X-Git-Url: https://www.fleuret.org/cgi-bin/gitweb/gitweb.cgi?a=blobdiff_plain;f=tasks.py;h=f2b7709f1dc742979bad1e9a44e27da4525904d3;hb=1eeba5d817d6e440a93895d42f6e580e9ba273fd;hp=12c6125348691381a7bea80787f7da3107a45253;hpb=2bb362ef385f477da4af7d8679cc94d42cf6c146;p=picoclvr.git diff --git a/tasks.py b/tasks.py index 12c6125..f2b7709 100755 --- a/tasks.py +++ b/tasks.py @@ -1893,7 +1893,7 @@ class Escape(Task): states, actions, rewards = escape.generate_episodes( nb_train_samples + nb_test_samples, height, width, T, nb_walls ) - seq = escape.episodes2seq(states, actions, rewards, lookahead_delta=T) + seq = escape.episodes2seq(states, actions, rewards) # seq = seq[:, seq.size(1) // 3 : 2 * seq.size(1) // 3] self.train_input = seq[:nb_train_samples].to(self.device) self.test_input = seq[nb_train_samples:].to(self.device) @@ -1920,10 +1920,11 @@ class Escape(Task): t = torch.arange(result.size(1), device=result.device)[None, :] state_len = self.height * self.width - index_action = state_len - index_reward = state_len + 1 - index_lookahead_reward = state_len + 2 - it_len = state_len + 3 # state / action / reward / lookahead_reward + index_lookahead_reward = 0 + index_states = 1 + index_action = state_len + 1 + index_reward = state_len + 2 + it_len = state_len + 3 # lookahead_reward / state / action / reward result[:, it_len:] = -1 @@ -1952,20 +1953,16 @@ class Escape(Task): for u in tqdm.tqdm( range(it_len, result.size(1) - it_len + 1, it_len), desc="thinking" ): - # Re-generate the lookahead_reward pessimistically in the - # previous iterations - ar_mask = (t < u).long() * (t % it_len == index_lookahead_reward).long() - ar(result, ar_mask, logit_biases=-optimistic_bias) - snapshots.append(result[:10].detach().clone()) - - # Generate the state - ar_mask = (t >= u).long() * (t < u + state_len).long() + # Generate the lookahead_reward and state + ar_mask = (t >= u + index_lookahead_reward).long() * ( + t < u + index_states + state_len + ).long() ar(result, ar_mask) snapshots.append(result[:10].detach().clone()) + backup_lookahead_reward = result[:, u + index_lookahead_reward] - # Re-generate the lookahead_reward optimistically in the - # previous iterations - ar_mask = (t < u).long() * (t % it_len == index_lookahead_reward).long() + # Re-generate the lookahead_reward + ar_mask = (t == u + index_lookahead_reward).long() ar(result, ar_mask, logit_biases=optimistic_bias) snapshots.append(result[:10].detach().clone()) @@ -1974,12 +1971,14 @@ class Escape(Task): ar(result, ar_mask) snapshots.append(result[:10].detach().clone()) + result[:, u + index_lookahead_reward] = backup_lookahead_reward + filename = os.path.join(result_dir, f"test_thinking_compute_{n_epoch:04d}.txt") with open(filename, "w") as f: for n in range(10): for s in snapshots: lr, s, a, r = escape.seq2episodes( - s[n : n + 1], self.height, self.width, lookahead=True + s[n : n + 1], self.height, self.width ) str = escape.episodes2str( lr, s, a, r, unicode=True, ansi_colors=True @@ -1989,7 +1988,7 @@ class Escape(Task): # Saving the generated sequences - s, a, r, lr = escape.seq2episodes(result, self.height, self.width) + lr, s, a, r = escape.seq2episodes(result, self.height, self.width) str = escape.episodes2str(lr, s, a, r, unicode=True, ansi_colors=True) filename = os.path.join(result_dir, f"test_thinking_seq_{n_epoch:04d}.txt") @@ -2004,7 +2003,7 @@ class Escape(Task): # Saving the ground truth - s, a, r, lr = escape.seq2episodes( + lr, s, a, r = escape.seq2episodes( result, self.height, self.width, @@ -2036,7 +2035,7 @@ class Escape(Task): # Saving the generated sequences - s, a, r, lr = escape.seq2episodes( + lr, s, a, r = escape.seq2episodes( result, self.height, self.width,