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1 /*
2  * Copyright (c) 2022 Huawei Device Co., Ltd.
3  * Licensed under the Apache License, Version 2.0 (the "License");
4  * you may not use this file except in compliance with the License.
5  * You may obtain a copy of the License at
6  *
7  *     http://www.apache.org/licenses/LICENSE-2.0
8  *
9  * Unless required by applicable law or agreed to in writing, software
10  * distributed under the License is distributed on an "AS IS" BASIS,
11  * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
12  * See the License for the specific language governing permissions and
13  * limitations under the License.
14  */
15 
16 #include "squeeze_builder.h"
17 
18 #include "mindir.h"
19 
20 namespace OHOS {
21 namespace NeuralNetworkRuntime {
22 namespace Ops {
23 static const int INPUT_NUM = 1;
24 static const int OUTPUT_NUM = 1;
25 static const std::string OP_NAME = "Squeeze";
26 
SqueezeBuilder()27 SqueezeBuilder::SqueezeBuilder() {}
28 
~SqueezeBuilder()29 SqueezeBuilder::~SqueezeBuilder() {}
30 
SetAxis(std::shared_ptr<NNTensor> tensor)31 OH_NN_ReturnCode SqueezeBuilder::SetAxis(std::shared_ptr<NNTensor> tensor)
32 {
33     if (tensor->GetDataType() != OH_NN_INT64) {
34         LOGE("[SqueezeBuilder] The 2nd input axis should be type OH_NN_INT64.");
35         return OH_NN_INVALID_PARAMETER;
36     }
37 
38     void* buffer = tensor->GetBuffer();
39     if (buffer == nullptr) {
40         LOGE("[SqueezeBuilder] Tensor buffer is nullptr.");
41         return OH_NN_INVALID_PARAMETER;
42     }
43 
44     int64_t *axis_data_ptr = static_cast<int64_t *>(buffer);
45     const uint32_t elementSize = tensor->GetElementCount();
46     for (uint32_t i = 0; i < elementSize; ++i) {
47         m_axis.push_back(*axis_data_ptr);
48         ++axis_data_ptr;
49     }
50 
51     return OH_NN_SUCCESS;
52 }
53 
54 /* *
55  * Build method.
56  * 1.set attr of ops.
57  * 2.set inputIndex of ops.
58  * 3.set outputIndex of ops.
59  */
Build(const std::vector<uint32_t> & paramsIndex,const std::vector<uint32_t> & inputsIndex,const std::vector<uint32_t> & outputsIndex,const std::vector<std::shared_ptr<NNTensor>> & allTensors)60 OH_NN_ReturnCode SqueezeBuilder::Build(const std::vector<uint32_t> &paramsIndex,
61                                        const std::vector<uint32_t> &inputsIndex,
62                                        const std::vector<uint32_t> &outputsIndex,
63                                        const std::vector<std::shared_ptr<NNTensor>> &allTensors)
64 {
65     if (m_isBuild) {
66         LOGE("[SqueezeBuilder] Squeeze operation has been build, cannot build again.");
67         return OH_NN_OPERATION_FORBIDDEN;
68     }
69 
70     OH_NN_ReturnCode returnCode = CheckIOIndex(inputsIndex, outputsIndex, allTensors, INPUT_NUM, OUTPUT_NUM);
71     if (returnCode != OH_NN_SUCCESS) {
72         LOGE("[SqueezeBuilder] Passed invalid input or output index.");
73         return returnCode;
74     }
75 
76     m_inputsIndex = inputsIndex;
77     m_outputsIndex = outputsIndex;
78 
79     for (int i : paramsIndex) {
80         std::shared_ptr<NNTensor> tensor = allTensors[i];
81         tensor->IdentifyOpParameter();
82         switch (tensor->GetType()) {
83             case OH_NN_SQUEEZE_AXIS:
84                 returnCode = SetAxis(tensor);
85                 break;
86             default:
87                 LOGE("[SqueezeBuilder] Parameter Type is invalid. type=%d", tensor->GetType());
88                 return OH_NN_INVALID_PARAMETER;
89         }
90 
91         if (returnCode != OH_NN_SUCCESS) {
92             LOGE("[SqueezeBuilder] Passed invalid param.");
93             return returnCode;
94         }
95     }
96 
97     // The quantization type of the first output determinies that of the operator.
98     SetQuantType(outputsIndex, allTensors);
99 
100     m_isBuild = true;
101     m_name = OP_NAME;
102     return OH_NN_SUCCESS;
103 }
104 
GetPrimitive()105 LiteGraphTensorPtr SqueezeBuilder::GetPrimitive()
106 {
107     if (!m_isBuild) {
108         LOGE("[SqueezeBuilder] Cannot get primitive before call build.");
109         return { nullptr, DestroyLiteGraphPrimitive };
110     }
111 
112     auto primitive = mindspore::lite::MindIR_Squeeze_CreatePrimitive(m_axis);
113     if (primitive == nullptr) {
114         LOGE("[SqueezeBuilder] MindIR_Squeeze_CreatePrimitive failed.");
115         return { nullptr, DestroyLiteGraphPrimitive };
116     }
117 
118     LiteGraphTensorPtr graphPrimitivePtr(primitive, DestroyLiteGraphPrimitive);
119     return graphPrimitivePtr;
120 }
121 
122 REGISTER_OPS(SqueezeBuilder, OH_NN_OPS_SQUEEZE);
123 } // namespace Ops
124 } // namespace NeuralNetworkRuntime
125 } // namespace OHOS