as in #6 (comment), the implementation is not same as what the paper shows in equation 3.
i think line50 in model.py should be replaced as follows:
G = tf.expand_dims(G, axis=-1) # bsc1 filter: ngram1 filter_num:1
Att_v = tf.contrib.layers.conv2d(G, num_outputs=1, kernel_size=[opt.ngram,1], padding='SAME',activation_fn=tf.nn.relu) #b * s * c * 1
Att_v = tf.squeeze(Att_v,)
as in #6 (comment), the implementation is not same as what the paper shows in equation 3.
i think line50 in model.py should be replaced as follows:
G = tf.expand_dims(G, axis=-1) # bsc1 filter: ngram1 filter_num:1
Att_v = tf.contrib.layers.conv2d(G, num_outputs=1, kernel_size=[opt.ngram,1], padding='SAME',activation_fn=tf.nn.relu) #b * s * c * 1
Att_v = tf.squeeze(Att_v,)