19949232ba3d5b1d95f5b3d9ea310b88b81ee1a45gfan// Generated file (from: depth_to_space_float_3.mod.py). Do not edit 29949232ba3d5b1d95f5b3d9ea310b88b81ee1a45gfanvoid CreateModel(Model *model) { 39949232ba3d5b1d95f5b3d9ea310b88b81ee1a45gfan OperandType type1(Type::INT32, {}); 49949232ba3d5b1d95f5b3d9ea310b88b81ee1a45gfan OperandType type0(Type::TENSOR_FLOAT32, {1, 2, 2, 8}); 59949232ba3d5b1d95f5b3d9ea310b88b81ee1a45gfan OperandType type2(Type::TENSOR_FLOAT32, {1, 4, 4, 2}); 69949232ba3d5b1d95f5b3d9ea310b88b81ee1a45gfan // Phase 1, operands 79949232ba3d5b1d95f5b3d9ea310b88b81ee1a45gfan auto input = model->addOperand(&type0); 89949232ba3d5b1d95f5b3d9ea310b88b81ee1a45gfan auto block_size = model->addOperand(&type1); 99949232ba3d5b1d95f5b3d9ea310b88b81ee1a45gfan auto output = model->addOperand(&type2); 109949232ba3d5b1d95f5b3d9ea310b88b81ee1a45gfan // Phase 2, operations 119949232ba3d5b1d95f5b3d9ea310b88b81ee1a45gfan static int32_t block_size_init[] = {2}; 129949232ba3d5b1d95f5b3d9ea310b88b81ee1a45gfan model->setOperandValue(block_size, block_size_init, sizeof(int32_t) * 1); 139949232ba3d5b1d95f5b3d9ea310b88b81ee1a45gfan model->addOperation(ANEURALNETWORKS_DEPTH_TO_SPACE, {input, block_size}, {output}); 149949232ba3d5b1d95f5b3d9ea310b88b81ee1a45gfan // Phase 3, inputs and outputs 159949232ba3d5b1d95f5b3d9ea310b88b81ee1a45gfan model->identifyInputsAndOutputs( 169949232ba3d5b1d95f5b3d9ea310b88b81ee1a45gfan {input}, 179949232ba3d5b1d95f5b3d9ea310b88b81ee1a45gfan {output}); 189949232ba3d5b1d95f5b3d9ea310b88b81ee1a45gfan assert(model->isValid()); 199949232ba3d5b1d95f5b3d9ea310b88b81ee1a45gfan} 209949232ba3d5b1d95f5b3d9ea310b88b81ee1a45gfan 219949232ba3d5b1d95f5b3d9ea310b88b81ee1a45gfanbool is_ignored(int i) { 229949232ba3d5b1d95f5b3d9ea310b88b81ee1a45gfan static std::set<int> ignore = {}; 239949232ba3d5b1d95f5b3d9ea310b88b81ee1a45gfan return ignore.find(i) != ignore.end(); 249949232ba3d5b1d95f5b3d9ea310b88b81ee1a45gfan} 25