X-Git-Url: https://fleuret.org/cgi-bin/gitweb/gitweb.cgi?a=blobdiff_plain;f=escape.py;h=f51863b0c42e9c4c0d38fa334296c6ebfca9ed04;hb=19ec7f3e4030ddece2647983dcf1bed5eb0d9544;hp=aa87cddd728220933bcba5d137a36953ad4b08b8;hpb=a85b2f79ae551da3454daa7b90554be5ca3c5bf6;p=picoclvr.git diff --git a/escape.py b/escape.py index aa87cdd..f51863b 100755 --- a/escape.py +++ b/escape.py @@ -12,18 +12,20 @@ from torch.nn import functional as F ###################################################################### nb_state_codes = 4 -nb_rewards_codes = 3 nb_actions_codes = 5 +nb_rewards_codes = 3 +nb_lookahead_rewards_codes = 3 first_state_code = 0 -first_rewards_code = first_state_code + nb_state_codes -first_actions_code = first_rewards_code + nb_rewards_codes -nb_codes = first_actions_code + nb_actions_codes +first_actions_code = first_state_code + nb_state_codes +first_rewards_code = first_actions_code + nb_actions_codes +first_lookahead_rewards_code = first_rewards_code + nb_rewards_codes +nb_codes = first_lookahead_rewards_code + nb_lookahead_rewards_codes ###################################################################### -def generate_episodes(nb, height=6, width=6, T=10): +def generate_episodes(nb, height=6, width=6, T=10, nb_walls=3): rnd = torch.rand(nb, height, width) rnd[:, 0, :] = 0 rnd[:, -1, :] = 0 @@ -31,11 +33,12 @@ def generate_episodes(nb, height=6, width=6, T=10): rnd[:, :, -1] = 0 wall = 0 - for k in range(3): + for k in range(nb_walls): wall = wall + ( rnd.flatten(1).argmax(dim=1)[:, None] == torch.arange(rnd.flatten(1).size(1))[None, :] ).long().reshape(rnd.size()) + rnd = rnd * (1 - wall.clamp(max=1)) states = wall[:, None, :, :].expand(-1, T, -1, -1).clone() @@ -91,7 +94,7 @@ def generate_episodes(nb, height=6, width=6, T=10): ) hit = (hit > 0).long() - assert hit.min() == 0 and hit.max() <= 1 + # assert hit.min() == 0 and hit.max() <= 1 rewards[:, t + 1] = -hit + (1 - hit) * agent[:, t + 1, -1, -1] @@ -103,47 +106,107 @@ def generate_episodes(nb, height=6, width=6, T=10): ###################################################################### -def episodes2seq(states, actions, rewards): +def episodes2seq(states, actions, rewards, lookahead_delta=None): states = states.flatten(2) + first_state_code actions = actions[:, :, None] + first_actions_code - rewards = (rewards[:, :, None] + 1) + first_rewards_code - - assert ( - states.min() >= first_state_code - and states.max() < first_state_code + nb_state_codes - ) - assert ( - actions.min() >= first_actions_code - and actions.max() < first_actions_code + nb_actions_codes - ) - assert ( - rewards.min() >= first_rewards_code - and rewards.max() < first_rewards_code + nb_rewards_codes - ) - - return torch.cat([states, actions, rewards], dim=2).flatten(1) - - -def seq2episodes(seq, height, width): - seq = seq.reshape(seq.size(0), -1, height * width + 2) + + if lookahead_delta is not None: + # r = rewards + # u = F.pad(r, (0, lookahead_delta - 1)).as_strided( + # (r.size(0), r.size(1), lookahead_delta), + # (r.size(1) + lookahead_delta - 1, 1, 1), + # ) + # a = u[:, :, 1:].min(dim=-1).values + # b = u[:, :, 1:].max(dim=-1).values + # s = (a < 0).long() * a + (a >= 0).long() * b + # lookahead_rewards = (1 + s[:, :, None]) + first_lookahead_rewards_code + + # a[n,t]=min_s>t r[n,s] + a = rewards.new_zeros(rewards.size()) + b = rewards.new_zeros(rewards.size()) + for t in range(a.size(1) - 1): + a[:, t] = rewards[:, t + 1 :].min(dim=-1).values + b[:, t] = rewards[:, t + 1 :].max(dim=-1).values + s = (a < 0).long() * a + (a >= 0).long() * b + lookahead_rewards = (1 + s[:, :, None]) + first_lookahead_rewards_code + + r = rewards[:, :, None] + rewards = (r + 1) + first_rewards_code + + # assert ( + # states.min() >= first_state_code + # and states.max() < first_state_code + nb_state_codes + # ) + # assert ( + # actions.min() >= first_actions_code + # and actions.max() < first_actions_code + nb_actions_codes + # ) + # assert ( + # rewards.min() >= first_rewards_code + # and rewards.max() < first_rewards_code + nb_rewards_codes + # ) + + if lookahead_delta is None: + return torch.cat([states, actions, rewards], dim=2).flatten(1) + else: + # assert ( + # lookahead_rewards.min() >= first_lookahead_rewards_code + # and lookahead_rewards.max() + # < first_lookahead_rewards_code + nb_lookahead_rewards_codes + # ) + return torch.cat([states, actions, rewards, lookahead_rewards], dim=2).flatten( + 1 + ) + + +def seq2episodes(seq, height, width, lookahead=False): + seq = seq.reshape(seq.size(0), -1, height * width + (3 if lookahead else 2)) states = seq[:, :, : height * width] - first_state_code states = states.reshape(states.size(0), states.size(1), height, width) actions = seq[:, :, height * width] - first_actions_code rewards = seq[:, :, height * width + 1] - first_rewards_code - 1 - return states, actions, rewards + + if lookahead: + lookahead_rewards = ( + seq[:, :, height * width + 2] - first_lookahead_rewards_code - 1 + ) + return states, actions, rewards, lookahead_rewards + else: + return states, actions, rewards + + +def seq2str(seq): + def token2str(t): + if t >= first_state_code and t < first_state_code + nb_state_codes: + return " #@$"[t - first_state_code] + elif t >= first_actions_code and t < first_actions_code + nb_actions_codes: + return "ISNEW"[t - first_actions_code] + elif t >= first_rewards_code and t < first_rewards_code + nb_rewards_codes: + return "-0+"[t - first_rewards_code] + elif ( + t >= first_lookahead_rewards_code + and t < first_lookahead_rewards_code + nb_lookahead_rewards_codes + ): + return "n.p"[t - first_lookahead_rewards_code] + else: + return "?" + + return ["".join([token2str(x.item()) for x in row]) for row in seq] ###################################################################### -def episodes2str(states, actions, rewards, unicode=False, ansi_colors=False): +def episodes2str( + states, actions, rewards, lookahead_rewards=None, unicode=False, ansi_colors=False +): if unicode: - symbols = " █@$" + symbols = "·█@$" # vert, hori, cross, thin_hori = "║", "═", "╬", "─" - vert, hori, cross, thin_hori = "┃", "━", "╋", "─" + vert, hori, cross, thin_vert, thin_hori = "┃", "━", "╋", "│", "─" else: symbols = " #@$" - vert, hori, cross, thin_hori = "|", "-", "+", "-" + vert, hori, cross, thin_vert, thin_hori = "|", "-", "+", "|", "-" hline = (cross + hori * states.size(-1)) * states.size(1) + cross + "\n" @@ -165,20 +228,46 @@ def episodes2str(states, actions, rewards, unicode=False, ansi_colors=False): + "\n" ) - result += (vert + thin_hori * states.size(-1)) * states.size(1) + vert + "\n" - - def status_bar(a, r): - a = a.item() - a = "ISNEW"[a] if a >= 0 and a < 5 else "?" - r = "?" if r < -1 or r > 2 else ("" if r == 0 else f"{r.item()}") - return a + " " * (states.size(-1) - len(a) - len(r)) + r + # result += (vert + thin_hori * states.size(-1)) * states.size(1) + vert + "\n" + + def status_bar(a, r, lr=None): + a, r = a.item(), r.item() + sb_a = "ISNEW"[a] if a >= 0 and a < 5 else "?" + sb_r = "- +"[r + 1] if r in {-1, 0, 1} else "?" + if lr is None: + sb_lr = "" + else: + lr = lr.item() + sb_lr = "n p"[lr + 1] if lr in {-1, 0, 1} else "?" + return ( + sb_a + + "/" + + sb_r + + " " * (states.size(-1) - 1 - len(sb_a + sb_r + sb_lr)) + + sb_lr + ) - result += ( - vert - + vert.join([status_bar(a, r) for a, r in zip(actions[n], rewards[n])]) - + vert - + "\n" - ) + if lookahead_rewards is None: + result += ( + vert + + vert.join([status_bar(a, r) for a, r in zip(actions[n], rewards[n])]) + + vert + + "\n" + ) + else: + result += ( + vert + + vert.join( + [ + status_bar(a, r, lr) + for a, r, lr in zip( + actions[n], rewards[n], lookahead_rewards[n] + ) + ] + ) + + vert + + "\n" + ) result += hline @@ -192,8 +281,11 @@ def episodes2str(states, actions, rewards, unicode=False, ansi_colors=False): ###################################################################### if __name__ == "__main__": - nb, height, width, T = 8, 4, 6, 20 - states, actions, rewards = generate_episodes(nb, height, width, T) - seq = episodes2seq(states, actions, rewards) - s, a, r = seq2episodes(seq, height, width) - print(episodes2str(s, a, r, unicode=True, ansi_colors=True)) + nb, height, width, T, nb_walls = 25, 5, 7, 25, 5 + states, actions, rewards = generate_episodes(nb, height, width, T, nb_walls) + seq = episodes2seq(states, actions, rewards, lookahead_delta=T) + s, a, r, lr = seq2episodes(seq, height, width, lookahead=True) + print(episodes2str(s, a, r, lookahead_rewards=lr, unicode=True, ansi_colors=True)) + # print() + # for s in seq2str(seq): + # print(s)