From: Francois Fleuret <francois@fleuret.org>
Date: Wed, 27 Jul 2022 16:52:54 +0000 (+0200)
Subject: Fixed stuff.
X-Git-Url: https://fleuret.org/cgi-bin/gitweb/gitweb.cgi?a=commitdiff_plain;h=f031f7f87b5be907df081395023a9acba8ba9c7c;p=mygpt.git

Fixed stuff.
---

diff --git a/main.py b/main.py
index 5f3e8cf..1b011a2 100755
--- a/main.py
+++ b/main.py
@@ -126,7 +126,7 @@ def autoregression(
         results = torch.cat((primer, results), 1)
 
     for input in results.split(batch_size):
-        for s in tqdm.tqdm(range(first, input.size(1)), desc = 'synth'):
+        for s in range(first, input.size(1)):
             output = model(input)
             logits = output[:, s]
             if args.synthesis_sampling:
@@ -157,6 +157,10 @@ import picoclvr
 class TaskPicoCLVR(Task):
 
     def tensorize(self, descr):
+        descr = [ s.strip().split(' ') for s in descr ]
+        l = max([ len(s) for s in descr ])
+        #descr = [ [ '<nul>' ] * (l - len(s)) + s for s in descr ]
+        descr = [ s + [ '<nul>' ] * (l - len(s)) for s in descr ]
         t = [ [ self.token2id[u] for u in s ] for s in descr ]
         return torch.tensor(t, device = self.device)
 
@@ -165,19 +169,12 @@ class TaskPicoCLVR(Task):
                  device = torch.device('cpu')):
 
         def generate_descr(nb):
-            descr = picoclvr.generate(
+            return picoclvr.generate(
                 nb,
                 height = self.height, width = self.width,
                 nb_colors = nb_colors
             )
 
-            descr = [ s.strip().split(' ') for s in descr ]
-            l = max([ len(s) for s in descr ])
-            #descr = [ [ '<nul>' ] * (l - len(s)) + s for s in descr ]
-            descr = [ s + [ '<nul>' ] * (l - len(s)) for s in descr ]
-
-            return descr
-
         self.height = height
         self.width = width
         self.batch_size = batch_size
@@ -188,10 +185,10 @@ class TaskPicoCLVR(Task):
         self.test_descr = generate_descr((nb * 1) // 5)
 
         # Build the tokenizer
-        tokens = set()
+        tokens = { '<nul>' }
         for d in [ self.train_descr, self.test_descr ]:
             for s in d:
-                for t in s: tokens.add(t)
+                for t in s.strip().split(' '): tokens.add(t)
         self.token2id = dict([ (t, n) for n, t in enumerate(tokens) ])
         self.id2token = dict([ (n, t) for n, t in enumerate(tokens) ])
 
@@ -223,8 +220,8 @@ class TaskPicoCLVR(Task):
             for k in range(nb_per_primer):
                 results = autoregression(
                     model, self.batch_size,
-                    nb_samples = 1, nb_tokens = nb_tokens,
-                    primer = self.tensorize(primer_descr),
+                    nb_samples = 1, nb_tokens_to_generate = nb_tokens,
+                    primer = self.tensorize([ primer_descr ]),
                     device = self.device
                 )
                 r = ' '.join([ self.id2token[t.item()] for t in results.flatten() ])