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taolei87 avatar taolei87 commented on June 10, 2024

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.

hoagy-davis-digges avatar hoagy-davis-digges commented on June 10, 2024

Exactly

from sru.

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