret = kg->get_return();
+  EXPECT_NE(ret, nullptr);
+  auto make_tuple = ret->input(1);
+  EXPECT_NE(make_tuple, nullptr);
+  auto momentum = make_tuple->cast<CNodePtr>()->input(1);
+  EXPECT_NE(momentum, nullptr);
+  EXPECT_NE(momentum->abstract(), nullptr);
+  EXPECT_FALSE(momentum->abstract()->isa<abstract::AbstractTuple>());
+
+  auto optimizer = std::make_shared<opt::GraphOptimizer>();
+  auto pm = std::make_shared<opt::PassManager>();
+  auto pass = std::make_shared<opt::AddInputToOutput>();
+  pass->op_finder_ = std::make_shared<MockOpFinder>();
+  pm->AddPass(pass);
+  optimizer->AddPassManager(pm);
+  (void)optimizer->Optimize(kg);
+  EXPECT_TRUE(momentum->abstract()->isa<abstract::AbstractTuple>());
+}
+}  // namespace opt
+}  // namespace mindspore

tests/ut/cpp/python_input/gtest_input/pre_activate/add_input_to_output_test.py

@@ -0,0 +1,39 @@
+# Copyright 2020 Huawei Technologies Co., Ltd
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+# http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+# ============================================================================
+
+from mindspore.ops import operations as P
+
+ApplyMomentum = P.ApplyMomentum()
+
+
+class FnDict:
+    def __init__(self):
+        self.fnDict = {}
+
+    def __call__(self, fn):
+        self.fnDict[fn.__name__] = fn
+
+    def __getitem__(self, name):
+        return self.fnDict[name]
+
+
+def test_add_input_to_output(tag):
+    fns = FnDict()
+
+    @fns
+    def before(input0, input1, input2, input3, input4):
+        return ApplyMomentum(input0, input1, input2, input3, input4)
+
+    return fns[tag]