def get_feed_dict(self, inps, trgts=None):
"""Creates the feed_dict that is fed into training or inference network.
Pads inputs and targets.
Returns feed_dict and sequence_length(s) depending on training mode.
"""
if self.mode != 'INFER':
inp_ids, sequence_lengths_1 = summarizer_model_utils.pad_sequences(inps,
self.word2ind[self.pad],
tail=False)
feed = {
self.ids_1: inp_ids,
self.sequence_lengths_1: sequence_lengths_1
}
if trgts is not None:
trgt_ids, sequence_lengths_2 = summarizer_model_utils.pad_sequences(trgts,
self.word2ind[self.pad],
tail=True)
feed[self.ids_2] = trgt_ids
feed[self.sequence_lengths_2] = sequence_lengths_2
return feed, sequence_lengths_1, sequence_lengths_2
else:
inp_ids, sequence_lengths_1 = summarizer_model_utils.pad_sequences(inps,
self.word2ind[self.pad],
tail=False)
feed = {
self.ids_1: inp_ids,
self.sequence_lengths_1: sequence_lengths_1
}
if trgts is not None:
trgt_ids, sequence_lengths_2 = summarizer_model_utils.pad_sequences(trgts,
self.word2ind[self.pad],
tail=True)
feed[self.sequence_lengths_2] = sequence_lengths_2
return feed, sequence_lengths_1, sequence_lengths_2
else:
return feed, sequence_lengths_1
def get_feed_dict(self, inps, trgts=None):
if self.mode != 'INFER':
inp_ids, sequence_lengths_1 = summarizer_model_utils.pad_sequences(
inps, self.word2ind[self.pad], tail=False)
feed = {
self.ids_1: inp_ids,
self.sequence_lengths_1: sequence_lengths_1
}
if trgts is not None:
trgt_ids, sequence_lengths_2 = summarizer_model_utils.pad_sequences(
trgts, self.word2ind[self.pad], tail=True)
feed[self.ids_2] = trgt_ids
feed[self.sequence_lengths_2] = sequence_lengths_2
return feed, sequence_lengths_1, sequence_lengths_2
else:
inp_ids, sequence_lengths_1 = summarizer_model_utils.pad_sequences(
inps, self.word2ind[self.pad], tail=False)
feed = {
self.ids_1: inp_ids,
self.sequence_lengths_1: sequence_lengths_1
}
if trgts is not None:
trgt_ids, sequence_lengths_2 = summarizer_model_utils.pad_sequences(
trgts, self.word2ind[self.pad], tail=True)
feed[self.sequence_lengths_2] = sequence_lengths_2
return feed, sequence_lengths_1, sequence_lengths_2
else:
return feed, sequence_lengths_1