Update.

[picoclvr.git] / problems.py

diff --git a/problems.py b/problems.py
index 2c8602c..22b6517 100755 (executable)
--- a/problems.py
+++ b/problems.py
@@ -17,6 +17,95 @@ class Problem:
     def seq2str(self, seq):
         return "[NOT IMPLEMENTED]"
 
+    def compute_nb_correct(self, input, ar_mask, result):
+        nb_total = ar_mask.sum().item()
+        nb_correct = ((result == input).long() * ar_mask).sum().item()
+        return nb_total, nb_correct
+
+
+####################
+
+
+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
+        self.nb_state_tokens = nb_state_tokens
+        self.nb_time_steps = nb_time_steps
+        self.value_max = value_max
+        self.hard = hard
+
+    def generate_sequences(self, nb):
+        x = (
+            torch.rand(nb, self.nb_state_tokens).sort(dim=-1).indices == 0
+        ).long() * self.value_max
+        seq = [x]
+
+        for t in range(self.nb_time_steps - 1):
+            v = (torch.rand(x.size()).sort(dim=-1).indices + 1) * (x >= 2).long()
+            u = (v.max(dim=-1, keepdim=True).values == v).long()
+            n = (
+                (u * x)
+                .minimum(2 + torch.randint(self.value_max // 4 - 2, x.size()))
+                .sum(dim=-1, keepdim=True)
+            )
+            m = 1 + ((n - 1) * torch.rand(n.size())).long()
+            x = (
+                x
+                + m * u.roll(shifts=-1, dims=-1)
+                - n * u
+                + (n - m) * u.roll(shifts=1, dims=-1)
+            )
+            seq.append(x)
+
+        if self.hard:
+            seq.reverse()
+
+        seq = torch.cat(seq, dim=1)
+        return seq, seq.new_full(seq.size(), 1, dtype=torch.int64)
+
+    def compute_nb_correct(self, input, ar_mask, result):
+        nb_total = result.size(0)
+        nb_correct = 0
+        e = result.new_zeros(self.nb_state_tokens)
+
+        for seq in result:
+            states = list(seq.split(self.nb_state_tokens))
+            if self.hard:
+                states.reverse()
+
+            d = states[0]
+            j = d.sort(descending=True).indices[0]
+            e.zero_()
+            e[j] = self.value_max
+            if (d - e).abs().sum() == 0:
+                nb_errors = 0
+                for k in range(len(states) - 1):
+                    d = states[k + 1] - states[k]
+                    j = d.sort(descending=False).indices[0]
+                    if (
+                        d[j] == 0
+                        or d[j] > self.value_max // 4
+                        or d[(j + 1) % e.size(0)] <= 0
+                        or d[(j + 1) % e.size(0)] >= -d[j]
+                    ):
+                        nb_errors += 1
+                    else:
+                        e.zero_()
+                        e[j] = d[j]
+                        e[(j + 1) % e.size(0)] = d[(j + 1) % e.size(0)]
+                        e[(j - 1) % e.size(0)] = -d[(j + 1) % e.size(0)] - d[j]
+                        if (d - e).abs().sum() > 0:
+                            nb_errors += 1
+                if nb_errors == 0:
+                    nb_correct += 1
+
+        return nb_total, nb_correct
+
+    def seq2str(self, seq):
+        return " | ".join(
+            [" ".join([f"{x:02d}" for x in s]) for s in seq.split(self.nb_state_tokens)]
+        )
+
 
 ####################
 
@@ -197,7 +286,8 @@ class ProblemAddition(Problem):
 
 
 if __name__ == "__main__":
-    p = ProblemTwoTargets(12, 4)
-    s, m = p.generate_sequences(10)
-    for x in s:
+    p = ProblemDegradation(hard=False)
+    s, m = p.generate_sequences(10000)
+    for x in s[:100]:
         print(p.seq2str(x))
+    print(p.compute_nb_correct(None, None, s))