Questions tagged [torch]

Scientific computing framework for LuaJIT.

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Graph convolution network for variable number of nodes

Is it possible to train a graph convolutional network on graphs with a varying number of nodes? I have a dataset of graphs with a range of 400-1000 nodes, though I could see a higher number of nodes ...
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1answer
62 views

he_normal (Keras) is truncated when kaiming_normal_ (pytorch) is not

Thanks for having a look at my post. I had an extensive look at the difference in weight initialization between pytorch and Keras, and it appears that the definition of he_normal (Keras) and ...
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25 views

Python Fastai library - Loss and Validation interpretation

The following is a regression problem, where I have a dataset with composed by more than 40k consumption ids with some variables such as DateTime, month, year, temperature, humidity. I built a Fastai ...
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47 views

How exactly does conv1d filter work when operating on a sequence of characters?

I understand convolution filters when applied to an image (e.g. an 224x224 image with 3 in-channels transformed by 56 total filters of 5x5 conv to a 224x224 image with 56 out-channels). The key is ...
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58 views

Training loss increase after warm-start

I have trained a 2D UNet with ResNet34 encoder using Pytorch over a certain dataset. Training loss over the final epochs was stable around 0.18. I have then saved the trained network and optimizer (...
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1answer
88 views

Outliers Kalman Filtering

This might not be the right place to ask this questions, but I figured it's more of a machine learning question. I am also asking on the pyro forum for brevity. I'm working with the simple extended ...
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1answer
363 views

Increasing image size in pytorch celebrity generating GAN? [closed]

complete newbie here, bear with me. I'm making my way through this tutorial: https://pytorch.org/tutorials/beginner/dcgan_faces_tutorial.html Upon attempting to make a simple change to the image ...
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0answers
49 views

When to stop training a Auixilary Classifier GAN?

When should I stop training an Auxiliary Classifier GAN? when the discriminator loss converges or when the auxiliary classification accuracy converges or when the Real vs Fake classifier converges to ...
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1answer
1k views

Pytorch Cross Entropy Loss implementation counterintuitive

there is something I don't understand in the PyTorch implementation of Cross Entropy Loss. As far as I understand, theoretical Cross Entropy Loss is taking log-softmax probabilities and output a real ...
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1answer
58 views

RNN not matching expected output

I am trying to build an RNN to predict a time-series signal based on knowledge of 3 others that I believe to be related to the output. I am using the rnn Lua Torch ...
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1answer
4k views

Sigmoid activation hurts training a NN on pyTorch

I'm a beginner in the field of Machine Learning and I'm currently trying to get my hands "dirty" for the first time with some code after completing a course in that field. I'm using pyTorch to train ...
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1answer
6k views

Dynamic graphs versus static graphs in deep learning libraries

What is the difference between dynamic graphs and static graphs in deep learning libraries? Which one is faster? and when to use each one of them?
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1answer
251 views

Weight matrices computation in attention-based encoder of Deep Learning NLP

On page 4 of this research paper titled A Neural Attention Model for Sentence Summarization , it is mentioned the attention-based encoder is determined by the ...
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46 views

Prediction with large inputs and outputs

Being a total newbie with machine learning, I thought I would seek your advice on a problem of mine. I'm looking for any leads, starting points ans help you could provide me. I'm looking to predict ...
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1answer
271 views

How to use torch RNN and LSTM packages and are they necessary?

I have come across this brilliant site where I finally understood BPTT for RNN's and want to implement it. The code is given in python but I want to implement it in torch using lua. I have understood ...
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1answer
3k views

Loss functions that act on real-valued output vectors (and NOT just on 1-hot vectors)

I am trying to modify Andrej Karpathy's char-RNN code. As far as I understand, the loss function used in his code for a LSTM is the Softmax function function (in the file model/LSTM.lua ). I ...
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2answers
730 views

How to train LSTM for a simplest function recognition

I'm learning LSTM networks and decided to try synthetic test. I want LSTM network fed by some points (x,y) to distinguish between three basic functions: line: y = k*x + b parabola: y = k*x^2 + b sqrt:...
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1answer
5k views

In neural networks, how to compute the mean square error (MSE) in gradient update when using a minibatch?

I've been using a siamese neural network for the binary classification of biological data. I've implemented a Torch version of this algorithm, including a stochastic gradient update function. At ...
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0answers
299 views

Difficulty learning parameters in RNN?

I'm implementing an LSTM using the RNN package in Torch. I've been able to get very simple models to converge (like learning the relation f(x) = x), but haven't been able to get basic things like ...
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2answers
8k views

How does the DepthConcat operation in 'Going deeper with convolutions' work?

Reading Going deeper with convolutions I came across a DepthConcat layer, a building block of the proposed inception modules, which combines the output of multiple tensors of varying size. The authors ...