I am a Pytorch beginner and I have read  the Pytorch seq2seq tutorial 26 for machine translation .I have a Data of (video frames , summary ) pairs used in video summarization. I want to adjust the encoder class in the tutorial to make it take sequence of video frames(each frame  is represented as 2048 features extracted from a CNN) instead of a sequence of words as an input. one input sequence is of size(NumOfFrames X 2048).  how do i go about doing that ?
thanks in advance
class EncoderRNN(nn.Module):
    def __init__(self, input_size, hidden_size):
        super(EncoderRNN, self).__init__()
        self.hidden_size = hidden_size

        self.embedding = nn.Embedding(input_size, hidden_size)
        self.gru = nn.GRU(hidden_size, hidden_size)

    def forward(self, input, hidden):
        embedded = self.embedding(input).view(1, 1, -1)
        output = embedded
        output, hidden = self.gru(output, hidden)
        return output, hidden

    def initHidden(self):
        result = Variable(torch.zeros(1, 1, self.hidden_size))
        if use_cuda:
            return result.cuda()
        else:
            return result