Questions tagged [sequence-to-sequence]
The sequence-to-sequence tag has no usage guidance.
50
questions with no upvoted or accepted answers
3
votes
1
answer
55
views
String together a set of tokens into a sequence
I have this problem scenario - Given a set of tokens, string them or a subset of the tokens together using stop words into a sequence. I am clear that I can have potentially infinite pre-training data ...
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3
votes
0
answers
114
views
Encoder-Decoder Sequence-to-Sequence Model for Translations in Both Directions
Is it possible to use a pre-trained sequence to sequence encoder-decoder model which translates an input text in source language to an output in target language to do an inverse translation? That is, ...
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2
votes
0
answers
175
views
Why the LSTM on Keras does not work correctly when it is necessary to predict several steps forward
I used AirPassenger Dataset. And based on several previous values(for examples 20) I want to predict several(3 or 5) steps in future.
Like
X -> y
[10,20,30,....200]->[210,220,230]
[20,30,40,.......
2
votes
1
answer
288
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Timeseries LSTM: does test data need to come after training data?
I have one single, very long time series. I want to train an LSTM to distinguish between two behaviours (A or B) at every timestep (sequence-to-sequence).
Because the time series is very long, I plan ...
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2
votes
0
answers
172
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LSTM low training/validation error but really bad predictions
I'm building a LSTM model to create an automatic drums composer.
I'm following this post: LSTM Metallica
I've built my model and done all the enconding, I was able to emulate the behavior of the ...
2
votes
0
answers
387
views
Weight matrices in transformers
I am trying to understand the transformer architecture.
I am aware that the encoder/decoder contains multiple stacked self attention layers. Further each layer contains multiple heads. For example ...
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2
votes
0
answers
305
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Why isnt my seq2seq model reconising what the <END> tag is?
I am making a seq2seq chatbot with the help of this guide: https://medium.com/predict/creating-a-chatbot-from-scratch-using-keras-and-tensorflow-59e8fc76be79 . I set up the model and data processing ...
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2
votes
1
answer
4k
views
IndexError: list index out of range
I'm implementing a sequence-2-sequence model with RNN-VAE architecture, and I use an attention mechanism. I have problem in the decoder part.
I'm struggling with this error: IndexError: list index ...
- 614
2
votes
0
answers
1k
views
Recommended model for univariate or multivariate multistep ahead time series forecasting
I have a dataset consisting of recurring and non-recurring expense transactions from bank accounts, as well as other features describing the bank account and each transation. I aggregate these ...
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2
votes
1
answer
4k
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Predicting next number in a sequence - data analysis
I am a machine learning newbie and I am working on a project where I'm given a sequence of integers all of which are in the range 0 to 70. My goal is to predict the next integer in the sequence given ...
- 21
2
votes
1
answer
299
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Keras: Softmax output into embedding layer
I'm trying to build an encoder-decoder network in Keras to generate a sentence of a particular style. As my problem is unsupervised i.e. I don't have the ground truths for the generated sentences, I ...
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1
vote
1
answer
154
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Why does a decoder generate all hidden states during inference?
Seems that in Vanilla transformers at least (a la AIAYN), during inference time, the hidden states are generated for all tokens in the input sequence, but only the last one is used to predict the next ...
- 163
1
vote
0
answers
29
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RNN to model DNA sequencing classification
I have a DNA sequence dataset each mapped to a certain class.
e,g
TCAGCCGAGAGCTCATCGATCGTACGT 2
ATGCAGTGCATCGATCGATCGTAGAAC 3
Where the number after the sequence specifies the type of protein this ...
1
vote
1
answer
176
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Seq2Seq loss function
I was reading the paper neural_approach_conversational_ai.pdf. And in the section Seq2Seq for Text Generation there is a formula that i feel a bit wrong
[1]: https://i.stack.imgur.com/sX0it.png
Can ...
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1
vote
1
answer
173
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Multioutput prediction using LSTM encoder decoder with Attention
(I am working on Jupter notebook with python version 3.6.12, running Tensorflow 2.4.0 version.)
I have a dataset that consists of 5 input features and 3 output features (that requires to be predicted)....
1
vote
0
answers
15
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Sequence learning from farm operations data
I need to generalize a single sequence from N sequences entailing farming tasks/operations and ultimately plotting it on Gantt chart.
There are a total let's assume N sequences = n (total fields) * t (...
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1
vote
1
answer
189
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Multi-step forecasts of factory production data using a Seq2Seq Encoder-Decoder Model with Attention
I am attempting to use a Seq2Seq model to make forecasts of factory production data using an Encoder-Decoder model augmented with Attention. I have become a little stuck as the output of the model ...
1
vote
0
answers
33
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Workaround / fallback value for tfp.distributions.Categorical.log_prob in tensorflow graph mode
Is there a way to avoid tfp.distributions.Categorical.log_probraising an error if the input is a label out of range?
I am passing a batch of samples to the ...
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1
vote
0
answers
79
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Dummy Variables of Weights in RNN Backpropagation Through Time
In the deep learning book RNN chapter (https://www.deeplearningbook.org/contents/rnn.html), it is mentioned that -
To resolve this ambiguity, we introduce dummy variables $W^{(t)}$ that are defined to ...
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1
vote
0
answers
113
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Multiple time series sequence prediction for multiple multivariate time series
My question is somehow similar to this question, but not satisfied with the answer. I have 100 samples, each sample consists of ...
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1
vote
0
answers
40
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Seq2Seq for sentence correction
I have a task in hand where I get a dirty formed sentence and need to correct it. Examples are, "StackOverflow best question answering platform" to be converted to "StackOverflow is best question ...
- 874
1
vote
0
answers
192
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How can I finetune XLM-R for neural machine translation between the same language(Catalan to Catalan-with different grammar structure))?
Can I fine-tune XLM-R to do something similar to https://www.guru99.com/seq2seq-model.html
(encoder-decoder architecture or any other way that perform good in small dataset - around 1000)
For example:
...
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1
vote
0
answers
34
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How can I do a sequence to sequence model (RNN / LSTM) with Keras with fixed length data?
What I'm trying to do seems so simple, but I can't find any examples online. First, I'm not working in language, so all of the embedding stuff adds needless ...
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1
vote
0
answers
125
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Improving Performance of LSTM for time series prediction
My data consists of two features and a set of time series data labeled as "bookings". I have 1056 data point in the times series, for which I have two features for each. The data size is 1056x3.
My ...
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1
vote
0
answers
107
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How to create a seq2seq without specifying a fixed decoder length?
Based on the model presented in this answer:
...
- 167
1
vote
0
answers
33
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Adding context in a sequence to sequence problem
The encoder of a seq2seq model is meant to generate a conditioning context for the decoder, as mentioned here
A RNN layer (or stack thereof) acts as "encoder": it processes the input sequence and ...
- 1,638
1
vote
0
answers
46
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Initialising states in a multilayer sequence to sequence model
With a sequence to sequence model where the enocoder and decoder are both comprised of one layer each, the initial state of the decoder is initialised to use the final states of the encoder layer.
In ...
- 418
1
vote
0
answers
249
views
What should the size of the decoder output be in a sequence to sequence model
In a sequence to sequence model, a lot of the tutorials I have read state that the decoder target length should be the same as the encoder input length (https://blog.keras.io/building-autoencoders-in-...
- 418
1
vote
0
answers
71
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On-the-fly seq2seq: starting translation before the input sequence ends
By now anybody even remotely familiar with RNNs has been exposed to the famous figure representing variants of such networks:
However one type that is missing is one where there would be a partial ...
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1
vote
0
answers
291
views
Neural network outputting same result for all inputs
I'm building an encoder-decoder neural network in Keras for sequence generation. The specific task is to try and change the styles of the text.
Both my encoder and decoders are LSTMs with latent ...
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1
vote
2
answers
157
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How to pad real-valued sequences
I have several sequences of univariate real-valued time-series data. The sequences are of different lengths and right now I cannot batch them and feed them to a network.
What is the correct procedure ...
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0
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0
answers
8
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In abstractive document summarization task, if I have multiple target sequences for one input document, what is the ideal loss form?
I use autoregressive model like T5 to tackle the abstractive document summarization task. In my case there are multiple target summarizations for one input document. Is there some related works about ...
- 103
0
votes
0
answers
45
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I can't figure out why even when training the seq2seq chatbot neural network, it doesn't give adequate answers
When training with 50 thousand pairs of questions and loss 0.2 accuracy 0.9 it does not give adequate answers
...
- 1
0
votes
0
answers
20
views
Batch inference and seq2seq
I am following this guide to the Seq2Seq architecture. It is clear that the author suggests batch training during the teacher forcing step. However, during the inference step, the author restricts the ...
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0
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0
answers
38
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Siamese network for a sequence-to-sequence generation
Shall I use the siamese network for a sequence-to-sequence generation problem in machine learning?
Eg:
Input 1: Sentence 1 (sequence)
Input 2: Sentence 2 (sequence)
Output: Newly Generated sentence (...
- 1
0
votes
0
answers
41
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Dialogue history encoding for multi-turn dialogues using Seq2seq
In single-turn dialogue seq2seq models where the goal is to produce a good answer y to a query x, sentences are usually encoded such that x is fed to the encoder, while the decoder is only given a &...
0
votes
1
answer
57
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How to make a pipeline for Videos Dataset for TensorFlow [Sequence Matters] & train Model Effectively with Low Memory System
I am working on a Deep Learning project and I am facing an issue with the size of the dataset. I want to make a pipeline for video dataset [Sequence Matters]. Because if I try the load the whole ...
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0
votes
0
answers
232
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SOS / EOS tokens to encode fixed-size 1D real and complex-valued short signals with seq2seq
Are there any standard or recommended SOS (start of sequence) and EOS (end of sequence) tokens for seq2seq encoding using RNN/LSTM/Transformers applied to real-valued and/or complex-valued 1D signals (...
- 101
0
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0
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20
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Fixing/up-rezzing images is easily possible these days in practice. Is there any analogous tool available for low-quality audio?
Tools like waifu2x and Anime4k (for the MPV video player) can already easily de-noise and up-rez low quality images to 4k quality pretty darn well. Similar tools like DLSS and FSR are used for video ...
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0
votes
1
answer
37
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Forecasting of Images using ConvLSTM2D
I am working on a problem of seq2seq modelling using ConvLSTM2D layer in keras. Implementation of convLSTM in keras allows user to control over output sequence using 'return_sequence' option. When ...
- 101
0
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0
answers
61
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What does logits in Casual Language Modeling represent?
I am reading the docs for transformers by hugging face and I see that the logits produced by casual language models are of the shape (batch_size, sequence_length, config.vocab_size).
I also read the ...
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0
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33
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Image captioning using sequence to sequence model
I am trying to build a sequence to sequence model. I have used Vision transformer as the encoder and LSTM with 1 layers as the decoder. The output of the encoder is given as the hidden state for ...
0
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0
answers
17
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Given an audio file, output a processed audio file (with something like seq2seq)
I have a dataset of audio files of varying durations. Given audio file x, I would like to get audio file y (audio files ...
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0
votes
0
answers
63
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How to use batches for training in Sequence-to-Sequence models?
I am working on a seq-to-seq Image Captioning model, with Vision Transformer as the encoder and a LSTM based model as a decoder. The output from the encoder is given as the hidden state and cell state ...
0
votes
0
answers
127
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Predict sequence using seqGAN
I am trying to create a GAN model in which I am using this seq2seq as Generator and the following architecture as Discriminator:
...
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0
votes
1
answer
39
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Preprocess multi-sample time series data: encode each sample separately or in aggregate?
Let's say I have 3 dense sequences of uniform length. Should I fit a scaler on them separately or together?
...
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0
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0
answers
27
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How to reduce dimensionality of encoder decoder output?
I have an encoder decoder architecture where the output $ \bar{\bf{y}}_t $ is a sequence of integers of maximum length $n$. Each integer in the sequence is representative of a category so the ...
- 101
0
votes
1
answer
56
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two different attention methods for seq2seq
I see two different ways of applying attention in seq2seq:
(a) the context vector (the weighted sum of encoder hidden states) fed into the output softmax, as shown in the diagram below. The diagram ...
- 101
0
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0
answers
34
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Strategy for "forcing" number of labels in seq2seq predictions with Keras?
I'm trying to train a seq2seq model that for every timestep in a given timeseries sample will output 1 of 6 possible labels.
Furthermore, the training data is constructed in such a way that
Each ...
- 163
0
votes
2
answers
99
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Seq2Seq Model training: Encoder vs. Decoder
Can someone point me to an article which explains how the model training is done in Seq2Seq? I know "Teacher Forcing" is used but what I found so far hasn't been detailed enough. What I am most ...
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