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outputs, state = tf.nn.dynamic_rnn(cell, x, dtype=tf.float32) output = outputs[:, -1] preds = tf.sigmoid(output)
虽然gru中两者是等同的
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Vanilla RNN中也是这样的,这里应该是不考虑LSTM的。
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outputs, state = tf.nn.dynamic_rnn(cell, x, dtype=tf.float32)
output = outputs[:, -1]
preds = tf.sigmoid(output)
虽然gru中两者是等同的
The text was updated successfully, but these errors were encountered: