baselines/deepq/experiments/custom_cartpole.py
def model(inpt, num_actions, scope, reuse=False):
    """This model takes as input an observation and returns values of all actions."""
    with tf.variable_scope(scope, reuse=reuse):
        out = inpt
        out = layers.fully_connected(out, num_outputs=64, activation_fn=tf.nn.tanh)
        out = layers.fully_connected(out, num_outputs=num_actions, activation_fn=None)
        return out
def model(inpt, num_actions, scope, reuse=False):
    """This model takes as input an observation and returns values of all actions."""
    with tf.variable_scope(scope, reuse=reuse):
        out = inpt
        out = layers.fully_connected(out, num_outputs=64, activation_fn=tf.nn.tanh)
        out = layers.fully_connected(out, num_outputs=num_actions, activation_fn=None)
        return out
def model ( inpt , num_actions , scope , reuse = False ) : with tf . variable_scope ( scope , reuse = reuse ) : out = inpt out = layers . fully_connected ( out , num_outputs = 64 , activation_fn = tf . nn . tanh ) out = layers . fully_connected ( out , num_outputs = num_actions , activation_fn = None ) return out
This model takes as input an observation and returns values of all actions.
This model takes as input an observation and returns values of all actions .