Environment.py

# Copyright (c) 2016, NVIDIA CORPORATION. All rights reserved.
#
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions
# are met:
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#  * Redistributions in binary form must reproduce the above copyright
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#    documentation and/or other materials provided with the distribution.
#  * Neither the name of NVIDIA CORPORATION nor the names of its
#    contributors may be used to endorse or promote products derived
#    from this software without specific prior written permission.
#
# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS ``AS IS'' AND ANY
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# IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR
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# PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR
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import sys
if sys.version_info >= (3,0):
    from queue import Queue
else:
    from Queue import Queue

import numpy as np
#import scipy.misc as misc

from Config import Config
from GameManager import GameManager

class Environment:
    def __init__(self):
        self.game = GameManager(Config.MAP)
        self.nb_frames = Config.STACKED_FRAMES
        self.frame_q = Queue(maxsize=self.nb_frames)
        self.previous_state = None
        self.current_state = None
        self.total_reward = 0

        self.reset()
    
    def is_running(self):
        return self.game.is_running()
    
    @staticmethod
    def _rgb2gray(rgb):
        return np.dot(rgb[..., :3], [0.299, 0.587, 0.114])

    @staticmethod
    def _preprocess(image):
        #image = Environment._rgb2gray(image)
        #image = misc.imresize(image, [Config.IMAGE_HEIGHT, Config.IMAGE_WIDTH], 'bilinear')
        image = image.astype(np.float32) / 255.
        return image

    def _get_current_state_no_stacking(self):
        if not self.frame_q.full():
            return None  # frame queue is not full yet.
        return np.array(list(self.frame_q.queue)[0])

    def _get_current_state(self):
        if not self.frame_q.full():
            return None  # frame queue is not full yet.
        x_ = [np.array(i) for i in list(self.frame_q.queue)]
        x_ = np.concatenate(x_, axis=2)
        #x_ = np.array(self.frame_q.queue)
        #x_ = np.transpose(x_, [1, 2, 3, 0])  # move channels
        return x_

    def _update_frame_q(self, frame):
        if self.frame_q.full():
            self.frame_q.get()
        self.frame_q.put(frame)

        # the state is no longer just the image, but a concatenation of
        # image and auxiliary inputs. We can't use the same _preprocess()
        #image = Environment._preprocess(frame)
        #self.frame_q.put(image)

    def get_num_actions(self):
        return GameManager.get_num_actions()

    def reset(self):
        self.total_reward = 0
        self.frame_q.queue.clear()
        self.game.reset()
        self._update_frame_q(self.game.get_state())
        self.previous_state = self.current_state = None

    def step(self, action):
        reward, is_running = self.game.step(action)
        self.total_reward += reward
        self.previous_state = self.current_state
        
        if is_running:
          observation = self.game.get_state()
          self._update_frame_q(observation)
          self.current_state = self._get_current_state_no_stacking() 
          
        return reward, is_running