Update.

[culture.git] / tasks.py

diff --git a/tasks.py b/tasks.py
index b3b56ad..ee06c25 100755 (executable)
--- a/tasks.py
+++ b/tasks.py
@@ -22,6 +22,7 @@ def masked_inplace_autoregression(
     batch_size,
     input,
     ar_mask,
+    summed_logits,
     temperature,
     deterministic_synthesis,
     forbidden_tokens=None,
@@ -41,16 +42,15 @@ def masked_inplace_autoregression(
             total=(input.size(0) + batch_size - 1) // batch_size,
         )
 
-    sum_logits = 0
-
     with torch.autograd.no_grad():
         t = model.training
         model.eval()
 
         for input, ar_mask in batches:
-            sum_logits += model.masked_inplace_autoregression(
+            model.masked_inplace_autoregression(
                 input=input,
                 ar_mask=ar_mask,
+                summed_logits=summed_logits,
                 temperature=temperature,
                 deterministic_synthesis=deterministic_synthesis,
                 forbidden_tokens=forbidden_tokens,
@@ -59,8 +59,6 @@ def masked_inplace_autoregression(
 
         model.train(t)
 
-    return sum_logits
-
 
 ######################################################################
 
@@ -180,6 +178,7 @@ class World(Task):
                 batch_size=self.batch_size,
                 input=result,
                 ar_mask=ar_mask,
+                summed_logits=None,
                 temperature=1.0,
                 deterministic_synthesis=deterministic_synthesis,
                 progress_bar_desc=None,
@@ -219,6 +218,7 @@ class World(Task):
             batch_size=self.batch_size,
             input=result,
             ar_mask=ar_mask,
+            summed_logits=None,
             temperature=1.0,
             deterministic_synthesis=deterministic_synthesis,
             progress_bar_desc=None,
@@ -266,23 +266,27 @@ class World(Task):
         )
 
         ar_mask = torch.full(quizzes.size(), 1, device=self.device)
+        summed_logits = torch.empty(nb, device=self.device)
 
         temperature = 1
         d_temperature = 1
 
         while True:
-            sum_logits = masked_inplace_autoregression(
+            summed_logits[...] = 0
+
+            masked_inplace_autoregression(
                 model=model,
                 batch_size=self.batch_size,
                 input=quizzes,
                 ar_mask=ar_mask,
+                summed_logits=summed_logits,
                 temperature=temperature,
                 deterministic_synthesis=False,
                 progress_bar_desc="creating quizzes",
                 device=self.device,
             )
 
-            average_logits = sum_logits / quizzes.size(0)
+            average_logits = summed_logits.mean()
 
             logger(f"{average_logits=} {desired_average_logits=}")
 
@@ -290,14 +294,17 @@ class World(Task):
                 break
 
             # Oh man that's ugly
-            if average_logits > desired_average_logits:
-                if d_temperature < 0:
+            if average_logits < desired_average_logits * 1.1:
+                if d_temperature > 0:
                     d_temperature *= -0.5
                 temperature += d_temperature
-            else:
-                if d_temperature > 0:
+            elif average_logits > desired_average_logits:
+                if d_temperature < 0:
                     d_temperature *= -0.5
                 temperature += d_temperature
+            else:
+                break
+
             logger(f"chaging temperature to {temperature}")
 
         ###############################################################
@@ -328,6 +335,7 @@ class World(Task):
                 batch_size=self.batch_size,
                 input=result,
                 ar_mask=ar_mask,
+                summed_logits=None,
                 temperature=1.0,
                 deterministic_synthesis=True,
                 progress_bar_desc="solving quizzes",
@@ -343,6 +351,7 @@ class World(Task):
                 batch_size=self.batch_size,
                 input=reverse_result,
                 ar_mask=ar_mask,
+                summed_logits=None,
                 temperature=1.0,
                 deterministic_synthesis=True,
                 progress_bar_desc="solving reversed quizzes",
@@ -362,4 +371,4 @@ class World(Task):
         # for k in nb_correct:
         # f.write(f"{k}\n")
 
-        return quizzes, nb_correct.sum(dim=0), sum_logits
+        return quizzes, nb_correct.sum(dim=0), summed_logits.mean()