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justheuristic/Air Raid with GRUs and A2c algorithm (OpenAI Gym).ipynb

Created May 3, 2016 14:15
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Air Raid with GRUs and A2c algorithm (OpenAI Gym).ipynb
{
"cells": [
{
"cell_type": "code",
"execution_count": 1,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"#experiment name and snapshot folder (used for model persistence)\n",
"experiment_setup_name = \"tutorial.gym.atari.CrazyClimber-v0.cnn\"\n",
"snapshot_path = \".\"\n",
"\n",
"\n",
"#gym game title\n",
"GAME_TITLE = 'AirRaid-v0'\n",
"\n",
"#how many parallel game instances can your machine tolerate\n",
"N_PARALLEL_GAMES = 10\n",
"\n",
"\n",
"#how long is one replay session from a batch\n",
"\n",
"#since we have window-like memory (no recurrent layers), we can use relatively small session weights\n",
"replay_seq_len = 25"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {
"collapsed": false
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"env: THEANO_FLAGS='device=gpu1'\n",
"mkdir: cannot create directory `./agentnet_snapshots/': File exists\r\n"
]
}
],
"source": [
"#this is my machine-specific config. replace if are not me.\n",
"\n",
"#theano device selection\n",
"%env THEANO_FLAGS='device=gpu1'\n",
"\n",
"\n",
"#snapshot path - where neural network snapshots are saved during the main training loop\n",
"!mkdir ./agentnet_snapshots/\n",
"snapshot_path = \"./agentnet_snapshots/\"\n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# This tutorial is a showcase on how to use AgentNet for OpenAI Gym environments\n",
"\n",
"* We take Space Invadets game as an example\n",
"* We train a simple-stupid convolutional network for Q_learning objective\n",
"* We do have a GPU for that, so if you don't, we have a \"linear regression\" mode - just uncomment it :)\n",
"* We train via experience replay using SessionPoolEnvironment, explained below\n",
"* We do NOT use recurrent layers for simplicity\n",
"* We do NOT use \"smart\" experience replay for simplicity\n",
"* We use simple stupid one-step q-learning.. you guessed it, for simplicity\n",
"\n",
"\n",
"## About OpenAI Gym\n",
"\n",
"* Its a recently published platform that basicly allows you to train agents in a wide variety of environments with near-identical interface.\n",
"* This is twice as awesome since now we don't need to write a new wrapper for every game\n",
"* Go check it out!\n",
" * Blog post - https://openai.com/blog/openai-gym-beta/\n",
" * Github - https://github.com/openai/gym\n",
" \n",
" \n",
"### Installing it\n",
" * If nothing changed on their side, to run this, you bacically need to follow their install instructions - \n",
" \n",
"```\n",
"git clone https://github.com/openai/gym.git\n",
"cd gym\n",
"pip install -e .[all]\n",
"```"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {
"collapsed": false
},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"Using gpu device 1: Tesla K40m (CNMeM is disabled, CuDNN 4004)\n"
]
}
],
"source": [
"import numpy as np\n",
"from matplotlib import pyplot as plt\n",
"%matplotlib inline\n",
"\n",
"\n",
"#theano imports\n",
"\n",
"import theano\n",
"import theano.tensor as T\n",
"floatX = theano.config.floatX\n",
"\n",
"import lasagne\n"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"%load_ext autoreload\n",
"%autoreload 2"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Experiment setup\n",
"* Here we basically just load the game"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {
"collapsed": false
},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"[2016-05-01 23:55:06,877] Making new env: AirRaid-v0\n"
]
},
{
"data": {
"text/plain": [
"<matplotlib.image.AxesImage at 0x11dfd410>"
]
},
"execution_count": 5,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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"text/plain": [
"<matplotlib.figure.Figure at 0x11ca7d90>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"import gym\n",
"atari = gym.make(GAME_TITLE)\n",
"atari.reset()\n",
"plt.imshow(atari.render('rgb_array'))"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Game Parameters\n",
"* observation dimensions, actions, etc"
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {
"collapsed": false
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"['NOOP', 'FIRE', 'RIGHT', 'LEFT', 'RIGHTFIRE', 'LEFTFIRE']\n"
]
}
],
"source": [
"n_actions = atari.action_space.n\n",
"observation_shape = (None,)+atari.observation_space.shape\n",
"action_names = atari.get_action_meanings()\n",
"print action_names"
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"del atari"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# agent setup step by step\n",
"* An agent implementation may contain these parts:\n",
" * Observation(s)\n",
" * InputLayers where observed game states (here - images) are sent at each tick \n",
" * Memory layer(s)\n",
" * A dictionary that maps \"New memory layers\" to \"prev memory layers\"\n",
" * Policy layer (e.g. Q-values or probabilities)\n",
" * in this case, a lasagne dense layer based on observation layer\n",
" * Resolver - acton picker layer\n",
" * chooses what action to take given Q-values\n",
" * in this case, the resolver has epsilon-greedy policy\n",
" \n",
"\n",
"\n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"##### Agent observations\n",
"\n",
"* Here you define where observations (game images) appear in the network\n",
"* You can use any lasagne architecture you want. We provide several examples"
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"import lasagne\n",
"\n",
"from lasagne.layers import InputLayer,DropoutLayer,DenseLayer, ExpressionLayer, Conv2DLayer,MaxPool2DLayer\n",
"from lasagne.layers import flatten, dimshuffle"
]
},
{
"cell_type": "code",
"execution_count": 9,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"\n",
"\n",
"#image observation\n",
"observation_layer = lasagne.layers.InputLayer(observation_shape,\n",
" name=\"images input\")\n",
"\n",
"observation_reshape = lasagne.layers.dimshuffle(observation_layer,(0,3,1,2))\n",
"\n",
"\n",
"#conv\n",
"cnn = Conv2DLayer(observation_reshape, num_filters=32,filter_size=(5,5),name='conv0')\n",
"cnn = Conv2DLayer(cnn, num_filters=32,filter_size=(5,5),name='conv1')\n",
"cnn = MaxPool2DLayer(cnn,(5,5))\n",
"cnn = Conv2DLayer(cnn, num_filters=128,filter_size=(5,5),name='conv1')\n",
"cnn = MaxPool2DLayer(cnn,(5,5))\n",
"\n",
"#dense with dropout \n",
"dnn = DenseLayer(cnn,num_units=500,name='dense0')\n",
"dnn = DropoutLayer(dnn,name = \"dropout\", p=0.05) #will get deterministic during evaluation\n",
"dnn = DenseLayer(dnn,num_units=300,name='dense1')\n",
"\n",
"\n",
"inp_nn = dnn"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
" \n",
"### Agent memory states\n",
" * Here you can define arbitrary transitions between \"previous state\" variables and their next states\n",
" * The rules are\n",
" * previous states must be input layers\n",
" * next states must have same shape as previous ones\n",
" * otherwise it can be any lasagne network\n",
" * AgentNet.memory has several useful layers\n",
" \n",
" * During training and evaluation, your states will be updated recurrently\n",
" * next state at t=1 is given as previous state to t=2\n",
" \n",
" * Finally, you have to define a dictionary mapping new state -> previous state\n",
"\n",
"\n",
"Atari game environments are known to have __flickering__ effect where some sprites are shown only on odd frames and others on even ones - that was used to optimize performance at the time.\n",
"\n",
"To compensate for this, we shall use the memory layer called __WindowAugmentation__ which basically maintains a K previous time steps of what it is fed with.\n",
"\n",
"We shall also use a GRUMemoryLayer to represent agent's recurrent memory state. This state is updated on every turn given window state.\n",
"Not that this is __not the same__ as `lasagne.layers.GRULayer` as GRUMemoryLayer only does a single time tick (lasagne version iterates over the whole sequence).\n",
"\n"
]
},
{
"cell_type": "code",
"execution_count": 10,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"\n",
"#memory\n",
"#using simple window-based memory that stores several states\n",
"#the SpaceInvaders environment does not need any more as it is almost fully-observed\n",
"from agentnet.memory import WindowAugmentation, GRUMemoryLayer\n",
"\n",
"\n",
"#our window\n",
"window_size = 3\n",
"prev_window = InputLayer((None,window_size,inp_nn.output_shape[1]),\n",
" name = \"previous window state\")\n",
"\n",
"window = WindowAugmentation(inp_nn,prev_window,name = \"new window state\")\n",
"\n",
"\n",
"\n",
"# first (and so far only) GRU layer\n",
"\n",
"gru0_size = 256\n",
"\n",
"prev_gru0 = InputLayer((None,gru0_size),name=\"previous GRU0 state\")\n",
"\n",
"#neuron-wise maxima of window frames as an input to the GRU\n",
"window_max = ExpressionLayer(window,function=lambda v: v.max(axis=1), \n",
" output_shape=inp_nn.output_shape,\n",
" name = 'window_max')\n",
"\n",
"\n",
"window_max = lasagne.layers.FeaturePoolLayer(window,window_size)\n",
"\n",
"gru0 = GRUMemoryLayer(gru0_size,\n",
" observation_input = window_max,\n",
" prev_state_input = prev_gru0,\n",
" name=\"gru0\"\n",
" )\n",
"\n",
"\n",
"\n",
"#a dictionary that maps next agent memory states to previous ones\n",
"from collections import OrderedDict\n",
"memory_dict = OrderedDict([(window,prev_window),\n",
" (gru0,prev_gru0)])\n",
"\n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"##### Agent policy and action picking\n",
"* Since we are training a deep Q-network, we need it to predict Q-values and take actions.\n",
"* Hence we define a lasagne layer that is used for action output\n",
"\n",
"* To pick actions, we use an epsilon-greedy resolver\n",
" * Note that resolver outputs particular action IDs and not probabilities.\n",
" * These actions are than sent into the environment"
]
},
{
"cell_type": "code",
"execution_count": 11,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"#State values\n",
"state_value_layer = DenseLayer(gru0,\n",
" num_units = 1,\n",
" nonlinearity = lasagne.nonlinearities.linear,\n",
" name = \"Vpredicted\")\n",
"\n",
"\n",
"#a2c probabilities\n",
"\n",
"\n",
"policy_layer_pre_softmax = DenseLayer(gru0,\n",
" num_units = n_actions,\n",
" nonlinearity= None,\n",
" name=\"policy_original\")\n",
"\n",
"\n",
"from lasagne.layers import NonlinearityLayer\n",
"policy_layer = NonlinearityLayer(policy_layer_pre_softmax,\n",
" lasagne.nonlinearities.softmax)\n",
"\n",
"\n",
"#actual action probablilities\n",
"epsilon = theano.shared(np.float32(0.1),\"epsilon\")\n",
"\n",
"\n",
"#add laplacian smoothing\n",
"smooth_policy_layer = NonlinearityLayer(\n",
" policy_layer_pre_softmax,\n",
" lambda v: lasagne.nonlinearities.softmax(v*(1.-epsilon) + epsilon/n_actions)\n",
")\n",
"\n",
"\n",
"\n",
"\n",
"\n",
"#resolver\n",
"\n",
"from agentnet.resolver import ProbablisticResolver\n",
"\n",
"\n",
"resolver = ProbablisticResolver(smooth_policy_layer,assume_normalized=True,name=\"resolver\")\n",
"\n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"##### Finally, agent\n",
"We declare that this network is and MDP agent with such and such inputs, states and outputs"
]
},
{
"cell_type": "code",
"execution_count": 12,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"from agentnet.agent import Agent\n",
"\n",
"\n",
"#all together\n",
"agent = Agent(observation_layer,\n",
" memory_dict,\n",
" [policy_layer,state_value_layer],\n",
" resolver)\n"
]
},
{
"cell_type": "code",
"execution_count": 13,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/plain": [
"[conv0.W,\n",
" conv0.b,\n",
" conv1.W,\n",
" conv1.b,\n",
" conv1.W,\n",
" conv1.b,\n",
" dense0.W,\n",
" dense0.b,\n",
" dense1.W,\n",
" dense1.b,\n",
" gru0.W_in_to_updategate,\n",
" gru0.W_hid_to_updategate,\n",
" gru0.b_updategate,\n",
" gru0.W_in_to_resetgate,\n",
" gru0.W_hid_to_resetgate,\n",
" gru0.b_resetgate,\n",
" gru0.W_in_to_hidden_update,\n",
" gru0.W_hid_to_hidden_update,\n",
" gru0.b_hidden_update,\n",
" policy_original.W,\n",
" policy_original.b,\n",
" Vpredicted.W,\n",
" Vpredicted.b]"
]
},
"execution_count": 13,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"#Since it's a single lasagne network, one can get it's weights, output, etc\n",
"weights = lasagne.layers.get_all_params((resolver,state_value_layer),trainable=True)\n",
"weights"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Agent step function\n",
"* compute action and next state given observation and prev state"
]
},
{
"cell_type": "code",
"execution_count": 14,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"applier_observation = T.tensor4(\"input image\",dtype=floatX)\n",
"\n",
"\n",
"# inputs to all agent memory states (usng lasagne defaults, may use any theano inputs)\n",
"applier_memories = OrderedDict([ (new_st,prev_st.input_var)\n",
" for new_st, prev_st in agent.state_variables.items()\n",
" ])\n",
"\n",
"\n",
"res =agent.get_agent_reaction(applier_memories,\n",
" applier_observation,\n",
" deterministic = True #disable dropout here. Only enable in experience replay\n",
" )\n",
"\n",
"\n",
"applier_actions,applier_new_states,applier_policy = res\n",
"\n",
"applier_fun = theano.function([applier_observation]+applier_memories.values(),\n",
" applier_actions+applier_new_states)\n"
]
},
{
"cell_type": "code",
"execution_count": 15,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"#a nice pythonic interface\n",
"def step(observation, prev_memories = 'zeros',batch_size = N_PARALLEL_GAMES):\n",
" \"\"\" returns actions and new states given observation and prev state\n",
" Prev state in default setup should be [prev window,]\"\"\"\n",
" #default to zeros\n",
" if prev_memories == 'zeros':\n",
" prev_memories = [np.zeros((batch_size,)+tuple(mem.output_shape[1:]),\n",
" dtype=floatX) \n",
" for mem in agent.state_variables]\n",
" \n",
" res = applier_fun(np.array(observation),*prev_memories)\n",
" action = res[0]\n",
" memories = res[1:]\n",
" return action,memories"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Create and manage a pool of atari sessions to play with\n",
"\n",
"* To make training more stable, we shall have an entire batch of game sessions each happening independent of others\n",
"* We define a small container that stores\n",
" * game emulators\n",
" * last agent observations\n",
" * agent memories at last time tick\n",
"* This allows us to instantly continue a session from where it stopped\n",
"\n",
"\n",
"\n",
"* Why several parallel agents help training: http://arxiv.org/pdf/1602.01783v1.pdf"
]
},
{
"cell_type": "code",
"execution_count": 16,
"metadata": {
"collapsed": false
},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"[2016-05-01 23:55:09,259] Making new env: AirRaid-v0\n",
"[2016-05-01 23:55:09,287] Making new env: AirRaid-v0\n",
"[2016-05-01 23:55:09,315] Making new env: AirRaid-v0\n",
"[2016-05-01 23:55:09,343] Making new env: AirRaid-v0\n",
"[2016-05-01 23:55:09,371] Making new env: AirRaid-v0\n",
"[2016-05-01 23:55:09,399] Making new env: AirRaid-v0\n",
"[2016-05-01 23:55:09,426] Making new env: AirRaid-v0\n",
"[2016-05-01 23:55:09,455] Making new env: AirRaid-v0\n",
"[2016-05-01 23:55:09,483] Making new env: AirRaid-v0\n",
"[2016-05-01 23:55:09,510] Making new env: AirRaid-v0\n"
]
}
],
"source": [
"#A whole lot of space invaders\n",
"\n",
"class GamePool:\n",
" def __init__(self,game_title,n_games):\n",
" \"\"\"\n",
" A pool that stores several\n",
" - game states (gym environment)\n",
" - prev_observations - last agent observations\n",
" - prev memory states - last agent hidden states\n",
" \n",
" \"\"\"\n",
" \n",
" \n",
" self.ataries = [gym.make(game_title) for i in range(n_games)]\n",
"\n",
" self.prev_observations = [atari.reset() for atari in self.ataries]\n",
" \n",
" self.prev_memory_states = 'zeros'\n",
"\n",
"pool = GamePool(GAME_TITLE, N_PARALLEL_GAMES)\n"
]
},
{
"cell_type": "code",
"execution_count": 17,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"# a function that creates and records environment interaction sessions\n",
"def interact(pool,n_steps = 100,verbose=False):\n",
" \"\"\"generate interaction sessions with ataries (openAI gym atari environments)\n",
" Sessions will have length n_steps. \n",
" Each time one of games is finished, it is immediately getting reset\"\"\"\n",
" history_log = []\n",
" \n",
" prev_observations = pool.prev_observations \n",
" \n",
" prev_memory_states = pool.prev_memory_states\n",
" \n",
" \n",
" \n",
" for i in range(n_steps):\n",
" \n",
" actions,new_memory_states = step(prev_observations,prev_memory_states)\n",
"\n",
" \n",
" new_observations, cur_rewards, is_done, infos = \\\n",
" zip(*map(\n",
" lambda atari, action: atari.step(action), \n",
" pool.ataries,actions))\n",
" \n",
" new_observations = np.array(new_observations)\n",
" \n",
" for i in range(len(pool.ataries)):\n",
" if is_done[i]:\n",
" new_observations[i] = pool.ataries[i].reset()\n",
" \n",
" for m_i in range(len(new_memory_states)):\n",
" new_memory_states[m_i][i] = 0\n",
" \n",
" if verbose:\n",
" print \"atari\",i,\"reloaded\"\n",
" \n",
" \n",
" #append observation -> action -> reward tuple\n",
" history_log.append((prev_observations,actions,cur_rewards,new_memory_states,is_done,infos))\n",
" \n",
" prev_observations = new_observations\n",
" prev_memory_states = new_memory_states\n",
" \n",
" pool.prev_memory_states = prev_memory_states\n",
" pool.prev_observations = prev_observations\n",
" \n",
" return zip(*history_log)\n",
" "
]
},
{
"cell_type": "code",
"execution_count": 18,
"metadata": {
"collapsed": false
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"[[ 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.]\n",
" [ 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.]\n",
" [ 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.]\n",
" [ 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.]\n",
" [ 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.]\n",
" [ 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.]\n",
" [ 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.]\n",
" [ 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.]\n",
" [ 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.]\n",
" [ 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.]]\n",
"[['LEFTFIRE' 'NOOP' 'NOOP' 'LEFTFIRE' 'LEFT']\n",
" ['NOOP' 'LEFTFIRE' 'LEFT' 'LEFT' 'NOOP']\n",
" ['LEFT' 'LEFT' 'LEFTFIRE' 'LEFTFIRE' 'LEFTFIRE']]\n",
"CPU times: user 5.73 s, sys: 1.02 s, total: 6.75 s\n",
"Wall time: 6.97 s\n"
]
}
],
"source": [
"%%time\n",
"observation_log,action_log,reward_log,_,_,_ = interact(pool,50)\n",
"\n",
"\n",
"print np.array(reward_log)[:10].T\n",
"print np.array(action_names)[np.array(action_log)[:3,:5]]"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# experience replay pool\n",
"\n",
"Since our network exists in a theano graph and OpenAI gym doesn't, we shall train out network via experience replay.\n",
"\n",
"To do that in AgentNet, one can use a SessionPoolEnvironment.\n",
"\n",
"It's simple: you record new sessions using `interact(...)`, and than immediately train on them.\n",
"\n",
"1. Interact with Atari, get play sessions\n",
"2. Store them into session environment\n",
"3. Train on them\n",
"4. Repeat\n"
]
},
{
"cell_type": "code",
"execution_count": 19,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"#Create an environment with all default parameters\n",
"from agentnet.environment import SessionPoolEnvironment\n",
"env = SessionPoolEnvironment(observations = observation_layer,\n",
" actions=resolver,\n",
" agent_memories=[])"
]
},
{
"cell_type": "code",
"execution_count": 20,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"def update_pool(env, pool,n_steps=100):\n",
" \"\"\" a function that creates new sessions and ads them into the pool\n",
" throwing the old ones away entirely for simplicity\"\"\"\n",
"\n",
" \n",
" observation_log,action_log,reward_log,_,is_done_log,_= interact(pool,n_steps=n_steps)\n",
" \n",
" \n",
" #tensor dimensions\n",
" \n",
" # [batch_i, time_i, width, height, rgb]\n",
" observation_tensor = np.array(observation_log).swapaxes(0,1)\n",
" \n",
" # [batch_i,time_i]\n",
" action_tensor = np.array(action_log).swapaxes(0,1)\n",
" \n",
" # [batch_i, time_i]\n",
" reward_tensor = np.array(reward_log).swapaxes(0,1)\n",
"\n",
" # [batch_i, time_i]\n",
" is_alive_tensor = 1- np.array(is_done_log,dtype = 'int8').swapaxes(0,1)\n",
" \n",
" env.load_sessions(observation_tensor,action_tensor,reward_tensor,is_alive_tensor,[])\n",
" \n",
" "
]
},
{
"cell_type": "code",
"execution_count": 21,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"#load first sessions\n",
"update_pool(env,pool,replay_seq_len)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"A more sophisticated way of training is to store a large pool of sessions and train on random batches of them. \n",
"* Why that is expected to be better - http://www.nature.com/nature/journal/v518/n7540/full/nature14236.html\n",
"* Or less proprietary - https://www.cs.toronto.edu/~vmnih/docs/dqn.pdf\n",
"\n",
"To do that, one might make use of\n",
"* ```env.load_sessions(...)``` - load new sessions\n",
"* ```env.get_session_updates(...)``` - does the same thing via theano updates (advanced)\n",
"* ```batch_env = env.sample_session_batch(batch_size, ...)``` - create an experience replay environment that contains batch_size random sessions from env (rerolled each time). Should be used in training instead of env.\n",
"* ```env.select_session_batch(indices)``` does the same thing deterministically.\n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Interacting with environment\n",
"* An agent has a method that produces symbolic environment interaction sessions\n",
"* Such sessions are in sequences of observations, agent memory, actions, q-values,etc\n",
" * one has to pre-define maximum session length.\n",
"\n",
"* SessionPool also stores rewards (Q-learning objective)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Training via experience replay\n",
"\n",
"* We use agent we have created to replay environment interactions inside Theano\n",
"* to than train on the replayed sessions via theano gradient propagation\n",
"* this is essentially basic Lasagne code after the following cell"
]
},
{
"cell_type": "code",
"execution_count": 22,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"#replay interaction sequences of length <= replay_seq_len\n",
"\n",
"_,observation_seq,_,_,(policy_seq,V_seq) = agent.get_sessions(\n",
" env,\n",
" session_length=replay_seq_len,\n",
" batch_size=env.batch_size,\n",
")\n",
"\n",
"V_seq = V_seq[:,:,0]\n",
"\n",
"\n",
"#!!!REWRITE ME!!!\n",
"\n",
"#observation seq are the observation tensor we just loaded\n",
"#qvalues seq are agent's Qvalues obtained via experience replay\n",
"\n",
"\n",
"#The three \"_\"s are\n",
"#first - environment states - which is empty since we are using session pool as our environment\n",
"#second - a dictionary of all agent memory units (RNN, GRU, NTM) - empty as we use none of them\n",
"#last - \"imagined\" actions - actions agent would pick now if he was in that situation \n",
"# - irrelevant since we are replaying and not actually playing the game now\n",
"\n",
"#the actions agent took in the original recorded game\n",
"action_seq = env.actions[0]\n",
"\n",
"#get rewards for all actions\n",
"rewards_seq = env.rewards\n",
"\n",
"#get indicator whether session is still active\n",
"is_alive_seq = env.is_alive\n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Evaluating loss function\n",
"* In this part we are using some basic Reinforcement Learning methods (here - Q-learning) to train\n",
"* AgentNet has plenty of such methods, but we shall use the simple Q_learning for now.\n",
"* Later you can try:\n",
" * SARSA - simpler on-policy algorithms\n",
" * N-step q-learning (requires n_steps parameter)\n",
" * Advantage Actor-Critic (requires state values and probabilities instead of Q-values)\n",
"\n",
"\n",
"* The basic interface is .get_elementwise_objective \n",
" * it returns loss function (here - squared error against reference Q-values) values at each batch and tick\n",
" \n",
"* If you want to do it the hard way instead, try .get_reference_Qvalues and compute errors on ya own\n",
" "
]
},
{
"cell_type": "code",
"execution_count": 23,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"#get reference Qvalues according to Qlearning algorithm\n",
"\n",
"\n",
"from agentnet.learning import a2c_n_step\n",
"\n",
"#gamma - delayed reward coefficient - what fraction of reward is retained if it is obtained one tick later\n",
"gamma = theano.shared(np.float32(0.99),name = 'q_learning_gamma')\n",
"\n",
"\n",
"#IMPORTANT!\n",
"# If you are training on a game that has rewards far outside some [-5,+5]\n",
"# it is a good idea to downscale them to avoid divergence\n",
"scaled_reward_seq = rewards_seq\n",
"#For SpaceInvaders, however, not scaling rewards is at least working\n",
"\n",
"\n",
"elwise_a2c_loss = a2c_n_step.get_elementwise_objective(policy_seq,\n",
" V_seq,\n",
" action_seq,\n",
" rewards_seq,\n",
" is_alive_seq,\n",
" n_steps=10, #using n-step on-policy actor-critic\n",
" gamma_or_gammas=gamma,)\n",
"\n",
"#compute mean over \"alive\" fragments\n",
"a2c_loss = elwise_a2c_loss.sum() / is_alive_seq.sum()"
]
},
{
"cell_type": "code",
"execution_count": 24,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"#regularize network weights\n",
"\n",
"from lasagne.regularization import regularize_network_params, l2\n",
"reg_l2 = regularize_network_params(resolver,l2)*10**-4\n",
"\n",
"\n",
"\n",
"#regularize with entropy, - H(p(s,theta)). \n",
"\n",
"entropy_reg_elwise = - T.sum(policy_seq * T.log(policy_seq),axis=-1)\n",
"\n",
"is_bad = T.or_(T.isinf(entropy_reg_elwise), T.isnan(entropy_reg_elwise))\n",
"\n",
"entropy_reg_elwise = T.switch(is_bad, 0, entropy_reg_elwise)\n",
"\n",
"reg_entropy = T.sum(entropy_reg_elwise*is_alive_seq)/ is_alive_seq.sum() * 0.05\n",
"\n",
"\n",
"reg = reg_l2 + reg_entropy"
]
},
{
"cell_type": "code",
"execution_count": 25,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"loss = a2c_loss + reg"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"#### Compute weight updates"
]
},
{
"cell_type": "code",
"execution_count": 26,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"\n",
"updates = lasagne.updates.adadelta(loss,\n",
" weights,learning_rate=0.01)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"#### Some auxilary evaluation metrics"
]
},
{
"cell_type": "code",
"execution_count": 27,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"mean_session_reward = rewards_seq.sum(axis=1).mean()\n",
"#..."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Compile train and evaluation functions"
]
},
{
"cell_type": "code",
"execution_count": 28,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"train_fun = theano.function([],[loss,mean_session_reward],updates=updates)\n",
"\n",
"evaluation_fun = theano.function([],[loss,a2c_loss,reg,mean_session_reward])"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Session visualization tools\n",
"\n",
"__[warning, this thing basicly tries to track various Qvalues over time]__\n",
"\n",
"__[but it's bulky and stupid, so don't try to understand it if it didn't come naturally]__\n",
"\n",
"\n",
"* this is a completely optional step of visualizing agent's sessions as chains of actions\n",
"* in this function, we display game image and than print strings following pattern\n",
" * [action_name] ([predicted action qvalue]) -> reward | next iteration\n",
" * each block represents agent's decision in a single time step following the shown game state \n",
"\n",
"* plot shows\n",
" * time ticks over X, abstract values over Y\n",
" * bold lines are Qvalues for actions\n",
" * dots on bold lines represent what actions were taken at each moment of time\n",
" * dashed lines are agent's hidden state neurons\n",
" * blue vertical line - session end\n",
" \n",
" \n",
"if you found yourself struggling to make it do what you want for 5 minutes, go write your own tool [and contribute it :)]\n",
"\n",
"At the beginning, agent knows nothing (Jon) and behaves randomly\n"
]
},
{
"cell_type": "code",
"execution_count": 29,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"from agentnet.display.sessions import print_sessions\n",
"get_printables = theano.function([], [\n",
" policy_seq, action_seq,rewards_seq,is_alive_seq\n",
" ])\n",
"\n",
"def display_sessions(with_plots = False,max_n_sessions = 3,update = True):\n",
" \n",
" pictures = [atari.render(\"rgb_array\") for atari in pool.ataries[:max_n_sessions]]\n",
" \n",
" if update:\n",
" #load these pics into environment\n",
" update_pool(env,pool,replay_seq_len)\n",
" \n",
" \n",
" printables = get_printables()\n",
" \n",
" \n",
" for i in range(max_n_sessions):\n",
" plt.imshow(pictures[i])\n",
" plt.show()\n",
" \n",
" policy_log,actions_log,reward_log, is_alive_log = map(lambda v: np.array(v[i:i+1]), printables)\n",
" \n",
"\n",
" print_sessions(policy_log,actions_log,reward_log,\n",
" is_alive_seq = is_alive_log,\n",
" action_names=action_names,\n",
" legend = True, #do not show legend since there's too many labeled objects\n",
" plot_policy = with_plots)"
]
},
{
"cell_type": "code",
"execution_count": 30,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
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"text/plain": [
"<matplotlib.figure.Figure at 0x61dcf510>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"session # 0\n",
" RIGHT(qv = 0.166666671634) -> 0.0 | NOOP(qv = 0.166666671634) -> 0.0 | RIGHTFIRE(qv = 0.166666671634) -> 0.0 | LEFT(qv = 0.166666671634) -> 0.0 | RIGHTFIRE(qv = 0.166666671634) -> 0.0 | LEFT(qv = 0.166666671634) -> 0.0 | RIGHTFIRE(qv = 0.166666671634) -> 0.0 | LEFTFIRE(qv = 0.166666671634) -> 0.0 | RIGHTFIRE(qv = 0.166666671634) -> 0.0 | NOOP(qv = 0.166666671634) -> 0.0 | LEFTFIRE(qv = 0.166666671634) -> 0.0 | RIGHTFIRE(qv = 0.166666671634) -> 0.0 | FIRE(qv = 0.166666671634) -> 0.0 | RIGHT(qv = 0.166666671634) -> 0.0 | LEFT(qv = 0.166666671634) -> 0.0 | NOOP(qv = 0.166666671634) -> 0.0 | LEFT(qv = 0.166666671634) -> 0.0 | NOOP(qv = 0.166666671634) -> 0.0 | FIRE(qv = 0.166666671634) -> 0.0 | LEFTFIRE(qv = 0.166666671634) -> 0.0 | RIGHT(qv = 0.166666671634) -> 0.0 | RIGHT(qv = 0.166666671634) -> 0.0 | RIGHT(qv = 0.166666671634) -> 0.0 | NOOP(qv = 0.166666671634) -> 0.0 | RIGHTFIRE(qv = 0.166666671634) -> 0.0 | reached max session length\n"
]
},
{
"data": {
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7mTNnDlOnTh3cd9tttzF16lR22GEHAFJKRAQ333wzBx98MH19fSxcuJDRo0cP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\ngg==\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x63291b50>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"image/png": 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"text/plain": [
"<matplotlib.figure.Figure at 0x63291d50>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"session # 0\n",
" LEFT(qv = 0.166666671634) -> 0.0 | RIGHT(qv = 0.022886864841) -> 0.0 | NOOP(qv = 0.0746995955706) -> 0.0 | FIRE(qv = 0.40575504303) -> 0.0 | LEFT(qv = 0.218471750617) -> 0.0 | LEFT(qv = 0.155765086412) -> 0.0 | LEFTFIRE(qv = 0.147297471762) -> 0.0 | FIRE(qv = 0.426374852657) -> 0.0 | LEFTFIRE(qv = 0.169384285808) -> 0.0 | RIGHTFIRE(qv = 0.0864844918251) -> 0.0 | LEFTFIRE(qv = 0.197569042444) -> 0.0 | LEFTFIRE(qv = 0.211521908641) -> 0.0 | FIRE(qv = 0.281429290771) -> 0.0 | RIGHTFIRE(qv = 0.0772710219026) -> 0.0 | FIRE(qv = 0.479812294245) -> 0.0 | NOOP(qv = 0.0877387970686) -> 0.0 | LEFTFIRE(qv = 0.0663592219353) -> 0.0 | NOOP(qv = 0.14674565196) -> 0.0 | RIGHTFIRE(qv = 0.0821969434619) -> 0.0 | LEFT(qv = 0.277442365885) -> 0.0 | LEFTFIRE(qv = 0.165054440498) -> 0.0 | NOOP(qv = 0.0789829865098) -> 0.0 | RIGHTFIRE(qv = 0.102720528841) -> 0.0 | LEFTFIRE(qv = 0.172904744744) -> 0.0 | RIGHTFIRE(qv = 0.080992102623) -> 0.0 | reached max session length\n"
]
},
{
"data": {
"image/png": 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OayrJ5/nLxA5d7FBXA8AOfezQpYYONTQA7NDHDnU1AOzQxw5d6ugIkh2QYbdu3cLWrVtR\nv379t+7bvXs36tevrzMwTS9LH4CmxlwXRCIiIiIiIjI9xeCM0YzL5CCwY8eOAIBnz56hQ4cOGDdu\n3Fv7PHjwAMWKFUu6/fjxY7i6ukIIgZiYGLx8+VLneNbW/w3bYmJi4O7unqk2tcvymlNj45pTIiIi\nIiJKzhLXnIaEhKB9+/bYuXMn6tatq7PmdPTo0Th8+DACAwN1Hn/lyhWUL18eCQkJbx0vUUprTg2t\nT5VJ1uecEhEREREREf6bdtu0aVMMGTIEo0aNemuf5s2bIzQ0FHfu3Enx8Sndzs44ODVAHfPq2aGP\nHepqANihjx261NChhgaAHfrYoa4GgB362KFLHR1BsgMyZfjw4Thy5AgOHz6ss71Fixbw9vZGx44d\nceTIEcTFxSE+Ph4HDx6EYqxpyRaIg1MiIiIiIiIj0B9YOjo6olevXpg6depb961fvx7t2rVDz549\nUbBgQbi6umLlypXYsWNHisfLyLktEdecEhERERGRqlnKmlP6D9ecEhERERERkUXi4NQAdcyrZ4c+\ndqirAWCHPnboUkOHGhoAduhjh7oaAHboY4cudXQEyQ4gM+DglIiIiIiIiKTjmlMiIiIiIlI1rjm1\nPFxzSkRERERERBaJg1MD1DGvnh362KGuBoAd+tihSw0damgA2KGPHepqANihjx261NERJDuAzICD\nUyIiIiIiIpKOa06JiIiIiEjVuObU8nDNKREREREREVkkDk4NUMe8enboY4e6GgB26GOHLjV0qKEB\nYIc+dqirAWCHPnboUkdHkOyAdHFxccGePXt0tgUHB8PKygoODg5wcHCAvb09HBwccPjwYQCAl5cX\nbG1tde4LCQlJ+t7e3h4ajQb58uVL2rZ//34ZP57JWcsOICIiIiIiys5KliyJGzduGLxPURTMnTsX\nfn5+Otujo6OTvreyssKZM2fg4uJi0k7ZuOaUiIiIiIhUzVLWnLq4uGDRokVo1qxZ0rbg4GD4+Pik\nODj19vaGj48PevfuneJxNRoNLl++DFdXV6M3mwrXnBIREREREZFF4uDUAHXMq2eHPnaoqwFghz52\n6FJDhxoaAHboY4e6GgB26GOHLnV0BKV7TyUoyChfxnT79m0UKlQIhQoVQsGCBVGoUCG8fPky6f7P\nPvss6b46deoY9dyWhGtOiYiIiIgo2xBeXrIT3pLamlMAmD17dqrTenMKrjklSiet0KKTfydM8Z6C\nKu9UkZ1DRGSRwiLDUNK+JPLnyS87hYjSIITAiJ0jMKLRCBTNV1RqC9eccs0pESWz4cIGbA3figlB\nE2SnEBFZpO2Xt6PO73Xw2bbPZKcQUTqcuHcCMw7NgM96H2iFVnaOxYiNjUVMTEzSV1xcnGoH02rD\nwakB6phXzw59MjuEEJgSMgV/dPgDewL34NS9U9JaAL4m+tihix3qagDYAQAbL2yEz3ofbOi+AVt2\nbMGhW4ektSRSw+uihgaAHfrY8dqac2vwZcMvce/sPfy470epLZbyOacA0LZtW9jZ2SV9TZ48GXfv\n3n3rc07Xr18P4PU7iWlJzz7ZAdecEqXDtsvbEKeNQ7eq3bC36l5MCp6Ev7v9LTuLiMgirDq7CsO3\nDcfWj7fCvYQ7BrgPwNCtQ3G472FoFP6enEiNhBDwD/PH2i5rUTe2LoYeHoompZugSZkmstNU7dq1\naxl+zJ49e9LcJyEhITM5FodrTonSIIRA4z8aY2i9oehetTtexL1A2dll8c/H/6BmsZqy84iIVO2P\nE39g3J5x2N5zO6oVrQbg9d+rHos90Ld2X/SuxQuAEKnRsTvH0H1dd1wacgmKomBr+Fb039wfJwac\ngKOdo9l7LGXNKf2Ha06JTCD4ejAin0eiS+UuAAA7GzuM9BiJScGTJJcREanb3NC5+CboGwT2Ckwa\nmAKv/2HyS5tfMG7PODx59URiIRGlZE3YGnSp3CVpOmmbcm3wUdWP8Mn6T7j+lEyGg1MDZM/vT8QO\nXbI6poRMwZjGY2ClsUrqGOA+AEduH8GJuyekNOX010QfO3SxQ10NQM7smHZgGqYdmIYQ3xBUcKzw\nVod7CXe8X/59TA6ebLYmfWp4XdTQALBDX07vEELA/5w/ulbpqtMxpdkUPHn1BNMPTJdQFSThnGRu\nHJwSpeLQrUO4/OgyelbvqbPd1sYWozxGYWLwRDlhREQqJYTA5ODJWHB8AUL8QuBS0CXFfb9r9h2W\nnV6GsMgwMxYSUVqO3T0Ga401ahStobPdxsoGqzqvwrSD03Dw5kFJdZSdcc0pUSreX/k+2pRtg0F1\nB71138u4lyj7S1kEdA+Aewl3CXVEROoihMCY3WOwJXwLdvrsRLF8xdJ8zKxDs7AlfAu299yeY65G\nSaR2o3aOgrXGGt81/87g/QEXAzB061CcGHAChWwLmaWJa04tD9ecEhnRyXsncezOsRQv1mFrY4vR\nHqO59pSICIBWaDFs2zDsvLoTQb2C0jUwBYBBdQfhdvRtBFwMMHEhEaVH4lV6E6f0GtK+Qnt8WPFD\n+G304yCRjIqDUwNy+joDfTm14/u93+PLhl8ij3WeFDv6uffD8bvHcfTOUbO25dTXJCXs0MUOdTUA\n2b8jQZuA/pv64+ido9j9yW4Utiuc7g4bKxvMaj0Ln2//HK/iX5mkLz0dsqihAWCHvpzccfTOUeSy\nyoXqRaun2jG1xVTcjb6LWYdnmans7QbKfjg4JTLgfOR5BEUEYUCdAanul8c6D8Y0HoOJQRPNE0ZE\npDLx2nh8suETXHl8BTt8dqBAngIZPsa7ru+iVvFaki6yQkTJ+Z/z17lKb0pyWeXC6s6r8f3e7xF6\nO9RMdZTdcc0pkQG9NvRCuULlML7p+DT3jYmPQdlfymJd13WoV7KeGeqIiNQhNiEWPdb1wIu4F/i7\n69+wtbHN9LEinkSgzu91cGLACTjldzJiJRGllxACLrNcENAjQOed09SsC1uHkbtG4lj/Y5n65VR6\ncc2p5eGaUyIjuPr4KjZf2owh9Yaka//c1rn57ikR5Tgv416i46qOEEJgQ7cNWRqYAoBzAWcMqjsI\nI3eNNFIhEWVU6J1Q5LHOg2rvVEt75zc6Ve6ENmXboG9AXw4YATg7O8POzg4ODg4oXrw4fHx8EB0d\nDQDw8/PDN998k7RvXFwcJk+ejIoVK8Le3h5OTk5o27Ytdu7cmbSPi4sL9uzZo3OOpUuXokmTJgAA\ne3t7ODg4wMHBAVZWVrCzs0vatnLlSkyaNAm5cuWCg4ND0vZp06YBALy9vbF48WIAQHBwMKysrODg\n4ID8+fOjQoUK+P3333XOq9Foko6hfyxj4eDUgJy8zsCQnNbx0/6f8Kn7pyn+9s9QR59afXD237M4\nfOuwietSbpCBHbrYoUsNHWpoALJfx7PYZ2i7oi0K5CmA1Z1XI7d1bqN0jG48Gvtv7EfI9RAjVGa+\nw5zU0ACwQ19O7Uj8bFP9Kb1pdUxrOQ1XH1/F3NC5JqxLvUEtFEXBli1bEBUVhVOnTuHMmTOYMmWK\nwX07deqETZs2Yfny5Xj8+DGuXbuGYcOG4Z9//knXeQAgOjoaUVFRiIqKQpkyZbBly5akbT169AAA\ndO/eHVFRUUnbv/rqK4PHLFmyJKKiovD06VPMnDkTgwYNQlhYmM45T58+na5jZRYHp0TJ3I66Df9z\n/hjeYHiGHpfbOjfGNhnLzz0lomzv6aunaLW8FVwKuGDZB8tgY2VjtGPb2dhhWstp+GzrZ0jQJhjt\nuESUNiEE1oStQZfKXTL82DzWeeDfxR8TgyfixN0TJqizLInvIL/zzjto1aoVzp0799Y+u3btwu7d\nuxEQEIA6derA2toa1tbWaNmyJWbMmJHp8xrr3es2bdqgcOHCOoNTYx4/JRycGuDl5SU7AQA79Jmj\nY9qBafCr6YcieYtkuKN3rd4Iiwwzy4dS56TXJD3YoYsd6moAsk/HwxcP0fzP5qhdrDYWtF8AK42V\n0Tu6VO6CAnkKYMHxBZmsNE6HuaihAWCHvpzYceT2EdjZ2KHqO1Uz1VG2UFn80uYXdF3bFVExUSYo\nTLtBbW7duoWtW7eifv36b923e/du1K9fH8WLF8/wcU09QBRCICAgAE+fPkWtWrVMei591mY9G5GK\n/fv8Xyw9tRRnB53N1ONzWeXC2Mav3z3d3nO7keuIiOS6/+w+WixrgTZl2+DHd39M80qemaUoCma3\nmY0Wy1qga5WuKGRbyCTnISJd/uf80bXy21N6M6J71e4IvBaIAZsHYMWHK0z290RagpQgoxzHS3hl\n6nEdO3YEADx79gwdOnTAuHHj3trnwYMHKFbsv8+Dfvz4MVxdXSGEQExMDF6+fKlzPGvr/4ZtMTEx\ncHd3T3fP6tWrsXnzZgghoCgKwsLCdM6d6Pbt2yhUqBBevHiB+Ph4rFy5Em5ubjr71K5dGxqNJulY\nq1evRosWLdLdkha+c2pATl1nkJKc0jHj4Ax0r9odJexLZLrDr5YfLj64iAM3Dxi5Lv0N5sQOXezQ\npYYONTQAlt9xK+oWPJd4onPlzkYZmKbVUb1odXSp3AXfBH6T6n5ZpYbXRQ0NADv05bSOpCm9VQxP\n6c1Ix8zWM3Hu33NYeHyhkeqSKtK9p5fwMspXZm3cuBFRUVEICgpCYGAgjh079tY+hQsXxt27d5Nu\nFyxYEI8fP8axY8cQGxv71vEePXqU9DV3bsbW9nbr1g2PHj3C48eP8ejRI4MDU+D1mtNHjx4hOjoa\nw4YNw/fff//Wu7QnTpzQOZYxB6aAkQaniqK0VhTlgqIolxRFGWXgfk9FUZ4oinL8zVfan89BZEaP\nXz7G78d/x0iPrF0lMpdVLoxrMo5X7iWibOPa42vwXOKJPrX64BvPb8z2Tshk78lYE7YGp++fNsv5\niHKyw7cPI1+ufKhSpEqWj2VrYwv/Lv4Yu2dsjv3zmziga9q0KYYMGYJRo94aHqF58+YIDQ3FnTt3\nUnx8SrdNzcbGBj/++COePn2KZcuWmbUly4NTRVE0AOYAaAWgCoAeiqJUNLBriBCi9psvw5esUomc\nuM4gNTmh45cjv6B9hfZwLuCc5Q7fmr4IfxSO/Tf2GycuEw3mwg5d7NClhg41NACW23Hp4SV4LvHE\nFw2+wAiPEWbtKGRbCBM9J+KzrZ+Z7B9Danhd1NAAsENfTutI6Sq9me2o6FgRP7f8GV3XdMWz2GdG\nKAQscc0pAAwfPhxHjhzB4cO6n+jQokULeHt7o2PHjjhy5Aji4uIQHx+PgwcPSpsOnZyNjQ2+/PJL\nTJ061aznNcY7p/UAhAshrgsh4gCsAtDBwH7yn2UiA6JjovHLkV8w2mO0UY5nY2WD8U3GY0LQBKMc\nj4hIhrP/noX3Um9M9JqIwfUGS2no794fT149wZqwNVLOT5QTaIUWa8PWZuoqvanxqeGDRk6NMPgf\nOX9/yKI/sHR0dESvXr0wderUt+5bv3492rVrh549e6JgwYJwdXXFypUrsWPHjhSPl5FzZ3X/3r17\nIzIyEgEBAUn716hRQ+dzTr/44osMnTNNiZcEzuwXgE4Afk92uyeA2Xr7eAJ4AOAkgC0AKqdyPCFb\nYGCg7AQhBDv0marjp30/iW5ruhm1IzY+VrjMdBEhESFZKMtagzmwQxc7dKmhQw0NQlhex7E7x0TR\n/xUVK06vkNohhBDBEcGi9IzS4nnsc6kdpqKGBiHYoS8ndRy4cUBU/rWySTqexTwTlX+tLP448Uem\nHp8cEJjse/njBUpbSq/Tm+0Gx4LmuiDSMQClhRA18XoK8AYznZcoVS/jXuLnQz9jbJOxRj2ujZUN\nxjcdz889JSKLc/DmQbRe3hrz2s5Dj2o9ZOegaZmmaOTUCFP3mXdqGVFOkXiVXlPImysv/Dv7Y8TO\nEQiLDEv7AZTjGeOjZG4DKJ3sdqk325IIIZ4l+36roihzFUUpJIR4ZOiAvr6+cHZ2BgAUKFAANWvW\nTJrrnni1MFPfTmSu8xm67eXlJfX8yW8nym7Px+iFo+H61BXVi1bP0OMTpba/T3UfjF88HrNyzcKw\n7sOM/nyo4XbiNrX0yL6duE0tPbJvJ26T3ZO8Rcb5vSzo7/OT907i+5vf488P/kSeW3kQdN80r19G\nn4+f3v0SmiQDAAAgAElEQVQJVUdWRcVnFdHj/R5mez5y0u3EbWrpkX07cZtaekx1u6lnU6wJW4Mp\nrlNS/Xmz8nxUeacK/Ar4oe13bXHuf+dgZ2OX5T+vZFlmzpyJkydPJo3vUqOILF5kQFEUKwAXATQH\ncBfAEQA9hBDnk+1TVAhx/8339QD4CyEM1imKIrLaRJQesQmxKDu7LNZ2XYt6JeuZ5BxLTi7B0lNL\nEdgr0CTHJyIylm2Xt+GT9Z/Av4s/vJy9ZOe8ZUrIFJy4dwLruq6TnUKUbRy4eQD9N/XP9Ge8p5cQ\nAj7rfZDHOg8Wts/cR8woCpA4RFAUxexXsKWMS+l1erPd4IJXTVZPKoRIADAEwA4A5wCsEkKcVxRl\ngKIo/d/s1llRlLOKopwAMBNAt6ye15TU8tsZdugydseyU8tQ0bFihgemGenoWb0nbj69iaCI9D/G\n2A2mxA5d7NClhg41NADq79hwYQM+Wf8JNnbfaJaBaWaej68afYUTd09g19VdUjuMTQ0NADv05ZSO\nxKv0mrpDURTMazsPe2/sxV+n/8rkUbLWQJYhy4NTABBCbBNCVBBClBNC/Phm23whxO9vvv9VCFFV\nCFFLCNFICHE49SMSmVa8Nh4/7v8R45ua9iN3rTXW+Lrp1/zcUyJSrVVnV+HTzZ9i68db0dCpoeyc\nFOWxzoOfW/2MYduGIS4hTnYOkcXTCi3WhK0x+lV6U2Kf2x7+nf0xfPtwXHxw0SznJMuT5Wm9xsZp\nvWQOK86swLyj87DXb6/JzxWvjUflXytjfrv58HbxNvn5iIjS648Tf2B84Hhs77kdVd+pKjsnTUII\ntFreCu3Kt8Nn9T+TnUNk0fbf2I9Pt3yKMwPPmPW8vx39DfOOzsOhPodga2Ob7sdxWq/lkTKtl8jS\naIUW3+39DuObmPZd00SJ755OCJrAv0iJSDV+PfIrJgRNQGCvQIsYmAKv/0Ezq/UsfBvyLSKfR8rO\nIbJoprxKb2oGuA9ARceK+GK7kT8fk7IFDk4NyCnrDNIru3VsvLARtta2aOnW0mwdPar1wP3n97Hn\n2p5MndMYDabADl3s0KWGDjU0AOrrmHZgGqYfnI5g32CUL1xeWkdmVCpSCT7VfTBuzzipHcaihgaA\nHfqye4dWaLH2/Fp0qZK+Kb3G7FAUBQveX4CdV3fC/5x/Bh5pvAZSLw5OKUcRQmDK3ikY33Q8FMXg\nbAKT4LunRCRbZGQkzp8/j1H/jMLC4wsR4hcCl4IusrMy5RvPb7Dp0iYcu3NMdgqRRTpw8wAK2xZG\nRceKUs7vkNsB/l38MeSfIbjy6IqUBlIpIYSqvl4nEZnG1vCtosqvVUSCNsHs545PiBcVfqkgdl7Z\nafZzE1HOtmLFKpHHtqDI1baoUAZZiXl//iY7KcsWHlsoGi5sKLRarewUIosz9J+h4tvgb2VniNmH\nZova82uLV3Gv0tw3+RBBzeMFZ2dnsXv3bp1tQUFBQqPRCHt7e2Fvby/y5csn7O3txaFDh4QQQnh6\neoo8efLo3BccHJz0fb58+YSiKCJv3rxJ2/bt2yd8fX1Frly5dB7n7+//VseSJUuElZWVsLe3F/nz\n5xfVq1cXf//9d1JfRESEUBTlrb7EY2VWSq/Tm+0Gx4J855RyDCEEpoRMwbgm46BRzP+/vpXGCt94\nfsN3T4nIrCIjI9GnzyC8qt4PsSVLQvyxB18MGIvISMtes+lXyw9x2jj8dSazH0tBlDNphRZrw9aa\n7Sq9qRlSbwicCzhjxM4RslNMrmTJkoiKikJUVBSio6MRFRWF+vXrA3g91Xnu3Lk69zVt2jTp++jo\naCiKgjNnziRt8/DwAACMGjVK53Fduhh+XRs1aoSoqCg8efIEgwcPxkcffYTHjx8n3a8oCp4+fZqu\nY5kSB6cGZPd1BhmVXTpCrofg/vP76fo8L1N1dKvSDY9fPsbOqzulNRgTO3SxQ5caOtTQAMjtiIiI\ngE3uMkDDVcDaAcDLprCxKYOIiAhpTcZ4PjSKBrNbz8boXaMRHRMtrSOr1NAAsENfdu7Yf2M/iuQt\nggqOFaR2AK8HRIvaL8KmS5uw/vz6tCpM0qAWab1xIf6bZZplPj4+iImJwZUrulOq1fDmCQenlGNM\n2TsFYxqPgZXGSloD3z0lInNzdnbGK6dwILog8Kg8gNOIi7sOZ2dn2WlZ1tCpIZq7Nsf3e7+XnUJk\nMWRdpTclBfIUwKpOqzBg8wBEPImQnZPtJSQkYPHixShQoAAqVND9BYUa/m3KzzmlHOHwrcPourYr\nwoeGI5dVLqktCdoEVJtXDTNazUCrsq2kthBRzlDtf9VxcfVV2IaXR1zcdSxaNBc9enSTnWUUd6Pv\notq8ajjY5yDKFS4nO4dI1RK0CSg1o5S0K3Wn5ueDP2P1udXY67fX4L/VMvI5p0FBxrnopZdXxsck\nLi4uWLRoEZo1a5a0LTg4GM2aNUP+/PkBvB4EKoqC27dvw9bWFt7e3ggNDUWuXLkghICbmxuOHj2q\nc1yNRoPLly/D1dU1aZufnx9WrVoFW1tbCCFgY2ODf//9962OpUuXom/fvrC3t8ezZ89gY2ODHTt2\nJE0Nvn79OlxcXFCgQAGdvoMHD741gM2IzHzOqXWmz0ZkQb7b+x1GNhopfWAKvH73dILnBEwImoCW\nbi3NetVgIsp5Ljy4gEjlX1zdfAF3b96Fs7MzihQpIjvLaIrbF8dIj5H4YscX2NRjk+wcIlXbf3M/\niuYtqrqBKQB83uBzBEYEYsyuMZjeanqWjpWZQaWplSxZEjdu3Ejx/tmzZ6N3794ZPu6IESMwefLk\nNPdr2LAhQkJC8OLFC/Tp0wdTp05FQEBA0v2KouDhw4fS/13Kab0GZOd1Bplh6R2n7p3C0TtH0btW\nxv/AG7MjuS5VuuBZ7DNsu7xNWoMxsEMXO3SpoUMNDYDcjrmhc9Gvdj+UKlYKz58/V8XA1NjPx7D6\nw3DxwUX8E/6P1I7MUEMDwA592bXD/5x/pq69YY7nQ1EULOmwBGvPr8Wmi4Z+0WT6hpzAzs4Oc+fO\nRXBwMEJCQnTuU8PsVQ5OKdv7ft/3+KLhF7C1sZWdkkSjaJLePVXDXwRElD1Fx0Rj+enlGFBngOwU\nk8ptnRszW8/E8G3DEZsQKzuHSJUStAmquUpvSgrbFcbKTivRd1Nf3Hx6U3ZOpsXGxiImJibpKy4u\nTlX/3itYsCD69++PH374IWmbMS+4lBVcc0rZ2oUHF9D0j6a4Ouwq8uXKJztHh1ZoUeO3Gvix+Y9o\nW76t7Bwiyobmhs7Fnmt7sLbrWtkpZtFuRTt4lvHECI/s/7EURBkVFBGEz7d/jhMDTshOSdPUfVMR\ncCkAQb2CYGNlAyBja05lcnFxeWv6roeHBw4cOAA7OzsA/63pXLp0KT744AM0a9YMPXv2THVar5WV\nFcLDw3XWnPbu3RulSpUyOK3X1dUVCxcuTFpzumjRIp13Sm/fvo2yZcvi8OHDyJ8/P1xdXZE3b16d\nvsmTJ2P48OGZfi4ys+aUg1MVS/wfgzLPd4Mv3Aq64WvPr2WnGLQ2bC2m7p+KI32P8LUmIqMSQqDK\n3CqY23YuvJy9ZOeYRfjDcDRc1BBnBp5BcfvisnOIVGXwlsEo5VAKY5qMkZ2SJq3Qou2KtqhZtCZ+\nePf1u3uWMjil/2RmcMppvQaoYZ3BgmMLUHp4aYRFhslOUcXzAWS849rja9h0aROG1h8qtSM1H1b6\nELEJsdgSvkVaQ1awQxc7dKmhQw0NgJyOoIggaBQNPMt4Su0wxFQd5QqXQ59afTBmd/r+8a2G50MN\nDQA79GW3jgRtAtadX4cuVTI3pdfcz4dG0eDPjn9i+Znlya7PYd4GkoODUxW6+vgqxuweg5auLeG1\nxAubL22WnWSRftr/Ewa4D0CBPAVkp6Qoce3pxKCJ/A0gERnVnNA5GFJvSI6blTG+6XjsvLoTh24d\nkp1CpBoh10NQ0qEkyhYqKzsl3YrkLYK/PvwLfhv9cDvqdtL2Cw8uSKwiU+O0XpXRCi28l3qjffn2\n+LLRlzh48yA6r+mMYfWHYUSjETnuHxmZdTvqNqrNq4aLQy6iSF75V6ZMjVZoUXt+bUz2noz2FdrL\nziGibODG0xuoNb8Wrg+/rrr19uaw7NQyzD4yG4f7HoZG4e/hiQZtGYTS+UtjdOPRslMybErIFOy8\nuhMhfsFYe24dPt3yKR6MfMBf6lsATuvNBn45/AsStAkY3uD14uOGTg1xqM8hrD63Gr029MKr+FeS\nCy3D9IPT0atGL9UPTAG+e0pExjf/6Hz0rNYzRw5MAeDj6h/DRmODJSeXyE4hki5eG/96Sq+Kr9Kb\nmjGNx8BG8/qiSF/u+BJbP94quYhMiYNTA2StM7j08BK+DfkWSzougZXGKqnDKb8T9vrtRUxCDDyX\neOJu9F2zdlnauovI55FYcnIJvmr0ldSOjOhYsSMEBAIuBqS9s4kaMoMdutihSw0damgAzNsREx+D\nhScWYlDdQVI7UmPqDo2iwew2szFuzzg8ffVUWkd6qKEBYIe+7NQRcj0ETg5OcCvkJrUjs6w0Vlj+\n4XIAQTja/yjqlKgjrYVMj4NTlUjQJsB3gy8meE4wuB7AzsYOqzqtwvvl30e9hfVw9M5RCZWWYeah\nmehWpRtKOpSUnZJuiqJgoudETAzmu6dElDVrwtagZrGaqOBYQXaKVHVK1EG7cu0wOfjtj1ggyknW\nnFtjse+aJiqWrxgAwNHOUXIJmRrXnKrE//b/D1svb8WuT3aluT7m7/N/Y8DmAfilzS/oXrW7mQot\nw5NXT+A22w1H+x2FS0EX2TkZIoRAnQV1ML7JeHxQ6QPZOURkoRosbICxTcZyDTuAf5//iypzqyDE\nNwSVilSSnUNkdvHaeJSYXgKH+h6Ca0HXtB+gYsk/SsbZ2RnXr1+XG0RpKlOmDCIiIt7antqaU2tT\nR1HawiLD8NOBnxDaLzRdF274sNKHcCvoho6rO+LM/TP4ttm3vODDG3OOzMH75d+3uIEp8N+7p+MD\nx6NDxQ58TYkow47eOYp7z+6hbbm2slNU4Z2872Bck3EYvn04tn28jRcVpBwnOCIYZQqUsfiBqT5D\nAx7KHvivXwPMOa8+XhuPXht6YYr3FDgXcE53R41iNXC472GE3AjBh6s/RHRMtMkaLWXdxbPYZ5h9\neDbGNDbth0ub8vloV74dbDQ22HBhg7SGjGCHLnboUkOHGhoA83X8GvorBtUdBCuNldSOtJizY3Dd\nwbj59KbBNf1qeD7U0ACwQ1926VgTZpwpvep4PoJkB5AZcHAq2dR9U1HIthD6u/fP8GPfyfsOdn+y\nG452jvBY7IFrj6+ZoNByzD86H94u3ha9zkpRFEz0moiJQROhFVrZOURkQR68eIANFzagT60+slNU\nxcbKBrNaz8Ln2z/nFe8pR4nXxuPv839b/HpTylm45lSiU/dOocWyFjjW/xic8jtl+jhCCPxy5Bf8\nsO8HrOq0Cp7OnkastAwv417CbbYbtn68FTWK1ZCdkyVCCNRfWB8jPUaic+XOsnOIyEJM3TcVFx5e\nwB8d/pCdokofrv4Q7sXdMa7pONkpRGax6+oujN09Fkf6HZGdYhTJ15ySZePnnKpQbEIsem3ohZ9a\n/JSlgSnw+gX+rP5n+LPjn+i6tit+P/a7kSotx+ITi1GnRB2LH5gC/717Oil4Et89JaJ0SdAmYN7R\neRhSd4jsFNWa3nI6ZhyagVtRt2SnEJmF/zl/vmtKFoeDUwPMMa/+u5Dv4JTfCb1q9DJaRwu3Ftjr\ntxc/H/wZQ/8ZinhtfBYrM9dhKil1xCbE4qcDP2FcE/P8Ntwcz0ebsm1gZ2OHdWHrpDWkBzt0sUOX\nGjrU0ACYvmNL+BYUty8O9xLuUjvSS0aHS0EXDKwzECN3jpTaoU8NDQA79Fl6R7w2HusvrEeXKsYZ\nnKrj+QiSHUBmwMGpBMfuHMNvx37D7+1+N/qVA8sXLo9DfQ/h8uPLaL28NR69fGTU46vR8tPLUb5w\nedQvVV92itEkXrmX754SUXrMOTKH75qmw+jGo7Hvxj7svb5XdgqRSQVeC4RrQde3LrZJpHZcc2pm\nMfExcP/dHWObjMVH1T4y2XkStAkYuXMkAi4FIKB7QLb9fLcEbQIq/loRC95fAC9nL9k5RiWEQMNF\nDfF5g8/RrWo32TlEpFIXHlyA1xIvXB9+Hbmtc8vOUb3VZ1fjh30/4Fj/Yyle1ZjI0vUL6IcKjhXw\nVaOvZKcYDdecZh9cc6oiE4ImoIJjBfSo2sOk57HSWGF6q+kY23gsPJd44p/wf0x6Pln8z/mjaN6i\n8CyT/S4CpSgKJnlNwqTgSUjQJsjOeUtkZCRCQ0MRGRkpO4UoR5sbOhd9a/flwDSdulbpivx58mPB\n8QWyU4hMIi4hDhsubuB6U7JIHJwaYKp59YduHcKSk0swr+28dE3nNUaHXy0/bOi+AX0D+mLagWnI\nzLvS6lhn8HaHVmjx/b7vMb7peLN+sLo5n4+Wbi1RIE8B+J/zl9ZgyMqVq1GmTEV4e3+MMmUqYuXK\n1VJ7ZD8fidihSw0damgATNcRHRONv878hQHuA6R2ZJTMDkVRMLv1bEwImoDNOzZL60jE10QXO3Rl\npiMwIhBuBd1QpkAZqR3GFyQ7gMyAg1MzeRn3Er4bfDHnvTl4J+87Zj13I6dGONT3EP468xd8N/pm\nm895C7gYgNxWudHKrZXsFJNJvHLv5JDJqnn3NDIyEr37DcTLQrPwPO9QvHwZiD59BvEdVCIJlp9e\nDm9n7yxf9T2nqVGsBpq7NMe2y9tkpxAZnf85f3St0lV2BlGmcM2pmXyx/QvcfXYXKzutlNbwPPY5\nfDf64lbULazvth7F8hWT1pJVQgjUW1gPYxuPxQeVPpCdY1JCCDT+ozEG1x1s0nXKqXnw4gEO3DyA\nAzcPYFvYNpy6fwZ4VBXIfxOYfhsOdh7YtWs+6tatK6WPKCcSQqDqvKqY02YOvF28ZedYnL3X96Lf\npn44P/i8WWffEJlSXEIcik8vjuMDjqN0/tKyc4yKa06zD645lWzv9b1YdXYV5rSZI7Ujb668WN15\nNVq7tUa9BfVw/O5xqT1ZsePKDryMe4kOFTvITjG5xLWnk4PN8+6pVmgRFhmGhccXovfG3qgwpwLc\nZrthzpE5sLW2xbjG45Dn1/zAb8uAO+5AhTmIi7sOZ2dnk7cR0X+CIoIAINtdDM5cGpduDGuNNQIj\nAmWnEBnNnmt7UK5wuWw3MKWcg4NTA4w5r/557HP4bfTDb+1+Q2G7wtI6EmkUDSZ4TcCMVjPQanmr\nt9YymqsjM5J3fLf3O4xtMhYaxfz/C8t4Ppq7NEeRvEWw8uxKoze8iHuBoIggfL/3e7Rd0RaOPzmi\n3Yp2CL4ejLol6mJNlzV4NPIRdvjswASvCehSuwsWz5sHW1tv2Bw9DU2tcVi0aC6KFClitKaMUuP/\nozKxQ10NgGk6fg39FUPqDsnQu37Z+fnIKEVR0FxpjnlH50ntUMNzAbBDn6V2+J/zR9fKxp/Sq47n\nI0h2AJmBteyA7G7UrlHwKO2B9hXay07R0alyJ7gVckOHVR1w9t+zmOg1UcpALzNCrofgTvSdHLWe\nIvHd04FbBqJ71e5ZOtatqFtJU3T339yPsMgwVHunGjycPNC7Zm8sfH8hitsXT/UYPXp0w7vvNsNf\n/n9hQtQEvNu+WZaaiChjbj69icCIQCzpuER2ikVr6dYSPU/0xN3ou2n+vUekdnEJcdh4cSMmek2U\nnUKUaVxzakK7r+6G70ZfnBl4BgXyFJCdY9D9Z/fxof+HKJq3KP784E/ky5VPdlKaWi5riW5VuqFP\n7T6yU8xKCAHPJZ7oV7sffGr4pOsx8dp4nL5/OmkgeuDmAbyIe4FGTo3QqFQjeJT2gHtxd9ja2Ga6\nq+ffPVG/ZH0MrT8008cgoowZv2c8omKiMLvNbNkpFm/ApgEo5VAKX3t+LTuFKEu2Xd6GycGTcaDP\nAdkpJsE1p9lHamtOOTg1kaiYKFSfVx2/tfsNrcu2lp2Tqpj4GAzaMghH7x5FQPcAo1563NiO3D6C\nzv6dcfmzy8hllUt2jtkFXgtE/839cX7weVhr3p748OTVExy6dQj7b+zHgVsHEHo7FE75nZIGoo2c\nGqFcoXJGvfjH9svb8XXg1zjS74jRjklEKYuJj0GZmWUQ5BuEio4VZedYvJP3TuL9le/j2rBrBv9e\nJbIUvTf2RvWi1TG8wXDZKSbBwWn2wQsiZZAx5tV/teMrtHBtkaWBqbnm9+e2zo2F7RfCr6YfGixq\ngH039knpSEtQUBC+2/sdRnqMlDowlfl8eLt4o6R9SYxfPB5CCFx+dBl/nvoTAzYNQLV51eA0wwlT\n90+FVmjxZcMvETE8AucGncOC9gvgW9MX5QuXN+rANCgoCM1dm+Nm1E1cfHDRaMfNTIcasEOXGjrU\n0AAYt2Nt2FpUL1o9UwPT7Ph8ZEVQUBB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Ll4nIz9dohpqqTY51/uvUtnxMQzwf6lSTHGZG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\niwttajix03zv+WwN3EphaWGd8wuaVa4sZ/fl3bitd+OP6D/4Y9If7H5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2lsTiYr5xdZU7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\nKNJ5Dd6PdfrHGUC1AAAAAElFTkSuQmCC\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x64bab5d0>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"image/png": 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"text/plain": [
"<matplotlib.figure.Figure at 0x64bab790>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"session # 0\n",
" FIRE(qv = 0.166666671634) -> 0.0 | LEFT(qv = 0.375663101673) -> 0.0 | LEFTFIRE(qv = 0.202661842108) -> 0.0 | LEFT(qv = 0.198666974902) -> 0.0 | RIGHT(qv = 0.0369005724788) -> 0.0 | FIRE(qv = 0.382411718369) -> 0.0 | RIGHTFIRE(qv = 0.150206327438) -> 0.0 | FIRE(qv = 0.346163749695) -> 0.0 | LEFTFIRE(qv = 0.115187391639) -> 0.0 | FIRE(qv = 0.520020127296) -> 0.0 | FIRE(qv = 0.601854205132) -> 0.0 | FIRE(qv = 0.704921543598) -> 0.0 | FIRE(qv = 0.422966480255) -> 0.0 | RIGHT(qv = 0.0161071363837) -> 0.0 | FIRE(qv = 0.517137408257) -> 0.0 | LEFTFIRE(qv = 0.0887287259102) -> 0.0 | LEFT(qv = 0.0640554428101) -> 0.0 | FIRE(qv = 0.567632138729) -> 0.0 | FIRE(qv = 0.578736007214) -> 0.0 | NOOP(qv = 0.0907421857119) -> 0.0 | LEFT(qv = 0.135580763221) -> 0.0 | LEFT(qv = 0.173604145646) -> 0.0 | RIGHT(qv = 0.0184110067785) -> 0.0 | FIRE(qv = 0.417954862118) -> 0.0 | LEFTFIRE(qv = 0.166808322072) -> 0.0 | reached max session length\n"
]
},
{
"data": {
"image/png": 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VeLnGy26uExGR7ErLer2PlvWKiIjb7I7bzVMznmJyxOQMD6YArSq1Imp3lBvL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\nIuf+P64FynZ69/pLAAAAAElFTkSuQmCC\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x7f94f8019d90>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"#visualize untrained network performance (which is mostly random)\n",
"display_sessions(with_plots=True)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Training loop"
]
},
{
"cell_type": "code",
"execution_count": 31,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"#tools for model persistence (in progress now. Requires unique names)\n",
"from agentnet.utils.persistence import save,load\n",
"import os"
]
},
{
"cell_type": "code",
"execution_count": 32,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"from agentnet.display import Metrics\n",
"score_log = Metrics()"
]
},
{
"cell_type": "code",
"execution_count": 33,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"#starting epoch\n",
"epoch_counter = 1\n",
"#moving average estimation\n",
"alpha = 0.1\n",
"ma_reward_current = 0.\n",
"ma_reward_greedy = 0."
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": false
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"epoch 1000,loss 170.02169, epsilon 0.35164, rewards: ( e-greedy 17.45292, greedy 18.58063) \n",
"rec 169.405 reg 0.616\n",
"Learning curves:\n"
]
},
{
"data": {
"image/png": 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VnAb0FpECwCfAdMuFpByJ9hY4L82dc9P8OS/NnWMZPx5y5oTmzW0/9vPeySon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\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x66861dd0>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Random session examples\n"
]
},
{
"data": {
"image/png": 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"text/plain": [
"<matplotlib.figure.Figure at 0x660d9350>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"session # 0\n",
" NOOP(qv = 0.0815399736166) -> 0.0 | RIGHT(qv = 0.0259489417076) -> 0.0 | FIRE(qv = 0.814169645309) -> 0.0 | FIRE(qv = 0.814848542213) -> 0.0 | LEFTFIRE(qv = 0.0806952640414) -> 0.0 | LEFTFIRE(qv = 0.107709437609) -> 0.0 | FIRE(qv = 0.434188514948) -> 0.0 | LEFT(qv = 0.0557719431818) -> 0.0 | NOOP(qv = 0.124162815511) -> 0.0 | FIRE(qv = 0.430110901594) -> 0.0 | LEFTFIRE(qv = 0.125841468573) -> 0.0 | NOOP(qv = 0.134835496545) -> 0.0 | LEFTFIRE(qv = 0.110327087343) -> 0.0 | FIRE(qv = 0.46695959568) -> 0.0 | FIRE(qv = 0.454986095428) -> 100.0 | FIRE(qv = 0.446862727404) -> 0.0 | FIRE(qv = 0.73978716135) -> 0.0 | RIGHT(qv = 0.0405135266483) -> 0.0 | FIRE(qv = 0.775676250458) -> 0.0 | LEFTFIRE(qv = 0.0471654683352) -> 0.0 | FIRE(qv = 0.789975464344) -> 0.0 | FIRE(qv = 0.784973919392) -> 0.0 | FIRE(qv = 0.758663415909) -> 0.0 | NOOP(qv = 0.0716901496053) -> 0.0 | LEFT(qv = 0.0486764758825) -> 0.0 | reached max session length\n"
]
},
{
"data": {
"image/png": 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"text/plain": [
"<matplotlib.figure.Figure at 0x6764a390>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"session # 0\n",
" FIRE(qv = 0.538625895977) -> 0.0 | FIRE(qv = 0.817039847374) -> 0.0 | LEFT(qv = 0.0523682460189) -> 0.0 | FIRE(qv = 0.85275632143) -> 0.0 | RIGHT(qv = 0.0265860389918) -> 0.0 | RIGHTFIRE(qv = 0.0531402267516) -> 0.0 | FIRE(qv = 0.780806303024) -> 0.0 | NOOP(qv = 0.0627793222666) -> 0.0 | FIRE(qv = 0.837199449539) -> 0.0 | NOOP(qv = 0.076013058424) -> 0.0 | RIGHT(qv = 0.0351323001087) -> 0.0 | FIRE(qv = 0.83241724968) -> 0.0 | NOOP(qv = 0.0490548759699) -> 0.0 | FIRE(qv = 0.837901651859) -> 0.0 | FIRE(qv = 0.447726875544) -> 0.0 | FIRE(qv = 0.43726348877) -> 0.0 | LEFT(qv = 0.0534157790244) -> 0.0 | LEFTFIRE(qv = 0.146211341023) -> 0.0 | FIRE(qv = 0.426346391439) -> 0.0 | LEFTFIRE(qv = 0.150275051594) -> 0.0 | FIRE(qv = 0.472053408623) -> 0.0 | LEFT(qv = 0.0538235753775) -> 0.0 | FIRE(qv = 0.458600312471) -> 0.0 | RIGHTFIRE(qv = 0.0517999120057) -> 0.0 | RIGHT(qv = 0.177873164415) -> 0.0 | reached max session length\n"
]
},
{
"data": {
"image/png": 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"text/plain": [
"<matplotlib.figure.Figure at 0x68e7bad0>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"session # 0\n",
" LEFTFIRE(qv = 0.0595601461828) -> 0.0 | FIRE(qv = 0.861246287823) -> 0.0 | FIRE(qv = 0.835597276688) -> 0.0 | FIRE(qv = 0.787656009197) -> 0.0 | FIRE(qv = 0.795904755592) -> 0.0 | RIGHT(qv = 0.031145138666) -> 0.0 | FIRE(qv = 0.884184002876) -> 0.0 | FIRE(qv = 0.877139687538) -> 0.0 | RIGHTFIRE(qv = 0.01783920452) -> 0.0 | RIGHTFIRE(qv = 0.0199202802032) -> 0.0 | NOOP(qv = 0.0371097363532) -> 0.0 | FIRE(qv = 0.896901428699) -> 0.0 | RIGHT(qv = 0.0247416757047) -> 0.0 | FIRE(qv = 0.87251162529) -> 0.0 | FIRE(qv = 0.831593394279) -> 0.0 | FIRE(qv = 0.853965580463) -> 0.0 | FIRE(qv = 0.855138003826) -> 0.0 | FIRE(qv = 0.858782589436) -> 0.0 | NOOP(qv = 0.0610778778791) -> 0.0 | FIRE(qv = 0.825925648212) -> 0.0 | FIRE(qv = 0.785769581795) -> 0.0 | FIRE(qv = 0.815139591694) -> 0.0 | \n",
"\n",
"not saved ./agentnet_snapshots/tutorial.gym.atari.CrazyClimber-v0.cnn.epoch1000.pcl\n",
"epoch 1050,loss 136.08906, epsilon 0.34567, rewards: ( e-greedy 17.95763, greedy 20.72256) \n",
"rec 135.477 reg 0.612\n",
"epoch 1100,loss 318.82068, epsilon 0.33982, rewards: ( e-greedy 18.41186, greedy 19.90031) \n",
"rec 318.214 reg 0.607\n",
"epoch 1150,loss 153.43458, epsilon 0.33408, rewards: ( e-greedy 17.57068, greedy 19.16028) \n",
"rec 152.833 reg 0.601\n",
"epoch 1200,loss 263.85688, epsilon 0.32845, rewards: ( e-greedy 17.06361, greedy 20.24425) \n",
"rec 263.257 reg 0.600\n",
"epoch 1250,loss 186.42858, epsilon 0.32294, rewards: ( e-greedy 16.10725, greedy 19.71982) \n",
"rec 185.827 reg 0.601\n",
"epoch 1300,loss 55.16964, epsilon 0.31753, rewards: ( e-greedy 15.74652, greedy 20.99784) \n",
"rec 54.577 reg 0.593\n",
"epoch 1350,loss 104.13705, epsilon 0.31224, rewards: ( e-greedy 15.17187, greedy 20.39806) \n",
"rec 103.536 reg 0.601\n",
"epoch 1400,loss 285.64216, epsilon 0.30704, rewards: ( e-greedy 15.90468, greedy 21.35825) \n",
"rec 285.041 reg 0.601\n",
"epoch 1450,loss 82.16035, epsilon 0.30195, rewards: ( e-greedy 15.56422, greedy 21.22243) \n",
"rec 81.566 reg 0.595\n",
"epoch 1500,loss 377.32309, epsilon 0.29697, rewards: ( e-greedy 17.75779, greedy 22.35018) \n",
"rec 376.721 reg 0.602\n",
"Learning curves:\n"
]
},
{
"data": {
"image/png": 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//wKffgocPgy4uuodzdtxnywbwB4BY8yJNuZFG/OijXkxxpxoS6u8vHwJ+PgA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\nrkJggg==\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x68e929d0>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Random session examples\n"
]
},
{
"data": {
"image/png": 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"text/plain": [
"<matplotlib.figure.Figure at 0x68e97190>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"session # 0\n",
" FIRE(qv = 0.619221568108) -> 0.0 | FIRE(qv = 0.872491896152) -> 0.0 | FIRE(qv = 0.908886790276) -> 0.0 | FIRE(qv = 0.95200073719) -> 0.0 | FIRE(qv = 0.962680578232) -> 0.0 | NOOP(qv = 0.0066259726882) -> 0.0 | FIRE(qv = 0.961992800236) -> 0.0 | FIRE(qv = 0.940396428108) -> 0.0 | FIRE(qv = 0.943901538849) -> 0.0 | FIRE(qv = 0.959201335907) -> 0.0 | FIRE(qv = 0.975576639175) -> 0.0 | FIRE(qv = 0.981123030186) -> 0.0 | FIRE(qv = 0.984629273415) -> 0.0 | FIRE(qv = 0.983820080757) -> 0.0 | NOOP(qv = 0.00650177756324) -> 0.0 | FIRE(qv = 0.97316879034) -> 0.0 | FIRE(qv = 0.97768342495) -> 0.0 | FIRE(qv = 0.977700650692) -> 0.0 | NOOP(qv = 0.00431655207649) -> 0.0 | FIRE(qv = 0.962204098701) -> 0.0 | NOOP(qv = 0.00896452739835) -> 0.0 | FIRE(qv = 0.952093601227) -> 0.0 | FIRE(qv = 0.967345476151) -> 0.0 | FIRE(qv = 0.9743039608) -> 0.0 | FIRE(qv = 0.971819937229) -> 0.0 | reached max session length\n"
]
},
{
"data": {
"image/png": 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"text/plain": [
"<matplotlib.figure.Figure at 0x65a2a910>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"session # 0\n",
" FIRE(qv = 0.609430909157) -> 0.0 | LEFTFIRE(qv = 0.117184020579) -> 0.0 | FIRE(qv = 0.773866295815) -> 0.0 | FIRE(qv = 0.830187916756) -> 0.0 | FIRE(qv = 0.89211666584) -> 0.0 | FIRE(qv = 0.865386009216) -> 0.0 | LEFTFIRE(qv = 0.036550078541) -> 0.0 | FIRE(qv = 0.861637413502) -> 0.0 | FIRE(qv = 0.873663544655) -> 0.0 | FIRE(qv = 0.884404540062) -> 0.0 | FIRE(qv = 0.862088739872) -> 0.0 | FIRE(qv = 0.889590144157) -> 0.0 | FIRE(qv = 0.915596187115) -> 0.0 | FIRE(qv = 0.846425712109) -> 0.0 | FIRE(qv = 0.822192907333) -> 0.0 | FIRE(qv = 0.813772976398) -> 0.0 | FIRE(qv = 0.918209254742) -> 0.0 | FIRE(qv = 0.879773497581) -> 0.0 | LEFT(qv = 0.0303672160953) -> 0.0 | FIRE(qv = 0.882571876049) -> 0.0 | FIRE(qv = 0.86976981163) -> 0.0 | FIRE(qv = 0.843435943127) -> 0.0 | LEFTFIRE(qv = 0.0803235024214) -> 0.0 | FIRE(qv = 0.864513039589) -> 0.0 | FIRE(qv = 0.811148405075) -> 0.0 | reached max session length\n"
]
},
{
"data": {
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"text/plain": [
"<matplotlib.figure.Figure at 0x65a3ced0>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"session # 0\n",
" RIGHT(qv = 0.191571176052) -> 0.0 | NOOP(qv = 0.0753488615155) -> 0.0 | FIRE(qv = 0.591641843319) -> 0.0 | FIRE(qv = 0.593747079372) -> 0.0 | FIRE(qv = 0.527761757374) -> 0.0 | NOOP(qv = 0.078246511519) -> 0.0 | RIGHTFIRE(qv = 0.0330920293927) -> 0.0 | NOOP(qv = 0.0895728543401) -> 0.0 | RIGHT(qv = 0.182386785746) -> 0.0 | FIRE(qv = 0.600454330444) -> 0.0 | FIRE(qv = 0.595362067223) -> 0.0 | FIRE(qv = 0.590567111969) -> 0.0 | FIRE(qv = 0.612385451794) -> 0.0 | LEFTFIRE(qv = 0.0744539871812) -> 0.0 | RIGHT(qv = 0.178619876504) -> 0.0 | RIGHTFIRE(qv = 0.0292377583683) -> 0.0 | FIRE(qv = 0.829912364483) -> 0.0 | RIGHT(qv = 0.0380108691752) -> 0.0 | LEFTFIRE(qv = 0.0540369823575) -> 0.0 | FIRE(qv = 0.885944008827) -> 0.0 | FIRE(qv = 0.915231764317) -> 0.0 | FIRE(qv = 0.891591310501) -> 0.0 | FIRE(qv = 0.86448007822) -> 0.0 | NOOP(qv = 0.0100064985454) -> 0.0 | FIRE(qv = 0.831761360168) -> 0.0 | reached max session length\n",
"epoch 1550,loss 433.82001, epsilon 0.29207, rewards: ( e-greedy 18.48201, greedy 22.36517) \n",
"rec 433.217 reg 0.603\n",
"epoch 1600,loss 436.03833, epsilon 0.28728, rewards: ( e-greedy 19.13381, greedy 21.12865) \n",
"rec 435.439 reg 0.599\n",
"epoch 1650,loss 117.89100, epsilon 0.28258, rewards: ( e-greedy 17.72043, greedy 20.76578) \n",
"rec 117.287 reg 0.604\n"
]
}
],
"source": [
"n_epochs = 25000\n",
"batch_size= 10\n",
"\n",
"for i in range(n_epochs): \n",
" \n",
" \n",
" #train\n",
" update_pool(env,pool,replay_seq_len)\n",
" resolver.rng.seed(i) \n",
" loss,avg_reward = train_fun()\n",
" \n",
" \n",
" ##update resolver's epsilon (chance of random action instead of optimal one)\n",
" if epoch_counter%1 ==0:\n",
" current_epsilon = 0.05 + 0.45*np.exp(-epoch_counter/2500.)\n",
" epsilon.set_value(np.float32(current_epsilon))\n",
" \n",
" \n",
" \n",
" ##record current learning progress and show learning curves\n",
" if epoch_counter%50 ==0:\n",
"\n",
" ##update learning curves\n",
" full_loss, q_loss, l2_penalty, avg_reward_current = evaluation_fun()\n",
" ma_reward_current = (1-alpha)*ma_reward_current + alpha*avg_reward_current\n",
" score_log[\"expected e-greedy reward\"][epoch_counter] = ma_reward_current\n",
" \n",
" \n",
" \n",
" #greedy train\n",
" epsilon.set_value(0)\n",
" update_pool(env,pool,replay_seq_len)\n",
"\n",
" avg_reward_greedy = evaluation_fun()[-1]\n",
" ma_reward_greedy = (1-alpha)*ma_reward_greedy + alpha*avg_reward_greedy\n",
" score_log[\"expected greedy reward\"][epoch_counter] = ma_reward_greedy\n",
" \n",
" \n",
" #back to epsilon-greedy\n",
" epsilon.set_value(np.float32(current_epsilon))\n",
" update_pool(env,pool,replay_seq_len)\n",
"\n",
" print \"epoch %i,loss %.5f, epsilon %.5f, rewards: ( e-greedy %.5f, greedy %.5f) \"%(\n",
" epoch_counter,full_loss,current_epsilon,ma_reward_current,ma_reward_greedy)\n",
" print \"rec %.3f reg %.3f\"%(q_loss,l2_penalty)\n",
"\n",
" if epoch_counter %500 ==0:\n",
" print \"Learning curves:\"\n",
" score_log.plot()\n",
"\n",
"\n",
" print \"Random session examples\"\n",
" display_sessions(with_plots=False)\n",
" \n",
" #save snapshot\n",
" if epoch_counter %1000 ==0:\n",
" snap_name = \"{}.epoch{}.pcl\".format(os.path.join(snapshot_path,experiment_setup_name), epoch_counter)\n",
" #save(resolver,snap_name)\n",
" print \"not saved\", snap_name\n",
"\n",
" \n",
" \n",
" epoch_counter +=1\n",
"\n",
" \n",
"# Time to drink some coffee!"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Evaluating results\n",
" * Here we plot learning curves and sample testimonials"
]
},
{
"cell_type": "code",
"execution_count": 36,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
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KwnGPHj2TrnA2bwZmzADmzAlOusxmgAhoaemO2+q2otXRCqBrejEpFckJyf1W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\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x660e1b10>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"score_log.plot(\"final\")"
]
},
{
"cell_type": "code",
"execution_count": 37,
"metadata": {
"collapsed": false
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Random session examples\n"
]
},
{
"data": {
"image/png": 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"text/plain": [
"<matplotlib.figure.Figure at 0x71a46b10>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"session # 0\n",
" FIRE(qv = 0.998975038528) -> 0.0 | RIGHT(qv = 0.0255596060306) -> 0.0 | RIGHT(qv = 0.0115891238675) -> 0.0 | NOOP(qv = 0.00726029835641) -> 0.0 | LEFT(qv = 0.00672568799928) -> 0.0 | NOOP(qv = 0.0322714820504) -> 0.0 | RIGHTFIRE(qv = 0.0338855199516) -> 0.0 | NOOP(qv = 0.00605950225145) -> 0.0 | RIGHT(qv = 0.0129593322054) -> 0.0 | NOOP(qv = 0.00440588779747) -> 0.0 | RIGHT(qv = 0.0459647066891) -> 0.0 | FIRE(qv = 0.995325922966) -> 0.0 | RIGHTFIRE(qv = 0.00387548841536) -> 0.0 | FIRE(qv = 0.995754122734) -> 0.0 | FIRE(qv = 0.996752381325) -> 0.0 | FIRE(qv = 0.996604561806) -> 0.0 | FIRE(qv = 0.996810972691) -> 100.0 | RIGHT(qv = 0.000600593048148) -> 0.0 | FIRE(qv = 0.996688783169) -> 0.0 | FIRE(qv = 0.996595680714) -> 0.0 | FIRE(qv = 0.996110975742) -> 0.0 | FIRE(qv = 0.995953798294) -> 0.0 | FIRE(qv = 0.994358122349) -> 0.0 | FIRE(qv = 0.992375075817) -> 0.0 | RIGHTFIRE(qv = 0.177032873034) -> 0.0 | reached max session length\n"
]
},
{
"data": {
"image/png": 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CyRljZK3VqFGjtHDhQiUnJ0uSHnvsMVlro/5LUiwHp8nKH5yeHeWxKyUNtdb2\nNsZcIGmUtfaCIs5jdUdbhbKW65s/f612KUeNdQEAjnpnxju65eNbZRf+RtpwsRTKVkKN+/XHR+9Q\ns5RmysnLUXZutrLzsiO/+vfl5OV4Hs/OzVaOLd3n5dpcxYfiVSVcRVXCVRQfzv/9cfcd/n2xj4+y\nb+Xylbr/3pHau/t9KS9OsmHVqN5Hb/3zL2p/TnuFTCjqhzGm6MdkPMcVx9atW9WsWWsdODBTUjtJ\ni5SQ0E3r1y8r19lJdLjHlXsRyw5r8wfV/l+P9VjBr19//bX6XjtMmZkZkfMlJv5M//rw/9N5553n\nuYbnmkU8S+9/rLifu3DhQt1083Dt2fMfyeRJJlc1al6p198cobZntVVuXq5ybW6xfs3Jyyn2sf5f\n13+/Xq++PkGHsu6UTK4UylGVU17VdTf0UL369fLPffgaObbQ7w9/5Noj24UfK7z/WI/l5uUqKydL\n+w7sl0Jx0uNZUviQalbvoszMbxicVgAFg9Mi9kf/j1hR831L8iFprKQfJB2StEHSIOW/Ku+dhY55\nXtIqSd+qiPWmh4+zp1SvY6/7+/W2/l/r23f+987xpjPHXNDrPwrQ4UWHWw3W0uF3sndkrM2w9UbW\ns/EdqlvpWyvNtNK3NiEhKbC1SkF+T7Zs2WITEpKcuBcF6/mqVWvhxLpCOo4I+u8NV+6FCx2u/MzS\ncYyGdv/v8DZrTiuCor5POsaa05i9IFKsPiRF/tDP2zjPtvx7S/uLD35hdx7YecI3qLiC/g9FATq8\n6HCrwVo6/E7mjrcXvW1P/b9T7bTV05z4n8wCQX9PXLoXLryoCR1HC/rPqLXu3AsXOlz5maXj6AZp\npjV3hu3YseMZnFYQpRmcxmxab6wYY2zhpv3Z+/WbT3+jScsn6bU+r6lHao8A6wAAhVlrNfKLkRqz\nYIwm95uss+qfJSl/mt66deuUnJx80k2V9ONeABWLKz+zdHgb6tc/VY2fbqIPb/lQHRt1ZFpvBVCa\nab3OD04LfLLqEw2ZNEQ3nHmD/tLjL0qITwigDgBQICcvR/f9+z59tfErTe43WY1qNgo6CQBQSRkj\nPfXZSC3bvkyv932dwWkFUJrBaajMq2KkV4te+vbub7VpzyZ1eLmDvtn8TZldq+AVKINGhxcdbjVI\ndPidTB17s/aqz/g+WrdrnT4b9FnUgakL98OFBokOPzrcapDo8KPDy42ODA05b4gmLJsQdAjKUIUZ\nnEpS3WrJteETAAAgAElEQVR19c717+j3F/1evd7qpSc/e1K5eblBZwHASeXHvT/qZ6//TA1rNNRH\nt3ykxKqJQScBAE4C9arVU59WfYLOQBmqMNN6/Tbs3qCBEwbqUO4hvdn3TTVPal4OdQBwcluydYl6\nj+2tIecO0SMXP3LCb3gPAEBxGCNZK83fNF+dGndydlpvSkqK0tPT1b1798i+WbNmqXv37qpevbqk\n/NdrMMbo008/VefOnZWWlqa5c+cqPj4+8tjHH3+s3r17R6bG7tu3T9WqVZMxRsYYTZkyRa+88orG\njh2rqlWrRj4vPT1dN9xwg6fjjTfe0JAhQ1StWjWFQiE1a9ZMjz76qK699lpJ0vr165WSkqIaNWp4\n+grOVVqlmdYbV+qrBaxpraaadus0PffVc7og/QI92eNJDTl3CP+jBJSD7Nxszd00V0u3LlVqnVS1\nrNtSjWo2UshUqMkYKKFZ62bpxvdv1NOXPa0B5wwIOgcAcBLq2Khj0Aml0qhRI23YsCHqY8YYjR49\nWoMGDfLs37NnT+T34XBYixcvVkpKSmTfK6+8ouHDh2vEiBHHvf6FF16o2bNnS5Jeeukl9evXTz/8\n8IPq1KkTadi9e3fgY6kK/X+SIRPSr7r8Shm3ZeiF+S+oz/g++mnvTyd8Xjfm1dPhR0dwDdZardy+\nUi/My/85O/Wvp+qBKQ/o/Snv6/HZj6vzK52V+GSi2r/YXje+d6P+MOMPevPbN/XVxq+048COMu9z\n4XsiVe6OsYvH6ob3btDYn48t9sDUhfvhQoNEhx8dbjVIdPjR4eVGR0bQAWXqeM8E2yNvu3nCBgwY\noEOHDmn16tUlaigPFfaZ08La1m+rubfP1aMZj6r9P9rrxd4vqk9r5qMDJ2LHgR2asXaGpq6eqk/X\nfKrs3Gxd1vwy3dz2Zr189cuqX72+MjIylJaWJknac2iPVu5YqRXbV2jF9hX6ZPUn+vu8v2vF9hWK\nD8WrZd2WkY9WdVupZd2WapHUglfedlzht4qZcduMyFvFAACAiic3N1evvvqqateurVatWnkec2Fw\nWmHXnBbliw1f6NYJtyqtWZpGXT6KF+oAiik7N1tfbfxKU1dP1dQ1U7V061Jd3OxiXZZ6mXo276k2\n9dqUaqqHtVZb9m2JDFpXbF+hFTvyf12zc43qV6+fP2hNaukZwDar3UxxoUrx72cVFm8VAwBwRcGa\n0/zfR1/LWCAjIzZTU9PSSj4mOdaa01q1akk6sqZz06ZNSkhIULdu3TR//nxVqVJF1lo1b95cCxYs\n8Jw3FApp1apVSk1NjewbNGiQxo8fr4SEBFlrFR8fry1bthzV8cYbb+j2229XYmKi9u7dq/j4eE2d\nOlVdu3aVdGTNae3atT19c+bMOWoAWxIn1ZrTonRt2lUL71qoBz95UOe8eI7evPZNXdT0oqCzAOdY\na7Vyx8r8wejqqZq1fpbOSDpDPZv31FM9ntKFTS5U1biqJ3wdY4wa1GigBjUa6OJmF3sey83L1Ybd\nGyKD1uXbl2vyyslasX2Fftz7o1LqpHieaS34aFC9QeBrIiq7vVl7ddP7Nyk3L1efDfqMf+gDAFQY\npRlUlrVjrTmVpL/97W8aPHhwic/78MMPF2vNaZcuXTR79mzt379fQ4YM0ciRIzVp0qTI48YYbd++\nPfD/v6rQa06Lklg1US9f87JGXT5KN7x3g3437XfKys0q9ue7Ma+eDj86Trxh+/7teve7d3XHpDuU\n/FyyerzZQ99s/kb9zu6nVfev0oI7F+gvPf6ibindijUwPdF7EQ6FlVInRb1a9NL9ne/X81c+r6kD\npmrdsHXaOXyn3rvhPd12zm1KSkjSl99/qd9P/73ajWmnWk/VUoeXOqjfB/30aMajeiT9Ec3bNK9c\n1rceiwt/NqQT74jVW8W4cD9caJDo8KPDrQaJDj86vNzoyAg6oFKoVq2aRo8erVmzZkVeIKmACzNq\nK90zp4Vd0+oaXdD4At3x0R3q9HInvfXzt1gvhZNKVm6W5nw/R5+u+VRTV0/Vsm3LdEmzS9SzeU89\ndOFDalW3VeD/QlaUhPgEnVX/rKg/szsP7Iysb12+bbm+3PilPpn8iVbuWKmwCatFUouoH6dWO9XZ\nr9cVvFUMAAAnJisrS4cOHYpsZ2dnOzHwK1CnTh3deeedevLJJ3XJJZdIiu0LLp2ISrfmNBprrV5b\n+JqGTxuu3130Ow27YBhveYFKyVqr5duXR17EaPb62WpZt6V6pvZUz+Y91aVJF1UJVwk6s8xYa7X9\nwHat2rEq6kdWbtZRA9bmdZqrRVILNUxseNL/vcBbxQAAXFWSNadBSklJOWr6bteuXfXll1+qWrVq\nko6s6XzjjTd07bXXqnv37urfv/8xp/WGw2GtXLnSs+Z08ODBaty4cdRpvampqXrllVcia07T09M9\nz5Ru2rRJLVq00Ny5c1WrVi2lpqYe9T6sI0aM0LBhw0p9L0qz5vSkGJwWWLNzjW798FZVCVfR631f\nV9NaTcvkOkB52rZ/m6avmR4ZkEpSz+b5g9EeKT1Ut1rdgAvdsfPATq3euTrqwDXzUKaaJ+UPVFvU\n8Q5gG9dsrHAoHHR+mRq7eKyG/WeYxl03Tj1SewSdAwCAR0UZnOKI0gxOT6qnCVLrpGrWwFnq2byn\nzn/pfL216K2oN8yNefV0+NFxxN/f+bt+P/336vhyRzX/W3O9vfhttT+tvT4d8KnWD1uvV655RTe2\nvbHMB6Yu3Aup+B11Euqow+kddPNZN+sPl/xBr/d9XZ8P/lw//vpH/fTrn/TPa/+pX5z9C9WtVlfz\nf5ivx2c/rq6vdlX1v1RXmxfa6OpxV+tX//mVXpj3gj5Z9YlW71itnLycEneUtZJ0WGv11OdP6XfT\nf6cZt82I6cDUhfvhQoNEhx8dbjVIdPjR4eVGR0bQASgHlXrNaTThUFi/vei36tW8l/p/2F8Tl0/U\ni71f5NklVBgvzHtBI2aP0F3X3aVnej6jCxpfUKmn6paXxKqJan9ae7U/rf1Rj+3P3q81O9dEnmVd\nvGWxPlz2oVbtWKXNezeraa2mapHUQg22NlCd1nXUrkG7CrFWs+CtYuZumqs5Q+bo9MTTg04CAAAn\nsZNqWq/fwZyDemT6Ixr/3XilX5Ouy1tcXi7XBUrr7UVva/i04fps0GdKqZMSdA4kHco5pLW71mrl\n9pXKWJehCcsnKDcvV31b91WfVn10cbOLnXy/1sJvFfPeDe/xVjEAAKcxrbfiYc1pKc1YO0ODJg7S\nVWdcpf+77P9UvUr1cr0+UBwfLf9Id3x0h6bfOl1t67cNOgdFsNbqu63facKyCZq4fKLW7Fyj3mf0\nVp9WfdSrRS/VqFIj6ET9uPdH9R7bW+eedq7G9B6j+HB80EkAABwTg9OKh8HpCdh1cJfun3K/5m6c\nqzuT7lSvS3sp1+YqJy9HuXmHfy20He2xaMcd67HjnX/L/7bovAvP02k1TvN8NKjeoFjvQRkrGRkZ\nSktLK7fr0RHlmusydMN7N2hyv8nq1KjTSX0vKlrHxsyNmrR8kiYun6g538/RJc0uUd/WfXV1y6vV\noEaDcusoUJ5vFePC98WFBjr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yO/PQTkM1ZsEY5eTllNk1UDwMTgEAAACctM5reJ4a12ys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\npyIiIiIiIhK7/x/Nztfw7chxtgAAAABJRU5ErkJggg==\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x674cd390>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"image/png": 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"text/plain": [
"<matplotlib.figure.Figure at 0x7466c090>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"session # 0\n",
" RIGHT(qv = 5.56879749638e-05) -> 0.0 | FIRE(qv = 0.577715277672) -> 0.0 | FIRE(qv = 0.322500407696) -> 0.0 | RIGHT(qv = 0.620493113995) -> 0.0 | RIGHT(qv = 0.613712310791) -> 0.0 | RIGHT(qv = 0.642285585403) -> 0.0 | NOOP(qv = 0.0345493964851) -> 0.0 | FIRE(qv = 0.134482979774) -> 0.0 | RIGHT(qv = 0.79089564085) -> 0.0 | FIRE(qv = 0.138075724244) -> 0.0 | RIGHT(qv = 0.748723328114) -> 0.0 | RIGHT(qv = 0.589778006077) -> 0.0 | FIRE(qv = 0.147633269429) -> 0.0 | RIGHTFIRE(qv = 0.103272713721) -> 0.0 | RIGHT(qv = 0.742757797241) -> 0.0 | RIGHT(qv = 0.767797112465) -> 0.0 | RIGHTFIRE(qv = 0.104413174093) -> 0.0 | RIGHT(qv = 0.616171479225) -> 0.0 | FIRE(qv = 0.33625331521) -> 0.0 | RIGHTFIRE(qv = 0.122266419232) -> 0.0 | RIGHT(qv = 0.408966809511) -> 0.0 | RIGHT(qv = 0.558721899986) -> 0.0 | RIGHT(qv = 0.506978690624) -> 0.0 | FIRE(qv = 0.477399289608) -> 0.0 | FIRE(qv = 0.319364458323) -> 0.0 | reached max session length\n"
]
},
{
"data": {
"image/png": 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4D+uwYcMYPHhwmb8WZdlzav1wOmftHO6ceSffDvzWxyoREREREfFLpAynsl9Z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\nVr5/LXr2vIqMjFWMHDmQjIx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WRfx07LHw8cdmqIyPh+Qy/Gf9yy/NGdJ16+DBB+Haaw97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Z6NPWcuJvOm6TIvF5mfQXF4vO84V2yd3gXgRGZibp85/fa34ROfgGeegUz6vmBVBioMPl4vRAcf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\nOBUREREREZHE/f/dDyEJaulpdAAAAABJRU5ErkJggg==\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x739df350>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
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"text/plain": [
"<matplotlib.figure.Figure at 0x739df410>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"session # 0\n",
" FIRE(qv = 0.998960614204) -> 0.0 | FIRE(qv = 0.999006211758) -> 0.0 | FIRE(qv = 0.99909734726) -> 0.0 | FIRE(qv = 0.999053776264) -> 0.0 | FIRE(qv = 0.999016880989) -> 0.0 | FIRE(qv = 0.998828947544) -> 0.0 | FIRE(qv = 0.998530268669) -> 0.0 | FIRE(qv = 0.998357594013) -> 0.0 | FIRE(qv = 0.99832123518) -> 0.0 | FIRE(qv = 0.998305439949) -> 0.0 | FIRE(qv = 0.998028457165) -> 0.0 | RIGHT(qv = 0.062263481319) -> 0.0 | RIGHT(qv = 0.160946249962) -> 0.0 | RIGHT(qv = 0.132009997964) -> 0.0 | NOOP(qv = 0.0534337311983) -> 0.0 | RIGHTFIRE(qv = 0.193770587444) -> 0.0 | RIGHT(qv = 0.118478879333) -> 0.0 | RIGHT(qv = 0.177056267858) -> 0.0 | FIRE(qv = 0.99149698019) -> 0.0 | FIRE(qv = 0.984538197517) -> 0.0 | FIRE(qv = 0.977242231369) -> 0.0 | NOOP(qv = 0.00627785455436) -> 0.0 | FIRE(qv = 0.970509111881) -> 0.0 | FIRE(qv = 0.968253135681) -> 0.0 | FIRE(qv = 0.968186616898) -> 0.0 | reached max session length\n"
]
},
{
"data": {
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3R2TkJAwbFgohKkDKRKc3sIMdujewwxU6uiI7yhtp/d/Evxt/p3Qwzf237CW5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\n4YdwySXQsiXgj78tLl7KvffeyLy1y8n997/hyivpcUoJmR0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Dxx+HTz/1C8b33vPbt97q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\nmZlZOw9OzczMzMzMrN0/IRL8gdgy5MoAAAAASUVORK5CYII=\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x67404250>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"print \"Random session examples\"\n",
"display_sessions(with_plots=True)\n"
]
},
{
"cell_type": "markdown",
"metadata": {
"collapsed": true
},
"source": [
"# Submission"
]
},
{
"cell_type": "code",
"execution_count": 39,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"epsilon.set_value(0)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": false
},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"[2016-05-03 13:24:26,602] Making new env: AirRaid-v0\n",
"[2016-05-03 13:24:26,636] Clearing 4 monitor files from previous run (because force=True was provided)\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Episode finished after 521 timesteps\n",
"Episode finished after 297 timesteps\n",
"Episode finished after 196 timesteps\n",
"Episode finished after 448 timesteps\n",
"Episode finished after 199 timesteps\n",
"Episode finished after 475 timesteps\n",
"Episode finished after 588 timesteps\n",
"Episode finished after 369 timesteps\n",
"Episode finished after 336 timesteps\n",
"Episode finished after 348 timesteps\n",
"Episode finished after 373 timesteps\n",
"Episode finished after 261 timesteps\n",
"Episode finished after 562 timesteps\n",
"Episode finished after 229 timesteps\n",
"Episode finished after 192 timesteps\n",
"Episode finished after 487 timesteps\n",
"Episode finished after 503 timesteps\n",
"Episode finished after 639 timesteps\n",
"Episode finished after 405 timesteps\n",
"Episode finished after 194 timesteps\n",
"Episode finished after 363 timesteps\n",
"Episode finished after 243 timesteps\n",
"Episode finished after 614 timesteps\n",
"Episode finished after 352 timesteps\n",
"Episode finished after 541 timesteps\n",
"Episode finished after 191 timesteps\n",
"Episode finished after 288 timesteps\n",
"Episode finished after 294 timesteps\n",
"Episode finished after 297 timesteps\n",
"Episode finished after 570 timesteps\n",
"Episode finished after 406 timesteps\n",
"Episode finished after 324 timesteps\n",
"Episode finished after 475 timesteps\n",
"Episode finished after 400 timesteps\n",
"Episode finished after 337 timesteps\n",
"Episode finished after 343 timesteps\n",
"Episode finished after 355 timesteps\n",
"Episode finished after 843 timesteps\n",
"Episode finished after 404 timesteps\n",
"Episode finished after 418 timesteps\n",
"Episode finished after 307 timesteps\n",
"Episode finished after 770 timesteps\n",
"Episode finished after 261 timesteps\n",
"Episode finished after 1062 timesteps\n",
"Episode finished after 462 timesteps\n",
"Episode finished after 569 timesteps\n",
"Episode finished after 443 timesteps\n",
"Episode finished after 544 timesteps\n",
"Episode finished after 388 timesteps\n",
"Episode finished after 435 timesteps\n",
"Episode finished after 456 timesteps\n",
"Episode finished after 347 timesteps\n",
"Episode finished after 471 timesteps\n",
"Episode finished after 321 timesteps\n",
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"Episode finished after 563 timesteps\n",
"Episode finished after 526 timesteps\n"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"[2016-05-03 13:49:19,695] Finished writing results. You can upload them to the scoreboard via gym.upload('/tmp/AgentNet-simplenet-SpaceInvadersv0-Recording0')\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Episode finished after 565 timesteps\n"
]
}
],
"source": [
"\n",
"save_path = '/tmp/AgentNet-simplenet-AirRaid-v0-Recording0'\n",
"\n",
"subm_env = gym.make(GAME_TITLE)\n",
"\n",
"#starting monitor. This setup does not write videos\n",
"subm_env.monitor.start(save_path,lambda i: False,force=True)\n",
"\n",
"#this setup does\n",
"#subm_env.monitor.start(save_path,force=True)\n",
"\n",
"\n",
"for i_episode in xrange(200):\n",
" \n",
" #initial observation\n",
" observation = subm_env.reset()\n",
" #initial memory\n",
" prev_memories = [np.zeros((1,)+tuple(mem.output_shape[1:]),dtype=floatX) \n",
" for mem in agent.state_variables]\n",
" \n",
" \n",
" t = 0\n",
" while True:\n",
"\n",
" action,new_memories = step([observation],prev_memories)\n",
" observation, reward, done, info = subm_env.step(action)\n",
" \n",
" prev_memories = new_memories\n",
" if done:\n",
" print \"Episode finished after {} timesteps\".format(t+1)\n",
" break\n",
" t+=1\n",
"\n",
"subm_env.monitor.close()"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"gym.monitoring._monitors.clear()"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"\n",
"gym.upload(save_path,\n",
" \n",
" #this notebook\n",
" writeup=<url to my gist>, \n",
" \n",
" #your api key\n",
" api_key=<my_own_api_key>)\n"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": []
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"\n"
]
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 2",
"language": "python",
"name": "python2"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 2
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython2",
"version": "2.7.3"
}
},
"nbformat": 4,
"nbformat_minor": 0
}
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