Questions tagged [encoder]
The encoder tag has no usage guidance.
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What does the output of an encoder in encoder-decoder model represent?
So in most blogs or books touching upon the topic of encoder-decoder architectures the authors usually say that the last hidden state(s) of the encoder is passed as input to the decoder and the ...
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Explain the outputs of Bidirectional LSTM . There are 5 output , which of them are hidden state and cell state respectively?
I am trying to use bidirectional LSTM as encoder in my translation model.
I set return_sequence=True and return_state=True and I ...
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Why we need encoder-decoder architectures despite we already have RNN?
Why we need encoder-decoder architectures despite we already have RNN? From Googling, I was just told such architecture is used, in the context of NLP, that it allows:
The key benefits of the ...
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Use Beam Search in encoder-decoder
How can tfa.seq2seq.BeamSearchDecoder, for example, be used with a simple encoder-decoder architecture? Suppose the task is machine translation, where the encoder returns a vector representation of ...
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Encode categorical data for unsupervised learning
What is the best encoder for categorical data in unsupervised learning?
I am using unsupervised learning on mixed data (such as K-means).
Before running my unsupervised algorithm, I am using dimension ...
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Motivation of LSTM with no Input
I have read this paper where authors use LSTM to learn the attention applied to several sets. They use LSTM without input or output, LSTM just uses the hidden state and evolves it:
My question is ...
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SkLearn Categorical Naive Bayes Vs Mathematical theory of Naive Bayes
The Naive Bayes classification based on the following formula
$P(C_i|X) = {P(X|C_i)P(C_i) \over P(X)} ... i)$
$P(X|C_i)$ is the posterior probability of $X$ conditioned on $C_i$, $P(X)$ prior ...
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Self-Attention: Tensorflow to PyTorch Code Conversion
I have a TensorFlow encoder code with a Self-attention layer
X = layers.Attention()([X,X]) #Single-head Self-attention layer
What is the equivalent PyTorch code?
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Encoder Decoder model for parameter extraction from text input
I have an input as text from which I want to extract parameters as given in example below.
Input:
...
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Comparing encoders to same input of differnt output size
Let's say I have an input s1 and I pass it to two encoders e1 and e2. They output encodings ...
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What to do with Transformer Encoder output?
I'm in the middle of learning about Transformer layers, and I feel like I've got enough of the general idea behind them to be dangerous. I'm designing a neural network and my team would like to ...
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Is it vital to do label encoding with target variable
Should I always use label encoding while doing binary classification?
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How to Visualize attention weights in a Attention based Encoder-Decoder network in Time series forecasting
Below is one example Attention-based Encoder-decoder network for multivariate time series forecasting task. I want to visualize the attention weights.
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Special tokens for encoder and decoder in the transformer architecture
I am trying to wrap my head around the different special tokens that the different transformer architectures use.
For example, let's say we have the following input and target both for a text ...
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Get Hidden Layers in PyTorch TransformerEncoder
I am trying to access the hidden layers when using TransformerEncoder and TransformerEncoderLayer. I could not find anything ...
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Can anyone interpret this Recurrent Network Encoder-Decoder question?
I'm trying to earn some extra credit, so the professor won't elaborate further on what's being asked in this question:
The dataset that we're given is a line-by-line file of protein sequences (...
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Changing order of LabelEncoder() result
Assume I have a multi-class classification task. The labels are:
Class 1
Class 2
Class 3
After LabelEncoder(), the labels are transformed into 0-1-2.
My questions are:
Do the labels have to start ...
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Encoder-Decoder LSTM for Trajectory Prediction
I need to use encoder-decoder structure to predict 2D trajectories. As almost all available tutorials are related to NLP -with sparse vectors-, I couldn't be sure about how to adapt the solutions to a ...
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Encode time-series of different lengths with keras
I have time-series as my data (one time-series per training example). I would like to encode the data within these series in a fixed-length vector of features using a keras model.
The problem is that ...
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What is the difference between BERT architecture and vanilla Transformer architecture
I'm doing some research for the summarization task and found out BERT is derived from the Transformer model. In every blog about BERT that I have read, they focus on explaining what is a bidirectional ...
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Why transform embedding dimension in sin-cos positional encoding?
Positional encoding using sine-cosine functions is often used in transformer models.
Assume that $X \in R^{l\times d}$ is the embedding of an example, where $l$ is the sequence length and $d$ is the ...
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Role of decoder in Transformer?
I understand the mechanics of Encoder-Decoder architecture used in the Attention Is All You Need paper. My question is more high level about the role of the decoder. Say we have a sentence translation ...
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How to add a Decoder & Attention Layer to Bidirectional Encoder with tensorflow 2.0
I am a beginner in machine learning and I'm trying to create a spelling correction model that spell checks for a small amount of vocab (approximately 1000 phrases). Currently, I am refering to the ...
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sklearn serialize label encoder for multiple categorical columns
I have a model with several categorical features that need to be converted to numeric format. I am using a combination of LabelEncoder and OneHotEncoder to achieve this.
Once in production, I need to ...
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Encoding correlation
I have rather theory-based question as I'm not that experienced in encoders, embeddings etc. Scientifically I'm mostly oriented around novel evolutionary model-based methods.
Let's assume we have ...
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How do I implement Dual-encoder model in Pytorch?
I am trying to implement the paper titled Learning Cross-lingual Sentence Representations via a Multi-task Dual-Encoder Model.
Here the encoder and decoder share the same weights but I am unable to ...
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