View models.py
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def text_encoding(vocab_len, original_text, nt, nz,cap_length, batch_size): | |
# initialization of pytorch functions | |
# Word embedding here | |
text_embedding = nn.Embedding(batch_size * cap_length + 1, nt).cuda() | |
# RNN layers | |
rnn = nn.LSTM(cap_length + 1, 256, batch_size).cuda() | |
# FC layer |
View gist:c665c71814ce4801f354bba2f7af4cfd
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var powerSets = new Array(); | |
powerSets.push("Z"); | |
var statesInString = states.join(''); | |
statesInString = statesInString.substring(0, numLines); //take the NFA string only | |
string_recursive(powerSets,"",statesInString); | |
alert(powerSets[0]); | |
// for(i = 0; i<powerSetNumber ; i++){ | |
// alert(powerSets[i]); | |
// } |