Comments (2)
hi @hoagy-davis-digges , did you mean you tried the following example and got NaN?
import torch
from sru import SRU, SRUCell
# input has length 20, batch size 32 and dimension 128
x = torch.FloatTensor(20, 32, 128).cuda()
input_size, hidden_size = 128, 128
rnn = SRU(input_size, hidden_size,
num_layers = 2, # number of stacking RNN layers
dropout = 0.0, # dropout applied between RNN layers
bidirectional = False, # bidirectional RNN
layer_norm = False, # apply layer normalization on the output of each layer
highway_bias = -2, # initial bias of highway gate (<= 0)
)
rnn.cuda()
output_states, c_states = rnn(x) # forward pass
from sru.
Exactly
from sru.
Related Issues (20)
- nan in SRU output HOT 10
- batch_first flag HOT 1
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- 运行错误,求大神解决一下,谢谢。
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from sru.