1 /**
2 * Copyright 2020-2021 Huawei Technologies Co., Ltd
3 *
4 * Licensed under the Apache License, Version 2.0 (the "License");
5 * you may not use this file except in compliance with the License.
6 * You may obtain a copy of the License at
7 *
8 * http://www.apache.org/licenses/LICENSE-2.0
9 *
10 * Unless required by applicable law or agreed to in writing, software
11 * distributed under the License is distributed on an "AS IS" BASIS,
12 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
13 * See the License for the specific language governing permissions and
14 * limitations under the License.
15 */
16
17 #include "frontend/optimizer/irpass/branch_culling.h"
18
19 #include <memory>
20 #include <utility>
21 #include <queue>
22
23 #include "mindspore/core/ops/structure_ops.h"
24 #include "mindspore/core/ops/sequence_ops.h"
25 #include "mindspore/core/ops/nn_optimizer_ops.h"
26 #include "mindspore/core/ops/nn_ops.h"
27 #include "mindspore/core/ops/math_ops.h"
28 #include "mindspore/core/ops/array_ops.h"
29 #include "mindspore/core/ops/framework_ops.h"
30 #include "ops/auto_generate/gen_ops_primitive.h"
31 #include "utils/hash_map.h"
32 #include "ir/func_graph.h"
33 #include "frontend/operator/ops.h"
34 #include "include/common/utils/convert_utils.h"
35
36 namespace mindspore {
37 namespace opt {
38 namespace irpass {
39 constexpr size_t kCondIndex = 1;
40 constexpr size_t kTrueBranchIndex = 2;
41 constexpr size_t kFalseBranchIndex = 3;
42 namespace internal {
GenerateSwitchNode(const FuncGraphPtr & graph,const AnfNodePtr & cond,const AnfNodePtr & data,int64_t switch_idx)43 AnfNodePtr GenerateSwitchNode(const FuncGraphPtr &graph, const AnfNodePtr &cond, const AnfNodePtr &data,
44 int64_t switch_idx) {
45 auto switch_node = prim::GetPythonOps("geswitch", "mindspore.ops.functional")->cast<PrimitivePtr>();
46 std::vector<AnfNodePtr> switch_nodes{NewValueNode(switch_node), data, cond};
47 auto switch_apply = graph->NewCNode(switch_nodes);
48 std::vector<AnfNodePtr> tuple_getitem_nodes{NewValueNode(prim::kPrimTupleGetItem), switch_apply,
49 NewValueNode(MakeValue(switch_idx))};
50 return graph->NewCNode(tuple_getitem_nodes);
51 }
52
GenerateSwitchTrueNode(const FuncGraphPtr & graph,const AnfNodePtr & cond,const AnfNodePtr & data)53 AnfNodePtr GenerateSwitchTrueNode(const FuncGraphPtr &graph, const AnfNodePtr &cond, const AnfNodePtr &data) {
54 return GenerateSwitchNode(graph, cond, data, 1);
55 }
56
GenerateSwitchFalseNode(const FuncGraphPtr & graph,const AnfNodePtr & cond,const AnfNodePtr & data)57 AnfNodePtr GenerateSwitchFalseNode(const FuncGraphPtr &graph, const AnfNodePtr &cond, const AnfNodePtr &data) {
58 return GenerateSwitchNode(graph, cond, data, 0);
59 }
60
InConvertWhiteList(const AnfNodePtr & node,size_t index)61 bool InConvertWhiteList(const AnfNodePtr &node, size_t index) {
62 // The CNode inputs of the following Primitive with index in std::vector<size_t> should not be guarded by geswitch
63 // node because it is attribute or ge specific reason.
64 // Example : when convert CNode(kPrimReduceSum, x, axis), node of index 2 in CNode->inputs is axis which should not be
65 // converted to switch guarded.
66 #ifndef ENABLE_SECURITY
67 std::vector<std::pair<PrimitivePtr, std::vector<size_t>>> white_list({{prim::kPrimApplyMomentum, {1, 2}},
68 {prim::kPrimMomentum, {2, 3}},
69 {prim::kPrimStateSetItem, {1}},
70 {prim::kPrimTupleGetItem, {2}},
71 {prim::kPrimEnvironGet, {1}},
72 {prim::kPrimEnvironSet, {1}},
73 {prim::kPrimReduceSum, {2}},
74 {prim::kPrimReduceMean, {2}},
75 {prim::kPrimReduceAll, {2}},
76 {prim::kPrimCast, {2}},
77 {prim::kPrimTranspose, {2}},
78 {prim::kPrimOneHot, {2}},
79 {prim::kPrimGather, {3}},
80 {prim::kPrimReshape, {2}},
81 {prim::kPrimAssign, {1}},
82 {prim::kPrimAssignAdd, {1}},
83 {prim::kPrimAssignSub, {1}},
84 {prim::kPrimTensorSummary, {1}},
85 {prim::kPrimImageSummary, {1}},
86 {prim::kPrimScalarSummary, {1}},
87 {prim::kPrimApplyRMSProp, {6, 7, 8}},
88 {prim::kPrimCumSum, {2}},
89 {prim::kPrimTile, {2}},
90 {prim::kPrimExpandDims, {2}},
91 {prim::kPrimHistogramSummary, {1}}});
92 #else
93 std::vector<std::pair<PrimitivePtr, std::vector<size_t>>> white_list(
94 {{prim::kPrimApplyMomentum, {1, 2}}, {prim::kPrimMomentum, {2, 3}},
95 {prim::kPrimStateSetItem, {1}}, {prim::kPrimTupleGetItem, {2}},
96 {prim::kPrimEnvironGet, {1}}, {prim::kPrimEnvironSet, {1}},
97 {prim::kPrimReduceSum, {2}}, {prim::kPrimReduceMean, {2}},
98 {prim::kPrimReduceAll, {2}}, {prim::kPrimCast, {2}},
99 {prim::kPrimTranspose, {2}}, {prim::kPrimOneHot, {2}},
100 {prim::kPrimGather, {3}}, {prim::kPrimReshape, {2}},
101 {prim::kPrimAssign, {1}}, {prim::kPrimAssignAdd, {1}},
102 {prim::kPrimAssignSub, {1}}, {prim::kPrimApplyRMSProp, {6, 7, 8}},
103 {prim::kPrimCumSum, {2}}, {prim::kPrimTile, {2}},
104 {prim::kPrimExpandDims, {2}}});
105 #endif
106 for (auto &item : white_list) {
107 auto matched = std::any_of(item.second.begin(), item.second.end(), [&item, &node, &index](size_t idx) {
108 return IsPrimitiveCNode(node, item.first) && idx == index;
109 });
110 if (matched) {
111 return true;
112 }
113 }
114
115 std::vector<PrimitivePtr> adapter_convert_ops = {prim::kPrimDepend, prim::kPrimLoad};
116 for (auto &item : adapter_convert_ops) {
117 if (IsPrimitiveCNode(node, item)) {
118 return true;
119 }
120 }
121 return false;
122 }
123
124 using NodeInputReplMap = mindspore::HashMap<std::pair<AnfNodePtr, size_t>, AnfNodePtr, PairHasher>;
125 // replace the nodes which should be changed
RunSwitchNodeReplace(const FuncGraphManagerPtr & manager,std::vector<std::pair<CNodePtr,CNodePtr>> nodes_changed,mindspore::HashMap<AnfNodePtr,AnfNodePtr> repl_node,NodeInputReplMap repl_node_inputs,const FuncGraphPtr & func_graph)126 void RunSwitchNodeReplace(const FuncGraphManagerPtr &manager, std::vector<std::pair<CNodePtr, CNodePtr>> nodes_changed,
127 mindspore::HashMap<AnfNodePtr, AnfNodePtr> repl_node, NodeInputReplMap repl_node_inputs,
128 const FuncGraphPtr &func_graph) {
129 for (auto &node_pair : nodes_changed) {
130 CNodePtr old_node = node_pair.first;
131 CNodePtr new_node = node_pair.second;
132 MS_EXCEPTION_IF_NULL(old_node);
133 MS_EXCEPTION_IF_NULL(new_node);
134 for (size_t i = 0; i < old_node->size(); i++) {
135 auto input = old_node->input(i);
136 if (repl_node.count(input) != 0) {
137 new_node->add_input(repl_node[input]);
138 } else if (repl_node_inputs.count(std::pair<AnfNodePtr, size_t>(old_node, i)) != 0) {
139 new_node->add_input(repl_node_inputs[std::pair<AnfNodePtr, size_t>(old_node, i)]);
140 } else {
141 new_node->add_input(input);
142 }
143 }
144 }
145
146 for (auto &item : repl_node) {
147 if (IsPrimitiveCNode(item.second, prim::kPrimReturn)) {
148 func_graph->set_output(item.second->cast<CNodePtr>()->input(1));
149 } else if (!manager->Replace(item.first, item.second)) {
150 constexpr auto kDebugStrDepth = 2;
151 MS_LOG(INTERNAL_EXCEPTION) << "TransformGraphDependNode replace node failed original:"
152 << item.first->DebugString(kDebugStrDepth)
153 << " to new: " << item.second->DebugString(kDebugStrDepth);
154 }
155 }
156 }
157
HasDependencyOnSubGraph(const FuncGraphPtr & graph,const AnfNodePtr & state)158 bool HasDependencyOnSubGraph(const FuncGraphPtr &graph, const AnfNodePtr &state) {
159 std::queue<AnfNodePtr> nodes;
160 nodes.push(state);
161 while (!nodes.empty()) {
162 auto cur_node = nodes.front();
163 MS_EXCEPTION_IF_NULL(cur_node);
164 nodes.pop();
165 if (cur_node->isa<Parameter>() || cur_node->isa<ValueNode>()) {
166 continue;
167 }
168 if (cur_node->func_graph() == graph) {
169 return true;
170 }
171 auto cur_cnode = cur_node->cast<CNodePtr>();
172 MS_EXCEPTION_IF_NULL(cur_cnode);
173 for (size_t i = 1; i < cur_cnode->size(); i++) {
174 nodes.push(cur_cnode->input(i));
175 }
176 }
177 return false;
178 }
179
180 // trace the node that should add switch and replace them with new nodes in the graph
TransformGraphCondBranchNodes(const FuncGraphPtr & graph,const AnfNodePtr & cond,const std::function<AnfNodePtr (FuncGraphPtr graph,AnfNodePtr cond,AnfNodePtr data)> & generate_func)181 FuncGraphPtr TransformGraphCondBranchNodes(
182 const FuncGraphPtr &graph, const AnfNodePtr &cond,
183 const std::function<AnfNodePtr(FuncGraphPtr graph, AnfNodePtr cond, AnfNodePtr data)> &generate_func) {
184 auto manager = graph->manager();
185 MS_EXCEPTION_IF_NULL(manager);
186
187 // record the node that has been changed
188 std::vector<std::pair<CNodePtr, CNodePtr>> nodes_changed;
189 // record the node to be replaced
190 mindspore::HashMap<AnfNodePtr, AnfNodePtr> repl_node;
191 // record the node input to be replaced
192 NodeInputReplMap repl_node_inputs;
193 const AnfNodeSet &nodes = graph->nodes();
194 for (auto &node : nodes) {
195 MS_EXCEPTION_IF_NULL(node);
196 if (!node->isa<CNode>()) {
197 continue;
198 }
199 auto inputs = node->cast<CNodePtr>()->inputs();
200 bool should_replace = false;
201 // if the apply input does not belong to graph, insert a switch node
202 for (size_t index = 0; index < inputs.size(); index++) {
203 auto input_node = inputs[index];
204 MS_EXCEPTION_IF_NULL(input_node);
205 if (HasAbstractMonad(input_node)) {
206 // Do not guard with switch for monad inputs.
207 continue;
208 }
209 // for some ops input should not guard it with switch
210 if (InConvertWhiteList(node, index)) {
211 continue;
212 }
213
214 // If the input for node is not the graph belonged, or it is an ValueNode.
215 // Bypass the Primitive node which is inputs[0].
216 if ((index >= 1 && input_node->func_graph() != nullptr && input_node->func_graph() != graph) ||
217 ((index >= 1 && input_node->isa<ValueNode>()))) {
218 input_node = generate_func(graph, cond, input_node);
219 repl_node_inputs[std::pair<AnfNodePtr, size_t>(node, index)] = input_node;
220 should_replace = true;
221 }
222 // Insert GeSwitch after load
223 if (IsPrimitiveCNode(input_node, prim::kPrimLoad)) {
224 auto cnode_load = input_node->cast<CNodePtr>();
225 MS_EXCEPTION_IF_NULL(cnode_load);
226 auto load_real_input = cnode_load->inputs()[kLoadRealInput];
227 MS_EXCEPTION_IF_NULL(load_real_input);
228 auto load_state_input = cnode_load->inputs()[kLoadStateInput];
229 MS_EXCEPTION_IF_NULL(load_state_input);
230 if ((load_real_input->func_graph() != nullptr && load_real_input->func_graph() != graph) &&
231 !HasDependencyOnSubGraph(graph, load_state_input)) {
232 input_node = generate_func(graph, cond, input_node);
233 repl_node_inputs[std::pair<AnfNodePtr, size_t>(node, index)] = input_node;
234 should_replace = true;
235 }
236 }
237
238 if (input_node == nullptr) {
239 MS_LOG(INTERNAL_EXCEPTION) << "generate switch node failed";
240 }
241 }
242 if (should_replace) {
243 auto new_node = graph->NewCNode({});
244 repl_node[node] = new_node;
245 (void)nodes_changed.emplace_back(node->cast<CNodePtr>(), new_node);
246 }
247 }
248 RunSwitchNodeReplace(manager, nodes_changed, repl_node, repl_node_inputs, graph);
249 return graph;
250 }
251
252 struct SharedOp {
253 tensor::TensorPtr const_data;
254 CNodePtr square_ops[2];
255 CNodePtr merge_ops[2];
256 } MergeNetOutput;
257
GetConstData()258 inline tensor::TensorPtr GetConstData() { return MergeNetOutput.const_data; }
SetConstData(const tensor::TensorPtr & const_value)259 inline void SetConstData(const tensor::TensorPtr &const_value) { MergeNetOutput.const_data = const_value; }
260
GetSquareOp(int64_t switch_idx)261 inline CNodePtr GetSquareOp(int64_t switch_idx) { return MergeNetOutput.square_ops[switch_idx]; }
SetSquareOp(int64_t switch_idx,const CNodePtr & op)262 inline void SetSquareOp(int64_t switch_idx, const CNodePtr &op) { MergeNetOutput.square_ops[switch_idx] = op; }
263
GetMergeOp(int64_t switch_idx)264 inline CNodePtr GetMergeOp(int64_t switch_idx) { return MergeNetOutput.merge_ops[switch_idx]; }
SetMergeOp(int64_t switch_idx,const CNodePtr & op)265 inline void SetMergeOp(int64_t switch_idx, const CNodePtr &op) { MergeNetOutput.merge_ops[switch_idx] = op; }
266
ResetSharedOp()267 inline void ResetSharedOp() {
268 SetConstData(nullptr);
269 SetSquareOp(0, nullptr);
270 SetSquareOp(1, nullptr);
271 SetMergeOp(0, nullptr);
272 SetMergeOp(1, nullptr);
273 }
274
ConstData()275 tensor::TensorPtr ConstData() {
276 std::vector<int64_t> shp = {1};
277 tensor::TensorPtr const_data = std::make_shared<tensor::Tensor>(kInt64->type_id(), shp);
278 auto *val = static_cast<int64_t *>(const_data->data_c());
279 *val = 0;
280 return const_data;
281 }
282
SquareOp(const FuncGraphPtr & graph,const AnfNodePtr & cond,int64_t switch_idx,const tensor::TensorPtr & const_data)283 CNodePtr SquareOp(const FuncGraphPtr &graph, const AnfNodePtr &cond, int64_t switch_idx,
284 const tensor::TensorPtr &const_data) {
285 auto prim_square = prim::kPrimSquare;
286 // for the depended node , add two const data to merge the flow ,one for depended node with same switch,
287 // the other use the opposite
288 auto ctrl_data = NewValueNode(const_data);
289 auto ctrl_node = GenerateSwitchNode(graph, cond, ctrl_data, switch_idx);
290
291 std::vector<AnfNodePtr> square_nodes{NewValueNode(prim_square), ctrl_node};
292 auto square_op = graph->NewCNode(square_nodes);
293
294 return square_op;
295 }
296
MergeNode(const FuncGraphPtr & graph,const AnfNodePtr & cond,int64_t switch_idx,const tensor::TensorPtr & const_data,const CNodePtr & square_op)297 CNodePtr MergeNode(const FuncGraphPtr &graph, const AnfNodePtr &cond, int64_t switch_idx,
298 const tensor::TensorPtr &const_data, const CNodePtr &square_op) {
299 // for the depended node , add two const data to merge the flow ,one for depended node with same switch,
300 // the other use the opposite
301 auto oppsite_ctrl_data = NewValueNode(const_data);
302 auto opposite_ctrl_node = GenerateSwitchNode(graph, cond, oppsite_ctrl_data, 1 - switch_idx);
303
304 std::vector<AnfNodePtr> merge_nodes;
305 auto PrimMerge = prim::GetPythonOps("merge", "mindspore.ops.functional")->cast<PrimitivePtr>();
306 merge_nodes.push_back(NewValueNode(PrimMerge));
307 std::vector<AnfNodePtr> make_tuple_nodes{NewValueNode(prim::kPrimMakeTuple), square_op, opposite_ctrl_node};
308 merge_nodes.push_back(graph->NewCNode(make_tuple_nodes));
309 auto merge_op = graph->NewCNode(merge_nodes);
310
311 return merge_op;
312 }
313
314 // merge(square_op(switch(ctrl_data)), switch(opposite_ctrl_data))
GenerateSwitchDependNode(const FuncGraphPtr & graph,const AnfNodePtr & cond,const AnfNodePtr & output_node,int64_t switch_idx)315 AnfNodePtr GenerateSwitchDependNode(const FuncGraphPtr &graph, const AnfNodePtr &cond, const AnfNodePtr &output_node,
316 int64_t switch_idx) {
317 tensor::TensorPtr const_data = GetConstData();
318 if (const_data == nullptr) {
319 const_data = ConstData();
320 SetConstData(const_data);
321 }
322
323 CNodePtr square_op = GetSquareOp(switch_idx);
324 if (square_op == nullptr) {
325 square_op = SquareOp(graph, cond, switch_idx, const_data);
326 SetSquareOp(switch_idx, square_op);
327 }
328
329 auto manager = graph->manager();
330 MS_EXCEPTION_IF_NULL(manager);
331 AnfNodePtrList inputs = {NewValueNode(prim::kPrimDepend), square_op, output_node};
332 auto depend_cnode = graph->NewCNode(inputs);
333 if (!manager->Replace(square_op, depend_cnode)) {
334 MS_LOG(EXCEPTION) << square_op->DebugString() << ", replace node failed.";
335 }
336
337 CNodePtr merge_op = GetMergeOp(switch_idx);
338 if (merge_op == nullptr) {
339 merge_op = MergeNode(graph, cond, switch_idx, const_data, square_op);
340 SetMergeOp(switch_idx, merge_op);
341 }
342
343 return merge_op;
344 }
345
346 // generate switch nodes for true graph node inputs
GenerateSwitchDependTrueNode(const FuncGraphPtr & graph,const AnfNodePtr & cond,const AnfNodePtr & data)347 AnfNodePtr GenerateSwitchDependTrueNode(const FuncGraphPtr &graph, const AnfNodePtr &cond, const AnfNodePtr &data) {
348 // for switch op ,the output is a tuple ,0-th is false_branch, 1-th is true branch
349 return GenerateSwitchDependNode(graph, cond, data, 1);
350 }
351
352 // generate switch nodes for false graph node inputs
GenerateSwitchDependFalseNode(const FuncGraphPtr & graph,const AnfNodePtr & cond,const AnfNodePtr & data)353 AnfNodePtr GenerateSwitchDependFalseNode(const FuncGraphPtr &graph, const AnfNodePtr &cond, const AnfNodePtr &data) {
354 // for switch op ,the output is a tuple ,0-th is false_branch, 1-th is true branch
355 return GenerateSwitchDependNode(graph, cond, data, 0);
356 }
357
358 // to judge if the node used in Depend is a net output node
IsNetOutputNode(const FuncGraphManagerPtr & manager,const AnfNodePtr & node)359 bool IsNetOutputNode(const FuncGraphManagerPtr &manager, const AnfNodePtr &node) {
360 auto uses = manager->node_users()[node];
361 bool is_output_node = true;
362 for (auto &item : uses) {
363 if (IsPrimitiveCNode(item.first, prim::kPrimDepend)) {
364 continue;
365 }
366 is_output_node = false;
367 break;
368 }
369 return is_output_node;
370 }
371
372 // generate node for Depended MakeTuple
GenerateReplNodeForDependMakeTuple(const AnfNodePtr & depended_node,const FuncGraphPtr & graph,const AnfNodePtr & cond,const std::shared_ptr<mindspore::HashMap<AnfNodePtr,AnfNodePtr>> & repl_node,const std::function<AnfNodePtr (FuncGraphPtr graph,AnfNodePtr cond,AnfNodePtr data)> & generate_func)373 void GenerateReplNodeForDependMakeTuple(
374 const AnfNodePtr &depended_node, const FuncGraphPtr &graph, const AnfNodePtr &cond,
375 const std::shared_ptr<mindspore::HashMap<AnfNodePtr, AnfNodePtr>> &repl_node,
376 const std::function<AnfNodePtr(FuncGraphPtr graph, AnfNodePtr cond, AnfNodePtr data)> &generate_func) {
377 MS_EXCEPTION_IF_NULL(graph->manager());
378
379 auto make_tuple_inputs = depended_node->cast<CNodePtr>()->inputs();
380 const size_t make_tuple_begin_idx = 1;
381 std::vector<AnfNodePtr> new_make_tuple_nodes;
382 bool replace_make_tuple = false;
383 new_make_tuple_nodes.push_back(NewValueNode(prim::kPrimMakeTuple));
384 for (size_t idx = make_tuple_begin_idx; idx < make_tuple_inputs.size(); idx++) {
385 auto depended_tuple_input_node = make_tuple_inputs[idx];
386 if (IsPrimitiveCNode(depended_tuple_input_node->cast<CNodePtr>(), prim::kPrimDepend)) {
387 new_make_tuple_nodes.push_back(depended_tuple_input_node);
388 continue;
389 }
390
391 if (graph->manager()->node_users()[depended_tuple_input_node].size() == 1) {
392 auto gen_node = generate_func(graph, cond, depended_tuple_input_node);
393 new_make_tuple_nodes.push_back(gen_node);
394 replace_make_tuple = true;
395 continue;
396 }
397
398 MS_LOG(WARNING) << "depended node being used by others, ";
399 }
400 if (replace_make_tuple) {
401 auto make_tuple_op = graph->NewCNode(new_make_tuple_nodes);
402 (*repl_node)[depended_node] = make_tuple_op;
403 }
404 }
405
406 // generate a replace depend node for a single network output node
GenerateRepDepend(const CNodePtr & node,const FuncGraphPtr & graph,const AnfNodePtr & cond,const std::shared_ptr<mindspore::HashMap<AnfNodePtr,AnfNodePtr>> & repl_node,const std::function<AnfNodePtr (FuncGraphPtr graph,AnfNodePtr cond,AnfNodePtr data)> & generate_func)407 void GenerateRepDepend(
408 const CNodePtr &node, const FuncGraphPtr &graph, const AnfNodePtr &cond,
409 const std::shared_ptr<mindspore::HashMap<AnfNodePtr, AnfNodePtr>> &repl_node,
410 const std::function<AnfNodePtr(FuncGraphPtr graph, AnfNodePtr cond, AnfNodePtr data)> &generate_func) {
411 MS_EXCEPTION_IF_NULL(graph->manager());
412
413 auto inputs = node->inputs();
414 if (inputs.size() != kDependInputSize) {
415 MS_LOG(EXCEPTION) << "For 'Depend', the inputs should be [depend_prim, actual_value, depended_node].";
416 }
417
418 std::vector<AnfNodePtr> new_depened_inputs;
419 // Inputs should be [depend, actual_value, depended_node]
420 auto depended_node = inputs[kDependAttachNodeIndex];
421 new_depened_inputs.push_back(inputs[0]);
422 new_depened_inputs.push_back(inputs[1]);
423 // depended node should be make_tuple or a single depended node
424 if (IsPrimitiveCNode(depended_node, prim::kPrimMakeTuple)) {
425 GenerateReplNodeForDependMakeTuple(depended_node, graph, cond, repl_node, generate_func);
426 } else {
427 // Check if there is only single user for depend_node.
428 if (graph->manager()->node_users()[depended_node].size() == 1) {
429 auto gen_node = generate_func(graph, cond, depended_node);
430 (*repl_node)[depended_node] = gen_node;
431 } else {
432 MS_LOG(WARNING) << "depended node being used by others";
433 }
434 }
435 }
436
437 // generate depend node for netoutput node, to resolve the stream synchronize problem of ge
438 // traverse all nodes of depend node, find the graph output node , generaete a merge node of (square, const)
TransformGraphDependNode(const FuncGraphPtr & graph,const AnfNodePtr & cond,const std::function<AnfNodePtr (FuncGraphPtr graph,AnfNodePtr cond,AnfNodePtr data)> & gen_depend_func)439 FuncGraphPtr TransformGraphDependNode(
440 const FuncGraphPtr &graph, const AnfNodePtr &cond,
441 const std::function<AnfNodePtr(FuncGraphPtr graph, AnfNodePtr cond, AnfNodePtr data)> &gen_depend_func) {
442 auto manager = graph->manager();
443 MS_EXCEPTION_IF_NULL(manager);
444
445 ResetSharedOp();
446 std::shared_ptr<mindspore::HashMap<AnfNodePtr, AnfNodePtr>> repl_node =
447 std::make_shared<mindspore::HashMap<AnfNodePtr, AnfNodePtr>>(); // record the node to be replaced
448 const AnfNodeSet &nodes = graph->nodes();
449 for (auto &node : nodes) {
450 MS_EXCEPTION_IF_NULL(node);
451 if (!node->isa<CNode>()) {
452 continue;
453 }
454 if (IsPrimitiveCNode(node, prim::kPrimDepend)) {
455 auto cnode = node->cast<CNodePtr>();
456 if (cnode->size() != kDependInputSize) {
457 MS_LOG(EXCEPTION) << "For primitive 'Depend', the input size must be " << kDependInputSize << ", but got "
458 << cnode->size();
459 }
460 auto depended_node = cnode->input(kDependAttachNodeIndex);
461 MS_EXCEPTION_IF_NULL(depended_node);
462 if (!depended_node->isa<CNode>()) {
463 continue;
464 }
465 if (IsPrimitiveCNode(depended_node, prim::kPrimDepend)) {
466 continue;
467 }
468 GenerateRepDepend(cnode, graph, cond, repl_node, gen_depend_func);
469 }
470 }
471 ResetSharedOp();
472
473 for (auto &item : *repl_node) {
474 if (!manager->Replace(item.first, item.second)) {
475 MS_LOG(INTERNAL_EXCEPTION) << "TransformGraphDependNode replace node failed";
476 }
477 }
478
479 return graph;
480 }
481
TransformGraphCondTrueBranchNodes(const FuncGraphPtr & graph,const AnfNodePtr & cond)482 FuncGraphPtr TransformGraphCondTrueBranchNodes(const FuncGraphPtr &graph, const AnfNodePtr &cond) {
483 (void)TransformGraphCondBranchNodes(graph, cond, GenerateSwitchTrueNode);
484 return TransformGraphDependNode(graph, cond, GenerateSwitchDependTrueNode);
485 }
486
TransformGraphCondFalseBranchNodes(const FuncGraphPtr & graph,const AnfNodePtr & cond)487 FuncGraphPtr TransformGraphCondFalseBranchNodes(const FuncGraphPtr &graph, const AnfNodePtr &cond) {
488 (void)TransformGraphCondBranchNodes(graph, cond, GenerateSwitchFalseNode);
489 return TransformGraphDependNode(graph, cond, GenerateSwitchDependFalseNode);
490 }
491
492 // Judge if the true and false graph output is compatible(they shall have same tuple size)
GraphOutputCompatible(const AbstractBasePtr & true_branch_abs,const AbstractBasePtr & false_branch_abs)493 bool GraphOutputCompatible(const AbstractBasePtr &true_branch_abs, const AbstractBasePtr &false_branch_abs) {
494 MS_EXCEPTION_IF_NULL(true_branch_abs);
495 MS_EXCEPTION_IF_NULL(false_branch_abs);
496
497 if (true_branch_abs->isa<abstract::AbstractTuple>() && false_branch_abs->isa<abstract::AbstractTuple>()) {
498 abstract::AbstractTuplePtr true_branch_tuple = true_branch_abs->cast<abstract::AbstractTuplePtr>();
499 abstract::AbstractTuplePtr false_branch_tuple = false_branch_abs->cast<abstract::AbstractTuplePtr>();
500 if (true_branch_tuple->elements().size() != false_branch_tuple->elements().size()) {
501 MS_LOG(ERROR) << "true branch size:" << true_branch_tuple->elements().size()
502 << ", not equal to false branch size:" << false_branch_tuple->elements().size() << " ";
503 return false;
504 }
505 bool all_compatible = true;
506 for (size_t i = 0; i < true_branch_tuple->elements().size(); i++) {
507 all_compatible =
508 all_compatible && GraphOutputCompatible(true_branch_tuple->elements()[i], false_branch_tuple->elements()[i]);
509 }
510 return all_compatible;
511 }
512 TypePtr true_branch_type = true_branch_abs->BuildType();
513 TypePtr false_branch_type = false_branch_abs->BuildType();
514 MS_LOG(DEBUG) << "branch output Type equal?" << (*true_branch_type == *false_branch_type)
515 << " true:" << true_branch_type->ToString() << " false:" << false_branch_type->ToString();
516 return (*true_branch_type == *false_branch_type);
517 }
518
519 // block_nodes[0]: condition node
520 // block_nodes[1]: true branch node
521 // block_nodes[2]: false branch node
522 // branch_output_abs[0]: true branch abstract
523 // branch_output_abs[1]: false branch abstract
GenerateMergeNodes(const std::vector<AnfNodePtr> & block_nodes,const std::vector<AbstractBasePtr> & branch_output_abs,const FuncGraphPtr & switch_graph)524 AnfNodePtr GenerateMergeNodes(const std::vector<AnfNodePtr> &block_nodes,
525 const std::vector<AbstractBasePtr> &branch_output_abs, const FuncGraphPtr &switch_graph) {
526 MS_EXCEPTION_IF_NULL(branch_output_abs[0]);
527 MS_EXCEPTION_IF_NULL(branch_output_abs[1]);
528 MS_EXCEPTION_IF_NULL(block_nodes[0]);
529 MS_EXCEPTION_IF_NULL(switch_graph);
530 auto PrimMerge = prim::GetPythonOps("merge", "mindspore.ops.functional")->cast<PrimitivePtr>();
531 MS_EXCEPTION_IF_NULL(PrimMerge);
532
533 if (!branch_output_abs[0]->isa<abstract::AbstractTuple>()) {
534 std::vector<AnfNodePtr> merge_nodes;
535 merge_nodes.push_back(NewValueNode(PrimMerge));
536 std::vector<AnfNodePtr> make_tuple_nodes{NewValueNode(prim::kPrimMakeTuple), block_nodes[1], block_nodes[2]};
537 merge_nodes.push_back(switch_graph->NewCNode(make_tuple_nodes));
538 std::vector<AnfNodePtr> tuple_getitem_nodes{NewValueNode(prim::kPrimTupleGetItem),
539 switch_graph->NewCNode(merge_nodes),
540 NewValueNode(MakeValue(static_cast<int64_t>(0)))};
541 return switch_graph->NewCNode(tuple_getitem_nodes);
542 } else {
543 auto true_branch_tuple = branch_output_abs[0]->cast<abstract::AbstractTuplePtr>();
544 auto false_branch_tuple = branch_output_abs[1]->cast<abstract::AbstractTuplePtr>();
545
546 std::vector<AnfNodePtr> make_tuple_nodes;
547 make_tuple_nodes.push_back(NewValueNode(prim::kPrimMakeTuple));
548 for (size_t i = 0; i < true_branch_tuple->elements().size(); i++) {
549 std::vector<AnfNodePtr> true_getitem_nodes{NewValueNode(prim::kPrimTupleGetItem), block_nodes[1],
550 NewValueNode(MakeValue(SizeToLong(i)))};
551 auto true_node = switch_graph->NewCNode(true_getitem_nodes);
552 std::vector<AnfNodePtr> false_getitem_nodes{NewValueNode(prim::kPrimTupleGetItem), block_nodes[2],
553 NewValueNode(MakeValue(SizeToLong(i)))};
554 auto false_node = switch_graph->NewCNode(false_getitem_nodes);
555
556 auto merge_node = GenerateMergeNodes(
557 {
558 block_nodes[0],
559 true_node,
560 false_node,
561 },
562 {true_branch_tuple->elements()[i], false_branch_tuple->elements()[i]}, switch_graph);
563 make_tuple_nodes.push_back(merge_node);
564 }
565 return switch_graph->NewCNode(make_tuple_nodes);
566 }
567 }
568
TransformMergeBranches(const std::vector<AnfNodePtr> & block_nodes,const std::vector<AbstractBasePtr> & branch_output_abs,const FuncGraphPtr & func_graph)569 AnfNodePtr TransformMergeBranches(const std::vector<AnfNodePtr> &block_nodes,
570 const std::vector<AbstractBasePtr> &branch_output_abs,
571 const FuncGraphPtr &func_graph) {
572 if (!GraphOutputCompatible(branch_output_abs[0], branch_output_abs[1])) {
573 MS_LOG(EXCEPTION) << "Switch output branch not compatible, true:" << branch_output_abs[0]->ToString()
574 << ", false:" << branch_output_abs[1]->ToString();
575 }
576 return GenerateMergeNodes(block_nodes, branch_output_abs, func_graph);
577 }
578 } // namespace internal
579
CheckSwitchBranch(const AnfNodePtr & node) const580 bool ConvertSwitchReplacement::CheckSwitchBranch(const AnfNodePtr &node) const {
581 if (!IsValueNode<FuncGraph>(node)) {
582 return false;
583 }
584 // If graph contains FuncGraph, then ignore this node.
585 auto graph = GetValueNode<FuncGraphPtr>(node);
586 for (auto &item : graph->value_nodes()) {
587 auto value_node = item.first;
588 if (IsValueNode<FuncGraph>(value_node)) {
589 return false;
590 }
591 }
592 return true;
593 }
594
CheckSwitchWrapNode(const AnfNodePtr & node) const595 bool ConvertSwitchReplacement::CheckSwitchWrapNode(const AnfNodePtr &node) const {
596 // {{prim::kPrimSwitch, X, G1, G2}, Xs}.
597 if (node->isa<CNode>()) {
598 auto inp0 = node->cast<CNodePtr>()->input(0);
599 if (IsPrimitiveCNode(inp0, prim::kPrimSwitch)) {
600 auto switch_node = inp0->cast<CNodePtr>();
601 // for switch replace method, only graphs without graph inside can be replaced
602 if (CheckSwitchBranch(switch_node->input(kTrueBranchIndex)) &&
603 CheckSwitchBranch(switch_node->input(kFalseBranchIndex))) {
604 return true;
605 }
606 }
607 }
608 return false;
609 }
610
TransformSwitchBranchReplace(const AnfNodePtr & node) const611 void ConvertSwitchReplacement::TransformSwitchBranchReplace(const AnfNodePtr &node) const {
612 auto cnode = node->cast<CNodePtr>();
613 MS_EXCEPTION_IF_NULL(cnode);
614 constexpr size_t input_index = 0;
615 auto switch_cnode = cnode->input(input_index)->cast<CNodePtr>();
616 MS_EXCEPTION_IF_NULL(switch_cnode);
617 auto cond = switch_cnode->input(kCondIndex);
618 auto true_br = switch_cnode->input(kTrueBranchIndex);
619 auto false_br = switch_cnode->input(kFalseBranchIndex);
620
621 auto g1 = GetValueNode<FuncGraphPtr>(true_br);
622 auto g2 = GetValueNode<FuncGraphPtr>(false_br);
623 auto true_output = g1->output()->abstract();
624 auto false_output = g2->output()->abstract();
625 auto trans_g1 = internal::TransformGraphCondTrueBranchNodes(g1, cond);
626 auto trans_g2 = internal::TransformGraphCondFalseBranchNodes(g2, cond);
627
628 std::vector<AnfNodePtr> params;
629 if (cnode->size() > 1) {
630 // There are arguments for the call of switch result,
631 // usually these are monad states added by auto-monad.
632 for (size_t i = 1; i < cnode->size(); ++i) {
633 params.push_back(cnode->inputs().at(i));
634 }
635 }
636 auto fg = node->func_graph();
637 auto cloned_g1 = InlineClone(trans_g1, fg, params);
638 auto cloned_g2 = InlineClone(trans_g2, fg, params);
639 auto new_node = internal::TransformMergeBranches({cond, cloned_g1, cloned_g2}, {true_output, false_output}, fg);
640 (void)fg->manager()->Replace(node, new_node);
641 }
642 } // namespace irpass
643 } // namespace opt
644 } // namespace mindspore
645