Fix combine_bidir function

[mingruimingrui]

This is a pull request to address the issue of tensors being incorrectly combined in combine_bidir.
This issue was raised in #138.

[OneDirection9]

Try to explain the bug more here,

It's used to concatenate the forward and backward hidden tensors from a bidirectional LSTM.

def combine_bidir(outs):
return torch.cat([
torch.cat([outs[2 * i], outs[2 * i + 1]], dim=0).view(1, bsz, self.output_units)
for i in range(self.num_layers)
], dim=0)
Here outs is a tensor of the shape [num_dir * num_layers, bsz, hidden_size].
The goal is to combine the tensor to the form [num_layers, bsz, num_dir * hidden_size].

denote the output of torch.cat([outs[2 * i], outs[2 * i + 1]], dim=0) as A and A has shape of 2 * batch_size, hidden_size

denote the output of res.view(1, bsz, self.output_units) as B and B[i] is equivalent to torch.cat([A[i], A[i + 1]]), (i in range [0, batch_size)). where A[i] and A[i + 1] are different entities from the same batch.