StateProcessor.py 文件源码

def __init__(self):

        self.history = StateProcessorSetting.history_length
        self.dims = StateProcessorSetting.observation_dims
        pass

        #get current,prev frame, set by env
        with tf.variable_scope('input', reuse =True):
            self.cur_frame = tf.get_variable('cur_frame',dtype = tf.uint8)
            self.prev_frame = tf.get_variable('prev_frame',dtype = tf.uint8)

        with tf.variable_scope('input'):
            maxOf2 = tf.maximum(tf.to_float(self.cur_frame), tf.to_float(self.prev_frame))
            toGray = tf.expand_dims(tf.image.rgb_to_grayscale(maxOf2), 0)
            resize = tf.image.resize_bilinear(toGray, self.dims, align_corners=None, name='observation')
            self.observe = tf.div(tf.squeeze(resize), 255.0) 

            self.state = tf.get_variable(name = 'state', shape = [self.dims[0],self.dims[1],self.history], dtype = tf.float32,initializer = tf.constant_initializer(0.0),trainable = False)
            self.to_stack = tf.expand_dims(self.observe, 2)
            self.f3, self.f2, self.f1, _ = tf.split(2, self.history, self.state)  # each is 84x84x1
            self.concat = tf.concat(2, [self.to_stack, self.f3, self.f2, self.f1], name='concat')
            self.updateState = self.state.assign(self.concat)