[run-slow] pixtral

src/transformers/models/pixtral/processing_pixtral.py

@@ -204,12 +204,21 @@ class PixtralProcessor(ProcessorMixin):
 
         if images is not None:
             if is_image_or_image_url(images):
-                images = [[images]]
-            elif isinstance(images, list) and is_image_or_image_url(images[0]):
-                if isinstance(text, list):
-                    images = [[im] for im in images]
+                if isinstance(text, str) or isinstance(text, list) and len(text) == 1:
+                    # If there's a single sample, the image must belong to it
+                    images = [[images]]
                 else:
+                    raise ValueError(
+                        "You have supplied multiple text samples, but `images` is not a nested list. When processing multiple samples, `images` should be a list of lists of images, one list per sample."
+                    )
+            elif isinstance(images, list) and is_image_or_image_url(images[0]):
+                if isinstance(text, str) or isinstance(text, list) and len(text) == 1:
+                    # If there's a single sample, all images must belong to it
                     images = [images]
+                else:
+                    raise ValueError(
+                        "You have supplied multiple text samples, but `images` is not a nested list. When processing multiple samples, `images` should be a list of lists of images, one list per sample."
+                    )
             elif isinstance(images, list) and isinstance(images[0], list) and is_image_or_image_url(images[0][0]):
                 pass
             else:

tests/models/pixtral/test_processor_pixtral.py

@@ -253,7 +253,7 @@ class PixtralProcessorTest(ProcessorTesterMixin, unittest.TestCase):
             "USER: [IMG]\nWhat's the content of the image? ASSISTANT:",
         ] * 5
         processor.tokenizer.pad_token = "</s>"
-        image_inputs = [self.image_0] * 5
+        image_inputs = [[self.image_0]] * 5
 
         # Make small for checking image token expansion
         processor.image_processor.size = {"longest_edge": 30}