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zhongkaifu / RNNSharp

RNNSharp is a toolkit of deep recurrent neural network which is widely used for many different kinds of tasks, such as sequence labeling, sequence-to-sequence and so on. It's written by C# language and based on .NET framework 4.6 or above versions. RNNSharp supports many different types of networks, such as forward and bi-directional network, sequence-to-sequence network, and different types of layers, such as LSTM, Softmax, sampled Softmax and others.
BSD 3-Clause "New" or "Revised" License
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Crash in UpdateLearningRate #8

Closed bratao closed 8 years ago

bratao commented 8 years ago

Hello !

Testing this last commit, I get a crash in UpdateLearningRate

Unhandled Exception: System.AggregateException: One or more errors occurred. ---> System.AggregateException: One or more errors occurred. ---> System.IndexOutOfRangeException: Index was outside the bounds of the array.
   at RNNSharp.RNN.UpdateLearningRate(Matrix`1 m, Int32 i, Int32 j, Double delta) in C:\sbuild\mine\backend_broka\Candidatos\RNNSharp-master\RNNSharp\RNN.cs:line 101
at RNNSharp.LSTMRNN.<LearnOutputWeight>b__25_0(Int32 i) in C:\sbuild\mine\backend_broka\Candidatos\RNNSharp-master\RNNSharp\LSTMRNN.cs:line 609

In LSTMRNN , Line 601 do this:


Parallel.For(0, L1, parallelOption, i =>
            {
                double cellOutput = neuHidden[i].cellOutput;
                for (int k = 0; k < L2; k++)
                {
                    double delta = NormalizeGradient(cellOutput * OutputLayer.er[k]);
                    double newLearningRate = UpdateLearningRate(Hidden2OutputWeightLearningRate, i, k, delta);

                    Hidden2OutputWeight[k][i] += newLearningRate * delta;
                }
            });

But in line 517 , it is initialized like : Hidden2OutputWeightLearningRate = new Matrix<float>(L2, L1);

zhongkaifu commented 8 years ago

Thanks, Bratao. This line has a bug: double newLearningRate = UpdateLearningRate(Hidden2OutputWeightLearningRate, i, k, delta); at LSTMRNN.cs line #607.

It should be double newLearningRate = UpdateLearningRate(Hidden2OutputWeightLearningRate, k, i, delta);

You can modify it in your private build, I will fix it tonight.

Thanks Zhongkai Fu

zhongkaifu commented 8 years ago

The bug has been mitigated. Could you please try it again ?

bratao commented 8 years ago

@zhongkaifu , thank you !!! It's not crashing anymore. However, compared to yesterday version, my LSTM do not converge anymore =( Using RNN it gave me a crash. I created another issue reporting this bug.

zhongkaifu commented 8 years ago

@bratao , thanks for letting me know another problem. I have reverted the previous change list, and checked-in LSTM crashing fix only along with a few of dynamic learning rate optimization. Could you please try it again ? Thanks in advance.

bratao commented 8 years ago

It is working great !!! Thank you so much !!