mirror of https://github.com/alibaba/MNN.git
83 lines
4.6 KiB
C++
83 lines
4.6 KiB
C++
//
|
|
// CoreMLActivation.cpp
|
|
// MNN
|
|
//
|
|
// Created by MNN on 2021/03/31.
|
|
// Copyright © 2018, Alibaba Group Holding Limited
|
|
//
|
|
|
|
#include "CoreMLActivation.hpp"
|
|
|
|
namespace MNN {
|
|
|
|
|
|
CoreMLActivation::CoreMLActivation(MNN::Backend *b, const MNN::Op *op, const std::vector<Tensor *> &inputs, const std::vector<MNN::Tensor *> &outputs) : CoreMLCommonExecution(b, op) {
|
|
initLayer();
|
|
}
|
|
|
|
ErrorCode CoreMLActivation::onResize(const std::vector<Tensor *> &inputs, const std::vector<Tensor *> &outputs) {
|
|
MNN_ASSERT(inputs.size() == 1 && outputs.size() == 1);
|
|
auto inputName = mCoreMLBackend->getTensorName(inputs[0]);
|
|
auto opType = mOp->type();
|
|
if (opType == OpType_Softmax) {
|
|
mLayer_->layer_case = CORE_ML__SPECIFICATION__NEURAL_NETWORK_LAYER__LAYER_SOFTMAX_ND;
|
|
mLayer_->softmaxnd = mCoreMLBackend->create<CoreML__Specification__SoftmaxNDLayerParams>();
|
|
core_ml__specification__softmax_ndlayer_params__init(mLayer_->softmaxnd);
|
|
mLayer_->softmaxnd->axis = mOp->main_as_Axis()->axis();
|
|
} else {
|
|
mLayer_->layer_case = CORE_ML__SPECIFICATION__NEURAL_NETWORK_LAYER__LAYER_ACTIVATION;
|
|
mLayer_->activation = mCoreMLBackend->create<CoreML__Specification__ActivationParams>();
|
|
core_ml__specification__activation_params__init(mLayer_->activation);
|
|
switch (opType) {
|
|
case OpType_ReLU:
|
|
mLayer_->activation->nonlinearity_type_case = CORE_ML__SPECIFICATION__ACTIVATION_PARAMS__NONLINEARITY_TYPE_LEAKY_RE_LU;
|
|
mLayer_->activation->leakyrelu = mCoreMLBackend->create<CoreML__Specification__ActivationLeakyReLU>();
|
|
core_ml__specification__activation_leaky_re_lu__init(mLayer_->activation->leakyrelu);
|
|
mLayer_->activation->leakyrelu->alpha = mOp->main_as_Relu()->slope();
|
|
break;
|
|
case OpType_ELU:
|
|
mLayer_->activation->nonlinearity_type_case = CORE_ML__SPECIFICATION__ACTIVATION_PARAMS__NONLINEARITY_TYPE_ELU;
|
|
mLayer_->activation->elu = mCoreMLBackend->create<CoreML__Specification__ActivationELU>();
|
|
core_ml__specification__activation_elu__init(mLayer_->activation->elu);
|
|
break;
|
|
case OpType_PReLU:
|
|
{
|
|
if (mOp->main_as_PRelu()->slopeCount() == 1) {
|
|
mLayer_->activation->nonlinearity_type_case = CORE_ML__SPECIFICATION__ACTIVATION_PARAMS__NONLINEARITY_TYPE_LEAKY_RE_LU;
|
|
mLayer_->activation->leakyrelu = mCoreMLBackend->create<CoreML__Specification__ActivationLeakyReLU>();
|
|
core_ml__specification__activation_leaky_re_lu__init(mLayer_->activation->leakyrelu);
|
|
mLayer_->activation->leakyrelu->alpha = mOp->main_as_PRelu()->slope()->data()[0];
|
|
break;
|
|
}
|
|
mLayer_->activation->nonlinearity_type_case = CORE_ML__SPECIFICATION__ACTIVATION_PARAMS__NONLINEARITY_TYPE_PRE_LU;
|
|
mLayer_->activation->prelu = mCoreMLBackend->create<CoreML__Specification__ActivationPReLU>();
|
|
core_ml__specification__activation_pre_lu__init(mLayer_->activation->prelu);
|
|
mLayer_->activation->prelu->alpha = mCoreMLBackend->create<CoreML__Specification__WeightParams>();
|
|
core_ml__specification__weight_params__init(mLayer_->activation->prelu->alpha);
|
|
int slopeCount = mOp->main_as_PRelu()->slopeCount();
|
|
mLayer_->activation->prelu->alpha->n_floatvalue = slopeCount;
|
|
mLayer_->activation->prelu->alpha->floatvalue = mCoreMLBackend->create<float>(slopeCount);
|
|
memcpy(mLayer_->activation->prelu->alpha->floatvalue, mOp->main_as_PRelu()->slope()->Data(), slopeCount * sizeof(float));
|
|
break;
|
|
}
|
|
case OpType_Sigmoid:
|
|
mLayer_->activation->nonlinearity_type_case = CORE_ML__SPECIFICATION__ACTIVATION_PARAMS__NONLINEARITY_TYPE_SIGMOID;
|
|
mLayer_->activation->sigmoid = mCoreMLBackend->create<CoreML__Specification__ActivationSigmoid>();
|
|
core_ml__specification__activation_sigmoid__init(mLayer_->activation->sigmoid);
|
|
break;
|
|
default:
|
|
return NOT_SUPPORT;
|
|
}
|
|
}
|
|
setLayerInputsAndOutputs(mLayer_, {inputName}, {mCoreMLBackend->getTensorName(outputs[0])});
|
|
mCoreMLBackend->addLayer(mLayer_);
|
|
return NO_ERROR;
|
|
}
|
|
|
|
REGISTER_COREML_OP_CREATOR(CoreMLActivation, OpType_ReLU)
|
|
REGISTER_COREML_OP_CREATOR(CoreMLActivation, OpType_ELU)
|
|
REGISTER_COREML_OP_CREATOR(CoreMLActivation, OpType_PReLU)
|
|
REGISTER_COREML_OP_CREATOR(CoreMLActivation, OpType_Sigmoid)
|
|
REGISTER_COREML_OP_CREATOR(CoreMLActivation, OpType_Softmax)
|
|
} // namespace MNN
|