Does `batch_first` really also work on the shape of RNN's hidden vector?

[iamkissg]

Hi, in your code for 12_1_rnn_basics, you mentioned that

#(batch, num_layers * num_directions, hidden_size) for batch_first=True

However, in pytorch's docs, it just said:

batch_first – If True, then the input and output tensors are provided as (batch, seq, feature)

So I got confused which one was right? Then I printed the shape of RNN's hidden vector after executing this line, which turned out to be [1, 3, 2].

So could you please tell me which one is right, and explain why the output is [1, 3, 2]?

Thank you very much.

[hunkim]

It's a bug.

This is correct. #(num_layers * num_directions, batch, hidden_size) for batch_first=True

Can you send me a PR?

On Fri, Dec 29, 2017 at 2:15 AM, Engine Chen [email protected] wrote:

Hi, in your code for 12_1_rnn_basics https://github.com/hunkim/PyTorchZeroToAll/blob/master/12_1_rnn_basics.py#L15, you mentioned that

#(batch, num_layers * num_directions, hidden_size) for batch_first=True

However, in pytorch's docs http://pytorch.org/docs/master/nn.html?highlight=batch_first#rnn, it just said:

batch_first – If True, then the input and output tensors are provided as (batch, seq, feature)

So I got confused which one was right? Then I printed the shape of RNN's hidden vector after executing this line https://github.com/hunkim/PyTorchZeroToAll/blob/59c86cc42b305807789291564501a667689fb812/12_1_rnn_basics.py#L45, which turned out to be [1, 3, 2].

So could you please tell me which one is right, and explain why the output is [1, 3, 2]?

Thank you very much.

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