# Path: lib/replay_memory.py
# class ReplayMemory(object):
#     def __init__(self, filepath, max_size, max_size_tolerance):
#     def create_instance_supervised(val=False):
#     def create_instance_reinforced(val=False):
#     def create_instance_by_config(cfg_name):
#     def add_states(self, states, shrink=True):
#     def add_state(self, state, commit=True, shrink=True):
#     def update_state(self, idx, state, commit=True):
#     def get_state_by_id(self, idx):
#     def get_states_by_ids(self, ids):
#     def get_random_states(self, count):
#     def get_states_range(self, pos_start, length):
#     def get_random_state_chain(self, length, from_pos_range=None):
#     def get_random_state_chain_timediff(self, length, max_timediff_ms=500, depth=50):
#     def update_caches(self):
#     def is_above_tolerance(self):
#     def shrink_to_max_size(self, force=False):
#     def commit(self):
#     def close(self):
#     def connect(self):
# 
# Path: lib/util.py
# def template_match(needle, haystack):
# def compress_to_jpg(img):
# def compress_img(img, method):
# def decompress_img(img_compressed):
# def draw_image(img, other_img, x, y, copy=True, raise_if_oob=False):
# def draw_point(img, y, x, size=5, color=[255, 0, 0], alpha=1.0, copy=True):
# def draw_line(img, y1, x1, y2, x2, color=[0, 255, 0], alpha=1.0, thickness=1, clip_result=True, copy=True):
# def draw_direction_circle(img, y, x, r_inner, r_outer, angle_start, angle_end, color_border=[0, 255, 0], color_fill=[0, 200, 0], alpha=1.0):
# def draw_text(img, y, x, text, color=[0, 255, 0], size=25):
# def to_variable(inputs, volatile=False, requires_grad=True):
# def to_variables(inputs, volatile=False, requires_grad=True):
# def to_cuda(inputs, gpu=Config.GPU):
# def to_numpy(var):
# def draw_heatmap_overlay(img, heatmap, alpha=0.5):
# def create_2d_gaussian_old(size, fwhm=3, center=None):
# def create_2d_gaussian(size, sigma):
# FONT_CACHE = dict()


import sys
import os
import train
import numpy as np
import cPickle as pickle
import gzip as gz
import random
from lib import replay_memory
from lib import util
    examples = dict()
    for i in xrange(nb_load):
        rnd_idx = random.randint(memory.id_min+max(train.PREVIOUS_STATES_DISTANCES), memory.id_max-10)
        key = str(rnd_idx)
        if key not in not_in:
            examples[key] = dataset_state_idx_to_example(rnd_idx, memory)

    return examples.values()

class Example(object):
    def __init__(self, state_idx, screenshot_rs_jpg):
        self.state_idx = state_idx
        self.screenshot_rs_jpg = screenshot_rs_jpg
        self.previous_screenshots_rs_jpg = None
        self.previous_multiaction_vec = None
        #self.previous_multiaction_vecs = None
        self.previous_multiaction_vecs_avg = None
        self.multiaction_vec = None
        self.next_multiaction_vec = None
        #self.next_multiaction_vecs = None
        self.next_multiaction_vecs_avg = None
        self.grids = dict()
        self.attributes = dict()

    @property
    def screenshot_rs(self):
        return util.decompress_img(self.screenshot_rs_jpg)

    @property
    def previous_screenshots_rs(self):

# Path: lib/replay_memory.py
# class ReplayMemory(object):
#     def __init__(self, filepath, max_size, max_size_tolerance):
#     def create_instance_supervised(val=False):
#     def create_instance_reinforced(val=False):
#     def create_instance_by_config(cfg_name):
#     def add_states(self, states, shrink=True):
#     def add_state(self, state, commit=True, shrink=True):
#     def update_state(self, idx, state, commit=True):
#     def get_state_by_id(self, idx):
#     def get_states_by_ids(self, ids):
#     def get_random_states(self, count):
#     def get_states_range(self, pos_start, length):
#     def get_random_state_chain(self, length, from_pos_range=None):
#     def get_random_state_chain_timediff(self, length, max_timediff_ms=500, depth=50):
#     def update_caches(self):
#     def is_above_tolerance(self):
#     def shrink_to_max_size(self, force=False):
#     def commit(self):
#     def close(self):
#     def connect(self):
# 
# Path: lib/util.py
# def template_match(needle, haystack):
# def compress_to_jpg(img):
# def compress_img(img, method):
# def decompress_img(img_compressed):
# def draw_image(img, other_img, x, y, copy=True, raise_if_oob=False):
# def draw_point(img, y, x, size=5, color=[255, 0, 0], alpha=1.0, copy=True):
# def draw_line(img, y1, x1, y2, x2, color=[0, 255, 0], alpha=1.0, thickness=1, clip_result=True, copy=True):
# def draw_direction_circle(img, y, x, r_inner, r_outer, angle_start, angle_end, color_border=[0, 255, 0], color_fill=[0, 200, 0], alpha=1.0):
# def draw_text(img, y, x, text, color=[0, 255, 0], size=25):
# def to_variable(inputs, volatile=False, requires_grad=True):
# def to_variables(inputs, volatile=False, requires_grad=True):
# def to_cuda(inputs, gpu=Config.GPU):
# def to_numpy(var):
# def draw_heatmap_overlay(img, heatmap, alpha=0.5):
# def create_2d_gaussian_old(size, fwhm=3, center=None):
# def create_2d_gaussian(size, sigma):
# FONT_CACHE = dict()


# Path: train_semisupervised/dataset.py
import sys
import os
import train
import numpy as np
import cPickle as pickle
import gzip as gz
import random
from lib import replay_memory
from lib import util

    examples = dict()
    for i in xrange(nb_load):
        rnd_idx = random.randint(memory.id_min+max(train.PREVIOUS_STATES_DISTANCES), memory.id_max-10)
        key = str(rnd_idx)
        if key not in not_in:
            examples[key] = dataset_state_idx_to_example(rnd_idx, memory)

    return examples.values()

class Example(object):
    def __init__(self, state_idx, screenshot_rs_jpg):
        self.state_idx = state_idx
        self.screenshot_rs_jpg = screenshot_rs_jpg
        self.previous_screenshots_rs_jpg = None
        self.previous_multiaction_vec = None
        #self.previous_multiaction_vecs = None
        self.previous_multiaction_vecs_avg = None
        self.multiaction_vec = None
        self.next_multiaction_vec = None
        #self.next_multiaction_vecs = None
        self.next_multiaction_vecs_avg = None
        self.grids = dict()
        self.attributes = dict()

    @property
    def screenshot_rs(self):
        return util.decompress_img(self.screenshot_rs_jpg)

    @property
    def previous_screenshots_rs(self):

        return [util.decompress_img(scr) for scr in self.previous_screenshots_rs_jpg]