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86 lines
2.6 KiB
86 lines
2.6 KiB
/* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserve.
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Licensed under the Apache License, Version 2.0 (the "License");
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you may not use this file except in compliance with the License.
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You may obtain a copy of the License at
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http://www.apache.org/licenses/LICENSE-2.0
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Unless required by applicable law or agreed to in writing, software
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distributed under the License is distributed on an "AS IS" BASIS,
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WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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See the License for the specific language governing permissions and
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limitations under the License. */
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#pragma once
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#include "Layer.h"
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namespace paddle {
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/**
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* Organize the classes into a binary tree. At each node, a sigmoid function
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* is used to calculate the probability of belonging to the right branch.
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* This idea is from "F. Morin, Y. Bengio (AISTATS 05):
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* Hierarchical Probabilistic Neural Network Language Model."
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*
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* Here we uses a simple way of making the binary tree.
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* Assuming the number of classes C = 6,
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* The classes are organized as a binary tree in the following way:
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*
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* @code{.py}
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* *-*-*- 2
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* | | |- 3
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* | |
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* | |-*- 4
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* | |- 5
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* |
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* |-*- 0
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* |- 1
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* @endcode
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*
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* where * indicates an internal node, and each leaf node represents a class.
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* - Node 0 ... C-2 are internal nodes.
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* - Node C-1 ... 2C-2 are leaf nodes.
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* - Class c is represented by leaf node \f$c+C-1\f$.
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*
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* We assign an id for each node:
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* - the id of root be 0.
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* - the left child of a node i is 2*i+1.
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* - the right child of a node i is 2*i+2.
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*
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* It's easy to see that:
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* - the parent of node i is \f$\left\lfloor(i-1)/2\right\rfloor\f$.
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* - the j-th level ancestor of node i is
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* \f$\left\lfloor(i+1)/2^{j+1}\right\rfloor - 1\f$.
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* - A node i is a left child of its parent if \f$(i-1)\%2==0\f$.
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*
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* The config file api is hsigmod_layer.
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*/
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class HierarchicalSigmoidLayer : public Layer {
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public:
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explicit HierarchicalSigmoidLayer(const LayerConfig& config)
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: Layer(config) {}
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bool init(const LayerMap& layerMap,
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const ParameterMap& parameterMap) override;
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void forward(PassType passType) override;
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void backward(const UpdateCallback& callback) override;
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protected:
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/**
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* The last of inputs is label layer.
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*/
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LayerPtr getLabelLayer() { return inputLayers_.back(); }
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WeightList weights_;
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std::unique_ptr<Weight> biases_;
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/// number of classes
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size_t numClasses_;
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/// codeLength_ = \f$1 + \left\lfloor log_{2}(numClasses-1)\right\rfloor\f$
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int codeLength_;
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/// temporary result of output_
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Argument preOutput_;
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};
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} // namespace paddle
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