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/**
* Licensed to the Apache Software Foundation (ASF) under one
* or more contributor license agreements. See the NOTICE file
* distributed with this work for additional information
* regarding copyright ownership. The ASF licenses this file
* to you under the Apache License, Version 2.0 (the
* "License"); you may not use this file except in compliance
* with the License. You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*/
#include "singa/model/layer.h"
#include "./activation.h"
#include "singa/utils/string.h"
namespace singa {
RegisterLayerClass(singa_relu, Activation);
RegisterLayerClass(singa_sigmoid, Activation);
RegisterLayerClass(singa_tanh, Activation);
RegisterLayerClass(singacpp_relu, Activation);
RegisterLayerClass(singacuda_relu, Activation);
RegisterLayerClass(singacl_relu, Activation);
RegisterLayerClass(singacpp_sigmoid, Activation);
RegisterLayerClass(singacuda_sigmoid, Activation);
RegisterLayerClass(singacl_sigmoid, Activation);
RegisterLayerClass(singacpp_tanh, Activation);
RegisterLayerClass(singacuda_tanh, Activation);
RegisterLayerClass(singacl_tanh, Activation);
void Activation::Setup(const Shape& in_sample, const LayerConf& conf) {
Layer::Setup(in_sample, conf);
auto pos = conf.type().find_first_of('_');
CHECK_NE(pos, string::npos) << "There should be a '_' in the laye type "
<< conf.type();
mode_ = ToLowerCase(conf.type().substr(pos + 1));
if (mode_ != "relu" && mode_ != "sigmoid" && mode_ != "tanh")
LOG(FATAL) << "Unkown activation type: " << conf.type() << " " << mode_
<< ". Please use singa_relu, singa_sigmoid, or singa_tanh";
if (mode_ == "relu") {
neg_slope_ = conf.relu_conf().negative_slope();
}
out_sample_shape_ = in_sample;
}
const Tensor Activation::Forward(int flag, const Tensor& input) {
Tensor output;
if (mode_ == "sigmoid") {
output = Sigmoid(input);
if (flag & kTrain) buf_.push(output);
} else if (mode_ == "tanh") {
output = Tanh(input);
if (flag & kTrain) buf_.push(output);
} else if (mode_ == "relu") {
output = ReLU(input);
if (flag & kTrain) buf_.push(input);
} else
LOG(FATAL) << "Unknown activation: " << mode_;
return output;
}
const std::pair<Tensor, vector<Tensor>> Activation::Backward(
int flag, const Tensor& grad) {
vector<Tensor> param_grad;
CHECK(!buf_.empty());
// inout means either input or output, but only one is valid for an
// activation.
Tensor input_grad, inout = buf_.top();
buf_.pop();
if (mode_ == "sigmoid")
input_grad = grad * inout * (inout * (-1.f) + 1.f);
else if (mode_ == "tanh")
input_grad = grad * (inout * inout * (-1.f) + 1.f);
else if (mode_ == "relu")
input_grad = grad * (inout > 0.f) + (inout <= 0.f) * neg_slope_;
else LOG(FATAL) << "Unkown activation: " << mode_;
return std::make_pair(input_grad, param_grad);
}
} // namespace singa