Update.

diff --git a/grids.py b/grids.py
index aa21543..e651940 100755 (executable)
--- a/grids.py
+++ b/grids.py
@@ -143,7 +143,7 @@ class Grids(problem.Problem):
             self.task_scale,
             self.task_symbols,
             self.task_isometry,
             self.task_scale,
             self.task_symbols,
             self.task_isometry,

-            #            self.task_path,
+            self.task_islands,

         ]
 
         if tasks is None:
         ]
 
         if tasks is None:


@@ -628,8 +628,8 @@ class Grids(problem.Problem):
                             1000,
                             self.height,
                             self.width,
                             1000,
                             self.height,
                             self.width,

-                            nb_seeds=self.height * self.width // 9,
-                            nb_iterations=self.height * self.width // 20,
+                            nb_seeds=self.height * self.width // 8,
+                            nb_iterations=self.height * self.width // 10,

                         )
                     )
 
                         )
                     )
 


@@ -1051,65 +1051,30 @@ class Grids(problem.Problem):
     def task_islands(self, A, f_A, B, f_B):
         c = torch.randperm(len(self.colors) - 1)[:2] + 1
         for X, f_X in [(A, f_A), (B, f_B)]:
     def task_islands(self, A, f_A, B, f_B):
         c = torch.randperm(len(self.colors) - 1)[:2] + 1
         for X, f_X in [(A, f_A), (B, f_B)]:

-            while True:
-                k = torch.randperm(self.height * self.width)
-                Z = torch.zeros(self.height + 2, self.width + 2)
-
-                i0, j0 = (
-                    torch.randint(self.height, (1,)).item() + 1,
-                    torch.randint(self.width, (1,)).item() + 1,
+            if not hasattr(self, "cache_islands") or len(self.cache_islands) == 0:
+                self.cache_islands = list(
+                    grow_islands(
+                        1000,
+                        self.height,
+                        self.width,
+                        nb_seeds=self.height * self.width // 20,
+                        nb_iterations=self.height * self.width // 2,
+                    )

                 )
 
                 )
 

-                Z[i0 - 1 : i0 + 2, j0 - 1 : j0 + 2] = 1
-
-                nb = 9
-
-                for q in k:
-                    i, j = q % self.height + 1, q // self.height + 1
-
-                    if Z[i, j] == 0:
-                        r, s, t, u, v, w, x, y = (
-                            Z[i - 1, j],
-                            Z[i - 1, j + 1],
-                            Z[i, j + 1],
-                            Z[i + 1, j + 1],
-                            Z[i + 1, j],
-                            Z[i + 1, j - 1],
-                            Z[i, j - 1],
-                            Z[i - 1, j - 1],
-                        )
-
-                        if (
-                            (nb < 16 or r + s + t + u + v + w + x + y > 0)
-                            and (s == 0 or r + t > 0)
-                            and (u == 0 or t + v > 0)
-                            and (w == 0 or x + v > 0)
-                            and (y == 0 or x + r > 0)
-                        ):
-                            # if r+s+t+u+v+w+x+y==0:
-                            Z[i, j] = 1
-                            nb += 1
-
-                    if nb == self.height * self.width // 2:
-                        break
-
-                if nb == self.height * self.width // 2:
-                    break
-
-            M = Z.clone()
-            Z[i0, j0] = 2
-            X[...] = (Z[1:-1, 1:-1] == 1) * c[0] + (Z[1:-1, 1:-1] == 2) * c[1]
+            A = self.cache_islands.pop()

 
 

-            for _ in range(self.height + self.width):
-                Z[1:-1, 1:-1] = Z[1:-1, 1:-1].maximum(
-                    torch.maximum(
-                        torch.maximum(Z[0:-2, 1:-1], Z[2:, 1:-1]),
-                        torch.maximum(Z[1:-1, 0:-2], Z[1:-1, 2:]),
-                    )
+            while True:
+                i, j = (
+                    torch.randint(self.height // 2, (1,)).item(),
+                    torch.randint(self.width // 2, (1,)).item(),

                 )
                 )

-                Z *= M
+                if A[i, j] > 0:
+                    break

 
 

-            f_X[...] = (Z[1:-1, 1:-1] == 1) * c[0] + (Z[1:-1, 1:-1] == 2) * c[1]
+            X[...] = (A > 0) * c[0]
+            X[i, j] = c[1]
+            f_X[...] = (A == A[i, j]) * c[1] + ((A > 0) & (A != A[i, j])) * c[0]

 
     ######################################################################
 
 
     ######################################################################
 


@@ -1201,7 +1166,7 @@ if __name__ == "__main__":
     # nb, nrow = 8, 2
 
     # for t in grids.all_tasks:
     # nb, nrow = 8, 2
 
     # for t in grids.all_tasks:

-    for t in [grids.task_count]:
+    for t in [grids.task_islands]:

         print(t.__name__)
         prompts, answers = grids.generate_prompts_and_answers_(nb, tasks=[t])
         grids.save_quiz_illustrations(
         print(t.__name__)
         prompts, answers = grids.generate_prompts_and_answers_(nb, tasks=[t])
         grids.save_quiz_illustrations(


@@ -1213,7 +1178,7 @@ if __name__ == "__main__":
     nb = 1000
 
     # for t in grids.all_tasks:
     nb = 1000
 
     # for t in grids.all_tasks:

-    for t in [grids.task_count]:
+    for t in [grids.task_islands]:

         start_time = time.perf_counter()
         prompts, answers = grids.generate_prompts_and_answers_(nb, tasks=[t])
         delay = time.perf_counter() - start_time
         start_time = time.perf_counter()
         prompts, answers = grids.generate_prompts_and_answers_(nb, tasks=[t])
         delay = time.perf_counter() - start_time

diff --git a/quiz_machine.py b/quiz_machine.py
index ef766c4..c49ecf2 100755 (executable)
--- a/quiz_machine.py
+++ b/quiz_machine.py
@@ -219,9 +219,6 @@ class QuizMachine:
     def generate_token_sequences(self, nb):
         prompts, answers = self.problem.generate_prompts_and_answers(nb)
 
     def generate_token_sequences(self, nb):
         prompts, answers = self.problem.generate_prompts_and_answers(nb)
 

-        print(f"DEBUG {prompts.size()=} {answers.size()=}")
-        sys.stdout.flush()
-

         if self.prompt_len is None:
             self.prompt_len = prompts.size(1)
 
         if self.prompt_len is None:
             self.prompt_len = prompts.size(1)