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Missing key(s) in state_dict: "lstm.lstm.weight_ih_l0_reverse", "lstm.lstm.weight_hh_l0_reverse", "lstm.lstm.bias_ih_l0_reverse", "lstm.lstm.bias_hh_l0_reverse", "output_layers.0.weight", "output_laye…
ghost updated
4 years ago
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在Sentiment-Analysis-Chinese-pytorch.py文件的LSTM_attention方法中，
LSTM_attention的forward方法，encoder的LSTM输入如下：
states, hidden = self.encoder(embeddings.permute([0, 1, 2]))#[batch, seq_len, embed_dim]
在LS…
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RuntimeError: Error(s) in loading state_dict for ConvLSTM:
Missing key(s) in state_dict: "lstm.lstm.weight_ih_l0_reverse", "lstm.lstm.weight_hh_l0_reverse", "lstm.lstm.bias_ih_l0_reverse", "l…
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Models envisioned:
- TCN / LSTM / GRU as sequential models;
- Decided to abandon HLSTM, indie LSTM, transformer for various reasons;
- Attention schemes:
- Average pooling
- Plain self-attent…
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AdditiveAttention cannot output weights. `weights, context_vector = AdditiveAttention(name='attention')([state_h, lstm])` should be modified to `context_vector = AdditiveAttention(name='attention')([s…
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运行官网两种test方式都报错，
下载的是youtube8m的frame格式文件，并且已经转成了pkl格式的。
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### 🐛 Describe the bug
When using `torch.nn.functional.scaled_dot_product_attention` with autograd a tensor filled with NaN values are returned after a few backward passes. `Using torch.autograd.s…
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Implements a couple of variants of LSTM. Then let's create some example neural networks with that (e.g., modify the existing MNIST RNN to use LSTM). If not and if no libraries offer a good alternative…
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- CNN
- RNN
- LSTM
- LSTM + Attention
- Transformer
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- PyTorch-Forecasting version: 1.0.0
- PyTorch version: 2.0.1+cpu
- Python version: 3.10
- Operating System: Ubuntu
### Expected behavior
I followed this guide [here](https://towardsdatascien…