69d978ed497856d05730c05564597e604713f5c4,beginner_source/chatbot_tutorial.py,,evaluate,#Any#Any#Any#Any#Any#Any#,1266

Before Change

    encoder_outputs, encoder_hidden = encoder(input_batch, lengths)

    // Prepare encoder"s final hidden layer to be first hidden input to the decoder
    decoder_hidden = encoder_hidden[:decoder.n_layers]

    // Decode sentence
    if beam_size == 1:
        return decode(decoder, decoder_hidden, encoder_outputs, voc)
    else:
        return beam_decode(decoder, decoder_hidden, encoder_outputs, voc, beam_size)

After Change

    input_batch = torch.LongTensor(indexes_batch).transpose(0, 1)
    // Use appropriate device
    input_batch = input_batch.to(device)
    lengths = lengths.to(device)
    // Decode sentence with searcher
    tokens, scores = searcher(input_batch, lengths, max_length)
    // indexes -> words
    decoded_words = [voc.index2word[token.item()] for token in tokens]
    return decoded_words


def evaluateInput(encoder, decoder, searcher, voc):
    input_sentence = ""

Instances