X-Git-Url: https://fleuret.org/cgi-bin/gitweb/gitweb.cgi?a=blobdiff_plain;f=problems.py;h=b8fcdb34b32a07e8fd46900c88d889c3cf9761ea;hb=76e62a5782fc2509ce989fcfc0d0aedc17322b3a;hp=51e90ed53237d25466f382e1cb101542b20999a3;hpb=559a50b8cd74180311d3347254c9cc84b794afa2;p=picoclvr.git diff --git a/problems.py b/problems.py index 51e90ed..b8fcdb3 100755 --- a/problems.py +++ b/problems.py @@ -287,7 +287,7 @@ class ProblemAddition(Problem): 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): self.height = height self.width = width self.nb_time_steps = nb_time_steps @@ -296,7 +296,15 @@ class ProblemMixing(Problem): 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() + # m = (torch.rand(y.size()).sort(dim=-1).indices < y.size(1) // 2).long() + + 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) + + m = 1 - torch.logical_or(i==ri,j==rj).long().flatten(1) y = (y * m + self.height * self.width * (1 - m)).reshape( nb, self.height, self.width @@ -305,12 +313,18 @@ class ProblemMixing(Problem): 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): @@ -376,7 +390,7 @@ class ProblemMixing(Problem): 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) ] @@ -386,7 +400,7 @@ class ProblemMixing(Problem): #################### 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))