All Questions
20 questions
3
votes
1
answer
32
views
RNN performing worse than random guessing on large dataset
I have to start off by saying I am 100% a beginner here.
I trained a RNN model on a 30 class dataset with over 90000 samples and it achieved less than 2% accuracy. Training the same model on a small ...
- 31
0
votes
0
answers
27
views
How to combine Embedding layer with 3D input and 2D input in Pytorch
This familiar with my ideas.
How to use Embedding() with 3D tensor in Keras?
I'm re-implementing some table-to-text papers using RNN-based seq2seq (like this one https://arxiv.org/pdf/1603.07771v3)
...
- 101
0
votes
0
answers
17
views
Adding sliding window dimension to data causes error: "Expected 3D or 4D (batch mode) tensor ..."
I wrote a pytorch data loader which used to return data of shape (4,1,192,320) representing the 4 samples of single channel image, each of size ...
- 219
0
votes
1
answer
1k
views
How to Implement padding and masking sequences for RNN
As an exercise, I'm building a network for binary classification of sequences (whether a sequence belongs to type A or type B). The network consists of an RNN with one LSTM layer, and on top of it an ...
- 103
1
vote
2
answers
2k
views
RNN with PyTorch - I don't understand the initial parameters
I would like to understand the pyTorch RNN module in detail. There I created a very simple and basic example:
...
- 21
1
vote
0
answers
871
views
Understanding batch size, sequence, sequence length and batch length of a RNN
My Problem
I'm struggling with the different definitions of batch size, sequence, sequence length and batch length of a RNN and how to use it in the correct way.
First things first - let's clarify the ...
- 21
0
votes
1
answer
933
views
How to make an RNN model in PyTorch that has a custom hidden layer(s) and that is compatible with PackedSequence
I want to make an RNN that has for example more hidden layers or layer normalization.
I know that is it possible to make a custom RNN by subclassing nn.module, but with this approach is it not ...
0
votes
0
answers
41
views
Input size vs hidden state in RNNs
Im using PyTorch to implement RNNs on univariate time series data. This is the documentation for the RNN class: link
I think I'm understanding the math behind an RNN cell. But I have an specific ...
- 101
1
vote
1
answer
539
views
pytorchs LSTMs use of 'bias' and 'weight' strings
Hi I am new to RNN and have come across this the following implementation of Pytorchs LSTM, but I cant understand how (or why) the 'bias' and ...
- 135
0
votes
1
answer
139
views
What is the right Pytorch RNN implementation?
I read about RNN in pytorch:
RNN — PyTorch documentation.
According to the document the RNN run the following function:
I looked on another RNN example (from pytorch tutorial):
NLP FROM SCRATCH: ...
- 527
2
votes
1
answer
3k
views
What is the purpose of Sequence Length parameter in RNN (specifically on PyTorch)?
I am trying to understand RNN. I got a good sense of how it works on theory. But then on PyTorch you have two extra dimensions to your input data: batch size (number of batches) and sequence length. ...
- 23
0
votes
0
answers
63
views
Trying to extend this code to include additional feature volume (in addition to adj close) RNN to predict adj close
I read this article on medium
https://medium.com/swlh/a-technical-guide-on-rnn-lstm-gru-for-stock-price-prediction-bce2f7f30346
prep
...
- 131
0
votes
1
answer
81
views
LSTM / GRU weights during test time
I am working on a historic time series dataset and using RNN, LSTM, GRU models, and I didn't find an answer if in test time, the h (or h, c) weights should be zeors for each batch?
If the weights ...
- 11
0
votes
1
answer
792
views
How do I disable libtorch warning
Recently I deployed a program using libtorch (PyTorch C++ API). The program run as expected but its gives me a warning.
...
1
vote
0
answers
494
views
Replicating RNN within PyTorch
I tried to create a manual RNN and followed the official PyTorch example, which tries to classify a name to a language. I should note that it does indeed work. I'm not using the final logsoftmax, ...
- 807
0
votes
1
answer
132
views
Architecture for linear regression with variable input where each input is n-sized one-hot encoded
I am relatively new to deep learning (got some experience with CNNs in PyTorch), and I am not sure how to tackle the following idea. I want to parse a sentence, e.g. I like trees., one-hot encoded the ...
- 75
1
vote
0
answers
313
views
LSTM Produces Random Predictions
I have trained an LSTM in PyTorch on financial data where a series of 14 values predicts the 15th. I split the data into Train, Test, and Validation sets. I trained the model until the loss ...
- 998
2
votes
1
answer
540
views
Query on unstable loss curves for RNN
I’m currently building sequence models for forecasting, and have tried using RNNs, LSTMs, and GRUs.
Something unusual I noticed was the highly unstable loss curves, where the loss sometimes goes back ...
- 121
5
votes
1
answer
11k
views
How/What to initialize the hidden states in RNN sequence-to-sequence models?
In an RNN sequence-to-sequence model, the encode input hidden states and the output's hidden states needs to be initialized before training.
What values should we initialize them with? How should we ...
- 2,460
13
votes
3
answers
2k
views
An Artificial Neural Network (ANN) with an arbitrary number of inputs and outputs
I would like to use ANNs for my problem, but the issue is my inputs and outputs node numbers are not fixed.
I did some google searches before asking my question and found that the RNN may help me with ...
- 303