######################################################################
-nb_state_codes = 4
+nb_states_codes = 5
nb_actions_codes = 5
nb_rewards_codes = 3
-nb_lookahead_rewards_codes = 3
+nb_lookahead_rewards_codes = 4 # stands for -1, 0, +1, and UNKNOWN
-first_state_code = 0
-first_actions_code = first_state_code + nb_state_codes
+first_states_code = 0
+first_actions_code = first_states_code + nb_states_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 state2code(r):
+ return r + first_states_code
+
+
+def code2state(r):
+ return r - first_states_code
+
+
+def action2code(r):
+ return r + first_actions_code
+
+
+def code2action(r):
+ return r - first_actions_code
+
+
+def reward2code(r):
+ return r + 1 + first_rewards_code
+
+
+def code2reward(r):
+ return r - first_rewards_code - 1
+
+
+def lookahead_reward2code(r):
+ # -1, 0, +1 or 2 for UNKNOWN
+ return r + 1 + first_lookahead_rewards_code
+
+
+def code2lookahead_reward(r):
+ return r - first_lookahead_rewards_code - 1
+
+
+######################################################################
+
+
+def generate_episodes(nb, height=6, width=6, T=10, nb_walls=3, nb_coins=2):
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):
+ 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))
+ rnd = torch.rand(nb, height, width)
+ coins = torch.zeros(nb, T, height, width, dtype=torch.int64)
+ rnd = rnd * (1 - wall.clamp(max=1))
+ for k in range(nb_coins):
+ coins[:, 0] = coins[:, 0] + (
+ rnd.flatten(1).argmax(dim=1)[:, None]
+ == torch.arange(rnd.flatten(1).size(1))[None, :]
+ ).long().reshape(rnd.size())
+
+ rnd = rnd * (1 - coins[:, 0].clamp(max=1))
+
states = wall[:, None, :, :].expand(-1, T, -1, -1).clone()
agent = torch.zeros(states.size(), dtype=torch.int64)
)
hit = (hit > 0).long()
- assert hit.min() == 0 and hit.max() <= 1
+ # assert hit.min() == 0 and hit.max() <= 1
+
+ got_coin = (agent[:, t + 1] * coins[:, t]).flatten(1).sum(dim=1)
+ coins[:, t + 1] = coins[:, t] * (1 - agent[:, t + 1])
- rewards[:, t + 1] = -hit + (1 - hit) * agent[:, t + 1, -1, -1]
+ rewards[:, t + 1] = -hit + (1 - hit) * got_coin
- states += 2 * agent + 3 * monster
+ states = states + 2 * agent + 3 * monster + 4 * coins
return states, agent_actions, rewards
######################################################################
-def episodes2seq(states, actions, rewards, lookahead_delta=None):
- states = states.flatten(2) + first_state_code
- 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
- # 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
+def episodes2seq(states, actions, rewards):
+ neg = rewards.new_zeros(rewards.size())
+ pos = rewards.new_zeros(rewards.size())
+ for t in range(neg.size(1) - 1):
+ neg[:, t] = rewards[:, t:].min(dim=-1).values
+ pos[:, t] = rewards[:, t:].max(dim=-1).values
+ s = (neg < 0).long() * neg + (neg >= 0).long() * pos
+
+ return torch.cat(
+ [
+ lookahead_reward2code(s[:, :, None]),
+ state2code(states.flatten(2)),
+ action2code(actions[:, :, None]),
+ reward2code(rewards[:, :, None]),
+ ],
+ dim=2,
+ ).flatten(1)
+
+
+def seq2episodes(seq, height, width):
+ seq = seq.reshape(seq.size(0), -1, height * width + 3)
+ lookahead_rewards = code2lookahead_reward(seq[:, :, 0])
+ states = code2state(seq[:, :, 1 : height * width + 1])
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
-
- if lookahead:
- lookahead_rewards = (
- seq[:, :, height * width + 2] - first_lookahead_rewards_code - 1
- )
- return states, actions, rewards, lookahead_rewards
- else:
- return states, actions, rewards
+ actions = code2action(seq[:, :, height * width + 1])
+ rewards = code2reward(seq[:, :, height * width + 2])
+ return lookahead_rewards, states, actions, rewards
def seq2str(seq):
def token2str(t):
- if t >= first_state_code and t < first_state_code + nb_state_codes:
- return " #@$"[t - first_state_code]
+ if t >= first_states_code and t < first_states_code + nb_states_codes:
+ return " #@T$"[t - first_states_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:
t >= first_lookahead_rewards_code
and t < first_lookahead_rewards_code + nb_lookahead_rewards_codes
):
- return "n.p"[t - first_lookahead_rewards_code]
+ return "n.pU"[t - first_lookahead_rewards_code]
else:
return "?"
def episodes2str(
- states, actions, rewards, lookahead_rewards=None, unicode=False, ansi_colors=False
+ lookahead_rewards, states, actions, rewards, unicode=False, ansi_colors=False
):
if unicode:
- symbols = "·█@$"
+ symbols = "·█@T$"
# vert, hori, cross, thin_hori = "║", "═", "╬", "─"
vert, hori, cross, thin_vert, thin_hori = "┃", "━", "╋", "│", "─"
else:
- symbols = " #@$"
+ symbols = " #@T$"
vert, hori, cross, thin_vert, thin_hori = "|", "-", "+", "|", "-"
hline = (cross + hori * states.size(-1)) * states.size(1) + cross + "\n"
+ sb_lr
)
- 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 += (
+ 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
######################################################################
if __name__ == "__main__":
- nb, height, width, T = 25, 5, 7, 25
- states, actions, rewards = generate_episodes(nb, height, width, T)
- 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))
+ nb, height, width, T, nb_walls = 5, 5, 7, 10, 5
+ states, actions, rewards = generate_episodes(nb, height, width, T, nb_walls)
+ seq = episodes2seq(states, actions, rewards)
+ lr, s, a, r = seq2episodes(seq, height, width)
+ print(episodes2str(lr, s, a, r, unicode=True, ansi_colors=True))
# print()
# for s in seq2str(seq):
# print(s)
projects / picoclvr.git / blobdiff