Update.
authorFrançois Fleuret <francois@fleuret.org>
Sun, 22 Oct 2023 17:54:13 +0000 (19:54 +0200)
committerFrançois Fleuret <francois@fleuret.org>
Sun, 22 Oct 2023 17:54:13 +0000 (19:54 +0200)
problems.py

index b8fcdb3..632c059 100755 (executable)
@@ -298,13 +298,21 @@ class ProblemMixing(Problem):
 
         # 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)
+        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)
+        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)
+        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
@@ -313,16 +321,20 @@ 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)
+        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)
+        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)
+        m = 1 - torch.logical_or(i == ri, j == rj).long().flatten(1)
 
         x = x.flatten(1)
-        u = torch.arange(self.height * self.width, device = x.device).reshape(1, -1)
+        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
@@ -390,7 +402,15 @@ class ProblemMixing(Problem):
         return " | ".join(
             [
                 " ".join(
-                    ["-".join([f"{x:02d}" if x < self.height * self.width else "**" 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)
             ]