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add eval_mode to init of rainbow_agent #129

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add eval_mode to init of rainbow_agent #129

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3 changes: 3 additions & 0 deletions dopamine/agents/rainbow/rainbow_agent.py
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Original file line number Diff line number Diff line change
Expand Up @@ -71,6 +71,7 @@ def __init__(self,
epsilon_decay_period=250000,
replay_scheme='prioritized',
tf_device='/cpu:*',
eval_mode=False,
use_staging=True,
optimizer=tf.train.AdamOptimizer(
learning_rate=0.00025, epsilon=0.0003125),
Expand Down Expand Up @@ -110,6 +111,7 @@ def __init__(self,
replay_scheme: str, 'prioritized' or 'uniform', the sampling scheme of the
replay memory.
tf_device: str, Tensorflow device on which the agent's graph is executed.
eval_mode: bool, True for evaluation and False for training.
use_staging: bool, when True use a staging area to prefetch the next
training batch, speeding training up by about 30%.
optimizer: `tf.train.Optimizer`, for training the value function.
Expand Down Expand Up @@ -144,6 +146,7 @@ def __init__(self,
epsilon_eval=epsilon_eval,
epsilon_decay_period=epsilon_decay_period,
tf_device=tf_device,
eval_mode=eval_mode,
use_staging=use_staging,
optimizer=self.optimizer,
summary_writer=summary_writer,
Expand Down