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 "conv2d_transpose_builder.h"
17
18 #include "transform.h"
19 #include "validation.h"
20 #include "ops_validation.h"
21
22 namespace OHOS {
23 namespace NeuralNetworkRuntime {
24 namespace Ops {
25 static constexpr int INPUT_NUM = 3;
26 static constexpr int OUTPUT_NUM = 1;
27 static constexpr int INPUT_WEIGHT = 1;
28 static constexpr int WEIGHT_SIZE = 4;
29 static constexpr int OUT_CHANNEL_INDEX = 0;
30 static constexpr int IN_CHANNEL_INDEX = 3;
31 static constexpr int KERNEL_HEIGHT_INDEX = 1;
32 static constexpr int KERNEL_WEIGHT_INDEX = 2;
33 static constexpr int PAD_MODE_PARAM_NUM = 1;
34 static constexpr int PAD_LIST_PARAM_NUM = 4;
35 static constexpr int SCALAR_LENGTH = 1;
36 static const std::string OP_NAME = "Conv2DTranspose";
37
Conv2DTransposeBuilder()38 Conv2DTransposeBuilder::Conv2DTransposeBuilder() {}
39
~Conv2DTransposeBuilder()40 Conv2DTransposeBuilder::~Conv2DTransposeBuilder() {}
41
SetInput(const std::vector<uint32_t> & inputsIndex,const std::vector<uint32_t> & outputsIndex,const std::vector<std::shared_ptr<NNTensor>> & allTensors)42 OH_NN_ReturnCode Conv2DTransposeBuilder::SetInput(const std::vector<uint32_t>& inputsIndex,
43 const std::vector<uint32_t>& outputsIndex,
44 const std::vector<std::shared_ptr<NNTensor>>& allTensors)
45 {
46 OH_NN_ReturnCode returnCode = CheckIOIndex(inputsIndex, outputsIndex, allTensors, INPUT_NUM, OUTPUT_NUM);
47 if (returnCode != OH_NN_SUCCESS) {
48 LOGE("[Conv2dTranspose] SetInput failed, Passed invalid input or output index.");
49 return returnCode;
50 }
51
52 m_inputsIndex = inputsIndex;
53 m_outputsIndex = outputsIndex;
54
55 // set inChannel, outChannel, kernelSize
56 auto weightShape = allTensors[inputsIndex[INPUT_WEIGHT]]->GetDimensions();
57 if (weightShape.size() != WEIGHT_SIZE) {
58 LOGE("[Conv2dTranspose] SetInput failed, the dimension of weight should be %d", WEIGHT_SIZE);
59 return OH_NN_INVALID_PARAMETER;
60 }
61
62 m_inChannel = weightShape[IN_CHANNEL_INDEX];
63 m_outChannel = weightShape[OUT_CHANNEL_INDEX];
64
65 return OH_NN_SUCCESS;
66 }
67
SetKernelSize(const std::vector<uint32_t> & inputsIndex,const std::vector<std::shared_ptr<NNTensor>> & allTensors)68 void Conv2DTransposeBuilder::SetKernelSize(const std::vector<uint32_t>& inputsIndex,
69 const std::vector<std::shared_ptr<NNTensor>>& allTensors)
70 {
71 auto weightShape = allTensors[inputsIndex[INPUT_WEIGHT]]->GetDimensions();
72
73 m_kernelSize.clear();
74 m_kernelSize.emplace_back(weightShape[KERNEL_HEIGHT_INDEX]);
75 m_kernelSize.emplace_back(weightShape[KERNEL_WEIGHT_INDEX]);
76 }
77
SetStrides(std::shared_ptr<NNTensor> tensor)78 OH_NN_ReturnCode Conv2DTransposeBuilder::SetStrides(std::shared_ptr<NNTensor> tensor)
79 {
80 tensor->IdentifyOpParameter();
81 // Set Strides
82 if (tensor->GetDataType() != OH_NN_INT64) {
83 LOGE("[Conv2DTranspose] SetStrides failed, the Strides should be type OH_NN_INT64.");
84 return OH_NN_INVALID_PARAMETER;
85 }
86
87 void* buffer = tensor->GetBuffer();
88 if (buffer == nullptr) {
89 LOGE("[Conv2DTranspose] SetStrides GetBuffer return nullptr");
90 return OH_NN_INVALID_PARAMETER;
91 }
92 const int64_t* pStrides = reinterpret_cast<const int64_t*>(buffer);
93 uint32_t elementSize = tensor->GetElementCount();
94 m_strides.assign(pStrides, pStrides + elementSize);
95
96 return OH_NN_SUCCESS;
97 }
98
SetDilation(std::shared_ptr<NNTensor> tensor)99 OH_NN_ReturnCode Conv2DTransposeBuilder::SetDilation(std::shared_ptr<NNTensor> tensor)
100 {
101 tensor->IdentifyOpParameter();
102 // Set Dilation
103 if (tensor->GetDataType() != OH_NN_INT64) {
104 LOGE("[Conv2DTranspose] SetDilation failed, the Dilation should be type OH_NN_INT64");
105 return OH_NN_INVALID_PARAMETER;
106 }
107
108 void* buffer = tensor->GetBuffer();
109 if (buffer == nullptr) {
110 LOGE("[Conv2DTranspose] SetDilation GetBuffer return nullptr");
111 return OH_NN_INVALID_PARAMETER;
112 }
113 const int64_t* pDilation = reinterpret_cast<const int64_t*>(buffer);
114 uint32_t dilationSize = tensor->GetElementCount();
115 m_dilation.assign(pDilation, pDilation + dilationSize);
116
117 return OH_NN_SUCCESS;
118 }
119
SetPad(std::shared_ptr<NNTensor> tensor)120 OH_NN_ReturnCode Conv2DTransposeBuilder::SetPad(std::shared_ptr<NNTensor> tensor)
121 {
122 tensor->IdentifyOpParameter();
123
124 bool isPadMode = false;
125 if (tensor->GetElementCount() == PAD_MODE_PARAM_NUM) {
126 isPadMode = true;
127 } else if (tensor->GetElementCount() != PAD_LIST_PARAM_NUM) {
128 LOGE("[Conv2DTranspose] SetPad failed, the inputs should be 1 if using padMode or 4 if using padList.");
129 return OH_NN_INVALID_PARAMETER;
130 }
131
132 void* buffer = tensor->GetBuffer();
133 if (buffer == nullptr) {
134 LOGE("[Conv2DTranspose] SetPadMode GetBuffer return nullptr");
135 return OH_NN_INVALID_PARAMETER;
136 }
137
138 // Set PadMode or PadList
139 if (isPadMode) {
140 if (tensor->GetDataType() != OH_NN_INT8) {
141 LOGE("[Conv2DTranspose] SetPad failed, the PadMode should have type OH_NN_INT8.");
142 return OH_NN_INVALID_PARAMETER;
143 }
144
145 int8_t* pPad = static_cast<int8_t*>(buffer);
146 if (!OHOS::NeuralNetworkRuntime::Validation::ValidatePadMode(*pPad)) {
147 LOGE("[Conv2DTranspose] SetPad failed, invalid pad mode.");
148 return OH_NN_INVALID_PARAMETER;
149 }
150 m_padMode = NNToMS::TransformPadModeValue(*pPad);
151 } else {
152 if (tensor->GetDataType() != OH_NN_INT64) {
153 LOGE("[Conv2DTranspose] SetPad failed, the PadList should have type OH_NN_INT64.");
154 return OH_NN_INVALID_PARAMETER;
155 }
156
157 const int64_t* pPadList = reinterpret_cast<const int64_t*>(buffer);
158 uint32_t padListPadSize = tensor->GetElementCount();
159 m_padList.assign(pPadList, pPadList + padListPadSize);
160 }
161
162 return OH_NN_SUCCESS;
163 }
164
SetGroup(std::shared_ptr<NNTensor> tensor)165 OH_NN_ReturnCode Conv2DTransposeBuilder::SetGroup(std::shared_ptr<NNTensor> tensor)
166 {
167 tensor->IdentifyOpParameter();
168 // Set Group
169 if (tensor->GetElementCount() != SCALAR_LENGTH) {
170 LOGE("[Conv2dTranspose] SetGroup failed, the Group shoule be a scalar");
171 return OH_NN_INVALID_PARAMETER;
172 }
173
174 if (tensor->GetDataType() != OH_NN_INT64) {
175 LOGE("[Conv2dTranspose] SetGroup failed, the Group should have type OH_NN_INT64.");
176 return OH_NN_INVALID_PARAMETER;
177 }
178
179 void* buffer = tensor->GetBuffer();
180 if (buffer == nullptr) {
181 LOGE("[Conv2DTranspose] SetGroup GetBuffer return nullptr");
182 return OH_NN_INVALID_PARAMETER;
183 }
184 m_group = *reinterpret_cast<const int64_t*>(buffer);
185
186 return OH_NN_SUCCESS;
187 }
188
SetOutPadding(std::shared_ptr<NNTensor> tensor)189 OH_NN_ReturnCode Conv2DTransposeBuilder::SetOutPadding(std::shared_ptr<NNTensor> tensor)
190 {
191 tensor->IdentifyOpParameter();
192 // Set outputPadding
193 if (tensor->GetDataType() != OH_NN_INT64) {
194 LOGE("[Conv2DTranspose] SetOutPadding failed, the outputPadding should be type OH_NN_INT64.");
195 return OH_NN_INVALID_PARAMETER;
196 }
197
198 void* buffer = tensor->GetBuffer();
199 if (buffer == nullptr) {
200 LOGE("[Conv2DTranspose] SetOutPadding GetBuffer return nullptr");
201 return OH_NN_INVALID_PARAMETER;
202 }
203 const int64_t* pOutputPadding = reinterpret_cast<const int64_t*>(buffer);
204 uint32_t outputPadSize = tensor->GetElementCount();
205 m_outputPaddings.assign(pOutputPadding, pOutputPadding + outputPadSize);
206
207 return OH_NN_SUCCESS;
208 }
209
SetActivation(std::shared_ptr<NNTensor> tensor)210 OH_NN_ReturnCode Conv2DTransposeBuilder::SetActivation(std::shared_ptr<NNTensor> tensor)
211 {
212 tensor->IdentifyOpParameter();
213
214 if (tensor->GetElementCount() != SCALAR_LENGTH) {
215 LOGE("[Conv2DTranspose] SetActivation failed, the ActivationType shoule be a scalar");
216 return OH_NN_INVALID_PARAMETER;
217 }
218
219 if (tensor->GetDataType() != OH_NN_INT8) {
220 LOGE("[Conv2DTranspose] SetActivation failed, the ActivationType should have type OH_NN_INT8.");
221 return OH_NN_INVALID_PARAMETER;
222 }
223
224 void* buffer = tensor->GetBuffer();
225 if (buffer == nullptr) {
226 LOGE("[Conv2DTranspose] SetOutPadding GetBuffer return nullptr");
227 return OH_NN_INVALID_PARAMETER;
228 }
229 int8_t* pFuseData = static_cast<int8_t*>(buffer);
230 if (!OHOS::NeuralNetworkRuntime::Validation::ValidateFuseType(static_cast<OH_NN_FuseType>(*pFuseData))) {
231 LOGE("[Conv2DTranspose] SetActivation failed, activation input is invalid.");
232 return OH_NN_INVALID_PARAMETER;
233 }
234 m_activationType = NNToMS::TransfromFusionType((OH_NN_FuseType)(*pFuseData));
235
236 return OH_NN_SUCCESS;
237 }
238
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)239 OH_NN_ReturnCode Conv2DTransposeBuilder::Build(const std::vector<uint32_t>& paramsIndex,
240 const std::vector<uint32_t>& inputsIndex,
241 const std::vector<uint32_t>& outputsIndex,
242 const std::vector<std::shared_ptr<NNTensor>>& allTensors)
243 {
244 if (m_isBuild) {
245 LOGE("[Conv2DTranspose] Build failed, conv2DTranspose operation has been build, cannot build again.");
246 return OH_NN_OPERATION_FORBIDDEN;
247 }
248
249 OH_NN_ReturnCode returnCode = SetInput(inputsIndex, outputsIndex, allTensors);
250 if (returnCode != OH_NN_SUCCESS) {
251 return returnCode;
252 }
253
254 SetKernelSize(inputsIndex, allTensors);
255
256 for (int i : paramsIndex) {
257 std::shared_ptr<NNTensor> tensor = allTensors[i]; // 参数 tensor
258 switch (tensor->GetType()) {
259 case OH_NN_CONV2D_TRANSPOSE_STRIDES:
260 returnCode = SetStrides(tensor);
261 break;
262 case OH_NN_CONV2D_TRANSPOSE_DILATION:
263 returnCode = SetDilation(tensor);
264 break;
265 case OH_NN_CONV2D_TRANSPOSE_PAD_MODE:
266 case OH_NN_CONV2D_TRANSPOSE_PAD:
267 returnCode = SetPad(tensor);
268 break;
269 case OH_NN_CONV2D_TRANSPOSE_GROUP:
270 returnCode = SetGroup(tensor);
271 break;
272 case OH_NN_CONV2D_TRANSPOSE_OUTPUT_PADDINGS:
273 returnCode = SetOutPadding(tensor);
274 break;
275 case OH_NN_CONV2D_TRANSPOSE_ACTIVATION_TYPE:
276 returnCode = SetActivation(tensor);
277 break;
278 default:
279 LOGE("[Conv2DTranspose] Build failed, param invalid, type = %d.", tensor->GetType());
280 return OH_NN_INVALID_PARAMETER;
281 }
282
283 if (returnCode != OH_NN_SUCCESS) {
284 LOGE("[Conv2DTranspose] Build failed, passed invalid param.");
285 return returnCode;
286 }
287 }
288
289 // The quantization type of the first output determinies that of the operator.
290 SetQuantType(outputsIndex, allTensors);
291
292 m_isBuild = true;
293 m_name = OP_NAME;
294 return OH_NN_SUCCESS;
295 }
296
GetPrimitive()297 LiteGraphPrimitvePtr Conv2DTransposeBuilder::GetPrimitive()
298 {
299 if (!m_isBuild) {
300 LOGE("[Conv2DTranspose] GetPrimitive failed, cannot get primitive before call build.");
301 return {nullptr, DestroyLiteGraphPrimitive};
302 }
303
304 void* primitive = MindIR_Conv2dTransposeFusion_CreatePrimitive(m_kernelSize,
305 m_strides, m_dilation, m_padMode, m_padList, m_group, m_inChannel, m_outChannel,
306 m_activationType, m_outputPaddings);
307 LiteGraphPrimitvePtr graphPrimitivePtr(primitive, DestroyLiteGraphPrimitive);
308 return graphPrimitivePtr;
309 }
310
311 REGISTER_OPS(Conv2DTransposeBuilder, OH_NN_OPS_CONV2D_TRANSPOSE);
312 } // namespace Ops
313 } // namespace NeuralNetworkRuntime
314 } // namespace OHOS
315