1 /*
2 * Copyright (c) 2023 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 "range_builder.h"
17
18 namespace OHOS {
19 namespace NeuralNetworkRuntime {
20 namespace Ops {
21 static const int INPUT_NUM = 1;
22 static const int OUTPUT_NUM = 1;
23 static const int PARAM_MAX_NUM = 3;
24 static const int SCALAR_LENGTH = 1;
25 static const std::string OP_NAME = "Range";
26
RangeBuilder()27 RangeBuilder::RangeBuilder() {}
28
~RangeBuilder()29 RangeBuilder::~RangeBuilder() {}
30
SetStart(const std::shared_ptr<NNTensor> & tensor)31 OH_NN_ReturnCode RangeBuilder::SetStart(const std::shared_ptr<NNTensor>& tensor)
32 {
33 if (tensor->GetDataType() != OH_NN_INT64) {
34 LOGE("[Range] The start should be type OH_NN_INT64.");
35 return OH_NN_INVALID_PARAMETER;
36 }
37
38 if (tensor->GetElementCount() != SCALAR_LENGTH) {
39 LOGE("[Range] The start should be scalar.");
40 return OH_NN_INVALID_PARAMETER;
41 }
42
43 void* buffer = tensor->GetBuffer();
44 if (buffer == nullptr) {
45 LOGE("[Range] Tensor buffer is nullptr.");
46 return OH_NN_INVALID_PARAMETER;
47 }
48 m_start = *(static_cast<const int64_t*>(buffer));
49
50 return OH_NN_SUCCESS;
51 }
52
SetLimit(const std::shared_ptr<NNTensor> & tensor)53 OH_NN_ReturnCode RangeBuilder::SetLimit(const std::shared_ptr<NNTensor>& tensor)
54 {
55 if (tensor->GetDataType() != OH_NN_INT64) {
56 LOGE("[Range] The limit should be type OH_NN_INT64.");
57 return OH_NN_INVALID_PARAMETER;
58 }
59
60 if (tensor->GetElementCount() != SCALAR_LENGTH) {
61 LOGE("[Range] The limit should be scalar.");
62 return OH_NN_INVALID_PARAMETER;
63 }
64
65 void* buffer = tensor->GetBuffer();
66 if (buffer == nullptr) {
67 LOGE("[Range] Tensor buffer is nullptr.");
68 return OH_NN_INVALID_PARAMETER;
69 }
70 m_limit = *(static_cast<const int64_t*>(buffer));
71
72 return OH_NN_SUCCESS;
73 }
74
SetDelta(const std::shared_ptr<NNTensor> & tensor)75 OH_NN_ReturnCode RangeBuilder::SetDelta(const std::shared_ptr<NNTensor>& tensor)
76 {
77 if (tensor->GetDataType() != OH_NN_INT64) {
78 LOGE("[Range] The delta should be type OH_NN_INT64.");
79 return OH_NN_INVALID_PARAMETER;
80 }
81
82 if (tensor->GetElementCount() != SCALAR_LENGTH) {
83 LOGE("[Range] The delta should be scalar.");
84 return OH_NN_INVALID_PARAMETER;
85 }
86
87 void* buffer = tensor->GetBuffer();
88 if (buffer == nullptr) {
89 LOGE("[Range] Tensor buffer is nullptr.");
90 return OH_NN_INVALID_PARAMETER;
91 }
92 m_delta = *(static_cast<const int64_t*>(buffer));
93
94 return OH_NN_SUCCESS;
95 }
96
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)97 OH_NN_ReturnCode RangeBuilder::Build(const std::vector<uint32_t>& paramsIndex,
98 const std::vector<uint32_t>& inputsIndex,
99 const std::vector<uint32_t>& outputsIndex,
100 const std::vector<std::shared_ptr<NNTensor>>& allTensors)
101 {
102 if (m_isBuild) {
103 LOGE("[Range] Build failed, the Range operation has been build. cannot build again.");
104 return OH_NN_OPERATION_FORBIDDEN;
105 }
106
107 auto ret = CheckIOIndex(inputsIndex, outputsIndex, allTensors, INPUT_NUM, OUTPUT_NUM);
108 if (ret != OH_NN_SUCCESS) {
109 LOGE("[Range] Build failed, passed invalid input or output index.");
110 return ret;
111 }
112
113 m_inputsIndex = inputsIndex;
114 m_outputsIndex = outputsIndex;
115
116 ret = CheckParamIndex(paramsIndex, allTensors, PARAM_MAX_NUM);
117 if (ret != OH_NN_SUCCESS) {
118 LOGE("[Range] Build failed, passed invalid param index.");
119 return ret;
120 }
121
122 for (int i : paramsIndex) {
123 std::shared_ptr<NNTensor> tensor = allTensors[i];
124 tensor->IdentifyOpParameter();
125 if (m_paramMap.find(tensor->GetType()) != m_paramMap.end()) {
126 ret = (this->*(m_paramMap[tensor->GetType()]))(tensor);
127 } else {
128 LOGE("[Range] Build failed, param invalid, type=%d", tensor->GetType());
129 return OH_NN_INVALID_PARAMETER;
130 }
131
132 if (ret != OH_NN_SUCCESS) {
133 LOGE("[Range] Build failed, passed invalid param.");
134 return ret;
135 }
136 }
137
138 m_name = OP_NAME;
139 m_isBuild = true;
140 return OH_NN_SUCCESS;
141 }
142
GetPrimitive()143 LiteGraphPrimitvePtr RangeBuilder::GetPrimitive()
144 {
145 if (!m_isBuild) {
146 LOGE("[Range] GetPrimitive failed, cannot get primitive before call build.");
147 return {nullptr, DestroyLiteGraphPrimitive};
148 }
149
150 int64_t dType {0.0f};
151 void* primitive = mindspore::lite::MindIR_Range_CreatePrimitive(dType, m_start, m_limit, m_delta);
152 LiteGraphPrimitvePtr graphPrimitivePtr(primitive, DestroyLiteGraphPrimitive) ;
153 return graphPrimitivePtr;
154 }
155
156 REGISTER_OPS(RangeBuilder, OH_NN_OPS_RANGE);
157 } // namespace Ops
158 } // namespace NeuralNetworkRuntime
159 } // namespace OHOS
160