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PyTorch LSTM Output Confusion
Jan. 19, 2022, 6:50 p.m. | /u/alkaway
Deep Learning www.reddit.com
The PyTorch documentation for the LSTM states at the top that o_t is essentially a linear layer with a sigmoid, and exactly how this is computed. Yet, the following snippet of code seems to contradict this information:
import torch import torch.nn as nn x_data = torch.tensor([[[0.1, 0.1]]]) model = nn.LSTM(2, 2, batch_first=True) model._parameters['weight_ih_l0'].data[6:8] = torch.zeros(2, 2) model._parameters['bias_ih_l0'].data[6:8] = torch.zeros(1, 2) model._parameters['bias_hh_l0'].data[6:8] = torch.zeros(1, 2) o_t, _ = model(x_data) print(o_t)
Here, I am setting the relevant weights (i.e. W_io) and biases …
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