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82 lines
2.4 KiB
82 lines
2.4 KiB
/* Copyright (c) 2016 Baidu, Inc. 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 "paddle/math/Matrix.h"
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namespace paddle {
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class LinearChainCRF {
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public:
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/*
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The size of para and grad must be (numClasses + 2) * numClasses.
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The first numClasses values of para are for starting weights (a).
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The next numClasses values of para are for ending weights (b),
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The remaning values are for transition weights (w).
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The probability of a state sequence s of length L is defined as:
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P(s) = (1/Z) exp(a_{s_1} + b_{s_L}
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+ \sum_{l=1}^L x_{s_l}
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+ \sum_{l=2}^L w_{s_{l-1},s_l})
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where Z is a normalization value so that the sum of P(s) over all possible
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sequences is 1, and x is the input feature to the CRF.
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*/
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LinearChainCRF(int numClasses, real* para, real* grad);
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/*
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Calculate the negative log likelihood of s given x.
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The size of x must be length * numClasses. Each consecutive numClasses
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values are the features for one time step.
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*/
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real forward(real* x, int* s, int length);
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/*
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Calculate the gradient with respect to x, a, b, and w.
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The gradient of x will be stored in dx.
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backward() can only be called after a corresponding call to forward() with
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the same x, s and length.
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NOTE: The gradient is added to dx and grad (provided at constructor).
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*/
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void backward(real* x, real* dx, int* s, int length);
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/*
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Find the most probable sequence given x. The result will be stored in s.
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*/
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void decode(real* x, int* s, int length);
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protected:
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int numClasses_;
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MatrixPtr a_;
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MatrixPtr b_;
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MatrixPtr w_;
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MatrixPtr da_;
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MatrixPtr db_;
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MatrixPtr dw_;
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MatrixPtr ones_;
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MatrixPtr expX_;
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MatrixPtr alpha_;
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MatrixPtr beta_;
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MatrixPtr maxX_;
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MatrixPtr expW_;
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// track_(k,i) = j means that the best sequence at time k for class i comes
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// from the sequence at time k-1 for class j
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IVectorPtr track_;
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};
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} // namespace paddle
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