X-Git-Url: https://fleuret.org/cgi-bin/gitweb/gitweb.cgi?a=blobdiff_plain;f=main.py;fp=main.py;h=b2adf986cb57c9bd447571be06d62379ad97d756;hb=8ea0e3c5cc303718a8b508b656f7aa9e64ea3070;hp=65922040a78fc60ada7bbf75c5373ace576ee4c6;hpb=c92c5abfa01b78a292929d2363bb05798c2af39f;p=mygpt.git

diff --git a/main.py b/main.py
index 6592204..b2adf98 100755
--- a/main.py
+++ b/main.py
@@ -111,7 +111,7 @@ for n in vars(args):
 ######################################################################
 
 def autoregression(
-        model,
+        model, batch_size,
         nb_samples, nb_tokens_to_generate, starting_input = None,
         device = torch.device('cpu')
 ):
@@ -126,7 +126,7 @@ def autoregression(
         first = starting_input.size(1)
         results = torch.cat((starting_input, results), 1)
 
-    for input in results.split(args.batch_size):
+    for input in results.split(batch_size):
         for s in tqdm.tqdm(range(first, input.size(1)), desc = 'synth'):
             output = model(input)
             logits = output[:, s]
@@ -386,7 +386,7 @@ class TaskMNIST(Task):
         return 256
 
     def produce_results(self, n_epoch, model, nb_samples = 64):
-        results = autoregression(model, nb_samples, 28 * 28, device = self.device)
+        results = autoregression(model, self.batch_size, nb_samples, 28 * 28, device = self.device)
         image_name = f'result_mnist_{n_epoch:04d}.png'
         torchvision.utils.save_image(1 - results.reshape(-1, 1, 28, 28) / 255.,
                                      image_name, nrow = 16, pad_value = 0.8)