######################################################################
-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
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()
)
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]
actions = actions[:, :, None] + first_actions_code
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
+ # 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
- )
+ # 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
- )
+ # 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
)
return states, actions, rewards
+def seq2str(seq):
+ def token2str(t):
+ if t >= first_state_code and t < first_state_code + nb_state_codes:
+ return " #@$"[t - first_state_code]
+ elif t >= first_actions_code and t < first_actions_code + nb_actions_codes:
+ return "ISNEW"[t - first_actions_code]
+ elif t >= first_rewards_code and t < first_rewards_code + nb_rewards_codes:
+ return "-0+"[t - first_rewards_code]
+ elif (
+ t >= first_lookahead_rewards_code
+ and t < first_lookahead_rewards_code + nb_lookahead_rewards_codes
+ ):
+ return "n.p"[t - first_lookahead_rewards_code]
+ else:
+ return "?"
+
+ return ["".join([token2str(x.item()) for x in row]) for row in seq]
+
+
######################################################################
states, actions, rewards, lookahead_rewards=None, unicode=False, ansi_colors=False
):
if unicode:
- symbols = " █@$"
+ symbols = "·█@$"
# vert, hori, cross, thin_hori = "║", "═", "╬", "─"
vert, hori, cross, thin_vert, thin_hori = "┃", "━", "╋", "│", "─"
else:
+ "\n"
)
- result += (vert + thin_hori * states.size(-1)) * states.size(1) + vert + "\n"
+ # 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 not None:
+ sb_r = "- +"[r + 1] if r in {-1, 0, 1} else "?"
+ if lr is None:
+ sb_lr = ""
+ else:
lr = lr.item()
- sb_r = sb_r + "/" + ("- +"[lr + 1] if lr in {-1, 0, 1} else "?")
- return sb_a + " " * (states.size(-1) - len(sb_a) - len(sb_r)) + sb_r
+ 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
+ )
if lookahead_rewards is None:
result += (
######################################################################
if __name__ == "__main__":
- nb, height, width, T = 10, 4, 6, 20
- states, actions, rewards = generate_episodes(nb, height, width, T)
+ 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)