A question about the nn.Embedding

[zhang-qiang-github]

Thank you for sharing this project code, and I have a question for nn.Embedding.

In this project, the shape of src and trg is (maxLen, batch size). The forward of Encoder is:

    def forward(self, src, hidden=None):
        embedded = self.embed(src)
        outputs, hidden = self.gru(embedded, hidden)
        # sum bidirectional outputs
        outputs = (outputs[:, :, :self.hidden_size] +
                   outputs[:, :, self.hidden_size:])
        return outputs, hidden

When I debug it, the shape of src is (37, 32), in which 32 is the batch size.
However, when I read the explanation of nn.Embedding, the example code shows:

>>> # a batch of 2 samples of 4 indices each
>>> input = torch.LongTensor([[1,2,4,5],[4,3,2,9]])
>>> embedding(input)

Thus, the input of Embedding should be (batch size, maxLen).

This problem make me very confuzed.

Any suggestion is apprciated!