Currently i think i'm experiencing a systematic offset in a LSTM model, between the predictions and the ground truth values. What's the best approach to continue further from now on? The model arc...

I am creating a chatbot trained on Cornell Movie Dialogs Corpus using NMT. I am basing my code in part from https://github.com/bshao001/ChatLearner and https://github.com/chiphuyen/stanford-tensor...

So I'm trying to learn RNN in R using keras with this beginner's tutorial: I'm going through the tutorial step by step, but I run into a weird error after adding the input layer. Here's the line ca...

I keep running into this error: RuntimeError: Trying to backward through the graph a second time, but the buffers have already been freed. Specify retain_graph=True when calling backward the first...

I would like to know more details about the merge mode when using Bidirectional LSTM for sequence classification, and especially for the "Concat" merge mode which is still quite unclear t...

I am running the following pixel recurrent neural network (RNN) code using Python 3.6 import os import logging import numpy as np from tqdm import trange import tensorflow as tf from utils impor...

I am working in RNN. I have following lines of code from some site. If you observe second layer has no "returnSequence" parameter. I am assuming return sequence is mandatory as it should return th...

I am trying to import LSTM in python from keras.layers.recurrent import LSTM However, I get below error message on compilation: ModuleNotFoundError: No module named 'keras.layers.recurrent' Can so...

I am new to deep learning and currently working on using LSTMs for language modeling. I was looking at the pytorch documentation and was confused by it. If I create a nn.LSTM(input_size, hidden_...

I am new to Tensorflow and deep leaning. I am trying to see how the loss decreases over 10 epochs in my RNN model that I created to read a dataset from kaggle which contains credit card fraud data....

I'm following this tutorial here https://cs230-stanford.github.io/pytorch-nlp.html. In there a neural model is created, using nn.Module, with an embedding layer, which is initialized here self.emb...

I tried to find a similar question and its answers but was not successful in doing so. That's why I'm asking a question that might be asked before: I'm working on a problem that outputs the cumula...

I have been trying to train some data using a model that utilizes src+img. When running the training script, I'm running into an error namely: RuntimeError: PytorchStreamReader failed locating file...

I have the following code in Keras (Basically I am modifying this code for my use) and I get this error: 'ValueError: Error when checking target: expected conv3d_3 to have 5 dimensions, but got ar...

If I use a stateful RNN in Keras for processing a sequence of length N divided into N parts (each time step is processed individually), how is backpropagation handled? Does it only affect the las...

I am stuck between hidden dimension and n_layers. What I understood so far, is that n_layers in the parameters of RNN using pytorch, is number of hidden layers. If n_layers represents the number if...

Nice evening everyone, i spent the last 6 hours trying to debug seemingly randomly occuring NaN-values in Jax. I have narrowed down that the NaNs initially stem from either the loss-function or its...

Given X with dimensions (m samples, n sequences, and k features), and y labels with dimensions (m samples, 0/1): Suppose I want to train a stateful LSTM (going by keras definition, where "stateful...

I train the following model based on GRU, note that I am passing the argument stateful=True to the GRU builder. class LearningToSurpriseModel(tf.keras.Model): def __init__(self, vocab_size, embedd...

An RNN, in keras, accepts an input with the following shape array([[['Xa0', 'Ya0'], ['Xa1', 'Ya1'], ['Xa2', 'Ya2']], [['Xb0', 'Yb0'], ['Xb1', 'Yb1'], ['Xb2', 'Yb2']], [['Xc0', 'Yc0'], ['Xc...

I'm trying to reshape a tensor from [A, B, C, D] into [A, B, C * D] and feed it into a dynamic_rnn. Assume that I don't know the B, C, and D in advance (they're a result of a convolutional network)...

I am making a neural network to predict audio data (to learn more about how neural networks function and how to use tensorflow), and everything is going pretty smoothly so far, with one exception. ...

In tensorflow, there's a method called ScheduledOutputTrainingSampler defined here. It basically adds scheduled sampling to the outputs of an LSTM model. I've been struggling to understand how to u...

I've been confused over how the hidden/cell states transfer from within one batch when you have a batch_size > 1, and across batches. My assumption currently is that hidden states never transfer f...

Can someone give a full working code (not a snippet, but something that runs on a variable-length recurrent neural network) on how would you use the PackedSequence method in PyTorch? There do not ...