i use pytorch to build my lstm network, it looks like
class TestNet(torch.nn.Module):
def __init__(self):
super(TestNet, self).__init__()
self.lstm = nn.LSTM(256,
256 // 2, 2,
batch_first=True, bidirectional=True)
return
def forward(self, x):
self.lstm.flatten_parameters()
res = self.lstm(x)
return res
how could i set max_seq_length when call network.add_rnn_v2?
when i set max_seq_length = input_tensor.shape[0], got a error
[TensorRT] ERROR: Parameter check failed at: ../builder/Network.cpp::addRNNCommon::397, condition: input.getDimensions().d[di.seqLen()] == maxSeqLen
i can set weights by calling
layer.set_weights_for_gate
but, how could i set a reverse weights?