Questions tagged [sequence-to-sequence]

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Concatenating Encoder hidden states in LSTM pytorch

I am implementing a seq2seq autoencoder in pytorch: Q1) While it is true that we can keep the encoder as bidirectional, but can we keep the decoder as bidirectional as well(does it make any sense) if ...
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14 views

How can I use Reinforcement Learning for sequence classification problem?

I have a serious problem statement. There is a betting website that gives a digit(0-9) for every 3 mins. If we guess it correct, we get 10 times the money we put. There are definitely patterns in ...
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24 views

How to add attention mechanism to my sequence-to-sequence architecture in Keras?

Based on this blog entry, I have written a sequence to sequence deep learning model in Keras: ...
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1answer
31 views

Comparing Language Model of two corpora

I know using Conditional Language Model I can learn the probability of a sentence given the corpus I used to train my model. I will then be able to generate meaningful text by sampling from the ...
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7 views

Tied embedding in Sequence to Sequence Task

Is it sensible to use a tied embedding between the encoder and decoder in a Sequence to Sequence task where the question and answering is within the same language? This will lower the number of ...
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1answer
99 views

Feeding XLM-R embeddings to neural machine translation?

I’m very new to the field of deep learning. My aim is to make a translation between Catalan to Catalan Sign Language. The grammar of the two languages is different Input: He sells food. Output (...
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20 views

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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1answer
95 views

Transformer seq2seq model and loading embeddings from XLM-RoBERTa

Is it possible to feed embeddings from XLM- RoBERTa to transformer seq2seq model? I'm working on NMT that translates verbal language sentences to sign language sentences (e.g Input: He sells food. ...
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19 views

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 ...
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1answer
14 views

Sequence labeling with partially known labels

I am working on a sequence labeling task where, based on experience, many of the labels of a given input sequence can be reliably extracted with a simple rule-based approach. For example, considering ...
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35 views

Seeking your advice on XLM-R for NMT

I want to use XLM-R for neural machine translation b/n the same low resource language? For example: Input-> He sells food(in Catalan) Output-> Food he sells(in Catalan) Anyone having code example/...
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2answers
25 views

Which input to use when generating a new sequence

I want to use sequence-to-sequence architecture to generate sequences. My data has such structure ...
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77 views

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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1answer
394 views

Can I fine-tune BERT, ELMO or XLnet for Seq2Seq neural machine translation?

I'm working on neural machine translator that translates English sentences to American sign language sentences(e.g below). I've a quite small dataset - around 1000 sentence pairs. I'm wondering if it ...
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1answer
395 views

Is it possible feed BERT to seq2seq encoder/decoder NMT (for low resource language)?

I'm working on NMT model which the input and the target sentences are from the same language (but the grammar differs). I'm planning to pre-train and use BERT since I'm working on small dataset and ...
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2answers
75 views

How are Q, K, and V Vectors Trained in a Transformer Self-Attention?

I am new to transformers, so this may be a silly question, but I was reading about transformers and how they use attention, and it involves the usage of three special vectors. Most articles say that ...
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1answer
35 views

Methods for learning with noisy labels

I am looking for a specific deep learning method that can train a neural network model with both clean and noisy labels. More precisely, I would like this method to be able to leverage noisy data as ...
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13 views

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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2answers
79 views

Sentences language translation with neural network, with a simple layer structure (if possible sequential)

Context: Many language sentences translation systems (e.g. French to English) with neural networks use a seq2seq structure: "the cat sat on the mat" -> [Seq2Seq ...
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1answer
40 views

Answer to Question

Looking for a system which can generate answers to questions. Most systems and blogs posted on internet are on Question to answer but not on answer to question or paraphrasing or keyword to questions. ...
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1k views

SymbolicException: Inputs to eager execution function cannot be Keras symbolic tensors

I am writing Encoder-Decoder architecture with Bahdanau Attention using tf.keras with TensorFlow 2.0. Below is my code This is working with TensorFlow 1.15 but getting the error in 2.0. you can check ...
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1answer
1k views

How can I feed BERT to neural machine translation?

I am trying to feed the input and target sentences to an NMT model, I am trying to use BERT here, But I don't have any idea how ...
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0answers
72 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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2answers
490 views

Any good Implementations of Bi-LSTM bahdanau attention in Keras?

From past few weeks I'm trying to learn sequence to sequence machine translation modelling but I couldn't find any good examples/tutorials with bahdanau attention implemented. I did come across a ton ...
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8 views

Output of a seq2seq network

I've created a seq2seq lstm that uses word embeddings, following the tutorial in tutorial , but I'm having some problems understanding the output, which is along these lines: ...
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28 views

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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178 views

Adapting Pytorch tutorial “NMT from Scratch…” for dynamic RNN

I have taken the code from the tutorial and attempted to modify it to include bi-directionality and any arbitrary numbers of layers for GRU. Link to the tutorial which uses uni-directional, single ...
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1answer
28 views

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 ...
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45 views

Neural Network for text generation

I'm new into ML and NN and I would like to figure out what is the best way to solve this (initially little) problem. Suppose i have a {number} in input and i want as output the phrase "The number in ...
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56 views

What's the meaning of having a UNK token for out of vocabulary words during decoding?

Adding a UNK token to the vocabulary is a conventional way to handle oov works in tasks of NLP. It is totally understandable to have it for encoding, but what's the ...
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17 views

How to create a seq2seq without specifying a fixed decoder length?

Based on the model presented in this answer: ...
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0answers
91 views

Scheduled Sampling in Keras

Im wondering how scheduled sampling (maybe together with curriculum learning) as described in this paper [https://arxiv.org/abs/1506.03099] could be implemented in keras. Lets assume a simple ...
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1answer
47 views

How can I build a seq2seq model , which is topic aware

I have developed a chatbot, which is basically a seq2seq LSTM network. Which can generate text based on input text. But the problem I am having right now is it is not topic aware. As an example : ...
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1answer
9 views

Confusion about Decoder labels for training seq-to-seq models

So in seq-to-seq models for say NMT, the decoder is a sequence model for the right-shifted intended output. My question is, during training, are the inputs and outputs of the decoder supposed to be ...
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183 views

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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17 views

Encoding numbers and words

I am fairly new to seq2seq models in nlp and just really learned about them. Anyway, in many of the examples, I have seen there has been to approaches to providing a model with data. One in which is ...
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161 views

Test case generation from user stories using NLP and NLG

I have an existing database with User stories (with multiple text fields like Description with Use cases, acceptance criteria etc) and corresponding test cases with steps for each test case. I am ...
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26 views

Which algorithm to use for path to prescription?

I am working on a business problem in the commercial pharma industry. In the pharma industry, we have medical representatives (Reps) selling drugs to health care providers (HCPs). They frequently ...
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1answer
47 views

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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1answer
2k 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 ...
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1answer
897 views

ValueError: Cannot convert a partially known TensorShape to a Tensor: (?, 256)

I'm working on a sequence to sequence approach using LSTM and a VAE with an attention mechanism. ...
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0answers
24 views

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 ...
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1answer
69 views

Working ofLSTM with multiple Units - NER

I am trying to understand working of LSTM networks and kind of not clear about how different neurons in a cell interact each other. I had a look at a similar question, but still not clear about few ...
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27 views

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 ...
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1answer
2k views

One-hot encode multi-class multi-label sequences

Suppose I want to build a timeseries where each timestep is represented by a categorical array: the encoded sequences look like [[2, 0, 5],[3, 1, 4],..] and each ...
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30 views

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 ...
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120 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-...
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1answer
10k views

How to determine feature importance in a neural network?

I have a neural network to solve a time series forecasting problem. It is a sequence-to-sequence neural network and currently it is trained on samples each with ten features. The performance of the ...
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0answers
677 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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1answer
2k views

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 ...