Newest 'sequence-to-sequence' Questions

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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. ...

asked Dec 21 '19 at 15:31

Sandeep Bhutani

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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 ...

deep-learning tensorflow recurrent-neural-net sequence-to-sequence attention-mechanism

asked Dec 8 '19 at 17:29

Uday

1366 bronze badges

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1answer

135 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 ...

keras tensorflow sequence-to-sequence bert machine-translation

asked Dec 6 '19 at 11:50

Hamed

214 bronze badges

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20 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 ...

sequence-to-sequence bert machine-translation transformer attention-mechanism

asked Dec 5 '19 at 10:34

Sahil

794 bronze badges

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1answer

82 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 ...

deep-learning keras sequence-to-sequence language-model attention-mechanism

asked Dec 2 '19 at 21:22

user_12

1974 bronze badges

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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: ...

lstm word-embeddings sequence-to-sequence

asked Dec 2 '19 at 10:51

Joao Diogo

31 bronze badge

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23 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 ...

keras lstm rnn sequence-to-sequence

asked Nov 26 '19 at 9:57

HaneenSu

433 bronze badges

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79 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 ...

neural-network deep-learning lstm pytorch sequence-to-sequence

asked Nov 18 '19 at 15:41

Dean

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21 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 ...

sequence-to-sequence attention-mechanism

asked Nov 5 '19 at 2:44

DSKim

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43 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 ...

neural-network sequence-to-sequence nlg

asked Nov 4 '19 at 8:46

rivamarco

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21 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 ...

neural-network nlp sequence-to-sequence

asked Oct 25 '19 at 23:34

Yu Gu

1012 bronze badges

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11 views

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

Based on the model presented in this answer: ...

python deep-learning keras lstm sequence-to-sequence

asked Oct 18 '19 at 17:48

user2182857

1354 bronze badges

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44 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 ...

keras sequence-to-sequence

asked Oct 11 '19 at 14:31

Simon Krannig

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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 : ...

keras lstm sequence-to-sequence

asked Oct 1 '19 at 12:45

Mithun Sarker Shuvro

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1answer

6 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 ...

rnn sequence-to-sequence

asked Aug 5 '19 at 22:57

user1893354

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104 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 ...

python neural-network keras tensorflow sequence-to-sequence

asked Jul 21 '19 at 21:56

Dup Dup

211 bronze badge

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12 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 ...

machine-learning nlp sequence-to-sequence

asked Jul 21 '19 at 20:05

BoredPerson

31 bronze badge

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83 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 ...

nlp sequence-to-sequence nlg

asked Jul 16 '19 at 4:41

sandy

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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 ...

deep-learning lstm reinforcement-learning sequence-to-sequence

asked Jul 12 '19 at 8:58

Rahul Poddar

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62 views

Error propagation in Time series forecast with many-to-many multi-steps RNN/LSTM

I am trying to do a many-to-many time series forecast, which features an encoder-decoder model to predict with variable input and fixed prediction period. In my case, I want to predict for the future ...

deep-learning time-series lstm forecast sequence-to-sequence

asked Jun 20 '19 at 7:19

Le0

11 bronze badge

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0answers

15 views

Deep Learning - Predict the relative order of data

I am facing a problem in which i want to predict the order of data. I was searching for research papers, however i do not know how this problem is named in academia. I encountered the following well ...

deep-learning classification sequence-to-sequence

asked Jun 19 '19 at 15:15

Chocolate

1011 bronze badge

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1answer

37 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 ...

sequence-to-sequence

asked Jun 14 '19 at 16:45

kee

1435 bronze badges

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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 ...

python keras tensorflow autoencoder sequence-to-sequence

asked May 2 '19 at 21:08

Kikio

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181 views

ValueError: Dimensions must be equal, but are 256 and 12 for 'attention_layer/MatMul_1' (op: 'MatMul') with input shapes: [?,256], [12,256]

I'm working on a sequence-to-sequence approach using LSTM and a VAE with an attention mechanism. ...

lstm sequence-to-sequence attention-mechanism vae

asked Apr 29 '19 at 12:23

Kikio

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0answers

498 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. ...

tensorflow lstm sequence-to-sequence attention-mechanism vae

asked Apr 28 '19 at 23:24

Kikio

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19 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 ...

neural-network keras time-series recurrent-neural-net sequence-to-sequence

asked Apr 25 '19 at 11:23

komodovaran_

1235 bronze badges

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0answers

33 views

What encoding to use for my musical vectors?

I'm trying to build a music recommendations system using an encoder-decoder sequence-to-sequence architecture using keras. My dataset comprises of playlists containing songs represented as a 13-...

machine-learning python keras recurrent-neural-net sequence-to-sequence

asked Apr 7 '19 at 6:36

FusRhoDa4897

11 bronze badge

2

votes

1answer

52 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 ...

deep-learning lstm recurrent-neural-net named-entity-recognition sequence-to-sequence

asked Apr 4 '19 at 23:47

B.K

233 bronze badges

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194 views

Seq2seq model that gets as input a sentence and outputs the same sentence

I tried to implement a model that takes as input sentences, which are hate_tweets and outputs exactly the same sentences. For this reason, I gave Input to the encoder and decoder exactly the same ...

machine-learning nlp lstm rnn sequence-to-sequence

asked Apr 2 '19 at 18:33

thelaw

133 bronze badges

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0answers

96 views

Using VAE with Sequence to Sequence Approach

In the code below, I'm using a VAE with a seq-to-seq approach for translation. At the beginning I sarted only by using a simple seq-to-seq approach which implements a RNN-AE, until this step I had not ...

python deep-learning tensorflow autoencoder sequence-to-sequence

asked Apr 1 '19 at 13:35

Kikio

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1

vote

0answers

23 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 ...

time-series lstm recurrent-neural-net sequence-to-sequence

asked Apr 1 '19 at 11:17

ignatius

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votes

1answer

1k 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 ...

time-series encoding sequence-to-sequence

asked Feb 26 '19 at 12:32

gico

1737 bronze badges

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0answers

28 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 ...

time-series lstm rnn sequence-to-sequence stacked-lstm

asked Feb 7 '19 at 12:46

Aesir

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95 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-...

neural-network keras time-series recurrent-neural-net sequence-to-sequence

asked Feb 2 '19 at 11:53

Aesir

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2

votes

1answer

6k 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 ...

neural-network keras feature-selection recurrent-neural-net sequence-to-sequence

asked Jan 27 '19 at 14:01

Aesir

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2

votes

0answers

508 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 ...

time-series lstm rnn forecasting sequence-to-sequence

asked Dec 19 '18 at 11:59

KOB

1793 bronze badges

1

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1answer

1k 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 ...

machine-learning time-series lstm rnn sequence-to-sequence

asked Dec 14 '18 at 14:05

varun

113 bronze badges

2

votes

2answers

3k views

Does this encoder-decoder LSTM make sense for time series sequence to sequence?

TASK given $\vec x = [x_{t=-3}, x_{t=-2}, x_{t=-1}, x_{t=0}]$ predict $\vec y = [x_{t=1}, x_{t=2}]$ Whith an LSTM encoder-decoder (seq2seq) MODEL NOTE: the ? symbol in the shape of the tensors ...

time-series lstm sequence-to-sequence

asked Dec 12 '18 at 13:07

ignatius

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3

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0answers

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Why does Position Embeddings work?

In the papers "Convolutional Sequence to Sequence Learning" and "Attention Is All You Need", positions embeddings are simply added to the input words embeddings to give the model a sense of the order ...

word-embeddings convolution sequence sequence-to-sequence attention-mechanism

asked Nov 8 '18 at 16:05

Robin

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1

vote

1answer

396 views

Give Variable Length input to LSTM

My input data consist of list of list. Both list have dynamic length for every example like below. ...

deep-learning lstm rnn sequence sequence-to-sequence

asked Nov 4 '18 at 15:21

Batuhan Bardak

1944 bronze badges

0

votes

1answer

42 views

What type of neural network could emulate a binary to HTML conversion tool?

I've got a problem, which I thought could be solved by using a neural network: I've got a binary file and a tool that converts that file into a readable html file (probably a text file as well). How ...

neural-network tensorflow sequence-to-sequence

asked Oct 11 '18 at 8:21

Gistiv

1012 bronze badges

1

vote

1answer

48 views

Can Sequence to sequence models be used to convert code from one programming language to another?

Is it possible to convert a code from one language to another using sequence to sequence programming. if not sequence to sequence, which algorithm can i use to do this?

deep-learning sequence-to-sequence

asked Oct 4 '18 at 19:29

InAFlash

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3

votes

3answers

120 views

Predict output sequence one at a time with feedback

I would like to solve the following classification problem: Given an input sequence and zero or more initial terms of the true output, predict the next term in the output sequence. For example, my ...

classification rnn lstm sequence-to-sequence

asked Aug 20 '18 at 6:34

Imran

2,1036 silver badges22 bronze badges

3

votes

2answers

341 views

Is this a problem for a Seq2Seq model?

I'm struggling to find a tutorial/example which covers using an seq2seq model for sequential inputs other then text/translation. I have a multivariate dataset with n number of input variables each ...

machine-learning rnn lstm sequence sequence-to-sequence

asked Aug 19 '18 at 19:45

Elliot

535 bronze badges

2

votes

0answers

105 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, ...

neural-network rnn autoencoder machine-translation sequence-to-sequence

asked Aug 1 '18 at 13:30

Amir

732 bronze badges

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0answers

60 views

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 ...

deep-learning sequence-to-sequence

asked Jul 30 '18 at 12:18

user209974

1311 bronze badge

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0answers

239 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 ...

neural-network keras sequence-to-sequence text-generation

asked Jul 26 '18 at 16:39

Physbox

1075 bronze badges

2

votes

1answer

180 views

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 ...

keras sequence-to-sequence embeddings

asked Jul 24 '18 at 19:57

Physbox

1075 bronze badges

1

vote

2answers

159 views

What are the benefits and tradeoffs of a 1D conv vs a multi-input seq2seq LSTM model?

I have 6 sequences, s1,..,s6. Using all sequences I want to predict a binary vector q = [0,0,0,1,1,1,0,0,0,1,1,1,...], which is a mask of the activity of the 6 sequences. I have looked at seq2seq ...

machine-learning convnet lstm recurrent-neural-net sequence-to-sequence

asked Jul 16 '18 at 13:47

Zach LeFevre

133 bronze badges

2

votes

1answer

141 views

Training Encoder-Decoder using Decoder Outputs

I am trying to build an encoder-decoder model for a text style transfer problem. The problem is I don't have parallel data between the two styles so I need to train the model in an unsupervised ...

training autoencoder sequence-to-sequence

asked Jul 7 '18 at 14:20

Physbox

1075 bronze badges

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