26de350ba308d7bb88d06ee9a317e36a157e7e4c,onmt/Models.py,RNNDecoderState,__init__,#RNNDecoderState#Any#Any#Any#,465
Before Change
self.hidden = rnnstate
self.input_feed = input_feed
self.coverage = coverage
self.all = self.hidden + (self.input_feed,)
def init_input_feed(self, context, hidden_size):
batch_size = context.size(1)
h_size = (batch_size, hidden_size)
After Change
self.coverage = None
// Init the input feed.
batch_size = context.size(1)
h_size = (batch_size, hidden_size)
self.input_feed = Variable(context.data.new(*h_size).zero_(),
requires_grad=False).unsqueeze(0)
@property
In pattern: SUPERPATTERN
Frequency: 3
Non-data size: 4
Instances
Project Name: OpenNMT/OpenNMT-py
Commit Name: 26de350ba308d7bb88d06ee9a317e36a157e7e4c
Time: 2017-09-10
Author: nasa4836@gmail.com
File Name: onmt/Models.py
Class Name: RNNDecoderState
Method Name: __init__
Project Name: maciejkula/spotlight
Commit Name: bc51dbc0c56f68ed30857755026633f78eef1ae8
Time: 2017-08-20
Author: maciej.kula@gmail.com
File Name: spotlight/layers.py
Class Name: BloomEmbedding
Method Name: forward
Project Name: maciejkula/spotlight
Commit Name: bc51dbc0c56f68ed30857755026633f78eef1ae8
Time: 2017-08-20
Author: maciej.kula@gmail.com
File Name: spotlight/layers.py
Class Name: BloomEmbedding
Method Name: _initialize_caches