recurrent-neural-network Questions

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I'm having some difficulty with chaining together two models in an unusual way. I am trying to replicate the following flowchart: For clarity, at each timestep of Model[0] I am attempting to gener...
Philadelphia asked 29/7, 2020 at 15:45

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I'm doing text tagger using Bidirectional dynamic RNN in tensorflow. After maching input's dimension, I tried to run a Session. this is blstm setting parts: fw_lstm_cell = BasicLSTMCell(LSTM_DIMS...

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It is a duplicate of this question How can I feed last output y(t-1) as input for generating y(t) in tensorflow RNN? I want to pass the output of RNN at time-step T as the input at time-step T+1. ...
Aesthetic asked 24/9, 2016 at 21:14

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I'm having trouble with preparing input data for RNN on Keras. Currently, my training data dimension is: (6752, 600, 13) 6752: number of training data 600: number of time steps 13: size of fea...

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I am using Tensorflow 1.0.0 and Python 3.5. When I try to do: cell = tf.nn.rnn_cell.BasicRNNCell(state_size) I get the following error: AttributeError <ipython-input-25-41a20d8458a7&gt...

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Following the tutorial writing custom layer, I am trying to implement a custom LSTM layer with multiple input tensors. I am providing two vectors input_1 and input_2 as a list [input_1, input_2] as...

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The question is like this one What's the input of each LSTM layer in a stacked LSTM network?, but more into implementing details. For simplicity how about 4 units and 2 units structures like the f...

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I am using Keras for computing a simple sequence classification neural network. I played with the different module and I found that there are two way to create Sequential neural network. The first...

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I'm learning pytorch and I'm wondering what does the padding_idx attribute do in torch.nn.Embedding(n1, d1, padding_idx=0)? I have looked everywhere and couldn't find something I can get. Can you ...
Blubbery asked 12/4, 2020 at 13:44

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I have an input data with the following shape:(5395, 69, 1) Should my input_shape be: (69,1) or (1,69) ? With 69 neurons in the LSTM layer I get in the first input_shape 19'596 parameters to tr...
Boycie asked 11/4, 2020 at 8:12

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I'm trying to solve the following problem: I have time series data from a number of devices. Each device recording is of length 3000. Every datapoint captured has 4 measurements. Therefore, my da...
Slough asked 10/4, 2020 at 22:21

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Can someone please explain this? I know bidirectional LSTMs have a forward and backward pass but what is the advantage of this over a unidirectional LSTM? What is each of them better suited for?

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The CuDNNGRU in TensorFlow 1.0 is really fast. But when I shifted to TensorFlow 2.0 i am unable to find CuDNNGRU. Simple GRU is really slow in TensorFlow 2.0. Is there any way to use CuDNNGRU in Te...

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Does anyone know the default activation function used in the recurrent layers in Keras? https://keras.io/layers/recurrent/ It says the default activation function is linear. But what about the def...

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I know what__call__ is,but what confuses me is that some classes like BasicRNNCell or tf.nn.rnn_cell.MultiRNNCell have this 'call' method instead of _call__ . What is this plain call method? it see...
Christos asked 1/4, 2018 at 21:34

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I would like to understand how an RNN, specifically an LSTM is working with multiple input dimensions using Keras and Tensorflow. I mean the input shape is (batch_size, timesteps, input_dim) where ...

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I'm trying to fill up GRU/LSTM with manually defined parameters in pytorch. I have numpy arrays for parameters with shapes as defined in their documentation (https://pytorch.org/docs/stable/nn.htm...
Borders asked 23/10, 2018 at 9:17

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I have a dataset from 4 temperature sensors measuring different places in/around a building: I'm training a model that takes inputs of shape (96, 4), 96 time steps for the 4 sensors. From this I ...
Somewhat asked 18/12, 2019 at 17:23

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I've come across research publications and Q&A's discussing a need for inspecting RNN weights; some related answers are in the right direction, suggesting get_weights() - but how do I actually ...
Ancylostomiasis asked 10/12, 2019 at 21:55

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Premise 1: Regarding neurons in a RNN layer - it is my understanding that at "each time step, every neuron receives both the input vector x (t) and the output vector from the previous time step y ...

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I know that a LSTM cell has a number of ANNs inside. But when defining the hidden layer for the same problem, I have seen some people using only 1 LSTM cell and others use 2, 3 LSTM cells like th...
Mathers asked 27/11, 2019 at 14:45

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I've come across research publications and Q&A's discussing a need for inspecting RNN gradients per backpropagation through time (BPTT) - i.e., gradient for each timestep. The main use is intro...

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I am building an RNN for classification (there is a softmax layer after the RNN). There are so many options for what to regularize and I am not sure if to just try all of them, would the effect be ...

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I've problems integrating Bert Embedding Layer in a BiLSTM model for word sense disambiguation task, Windows 10 Python 3.6.4 TenorFlow 1.12 Keras 2.2.4 No virtual environments were used PyCharm P...

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I am new to Neural Networks and found the concept of "hidden units" in individual LSTM cells. I understood the concept of having "gates"(input/output/forget etc.), but what are hidden units? I also...

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