Use the dataset class to initialize model parameters

Changes

1 changed files (+3/-2)

• model.py
  • @@ -2,13 +2,14 @@ import torch.nn as nn
    class Model(nn.Module): - def __init__(self, n_vocab, seq_size, embedding_size, lstm_size, num_layers, dropout): + def __init__(self, dataset, embedding_size, lstm_size, num_layers, dropout): super(Model, self).__init__() - self.seq_size = seq_size + self.seq_size = dataset.seq_size self.lstm_size = lstm_size self.num_layers = num_layers + n_vocab = len(dataset.uniq_words) self.embedding = nn.Embedding(n_vocab, embedding_size) self.lstm = nn.LSTM(