89ef2b21c7ea77929819dec7ba589c13c49bd702,tensorforce/core/models/pg_model.py,PGModel,tf_optimization,#PGModel#Any#Any#Any#Any#Any#Any#Any#,212
Before Change
)
baseline_optimization = self.baseline_optimizer.minimize(**arguments)
optimization = tf.group(optimization, baseline_optimization)
return optimization
After Change
)
baseline_optimization = self.baseline_optimizer.minimize(**arguments)
with tf.control_dependencies(control_inputs=(optimization, baseline_optimization)):
optimization = util.no_operation()
return optimization
In pattern: SUPERPATTERN
Frequency: 3
Non-data size: 5
Instances
Project Name: reinforceio/tensorforce
Commit Name: 89ef2b21c7ea77929819dec7ba589c13c49bd702
Time: 2019-01-26
Author: alexkuhnle@t-online.de
File Name: tensorforce/core/models/pg_model.py
Class Name: PGModel
Method Name: tf_optimization
Project Name: reinforceio/tensorforce
Commit Name: 89ef2b21c7ea77929819dec7ba589c13c49bd702
Time: 2019-01-26
Author: alexkuhnle@t-online.de
File Name: tensorforce/core/models/q_model.py
Class Name: QModel
Method Name: tf_optimization
Project Name: asyml/texar
Commit Name: cf0cb3360a77041187c655891da4ddffbe4b13dd
Time: 2018-11-27
Author: haoranshi97@gmail.com
File Name: texar/core/optimization.py
Class Name: AdamWeightDecayOptimizer
Method Name: apply_gradients