11.05.2017 · I am new to Pytorch and RNN, and don not know how to initialize the trainable parameters of nn.RNN, nn.LSTM, nn.GRU. I would appreciate it if some one could show some example or advice!!! Thanks
In this competition were speed is essential you can not afford to keep determinism by using the regular implementation of GRU and LSTM. PyTorch to the rescue!¶.
21.03.2018 · I recently implemented the VGG16 architecture in Pytorch and trained it on the CIFAR-10 dataset, and I found that just by switching to xavier_uniform initialization for the weights (with biases initialized to 0), rather than using the default initialization, my validation accuracy after 30 epochs of RMSprop increased from 82% to 86%.
Whether He, Xavier, or Lecun intialization is better or any other initializations depends on the overall model's architecture (RNN/LSTM/CNN/FNN etc.), activation functions (ReLU, Sigmoid, Tanh etc.) and more. For example, more advanced initializations we will cover subsequently is orthogonal initialization that works better for RNN/LSTM.
Custom weight initialization in PyTorch, You can define a method to ... Initializing parameters of a multi-layer LSTM, Module that contains an LSTM whose ...
04.08.2017 · I have a nn.Module that contains an LSTM whose number of layers is passed in the initialization. I would like to do Xavier initialization of its weights and setting the bias of the forget gate to 1, to promote learning of long-term dependencies. My problem is how to iterate over all the parameters in order to initialize them. Doing something like for name, param in …
17.01.2018 · My initialization is showed as following: [QQ图片20180117105948] But I want to initialize the weights with Xavier not randn. Does someone know how to do it?
01.03.2021 · Hi, I have started working on Video classification with CNN+LSTM lately and would like some advice. I have 2 folders that should be treated as class and many video files in them. I want to make a well-organised dataloader just like torchvision ImageFolder function, which will take in the videos from the folder and associate it with labels. I have tried manually creating a function that …
LSTM. class torch.nn.LSTM(*args, **kwargs) [source] Applies a multi-layer long short-term memory (LSTM) RNN to an input sequence. For each element in the input sequence, each layer computes the following function: i t = σ ( W i i x t + b i i + W h i h t − 1 + b h i) f t = σ ( W i f x t + b i f + W h f h t − 1 + b h f) g t = tanh ( W i ...
06.08.2020 · Hi, I am a kind of Newb in pytorch 🙂 What I’m trying to do is a time series prediction model. After many trials and errors, I found the Keras code I wanted and tried to apply it to the pytorch. The main point of the Keras model is set to stateful = True, so I also used the hidden state and cell state values of the previous mini-batch without initializing the values of the hidden state …