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I'm in the process of porting some Tensorflow models over to Candle and I have a [bidirectional](https://github.com/keras-team/keras/blob/v2.14.0/keras/layers/rnn/bidirectional.py#L36-L533) LSTM layer…
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According to [a recent paper on LSTM sentiment analysis](https://link.springer.com/chapter/10.1007/978-3-319-39958-4_19), using a bidirectional RNN instead of a regular ("one-way") one might lead to i…
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I tried to use bidirectional lstm with merge_mode='sum' for encoding, but when I try to predict headlines, the model barely generates anything; However, the loss is lower than when I use the simple ls…
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Hi! While it is relatively straightforward to implement higher level constructions like LSTM and GRU it's also nice to have a layer provided by the library like [PyTorch](https://github.com/pytorch/py…
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First of all, thanks for your great tutorial on pytorch! It's a great tip for beginners.
I have a question about the way you use the output of a bidirectional model.
https://github.com/yunjey/pyto…
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This is feedback from when trying to implement gru/lstm on CoreML driven by https://github.com/webmachinelearning/webnn/issues/689.
The biases and weights are stacked together for forward and backwa…
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I found that in the [origin CRNN implementation](https://github.com/bgshih/crnn/blob/master/model/crnn_demo/config.lua), the author used 2 layers of BLSTM, but i only found 2 layers of LSTM in your pr…
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I am using the following to define some input/output nodes for a t2t model:
```python
def load_translation_model(ckpt_dir, config):
d = get_model_hparams(ckpt_dir)
hparams = d['hparams']…
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Hi,
are there any plans to add cuDNN-accelerated versions of LSTM and GRU to the PyTorch backend? Without cuDNN acceleration, the LSTM and GRU are considerably (several times) slower, even when run…
foxik updated
3 months ago
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### Deep Learning Simplified Repository (Proposing new issue)
:red_circle: **Project Title** : Sarcasm Detection
:red_circle: **Aim**: various deep learning models for detecting sarcasm in text dat…