projects
/
culture.git
/ blobdiff
commit
grep
author
committer
pickaxe
?
search:
re
summary
|
shortlog
|
log
|
commit
|
commitdiff
|
tree
raw
|
inline
| side by side
Oups
[culture.git]
/
tasks.py
diff --git
a/tasks.py
b/tasks.py
index
324376d
..
c0ad5ff
100755
(executable)
--- a/
tasks.py
+++ b/
tasks.py
@@
-63,7
+63,7
@@
def masked_inplace_autoregression(
class Task:
class Task:
- def batches(self, split="train"):
+ def batches(self, split="train"
, nb_to_use=-1, desc=None
):
pass
def vocabulary_size(self):
pass
def vocabulary_size(self):
@@
-489,7
+489,7
@@
class PicoCLVR(Task):
self.train_input = self.tensorize(self.train_descr)
self.test_input = self.tensorize(self.test_descr)
self.train_input = self.tensorize(self.train_descr)
self.test_input = self.tensorize(self.test_descr)
- def batches(self, split="train"):
+ def batches(self, split="train"
, nb_to_use=-1, desc=None
):
assert split in {"train", "test"}
input = self.train_input if split == "train" else self.test_input
for batch in tqdm.tqdm(
assert split in {"train", "test"}
input = self.train_input if split == "train" else self.test_input
for batch in tqdm.tqdm(
@@
-1685,7
+1685,7
@@
class Grid(Task):
self.t_nul = self.token2id["#"]
self.t_true = self.token2id["true"]
self.t_false = self.token2id["false"]
self.t_nul = self.token2id["#"]
self.t_true = self.token2id["true"]
self.t_false = self.token2id["false"]
- self.t_pipe = self.token2id["|"]
+
#
self.t_pipe = self.token2id["|"]
# Tokenize the train and test sets
self.train_input = self.str2tensor(self.train_descr)
# Tokenize the train and test sets
self.train_input = self.str2tensor(self.train_descr)
@@
-1694,7
+1694,7
@@
class Grid(Task):
None if len(self.play_descr) == 0 else self.str2tensor(self.play_descr)
)
None if len(self.play_descr) == 0 else self.str2tensor(self.play_descr)
)
- def batches(self, split="train"):
+ def batches(self, split="train"
, nb_to_use=-1, desc=None
):
assert split in {"train", "test"}
input = self.train_input if split == "train" else self.test_input
for batch in tqdm.tqdm(
assert split in {"train", "test"}
input = self.train_input if split == "train" else self.test_input
for batch in tqdm.tqdm(
@@
-1823,7
+1823,7
@@
class QMLP(Task):
self.nb_codes = max(self.train_input.max(), self.test_input.max()) + 1
self.nb_codes = max(self.train_input.max(), self.test_input.max()) + 1
- def batches(self, split="train"):
+ def batches(self, split="train"
, nb_to_use=-1, desc=None
):
assert split in {"train", "test"}
input = self.train_input if split == "train" else self.test_input
for batch in tqdm.tqdm(
assert split in {"train", "test"}
input = self.train_input if split == "train" else self.test_input
for batch in tqdm.tqdm(
@@
-1944,7
+1944,7
@@
class Greed(Task):
progress_bar_desc=None,
)
warnings.warn("keeping thinking snapshots", RuntimeWarning)
progress_bar_desc=None,
)
warnings.warn("keeping thinking snapshots", RuntimeWarning)
- snapshots.append(result[:10].detach().clone())
+ snapshots.append(result[:10
0
].detach().clone())
# Generate iteration after iteration
# Generate iteration after iteration
@@
-1986,11
+1986,11
@@
class Greed(Task):
# Set the lookahead_reward to UNKNOWN for the next iterations
result[
:, u + self.world.index_lookahead_reward
# Set the lookahead_reward to UNKNOWN for the next iterations
result[
:, u + self.world.index_lookahead_reward
- ] = self.world.lookahead_reward2code(gree.REWARD_UNKNOWN)
+ ] = self.world.lookahead_reward2code(gree
d
.REWARD_UNKNOWN)
filename = os.path.join(result_dir, f"test_thinking_compute_{n_epoch:04d}.txt")
with open(filename, "w") as f:
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 n in range(
snapshots[0].size(0)
):
for s in snapshots:
lr, s, a, r = self.world.seq2episodes(
s[n : n + 1],
for s in snapshots:
lr, s, a, r = self.world.seq2episodes(
s[n : n + 1],