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## Motivation
I got the following error when I used GAE with an LSTM-based value network:
```
RuntimeError: Batching rule not implemented for aten::lstm.input. We could not generate a fallback.
…
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Hi everyone,
let's suppose I have a bidirectional LSTM encoder which is manually batched, let's also assume that my input sentences may have different lengths and thus I need to add PAD vectors fo…
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plaidML is extremely slow on bidirectional LSTM: see Keras sample code https://raw.githubusercontent.com/keras-team/keras/master/examples/imdb_bidirectional_lstm.py
On a i7-7700HQ + Nvidia GTX1060 …
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**### Title: Issue with Stock Price Prediction Model**
**Description:**
I am encountering issues with the stock price prediction model implemented in the Jupyter Notebook. The model aims to pred…
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## Issue description
The quantizable LSTM has a different behavior than the regular LSTM module in the bidirectional setting with multiple layers. In particular, the input parameters of the 2nd to …
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### Description
ILayer forwardLayer = keras.layers.LSTM(units: 10, activation: keras.activations.Sigmoid, return_sequences: true, go_backwards: false);
ILayer backwardlayer =…
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So I want to change below Keras bidirectional LSTM layer into Transformer encoder:
`lstmLayer = keras.layers.Bidirectional( keras.layers.CuDNNLSTM(args.rnnSize, return_sequences = True, recurrent_i…
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### 🐛 Describe the bug
Reposting from https://github.com/openxla/iree/issues/15291.
This user was trying to lower the following model:
```
import torch
import torch.nn as nn
from torch.nn.util…
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**Is your feature request related to a problem? Please describe.**
I wrote this up
https://gist.github.com/thistleknot/0edafe7c477290e300e5cac08e7a4984
Can be used with multivariate data to forecas…
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I am trying to implement language model kind of thing using bidirectional LSTM
In unidirectional LSTM, when we prepare data, if sentence is:
"A recurrent neural network is a class of artificial neur…