add LarsV2 fission pass

mindspore/ccsrc/pre_activate/ascend/ir_fission/lars_v2_fission.cc

@@ -0,0 +1,91 @@
+/**
+ * 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_fission/lars_v2_fission.h"
+#include <memory>
+#include <vector>
+#include "session/anf_runtime_algorithm.h"
+#include "pre_activate/common/helper.h"
+#include "utils/utils.h"
+
+namespace mindspore {
+namespace opt {
+namespace {
+void CreateOutputsOfSquareSumAll(const FuncGraphPtr &graph, const CNodePtr &lars_v2,
+                                 std::vector<AnfNodePtr> *square_sum_all_outputs) {
+  MS_EXCEPTION_IF_NULL(graph);
+  MS_EXCEPTION_IF_NULL(lars_v2);
+  if (lars_v2->size() != kLarsV2InputNum) {
+    MS_LOG(EXCEPTION) << "Op lars_v2's input not equal " << kLarsV2InputNum;
+  }
+
+  std::vector<AnfNodePtr> inputs = {NewValueNode(std::make_shared<Primitive>(kSquareSumAllOpName))};
+  inputs.push_back(lars_v2->input(1));
+  inputs.push_back(lars_v2->input(2));
+  auto square_sum_all = graph->NewCNode(inputs);
+  MS_EXCEPTION_IF_NULL(square_sum_all);
+  square_sum_all->set_scope(lars_v2->scope());
+
+  auto types = {kNumberTypeFloat32, kNumberTypeFloat32};
+  std::vector<size_t> shape;
+  auto shapes = {shape, shape};
+  AnfAlgo::SetOutputInferTypeAndShape(types, shapes, square_sum_all.get());
+
+  CreateMultipleOutputsOfAnfNode(graph, square_sum_all, 2, square_sum_all_outputs);
+}
+
+CNodePtr CreateLarsV2Update(const FuncGraphPtr &graph, const CNodePtr &lars_v2,
+                            const std::vector<AnfNodePtr> &square_sum_all_outputs) {
+  MS_EXCEPTION_IF_NULL(graph);
+  MS_EXCEPTION_IF_NULL(lars_v2);
+  if (square_sum_all_outputs.size() != 2) {
+    MS_LOG(EXCEPTION) << "square_sum_all_outputs' size not equal 2";
+  }
+  if (lars_v2->size() != kLarsV2InputNum) {
+    MS_LOG(EXCEPTION) << "Op lars_v2's input not equal " << kLarsV2InputNum;
+  }
+  std::vector<AnfNodePtr> inputs = {NewValueNode(std::make_shared<Primitive>(kLarsV2UpdateOpName))};
+  inputs.push_back(lars_v2->input(1));
+  inputs.push_back(lars_v2->input(2));
+  inputs.push_back(square_sum_all_outputs[0]);
+  inputs.push_back(square_sum_all_outputs[1]);
+  inputs.push_back(lars_v2->input(3));
+  inputs.push_back(lars_v2->input(4));
+  auto lars_v2_update = graph->NewCNode(inputs);
+  MS_EXCEPTION_IF_NULL(lars_v2_update);
+  lars_v2_update->set_scope(lars_v2->scope());
+  lars_v2_update->set_abstract(lars_v2->abstract());
+  return lars_v2_update;
+}
+}  // namespace
+
+const BaseRef LarsV2Fission::DefinePattern() const {
+  VarPtr Xs = std::make_shared<SeqVar>();
+  auto lars_v2_prim = std::make_shared<Primitive>(kLarsV2OpName);
+  return VectorRef({lars_v2_prim, Xs});
+}
+
+const AnfNodePtr LarsV2Fission::Process(const FuncGraphPtr &graph, const AnfNodePtr &node, const EquivPtr &) const {
+  MS_EXCEPTION_IF_NULL(graph);
+  MS_EXCEPTION_IF_NULL(node);
+  auto lars_v2 = node->cast<CNodePtr>();
+  MS_EXCEPTION_IF_NULL(lars_v2);
+
+  std::vector<AnfNodePtr> square_sum_all_outputs;
+  CreateOutputsOfSquareSumAll(graph, lars_v2, &square_sum_all_outputs);
+  return CreateLarsV2Update(graph, lars_v2, square_sum_all_outputs);
+}
+}  // namespace opt
+}  // namespace mindspore

mindspore/ccsrc/pre_activate/ascend/ir_fission/lars_v2_fission.h

@@ -0,0 +1,32 @@
+/**
+ * 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_FISSION_LARS_V2_FISSION_H_
+#define MINDSPORE_CCSRC_PRE_ACTIVATE_ASCEND_IR_FISSION_LARS_V2_FISSION_H_
+
+#include "pre_activate/common/optimizer.h"
+
+namespace mindspore {
+namespace opt {
+class LarsV2Fission : public PatternProcessPass {
+ public:
+  explicit LarsV2Fission(bool multigraph = true) : PatternProcessPass("lars_v2_fission", multigraph) {}
+  ~LarsV2Fission() override = default;
+  const BaseRef DefinePattern() const override;
+  const AnfNodePtr Process(const FuncGraphPtr &, const AnfNodePtr &, const EquivPtr &) const override;
+};
+}  // namespace opt
+}  // namespace mindspore
+#endif  // MINDSPORE_CCSRC_PRE_ACTIVATE_ASCEND_IR_FISSION_LARS_V2_FISSION_H_

mindspore/ccsrc/pre_activate/common/helper.h

@@ -91,6 +91,7 @@ constexpr size_t kBackendTransDataInputNum = 2;
 constexpr size_t kApplyMomentumInputNum = 6;
 constexpr size_t kBiasAddInputNum = 3;
 constexpr size_t kTopkInputNum = 3;
+constexpr size_t kLarsV2InputNum = 5;
 
 enum FusedBatchNormInput {
   kX = 1,

mindspore/ccsrc/utils/utils.h

@@ -144,6 +144,9 @@ constexpr auto kBNInferGradOpName = "BNInferGrad";
 constexpr auto kCallOpName = "call";
 constexpr auto kPartialOpName = "partial";
 constexpr auto kSwitchOpName = "switch";
+constexpr auto kLarsV2OpName = "LarsV2";
+constexpr auto kLarsV2UpdateOpName = "LarsV2Update";
+constexpr auto kSquareSumAllOpName = "SquareSumAll";
 
 // attr key name
 constexpr auto kAttrInputNames = "input_names";

tests/ut/cpp/pre_activate/ascend/ir_fission/lars_v2_fission_test.cc

@@ -0,0 +1,56 @@
+/**
+ * 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 "pre_activate/ascend/ir_fission/lars_v2_fission.h"
+
+namespace mindspore {
+namespace opt {
+class TestHWLarsV2Fission : public BackendCommon {
+ public:
+  TestHWLarsV2Fission() : get_py_fun_("gtest_input.pre_activate.lars_v2_fission_test", true) {}
+  ~TestHWLarsV2Fission() override = default;
+
+  UT::PyFuncGraphFetcher get_py_fun_;
+};
+
+TEST_F(TestHWLarsV2Fission, test_fission) {
+  FuncGraphPtr g = get_py_fun_.CallAndParseRet("test_lars_v2_fission", "before");
+  EXPECT_NE(g, nullptr);
+
+  // set abstract for all nodes in g
+  std::vector<int> shp{2, 32, 224, 224};
+  auto x_abstract = std::make_shared<abstract::AbstractTensor>(kFloat32, shp);
+  g->get_return()->input(1)->set_abstract(x_abstract);
+  for (auto &p: g->parameters()){
+    p->set_abstract(x_abstract);
+  }
+  AbstractBasePtrList args_spec_list;
+  auto kg = GetKernelGraph(g, args_spec_list, false);
+
+  auto optimizer = std::make_shared<opt::GraphOptimizer>();
+  auto pm = std::make_shared<opt::PassManager>();
+  pm->AddPass(std::make_shared<opt::LarsV2Fission>());
+  optimizer->AddPassManager(pm);
+  FuncGraphPtr new_graph = optimizer->Optimize(kg);
+
+  FuncGraphPtr g_after = get_py_fun_.CallAndParseRet("test_lars_v2_fission", "after");
+  EXPECT_NE(g_after, nullptr);
+  EXPECT_TRUE(CheckEqualGraph(g_after, new_graph));
+}
+}  // namespace opt
+}  // namespace mindspore

tests/ut/cpp/python_input/gtest_input/pre_activate/lars_v2_fission_test.py

@@ -0,0 +1,50 @@
+# 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 Primitive
+
+lars_v2 = Primitive('LarsV2')
+square_sum_all = Primitive('SquareSumAll')
+lars_v2_update = Primitive('LarsV2Update')
+make_tuple = Primitive('make_tuple')
+tuple_getitem = Primitive('tuple_getitem')
+
+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_lars_v2_fission(tag):
+    fns = FnDict()
+
+    @fns
+    def before(input0, input1, input2, input3):
+        res = lars_v2(input0, input1, input2, input3)
+        return res
+
+    @fns
+    def after(input0, input1, input2, input3):
+        res = square_sum_all(input0, input1)
+        item0 = tuple_getitem(res, 0)
+        item1 = tuple_getitem(res, 1)
+        res = lars_v2_update(input0, input1, item0, item1, input2, input3)
+        return make_tuple(res)
+
+    return fns[tag]