Batches of size 1 cause error: Expected query.is_contiguous() to be true, but got false

1 files changed, 9 insertions, 9 deletions

diff --git a/data/dreambooth/csv.py b/data/dreambooth/csv.py
index 85ed4a5..99bcf12 100644
--- a/data/dreambooth/csv.py
+++ b/data/dreambooth/csv.py
@@ -1,3 +1,4 @@
+import math
 import os
 import pandas as pd
 from pathlib import Path
@@ -57,11 +58,10 @@ class CSVDataModule(pl.LightningDataModule):
         train_dataset = CSVDataset(self.data_train, self.tokenizer, instance_prompt=self.instance_prompt,
                                    class_data_root=self.class_data_root, class_prompt=self.class_prompt,
                                    size=self.size, interpolation=self.interpolation, identifier=self.identifier,
-                                   center_crop=self.center_crop, repeats=self.repeats)
+                                   center_crop=self.center_crop, repeats=self.repeats, batch_size=self.batch_size)
         val_dataset = CSVDataset(self.data_val, self.tokenizer, instance_prompt=self.instance_prompt,
-                                 class_data_root=self.class_data_root, class_prompt=self.class_prompt,
                                  size=self.size, interpolation=self.interpolation, identifier=self.identifier,
-                                 center_crop=self.center_crop)
+                                 center_crop=self.center_crop, batch_size=self.batch_size)
         self.train_dataloader_ = DataLoader(train_dataset, batch_size=self.batch_size,
                                             shuffle=True, collate_fn=self.collate_fn)
         self.val_dataloader_ = DataLoader(val_dataset, batch_size=self.batch_size, collate_fn=self.collate_fn)
@@ -85,22 +85,24 @@ class CSVDataset(Dataset):
                  interpolation="bicubic",
                  identifier="*",
                  center_crop=False,
+                 batch_size=1,
                  ):
 
         self.data = data
         self.tokenizer = tokenizer
         self.instance_prompt = instance_prompt
+        self.identifier = identifier
+        self.batch_size = batch_size
+        self.cache = {}
 
         self.num_instance_images = len(self.data)
         self._length = self.num_instance_images * repeats
 
-        self.identifier = identifier
-
         if class_data_root is not None:
             self.class_data_root = Path(class_data_root)
             self.class_data_root.mkdir(parents=True, exist_ok=True)
 
-            self.class_images = list(Path(class_data_root).iterdir())
+            self.class_images = list(self.class_data_root.iterdir())
             self.num_class_images = len(self.class_images)
             self._length = max(self.num_class_images, self.num_instance_images)
 
@@ -123,10 +125,8 @@ class CSVDataset(Dataset):
             ]
         )
 
-        self.cache = {}
-
     def __len__(self):
-        return self._length
+        return math.ceil(self._length / self.batch_size) * self.batch_size
 
     def get_example(self, i):
         image_path, text = self.data[i % self.num_instance_images]