X-Git-Url: https://fleuret.org/cgi-bin/gitweb/gitweb.cgi?a=blobdiff_plain;f=evasion.py;fp=evasion.py;h=0000000000000000000000000000000000000000;hb=22b841a39cc73310cd03dbd1d32fb387f68521d0;hp=9f37494a41cbe21722ed744c95aa6d8850e0177f;hpb=734db1d1d2a34ccc5258babd483ddb96e22e676e;p=picoclvr.git diff --git a/evasion.py b/evasion.py deleted file mode 100755 index 9f37494..0000000 --- a/evasion.py +++ /dev/null @@ -1,191 +0,0 @@ -#!/usr/bin/env python - -import torch - -from torch.nn import functional as F - -###################################################################### - -nb_state_codes = 4 -nb_rewards_codes = 3 -nb_actions_codes = 5 - -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 - -###################################################################### - - -def generate_episodes(nb, height=6, width=6, T=10): - rnd = torch.rand(nb, height, width) - rnd[:, 0, :] = 0 - rnd[:, -1, :] = 0 - rnd[:, :, 0] = 0 - rnd[:, :, -1] = 0 - wall = 0 - - for k in range(3): - 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() - - agent = torch.zeros(states.size(), dtype=torch.int64) - agent[:, 0, 0, 0] = 1 - agent_actions = torch.randint(5, (nb, T)) - rewards = torch.zeros(nb, T, dtype=torch.int64) - - monster = torch.zeros(states.size(), dtype=torch.int64) - monster[:, 0, -1, -1] = 1 - monster_actions = torch.randint(5, (nb, T)) - - all_moves = agent.new(nb, 5, height, width) - for t in range(T - 1): - all_moves.zero_() - all_moves[:, 0] = agent[:, t] - all_moves[:, 1, 1:, :] = agent[:, t, :-1, :] - all_moves[:, 2, :-1, :] = agent[:, t, 1:, :] - all_moves[:, 3, :, 1:] = agent[:, t, :, :-1] - all_moves[:, 4, :, :-1] = agent[:, t, :, 1:] - a = F.one_hot(agent_actions[:, t], num_classes=5)[:, :, None, None] - after_move = (all_moves * a).sum(dim=1) - collision = ( - (after_move * (1 - wall) * (1 - monster[:, t])) - .flatten(1) - .sum(dim=1)[:, None, None] - == 0 - ).long() - agent[:, t + 1] = collision * agent[:, t] + (1 - collision) * after_move - - all_moves.zero_() - all_moves[:, 0] = monster[:, t] - all_moves[:, 1, 1:, :] = monster[:, t, :-1, :] - all_moves[:, 2, :-1, :] = monster[:, t, 1:, :] - all_moves[:, 3, :, 1:] = monster[:, t, :, :-1] - all_moves[:, 4, :, :-1] = monster[:, t, :, 1:] - a = F.one_hot(monster_actions[:, t], num_classes=5)[:, :, None, None] - after_move = (all_moves * a).sum(dim=1) - collision = ( - (after_move * (1 - wall) * (1 - agent[:, t + 1])) - .flatten(1) - .sum(dim=1)[:, None, None] - == 0 - ).long() - monster[:, t + 1] = collision * monster[:, t] + (1 - collision) * after_move - - hit = ( - (agent[:, t + 1, 1:, :] * monster[:, t + 1, :-1, :]).flatten(1).sum(dim=1) - + (agent[:, t + 1, :-1, :] * monster[:, t + 1, 1:, :]).flatten(1).sum(dim=1) - + (agent[:, t + 1, :, 1:] * monster[:, t + 1, :, :-1]).flatten(1).sum(dim=1) - + (agent[:, t + 1, :, :-1] * monster[:, t + 1, :, 1:]).flatten(1).sum(dim=1) - ) - hit = (hit > 0).long() - - assert hit.min() == 0 and hit.max() <= 1 - - rewards[:, t + 1] = -hit + (1 - hit) * agent[:, t + 1, -1, -1] - - states += 2 * agent + 3 * monster - - return states, agent_actions, rewards - - -###################################################################### - - -def episodes2seq(states, actions, rewards): - 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) - 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 - - -###################################################################### - - -def episodes2str(states, actions, rewards, unicode=False, ansi_colors=False): - if unicode: - symbols = " █@$" - # vert, hori, cross, thin_hori = "║", "═", "╬", "─" - vert, hori, cross, thin_hori = "┃", "━", "╋", "─" - else: - symbols = " #@$" - vert, hori, cross, thin_hori = "|", "-", "+", "-" - - hline = (cross + hori * states.size(-1)) * states.size(1) + cross + "\n" - - result = hline - - for n in range(states.size(0)): - for i in range(states.size(2)): - result += ( - vert - + vert.join( - [ - "".join([symbols[v.item()] for v in row]) - for row in states[n, :, i] - ] - ) - + vert - + "\n" - ) - - result += (vert + thin_hori * states.size(-1)) * states.size(1) + vert + "\n" - - def status_bar(a, r): - a = "ISNEW"[a.item()] - r = "" if r == 0 else f"{r.item()}" - return a + " " * (states.size(-1) - len(a) - len(r)) + r - - result += ( - vert - + vert.join([status_bar(a, r) for a, r in zip(actions[n], rewards[n])]) - + vert - + "\n" - ) - - result += hline - - if ansi_colors: - for u, c in [("$", 31), ("@", 32)]: - result = result.replace(u, f"\u001b[{c}m{u}\u001b[0m") - - return result - - -###################################################################### - -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))