2 files changed, 3 insertions, 3 deletions
diff --git a/modules/hypernetworks/hypernetwork.py b/modules/hypernetworks/hypernetwork.py
index dba52841..32c67ccc 100644
--- a/modules/hypernetworks/hypernetwork.py
+++ b/modules/hypernetworks/hypernetwork.py
@@ -456,7 +456,7 @@ def train_hypernetwork(hypernetwork_name, learn_rate, batch_size, gradient_step,
 
     pin_memory = shared.opts.pin_memory
 
-    ds = modules.textual_inversion.dataset.PersonalizedBase(data_root=data_root, width=training_width, height=training_height, repeats=shared.opts.training_image_repeats_per_epoch, placeholder_token=hypernetwork_name, model=shared.sd_model, cond_model=shared.sd_model.cond_stage_model, device=devices.device, template_file=template_file, include_cond=True, batch_size=batch_size, gradient_step=gradient_step, shuffle_tags=shuffle_tags, tag_drop_out=tag_drop_out, latent_sampling_method=latent_sampling_method)
+    ds = modules.textual_inversion.dataset.PersonalizedBase(data_root=data_root, width=training_width, height=training_height, repeats=shared.opts.training_image_repeats_per_epoch, placeholder_token=hypernetwork_name, model=shared.sd_model, cond_model=shared.sd_model.cond_stage_model, device=devices.device, template_file=template_file, include_cond=True, batch_size=batch_size, gradient_step=gradient_step, shuffle_tags=shuffle_tags, tag_drop_out=tag_drop_out, latent_sampling_method=latent_sampling_method, varsize=varsize)
 
     if shared.opts.save_training_settings_to_txt:
         saved_params = dict(
diff --git a/modules/textual_inversion/dataset.py b/modules/textual_inversion/dataset.py
index 7f8a314f..bcad6848 100644
--- a/modules/textual_inversion/dataset.py
+++ b/modules/textual_inversion/dataset.py
@@ -46,6 +46,8 @@ class PersonalizedBase(Dataset):
         assert data_root, 'dataset directory not specified'
         assert os.path.isdir(data_root), "Dataset directory doesn't exist"
         assert os.listdir(data_root), "Dataset directory is empty"
+        if varsize:
+            assert batch_size == 1, 'variable img size must have batch size 1'
 
         self.image_paths = [os.path.join(data_root, file_path) for file_path in os.listdir(data_root)]
 
@@ -61,8 +63,6 @@ class PersonalizedBase(Dataset):
                 image = Image.open(path).convert('RGB')
                 if not varsize:
                     image = image.resize((width, height), PIL.Image.BICUBIC)
-                else:
-                    assert batch_size == 1, 'variable img size must have batch size 1'
             except Exception:
                 continue