####################
+
+
class ProblemDegradation(Problem):
def __init__(self, nb_state_tokens=5, nb_time_steps=12, value_max=25, hard=False):
assert value_max // nb_state_tokens >= 2
class ProblemMixing(Problem):
- def __init__(self, height=3, width=3, nb_time_steps=12, hard=False):
+ def __init__(
+ self, height=4, width=4, nb_time_steps=9, hard=False, random_start=True
+ ):
self.height = height
self.width = width
self.nb_time_steps = nb_time_steps
self.hard = hard
+ self.random_start = random_start
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()
+ if self.random_start:
+ i = (
+ torch.arange(self.height)
+ .reshape(1, -1, 1)
+ .expand(nb, self.height, self.width)
+ )
+ j = (
+ torch.arange(self.width)
+ .reshape(1, 1, -1)
+ .expand(nb, self.height, self.width)
+ )
+
+ ri = torch.randint(self.height, (nb,)).reshape(nb, 1, 1)
+ rj = torch.randint(self.width, (nb,)).reshape(nb, 1, 1)
- y = (y * m + self.height * self.width * (1 - m)).reshape(
- nb, self.height, self.width
- )
+ m = 1 - torch.logical_or(i == ri, j == rj).long().flatten(1)
+
+ y = y * m + self.height * self.width * (1 - m)
+
+ y = y.reshape(nb, self.height, self.width)
return y
def start_error(self, x):
+ i = torch.arange(self.height, device=x.device).reshape(1, -1, 1).expand_as(x)
+ j = torch.arange(self.width, device=x.device).reshape(1, 1, -1).expand_as(x)
+
+ ri = (
+ (x == self.height * self.width).long().sum(dim=-1).argmax(-1).view(-1, 1, 1)
+ )
+ rj = (
+ (x == self.height * self.width).long().sum(dim=-2).argmax(-1).view(-1, 1, 1)
+ )
+
+ m = 1 - torch.logical_or(i == ri, j == rj).long().flatten(1)
+
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()
+ u = torch.arange(self.height * self.width, device=x.device).reshape(1, -1)
+
+ d = (x - (m * u + (1 - m) * self.height * self.width)).abs().sum(-1)
return d
def moves(self, x):
return " | ".join(
[
" ".join(
- ["-".join([f"{x:02d}" for x in s]) for s in r.split(self.width)]
+ [
+ "-".join(
+ [
+ f"{x:02d}" if x < self.height * self.width else "**"
+ for x in s
+ ]
+ )
+ for s in r.split(self.width)
+ ]
)
for r in seq.split(self.height * self.width)
]
####################
if __name__ == "__main__":
- p = ProblemMixing(width=4, hard=True)
+ p = ProblemMixing()
s, m = p.generate_sequences(10000)
for x in s[:5]:
print(p.seq2str(x))