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// Generated file (from: depthwise_conv.bin.mod.py). Do not edit
void CreateModel(Model *model) {
OperandType type0(Type::INT32, {});
OperandType type2(Type::TENSOR_FLOAT32, {1, 1, 1, 3});
OperandType type1(Type::TENSOR_FLOAT32, {1, 8, 8, 3});
OperandType type3(Type::TENSOR_FLOAT32, {3});
// Phase 1, operands
auto b4 = model->addOperand(&type0);
auto b5 = model->addOperand(&type0);
auto b6 = model->addOperand(&type0);
auto b7 = model->addOperand(&type0);
auto b8 = model->addOperand(&type0);
auto op2 = model->addOperand(&type1);
auto op3 = model->addOperand(&type1);
auto op0 = model->addOperand(&type2);
auto op1 = model->addOperand(&type3);
// Phase 2, operations
static int32_t b4_init[] = {1};
model->setOperandValue(b4, b4_init, sizeof(int32_t) * 1);
static int32_t b5_init[] = {1};
model->setOperandValue(b5, b5_init, sizeof(int32_t) * 1);
static int32_t b6_init[] = {1};
model->setOperandValue(b6, b6_init, sizeof(int32_t) * 1);
static int32_t b7_init[] = {1};
model->setOperandValue(b7, b7_init, sizeof(int32_t) * 1);
static int32_t b8_init[] = {0};
model->setOperandValue(b8, b8_init, sizeof(int32_t) * 1);
static float op0_init[] = {-0.966213f, -0.467474f, -0.82203f};
model->setOperandValue(op0, op0_init, sizeof(float) * 3);
static float op1_init[] = {0.0f, 0.0f, 0.0f};
model->setOperandValue(op1, op1_init, sizeof(float) * 3);
model->addOperation(ANEURALNETWORKS_DEPTHWISE_CONV_2D, {op2, op0, op1, b4, b5, b6, b7, b8}, {op3});
// Phase 3, inputs and outputs
model->identifyInputsAndOutputs(
{op2},
{op3});
assert(model->isValid());
}
bool is_ignored(int i) {
static std::set<int> ignore = {};
return ignore.find(i) != ignore.end();
}
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