I'm getting an error but it's buried down in the TensorFlow library so I'm struggling to figure out what's wrong with my model. I'm trying to use an RNN with LSTM. My model looks like this: model...

In an attempt to further explore the keras-tf RNN capabilities and different parameters, i decided to solve a toy problem as described - build a source data set composed of a sequence of random ...

I have a fully implemented LSTM RNN using Keras, and I want to use gradient clipping with the gradient norm limited to 5 (I'm trying to reproduce a research paper). I'm quite a beginner with regard...

My current LSTM network looks like this. rnn_cell = tf.contrib.rnn.BasicRNNCell(num_units=CELL_SIZE) init_s = rnn_cell.zero_state(batch_size=1, dtype=tf.float32) # very first hidden state outputs,...

I roughly followed this tutorial: https://machinelearningmastery.com/text-generation-lstm-recurrent-neural-networks-python-keras/ A notable difference is that I use 2 LSTM layers with dropout. My...

I'm doing video captioning on MSR-VTT dataset. In this dataset, I've got 10,000 videos and, for each videos, I've got 20 different captions. My model consists of a seq2seq RNN. Encoder's inputs a...

I get this error while trying to build a multiclass text classification network using LSTM (RNN). The code seems to run fine for the training part of the code whereas it throws the error for the va...

I have a similar open question here on Cross Validated (though not implementation focused, which I intend this question to be, so I think they are both valid). I'm working on a project that uses ...

I'm trying to use the approach described in this paper https://arxiv.org/abs/1712.01815 to make the algorithm learn a new game. There is only one problem that does not directly fit into this appr...

I'd like to use a pretrained GloVe embedding as the initial weights for an embedding layer in an RNN encoder/decoder. The code is in Tensorflow 2.0. Simply adding the embedding matrix as a weights ...

I'm trying to pass the output of one layer into two different layers and then join them back together. However, I'm being stopped by this error which is telling me that my input isn't a symbolic te...

I would like to implement attention to a trained image classification CNN model. For example, there are 30 classes and with the Keras CNN, I obtain for each image the predicted class. However, to v...

Correct me if I am wrong but according to the official Keras documentation, by default, the fit function has the argument 'shuffle=True', hence it shuffles the whole training dataset on each epoch....

I try to understand LSTMs and how to build them with Keras. I found out, that there are principally the 4 modes to run a RNN (the 4 right ones in the picture) Image source: Andrej Karpathy Now I...

I recently tried to implement a vanilla RNN from scratch. I implemented everything and even ran a seemingly OK example! yet I noticed the gradient check is not successful! and only some parts (spec...

It seems that the tf.nn.dynamic_rnn has been deprecated: Warning: THIS FUNCTION IS DEPRECATED. It will be removed in a future version. Instructions for updating: Please use keras.layers.RNN(cel...

I am training a model using Keras. model = Sequential() model.add(LSTM(units=300, input_shape=(timestep,103), use_bias=True, dropout=0.2, recurrent_dropout=0.2)) model.add(Dense(units=536)) model....

Context: I am currently working on time series prediction using Keras with Tensorflow backend and, therefore, studied the tutorial provided here. Following this tutorial, I came to the point wher...

I was trying to replicate How to use packing for variable-length sequence inputs for rnn but I guess I first need to understand why we need to "pack" the sequence. I understand why we &qu...

As I know, DropoutWrapper is used as follows __init__( cell, input_keep_prob=1.0, output_keep_prob=1.0, state_keep_prob=1.0, variational_recurrent=False, input_size=None, dtype=None, seed=None ) ...

I have created a stacked keras decoder model using the following loop: # Create the encoder # Define an input sequence. encoder_inputs = keras.layers.Input(shape=(None, num_input_features)) # Cre...

To be clear, I am referring to "self-attention" of the type described in Hierarchical Attention Networks for Document Classification and implemented many places, for example: here. I am not referri...

I'm a beginner in Keras and just write a toy example. It reports a TypeError. The code and error are as follows: Code: inputs = keras.Input(shape=(3, )) cell = keras.layers.SimpleRNNCell(units=5...

I have a mechanical problem as kind of a time series with raw data as follows time dtime cur dcur type proc start end 122088 1554207711521 3140 0.766106 0.130276 0 87556 1554203520000 15542077200...

I'm working on a smaller project to better understand RNN, in particualr LSTM and GRU. I'm not at all an expert, so please bear that in mind. The problem I'm facing is given as data in the form of...