remove/simplify some changes from #6481

3 files changed, 8 insertions, 12 deletions

diff --git a/modules/textual_inversion/dataset.py b/modules/textual_inversion/dataset.py
index bcad6848..fa48708e 100644
--- a/modules/textual_inversion/dataset.py
+++ b/modules/textual_inversion/dataset.py
@@ -17,7 +17,7 @@ re_numbers_at_start = re.compile(r"^[-\d]+\s*")
 

 

 class DatasetEntry:

-    def __init__(self, filename=None, filename_text=None, latent_dist=None, latent_sample=None, cond=None, cond_text=None, pixel_values=None, img_shape=None):

+    def __init__(self, filename=None, filename_text=None, latent_dist=None, latent_sample=None, cond=None, cond_text=None, pixel_values=None):

         self.filename = filename

         self.filename_text = filename_text

         self.latent_dist = latent_dist

@@ -25,7 +25,6 @@ class DatasetEntry:
         self.cond = cond

         self.cond_text = cond_text

         self.pixel_values = pixel_values

-        self.img_shape = img_shape

 

 

 class PersonalizedBase(Dataset):

@@ -46,12 +45,10 @@ 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'

+        assert batch_size == 1 or not varsize, '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)]

 

-

         self.shuffle_tags = shuffle_tags

         self.tag_drop_out = tag_drop_out

 

@@ -91,14 +88,14 @@ class PersonalizedBase(Dataset):
             if latent_sampling_method == "once" or (latent_sampling_method == "deterministic" and not isinstance(latent_dist, DiagonalGaussianDistribution)):

                 latent_sample = model.get_first_stage_encoding(latent_dist).squeeze().to(devices.cpu)

                 latent_sampling_method = "once"

-                entry = DatasetEntry(filename=path, filename_text=filename_text, latent_sample=latent_sample, img_shape=image.size)

+                entry = DatasetEntry(filename=path, filename_text=filename_text, latent_sample=latent_sample)

             elif latent_sampling_method == "deterministic":

                 # Works only for DiagonalGaussianDistribution

                 latent_dist.std = 0

                 latent_sample = model.get_first_stage_encoding(latent_dist).squeeze().to(devices.cpu)

-                entry = DatasetEntry(filename=path, filename_text=filename_text, latent_sample=latent_sample, img_shape=image.size)

+                entry = DatasetEntry(filename=path, filename_text=filename_text, latent_sample=latent_sample)

             elif latent_sampling_method == "random":

-                entry = DatasetEntry(filename=path, filename_text=filename_text, latent_dist=latent_dist, img_shape=image.size)

+                entry = DatasetEntry(filename=path, filename_text=filename_text, latent_dist=latent_dist)

 

             if not (self.tag_drop_out != 0 or self.shuffle_tags):

                 entry.cond_text = self.create_text(filename_text)

@@ -154,7 +151,6 @@ class BatchLoader:
         self.cond_text = [entry.cond_text for entry in data]

         self.cond = [entry.cond for entry in data]

         self.latent_sample = torch.stack([entry.latent_sample for entry in data]).squeeze(1)

-        self.img_shape = [entry.img_shape for entry in data]

         #self.emb_index = [entry.emb_index for entry in data]

         #print(self.latent_sample.device)

 

diff --git a/modules/textual_inversion/textual_inversion.py b/modules/textual_inversion/textual_inversion.py
index ad76297e..14be2c96 100644
--- a/modules/textual_inversion/textual_inversion.py
+++ b/modules/textual_inversion/textual_inversion.py
@@ -492,8 +492,8 @@ def train_embedding(embedding_name, learn_rate, batch_size, gradient_step, data_
                     else:

                         p.prompt = batch.cond_text[0]

                         p.steps = 20

-                        p.width = batch.img_shape[0][0]

-                        p.height = batch.img_shape[0][1]

+                        p.width = training_width

+                        p.height = training_height

 

                     preview_text = p.prompt

 

diff --git a/modules/ui.py b/modules/ui.py
index 9d6b141e..ddfe1b1a 100644
--- a/modules/ui.py
+++ b/modules/ui.py
@@ -1348,7 +1348,7 @@ def create_ui():
                     template_file = gr.Textbox(label='Prompt template file', value=os.path.join(script_path, "textual_inversion_templates", "style_filewords.txt"), elem_id="train_template_file")

                     training_width = gr.Slider(minimum=64, maximum=2048, step=8, label="Width", value=512, elem_id="train_training_width")

                     training_height = gr.Slider(minimum=64, maximum=2048, step=8, label="Height", value=512, elem_id="train_training_height")

-                    varsize = gr.Checkbox(label="Ignore dimension settings and do not resize images", value=False, elem_id="train_varsize")

+                    varsize = gr.Checkbox(label="Do not resize images", value=False, elem_id="train_varsize")

                     steps = gr.Number(label='Max steps', value=100000, precision=0, elem_id="train_steps")

 

                     with FormRow():