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Support for training on MADRAS env #4

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@buridiaditya buridiaditya commented Jan 4, 2019

Why and What?

  1. Adds new architecture and small fix in a2c/runner.py

obs = env.reset()
def initialize_placeholders(nlstm=128,**kwargs):
return np.zeros((args.num_env or 1, 2*nlstm)), np.zeros((1))
state, dones = initialize_placeholders(**extra_args)
while True:
actions, _, state, _ = model.step(obs,S=state, M=dones)
# actions, _, state, _ = model.step(obs)
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Used in ddpg model play.

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