1 /**
2 * Copyright 2020 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 <fstream>
18 #include <sstream>
19 #include <utility>
20 #include "src/common/graph_util.h"
21 #include "src/common/utils.h"
22 #include "src/common/log_adapter.h"
23 #include "src/common/version_manager.h"
24 #include "include/errorcode.h"
25 #ifdef ENABLE_V0
26 #include "schema/model_v0_generated.h"
27 #endif
28
29 namespace mindspore {
30 namespace lite {
GetGraphInputNodes(const lite::Model * model)31 std::vector<size_t> GetGraphInputNodes(const lite::Model *model) {
32 MS_ASSERT(model != nullptr);
33 MS_ASSERT(!(model->graph_.sub_graphs_.empty()));
34 std::vector<size_t> ret;
35 for (auto graph_in_index : model->graph_.input_indices_) {
36 auto node_size = model->graph_.all_nodes_.size();
37 for (size_t j = 0; j < node_size; ++j) {
38 auto node = model->graph_.all_nodes_[j];
39 MS_ASSERT(node != nullptr);
40 if (std::any_of(node->input_indices_.begin(), node->input_indices_.end(),
41 [&](const uint32_t &node_in_index) { return node_in_index == graph_in_index; })) {
42 if (!IsContain<size_t>(ret, j)) {
43 ret.emplace_back(j);
44 }
45 }
46 }
47 }
48 return ret;
49 }
50
GetGraphOutputNodes(const lite::Model * model)51 std::vector<size_t> GetGraphOutputNodes(const lite::Model *model) {
52 MS_ASSERT(model != nullptr);
53 std::vector<size_t> ret;
54 for (auto graph_out_index : model->graph_.output_indices_) {
55 auto node_size = model->graph_.all_nodes_.size();
56 for (size_t j = 0; j < node_size; ++j) {
57 auto node = model->graph_.all_nodes_[j];
58 MS_ASSERT(node != nullptr);
59 if (std::any_of(node->output_indices_.begin(), node->output_indices_.end(),
60 [&](const uint32_t &node_out_index) { return node_out_index == graph_out_index; })) {
61 if (!IsContain<size_t>(ret, j)) {
62 ret.emplace_back(j);
63 }
64 }
65 }
66 }
67 return ret;
68 }
69
GetLinkedPostNodeIdx(const lite::Model * model,const size_t tensor_idx)70 std::vector<size_t> GetLinkedPostNodeIdx(const lite::Model *model, const size_t tensor_idx) {
71 MS_ASSERT(model != nullptr);
72 std::vector<size_t> post_node_idxes;
73 auto nodes_size = model->graph_.all_nodes_.size();
74 for (size_t i = 0; i < nodes_size; ++i) {
75 auto node = model->graph_.all_nodes_[i];
76 if (node == nullptr) {
77 continue;
78 }
79
80 auto is_contain = std::any_of(node->input_indices_.begin(), node->input_indices_.end(),
81 [&](const uint32_t &node_input_idx) { return node_input_idx == tensor_idx; });
82 if (is_contain) {
83 post_node_idxes.emplace_back(i);
84 }
85 }
86 return post_node_idxes;
87 }
88
89 // only support op_type from current schema
IsPackedOp(int op_type)90 bool IsPackedOp(int op_type) {
91 static const std::vector<int> packed_ops = {schema::PrimitiveType_Conv2DFusion,
92 schema::PrimitiveType_Conv2dTransposeFusion,
93 schema::PrimitiveType_MatMulFusion};
94 return IsContain(packed_ops, op_type);
95 }
96 } // namespace lite
97 } // namespace mindspore
98