X-Git-Url: https://fleuret.org/cgi-bin/gitweb/gitweb.cgi?a=blobdiff_plain;f=sky.py;h=4ca4ba7136b40a5324dcb64ba4c6a3a19523b3c5;hb=c9c018e4c19ce92892d7652082fb90719d57441c;hp=fdc1689737831223d9d81925dc6a1a8b39c99d3d;hpb=979cff406de06137b7b5fb1876b906b2eb45153e;p=culture.git

diff --git a/sky.py b/sky.py
index fdc1689..4ca4ba7 100755
--- a/sky.py
+++ b/sky.py
@@ -44,24 +44,29 @@ class Sky(problem.Problem):
         "_" + "".join([chr(ord("A") + n) for n in range(len(colors) - 1)]) + "><"
     )
 
-    def __init__(self, height=6, width=8, nb_birds=3, speed=1, nb_iterations=4):
+    def __init__(
+        self,
+        height=6,
+        width=8,
+        nb_birds=3,
+        speed=2,
+        nb_iterations=2,
+        avoid_collision=True,
+    ):
         self.height = height
         self.width = width
         self.nb_birds = nb_birds
         self.speed = speed
         self.nb_iterations = nb_iterations
+        self.avoid_collision = avoid_collision
 
     def direction_tokens(self):
         return self.token_forward, self.token_backward
 
-    def generate_seq(self, nb, return_frame_sequences=False):
+    def generate_frame_sequences(self, nb):
         frame_sequences = []
 
         for _ in tqdm.tqdm(range(nb), dynamic_ncols=True, desc="world generation"):
-            result = torch.zeros(
-                self.nb_iterations, self.height, self.width, dtype=torch.int64
-            )
-
             i, j, vi, vj = (
                 torch.empty(self.nb_birds, dtype=torch.int64),
                 torch.empty(self.nb_birds, dtype=torch.int64),
@@ -69,52 +74,97 @@ class Sky(problem.Problem):
                 torch.empty(self.nb_birds, dtype=torch.int64),
             )
 
+            def collision_okay():
+                if not self.avoid_collision:
+                    return True
+
+                count = torch.zeros(self.height, self.width, dtype=torch.int64)
+
+                for n in range(self.nb_birds):
+                    count[i[n], j[n]] += 1
+                    count[i[n] - vi[n], j[n]] += 1
+                    count[i[n], j[n] - vj[n]] += 1
+
+                return count.max() <= 1
+
             col = (
                 torch.randperm(self.colors.size(0) - 1)[: self.nb_birds].sort().values
                 + 1
             )
 
-            for n in range(self.nb_birds):
+            while True:
                 while True:
-                    i[n] = torch.randint(self.height, (1,))
-                    j[n] = torch.randint(self.width, (1,))
-                    vm = torch.randint(4, (1,))
-                    vi[n], vj[n] = (vm % 2) * 2 - 1, (vm // 2) * 2 - 1
-                    if (
-                        i[n] - vi[n] >= 0
-                        and i[n] - vi[n] < self.height
-                        and j[n] - vj[n] >= 0
-                        and j[n] - vj[n] < self.width
-                    ):
+                    for n in range(self.nb_birds):
+                        while True:
+                            i[n] = torch.randint(self.height, (1,))
+                            j[n] = torch.randint(self.width, (1,))
+                            vm = torch.randint(4, (1,))
+                            vi[n], vj[n] = (vm % 2) * 2 - 1, (vm // 2) * 2 - 1
+                            if (
+                                i[n] - vi[n] >= 0
+                                and i[n] - vi[n] < self.height
+                                and j[n] - vj[n] >= 0
+                                and j[n] - vj[n] < self.width
+                            ):
+                                break
+
+                    if collision_okay():
                         break
 
-            for l in range(self.nb_iterations):
-                for n in range(self.nb_birds):
-                    c = col[n]
-                    result[l, i[n], j[n]] = c
-                    result[l, i[n] - vi[n], j[n]] = c
-                    result[l, i[n], j[n] - vj[n]] = c
+                result = torch.zeros(
+                    self.nb_iterations * self.speed,
+                    self.height,
+                    self.width,
+                    dtype=torch.int64,
+                )
 
-                    if (i[n] == 0 and vi[n] == -1) or (
-                        i[n] == self.height - 1 and vi[n] == 1
-                    ):
-                        vi[n] = -vi[n]
+                fine = torch.empty(self.nb_iterations * self.speed)
 
-                    if (j[n] == 0 and vj[n] == -1) or (
-                        j[n] == self.width - 1 and vj[n] == 1
-                    ):
-                        vj[n] = -vj[n]
+                t_to_keep = (
+                    torch.arange(self.nb_iterations, device=result.device) * self.speed
+                )
+
+                for l in range(self.nb_iterations * self.speed):
+                    fine[l] = collision_okay()
+                    for n in range(self.nb_birds):
+                        c = col[n]
+                        result[l, i[n], j[n]] = c
+                        result[l, i[n] - vi[n], j[n]] = c
+                        result[l, i[n], j[n] - vj[n]] = c
+
+                        if (i[n] == 0 and vi[n] == -1) or (
+                            i[n] == self.height - 1 and vi[n] == 1
+                        ):
+                            vi[n] = -vi[n]
+
+                        if (j[n] == 0 and vj[n] == -1) or (
+                            j[n] == self.width - 1 and vj[n] == 1
+                        ):
+                            vj[n] = -vj[n]
+
+                        i[n] += vi[n]
+                        j[n] += vj[n]
 
-                    i[n] += vi[n]
-                    j[n] += vj[n]
+                result = result[t_to_keep]
+                fine = fine[t_to_keep]
+
+                if fine[-1]:
+                    break
 
             frame_sequences.append(result)
 
-        if return_frame_sequences:
-            return frame_sequences
+        return frame_sequences
+
+    ######################################################################
+
+    def generate_prompts_and_answers(self, nb):
+        frame_sequences = self.generate_frame_sequences(nb)
+        prompts = frame_sequences[:, : frame_sequences.size(0) // 2].flatten(1)
+        answers = frame_sequences[:, frame_sequences.size(0) // 2 :].flatten(1)
+        return prompts, answers
 
-        # Randomize the time direction, annd convert to token
-        # sequences with the time direction tokens added
+    def generate_token_sequences(self, nb):
+        frame_sequences = self.generate_frame_sequences(nb)
 
         result = []
 
@@ -257,12 +307,12 @@ class Sky(problem.Problem):
 if __name__ == "__main__":
     import time
 
-    sky = Sky(height=6, width=8, speed=1, nb_iterations=4)
+    sky = Sky(height=6, width=8, speed=4, nb_iterations=2)
 
     start_time = time.perf_counter()
-    seq = sky.generate_seq(nb=64)
+    token_sequences = sky.generate_token_sequences(nb=64)
     delay = time.perf_counter() - start_time
-    print(f"{seq.size(0)/delay:02f} seq/s")
+    print(f"{token_sequences.size(0)/delay:02f} seq/s")
 
     # print(sky.seq2str(seq[:4]))
 
@@ -279,9 +329,9 @@ if __name__ == "__main__":
     # m = (torch.rand(seq.size()) < 0.05).long()
     # seq = (1 - m) * seq + m * 23
 
-    print(seq.size())
-    img = sky.seq2img(seq)
-    print(img.size())
+    # print(seq.size())
+    img = sky.seq2img(token_sequences)
+    # print(img.size())
 
     torchvision.utils.save_image(
         img.float() / 255.0, "/tmp/world.png", nrow=6, padding=6, pad_value=0