various
This commit is contained in:
parent
3d7741aa6e
commit
693eeb991e
160
main.lua
160
main.lua
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@ -24,15 +24,27 @@ end
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--randomseed(11)
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local enable_overlay = false
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local enable_network = true
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local playable_mode = false
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--
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local epoch_trials = 24
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local learning_rate = 3.2e-3
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local deviation = 1e-1 / epoch_trials
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local deterministic = false -- use argmax on outputs instead of random sampling.
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local det_epsilon = true -- take random actions with probability eps.
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local eps_start = 0.50
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local eps_stop = 0.05
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local eps_frames = 60*60*60
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local consider_past_rewards = false
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local learn_start_select = false
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--
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local epoch_trials = 40 -- 24
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local learning_rate = 1e-3
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local deviation = 1e-2 -- 4e-3
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--
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local timer_loser = 1/3
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local cap_time = 400
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local timer_loser = 1/3
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--
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local enable_overlay = playable_mode
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local enable_network = not playable_mode
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local input_size = 281 -- TODO: let the script figure this out for us.
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local epoch_i = 0
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local base_params
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@ -41,6 +53,9 @@ local trial_noise = {}
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local trial_rewards = {}
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local trials_remaining = 0
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local trial_frames = 0
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local total_frames = 0
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local force_start = false
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local force_start_old = false
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@ -51,12 +66,15 @@ local max_time
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local sprite_input = {}
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local tile_input = {}
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local extra_input = {}
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local reward
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local all_rewards = {}
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local powerup_old
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local status_old
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local coins_old
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local score_old
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local once = false
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local reset = true
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@ -125,6 +143,8 @@ end
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local function clamp(x, l, u) return min(max(x, l), u) end
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local function lerp(a, b, t) return a + (b - a) * clamp(t, 0, 1) end
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local function argmax(...)
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local max_i = 0
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local max_v = -999999999
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@ -142,6 +162,14 @@ local function argmax2(t)
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return t[1] > t[2]
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end
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local function rchoice2(t)
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return t[1] > random()
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end
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local function rbool(t)
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return 0.5 >= random()
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end
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local function empty(t)
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for k, _ in pairs(t) do t[k] = nil end
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return t
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@ -171,6 +199,15 @@ local function normalize(x, out)
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return out
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end
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local function normalize_wrt(x, s, out)
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out = out or x
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local mean, dev = calc_mean_dev(s)
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if dev <= 0 then dev = 1 end
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local devs = sqrt(dev)
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for i, v in ipairs(x) do out[i] = (v - mean) / devs end
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return out
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end
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-- game-agnostic stuff (i.e. the network itself)
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package.loaded['nn'] = nil -- DEBUG
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@ -188,10 +225,12 @@ local function make_network(input_size, buttons)
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nn_y = nn_y:feed(nn.Dense(input_size))
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nn_y = nn_y:feed(nn.Gelu())
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else
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nn_y = nn_y:feed(nn.Dense(114))
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nn_y = nn_y:feed(nn.Relu())
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nn_y = nn_y:feed(nn.Dense(57))
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nn_y = nn_y:feed(nn.Relu())
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nn_y = nn_y:feed(nn.Dense(128))
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nn_y = nn_y:feed(nn.Gelu())
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nn_y = nn_y:feed(nn.Dense(64))
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nn_y = nn_y:feed(nn.Gelu())
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nn_y = nn_y:feed(nn.Dense(48))
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nn_y = nn_y:feed(nn.Gelu())
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end
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for i = 1, buttons do
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nn_z[i] = nn_y
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@ -247,6 +286,14 @@ local function get_timer()
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return R(0x7F8) * 100 + R(0x7F9) * 10 + R(0x7FA)
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end
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local function get_score()
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return R(0x7DE) * 10000 +
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R(0x7DF) * 1000 +
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R(0x7E0) * 100 +
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R(0x7E1) * 10 +
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R(0x7E2)
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end
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local function set_timer(time)
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W(0x7F8, floor(time / 100))
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W(0x7F9, floor((time / 10) % 10))
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@ -460,7 +507,16 @@ end
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local function learn_from_epoch()
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print()
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print('rewards:', trial_rewards)
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normalize(trial_rewards)
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for _, v in ipairs(trial_rewards) do
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insert(all_rewards, v)
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end
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if consider_past_rewards then
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normalize_wrt(trial_rewards, all_rewards)
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else
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normalize(trial_rewards)
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end
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--print('normalized:', trial_rewards)
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local reward_mean, reward_dev = calc_mean_dev(trial_rewards)
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@ -501,9 +557,12 @@ local function learn_from_epoch()
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base_params[i] = v + step[i]
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end
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network:distribute(base_params)
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network:save()
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if enable_network then
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network:distribute(base_params)
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network:save()
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else
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print("note: not updating weights in playable mode.")
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end
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print()
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end
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@ -534,7 +593,7 @@ local function load_next_trial()
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end
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local function do_reset()
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print("resetting in state:", get_state())
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print("resetting in state: "..get_state()..". reward:", reward)
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if trial_i > 0 then trial_rewards[trial_i] = reward end
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@ -550,13 +609,15 @@ local function do_reset()
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powerup_old = R(0x754)
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status_old = R(0x756)
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coins_old = R(0x7ED) * 10 + R(0x7EE)
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score_old = get_score()
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-- set lives to 0. you only got one shot!
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-- unless you get a 1-up, in which case, please continue!
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W(0x75A, 0)
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--max_time = min(log(epoch_i) * 10 + 100, cap_time)
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max_time = min(8 * sqrt(15 * (epoch_i - 1)) + 100, cap_time)
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max_time = min(8 * sqrt(360 / epoch_trials * (epoch_i - 1)) + 100, cap_time)
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max_time = ceil(max_time)
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if once then
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savestate.load(startsave)
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@ -575,7 +636,7 @@ local function do_reset()
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end
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local function init()
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network = make_network(279, 8)
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network = make_network(input_size, learn_start_select and 8 or 6)
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network:reset()
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print("parameters:", network.n_param)
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@ -583,13 +644,14 @@ local function init()
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emu.unpause()
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emu.speedmode("turbo")
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network:load()
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local res, err = pcall(network.load, network)
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if res == false then print(err) end
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end
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init()
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local dummy_softmax_values = {0, 0}
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while true do
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gui.text(4, 12, get_state(), '#FFFFFF', '#0000003F')
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@ -638,6 +700,7 @@ while true do
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empty(sprite_input)
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empty(tile_input)
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empty(extra_input)
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-- player
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-- TODO: check if mario is playable.
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@ -646,6 +709,10 @@ while true do
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local status = R(0x756)
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mark_sprite(x + 8, y + 24, -powerup - 1)
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local vx, vy = S(0x57), S(0x9F)
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insert(extra_input, vx)
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insert(extra_input, vy)
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handle_enemies()
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handle_fireballs()
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-- blocks being hit. not interactable; we don't care!
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@ -666,7 +733,10 @@ while true do
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local status_delta = clamp(status - status_old, -1, 1)
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local screen_scroll_delta = R(0x775)
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local flagpole_bonus = R(0xE) == 4 and 1 or 0
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local reward_delta = screen_scroll_delta + status_delta * 256 + flagpole_bonus
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--local reward_delta = screen_scroll_delta + status_delta * 256 + flagpole_bonus
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local score_delta = get_score() - score_old
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if score_delta < 0 then score_delta = 0 end
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local reward_delta = screen_scroll_delta + score_delta + flagpole_bonus
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-- TODO: add ingame score to reward.
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@ -674,8 +744,9 @@ while true do
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--gui.text(4, 12, ("%02X"):format(#sprite_input), '#FFFFFF', '#0000003F')
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--gui.text(4, 22, ("%02X"):format(#tile_input), '#FFFFFF', '#0000003F')
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gui.text(72, 12, ("%+4i"):format(reward_delta), '#FFFFFF', '#0000003F')
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gui.text(112, 12, ("%+4i"):format(reward), '#FFFFFF', '#0000003F')
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--gui.text(72, 12, ("%+4i"):format(reward_delta), '#FFFFFF', '#0000003F')
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--gui.text(112, 12, ("%+4i"):format(reward), '#FFFFFF', '#0000003F')
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gui.text(96, 16, ("%+4i"):format(reward), '#FFFFFF', '#0000003F')
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if get_state() == 'dead' and state_old ~= 'dead' then
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--print("dead. lives remaining:", R(0x75A, 0))
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@ -698,7 +769,9 @@ while true do
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timer = timer - 1
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end
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timer = clamp(timer, 0, max_time)
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set_timer(timer)
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if enable_network then
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set_timer(timer)
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end
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-- if we've run out of time while the game is paused...
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-- that's cheating! unpause.
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@ -707,10 +780,19 @@ while true do
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local X = {} -- TODO: cache.
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for i, v in ipairs(sprite_input) do insert(X, v / 256) end
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for i, v in ipairs(tile_input) do insert(X, v / 256) end
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--error(#X)
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for i, v in ipairs(extra_input) do insert(X, v / 256) end
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if #X ~= input_size then error("input size should be: "..tostring(#X)) end
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if enable_network and get_state() == 'playing' or ingame_paused then
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local choose = deterministic and argmax2 or rchoice2
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local outputs = network:forward(X)
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-- TODO: predict the *rewards* of all possible actions?
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-- that's how DQN seems to work anyway.
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-- ah, but A3C just returns probabilities,
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-- besides the critic?
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local softmaxed = {
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outputs[nn_z[1]],
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outputs[nn_z[2]],
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@ -718,19 +800,29 @@ while true do
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outputs[nn_z[4]],
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outputs[nn_z[5]],
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outputs[nn_z[6]],
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outputs[nn_z[7]],
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outputs[nn_z[8]],
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learn_start_select and outputs[nn_z[7]] or dummy_softmax_values,
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learn_start_select and outputs[nn_z[8]] or dummy_softmax_values,
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}
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local jp = {
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up = argmax2(softmaxed[1]),
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down = argmax2(softmaxed[2]),
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left = argmax2(softmaxed[3]),
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right = argmax2(softmaxed[4]),
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A = argmax2(softmaxed[5]),
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B = argmax2(softmaxed[6]),
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start = argmax2(softmaxed[7]),
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select = argmax2(softmaxed[8]),
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up = choose(softmaxed[1]),
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down = choose(softmaxed[2]),
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left = choose(softmaxed[3]),
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right = choose(softmaxed[4]),
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A = choose(softmaxed[5]),
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B = choose(softmaxed[6]),
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start = choose(softmaxed[7]),
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select = choose(softmaxed[8]),
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}
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if det_epsilon then
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local eps = lerp(eps_start, eps_stop, total_frames / eps_frames)
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for k, v in pairs(jp) do
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local ss_ok = k ~= 'start' and k ~= 'select' or learn_start_select
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if random() < eps and ss_ok then jp[k] = rbool() end
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end
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end
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if force_start then
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jp = {
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up = false,
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@ -743,6 +835,7 @@ while true do
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select = false,
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}
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end
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joypad.write(1, jp)
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end
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@ -751,5 +844,6 @@ while true do
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status_old = status
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force_start_old = force_start
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state_old = get_state()
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score_old = get_score()
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advance()
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end
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29
nn.lua
29
nn.lua
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@ -173,6 +173,10 @@ function Layer:forward_deterministic(...)
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return self:forward(...)
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end
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function Layer:backward()
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error("Unimplemented.")
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end
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function Layer:_new_weights(init)
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local w = Weights(init)
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insert(self.weights, w)
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@ -227,6 +231,11 @@ function Input:forward(X)
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return X
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end
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function Input:backward(dY)
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assert(#dY == self.size_out)
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return zeros(#dY)
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end
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function Relu:init()
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Layer.init(self, "Relu")
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end
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@ -242,6 +251,18 @@ function Relu:forward(X)
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return Y
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end
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function Relu:backward(dY)
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assert(#dY == self.size_out)
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self.dcache = self.dcache or zeros(self.size_in)
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local Y = self.cache
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local dX = self.dcache
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for i = 1, #dY do dX[i] = Y[i] >= 0 and dY[i] or 0 end
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assert(#Y == self.size_in)
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return Y
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end
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function Gelu:init()
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Layer.init(self, "Gelu")
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end
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@ -383,8 +404,12 @@ function Model:distribute(W)
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end
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end
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function Model:default_filename()
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return ('network%07i.txt'):format(self.n_param)
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end
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function Model:save(fn)
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local fn = fn or 'network.txt'
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local fn = fn or self:default_filename()
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local f = open(fn, 'w')
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if f == nil then error("Failed to save network to file "..fn) end
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local W = self:collect()
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@ -396,7 +421,7 @@ function Model:save(fn)
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end
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function Model:load(fn)
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local fn = fn or 'network.txt'
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local fn = fn or self:default_filename()
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local f = open(fn, 'r')
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if f == nil then
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error("Failed to load network from file "..fn)
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