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Update.
author
François Fleuret
<francois@fleuret.org>
Sun, 22 Oct 2023 15:07:10 +0000
(17:07 +0200)
committer
François Fleuret
<francois@fleuret.org>
Sun, 22 Oct 2023 15:07:10 +0000
(17:07 +0200)
problems.py
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diff --git
a/problems.py
b/problems.py
index
28e4f7b
..
51e90ed
100755
(executable)
--- a/
problems.py
+++ b/
problems.py
@@
-293,13
+293,26
@@
class ProblemMixing(Problem):
self.nb_time_steps = nb_time_steps
self.hard = hard
self.nb_time_steps = nb_time_steps
self.hard = hard
- def start(self, nb):
- return (
- torch.arange(self.height * self.width)
- .reshape(1, 1, self.height, self.width)
- .expand(nb, -1, -1, -1)
+ def start_random(self, nb):
+ y = torch.arange(self.height * self.width).reshape(1, -1).expand(nb, -1)
+
+ m = (torch.rand(y.size()).sort(dim=-1).indices < y.size(1) // 2).long()
+
+ y = (y * m + self.height * self.width * (1 - m)).reshape(
+ nb, self.height, self.width
)
)
+ return y
+
+ def start_error(self, x):
+ x = x.flatten(1)
+ u = torch.arange(self.height * self.width).reshape(1, -1)
+ m = ((x - u).abs() == 0).long()
+ d = (x - (m * u + (1-m) * self.height * self.width)).abs().sum(-1) + (
+ m.sum(dim=-1) != self.height * self.width // 2
+ ).long()
+ return d
+
def moves(self, x):
y = (
x[:, None, :, :]
def moves(self, x):
y = (
x[:, None, :, :]
@@
-323,8
+336,7
@@
class ProblemMixing(Problem):
return y
def generate_sequences(self, nb):
return y
def generate_sequences(self, nb):
- y = self.start(nb)
- x = y[torch.arange(nb), torch.randint(y.size(1), (nb,))]
+ x = self.start_random(nb)
seq = [x.flatten(1)]
seq = [x.flatten(1)]
@@
-349,8
+361,7
@@
class ProblemMixing(Problem):
x = a[0]
x = a[0]
- y = self.start(result.size(0)).to(x.device)
- d = (x[:, None] - y).abs().sum((-1, -2)).min(dim=-1).values
+ d = self.start_error(x)
for t in range(self.nb_time_steps - 1):
x0, x = a[t], a[t + 1]
for t in range(self.nb_time_steps - 1):
x0, x = a[t], a[t + 1]
@@
-375,7
+386,7
@@
class ProblemMixing(Problem):
####################
if __name__ == "__main__":
####################
if __name__ == "__main__":
- p = ProblemMixing(hard=True)
+ p = ProblemMixing(
width=4,
hard=True)
s, m = p.generate_sequences(10000)
for x in s[:5]:
print(p.seq2str(x))
s, m = p.generate_sequences(10000)
for x in s[:5]:
print(p.seq2str(x))