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Itaicaspi/episode reset refactoring (#105)
* reordering of the episode reset operation and allowing to store episodes only when they are terminated * reordering of the episode reset operation and allowing to store episodes only when they are terminated * revert tensorflow-gpu to 1.9.0 + bug fix in should_train() * tests readme file and refactoring of policy optimization agent train function * Update README.md * Update README.md * additional policy optimization train function simplifications * Updated the traces after the reordering of the environment reset * docker and jenkins files * updated the traces to the ones from within the docker container * updated traces and added control suite to the docker * updated jenkins file with the intel proxy + updated doom basic a3c test params * updated line breaks in jenkins file * added a missing line break in jenkins file * refining trace tests ignored presets + adding a configurable beta entropy value * switch the order of trace and golden tests in jenkins + fix golden tests processes not killed issue * updated benchmarks for dueling ddqn breakout and pong * allowing dynamic updates to the loss weights + bug fix in episode.update_returns * remove docker and jenkins file
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@@ -59,7 +59,10 @@ class Head(object):
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self.loss = []
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self.loss_type = []
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self.regularizations = []
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self.loss_weight = force_list(loss_weight)
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# self.loss_weight = force_list(loss_weight)
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self.loss_weight = tf.Variable(force_list(loss_weight), trainable=False, collections=[tf.GraphKeys.LOCAL_VARIABLES])
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self.loss_weight_placeholder = tf.placeholder("float")
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self.set_loss_weight = tf.assign(self.loss_weight, self.loss_weight_placeholder)
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self.target = []
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self.importance_weight = []
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self.input = []
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