bugfix Idefics3 processor - handle gracefully cases with text and no images

src/transformers/models/idefics3/processing_idefics3.py

@@ -283,45 +283,53 @@ def __call__(
             image_inputs = self.image_processor(images, **output_kwargs["images_kwargs"])
             inputs.update(image_inputs)
 
-        if text is not None:
-            if n_images_in_images != n_images_in_text:
-                raise ValueError(
-                    f"The number of images in the text {n_images_in_text} and images  {n_images_in_images} should be the same."
-                )
-
-            image_rows = inputs.pop("rows", [[0] * len(text)])
-            image_cols = inputs.pop("cols", [[0] * len(text)])
-
-            fake_image_token = self.fake_image_token.content
-            image_token = self.image_token.content
-            global_img_token = self.global_image_tag
-
-            prompt_strings = []
-            for sample, sample_rows, sample_cols in zip(text, image_rows, image_cols):
-                # Replace the image token with fake tokens around the expanded image token sequence of length `image_seq_len`
-                image_prompt_strings = []
-                for n_rows, n_cols in zip(sample_rows, sample_cols):
-                    image_prompt_string = get_image_prompt_string(
-                        n_rows,
-                        n_cols,
-                        image_seq_len,
-                        image_token=image_token,
-                        fake_token_around_image=fake_image_token,
-                        global_img_token=global_img_token,
+            if text is not None:
+                if n_images_in_images != n_images_in_text:
+                    raise ValueError(
+                        f"The number of images in the text {n_images_in_text} and images {n_images_in_images} should be the same."
                     )
-                    image_prompt_strings.append(image_prompt_string)
 
-                split_sample = sample.split(image_token)
-                if len(split_sample) == 0:
-                    raise ValueError("The image token should be present in the text.")
+                image_rows = inputs.pop("rows", [[0] * len(text)])
+                image_cols = inputs.pop("cols", [[0] * len(text)])
+
+                fake_image_token = self.fake_image_token.content
+                image_token = self.image_token.content
+                global_img_token = self.global_image_tag
+
+                prompt_strings = []
+                for sample, sample_rows, sample_cols in zip(text, image_rows, image_cols):
+                    # Replace the image token with fake tokens around the expanded image token sequence of length `image_seq_len`
+                    image_prompt_strings = []
+                    for n_rows, n_cols in zip(sample_rows, sample_cols):
+                        image_prompt_string = get_image_prompt_string(
+                            n_rows,
+                            n_cols,
+                            image_seq_len,
+                            image_token=image_token,
+                            fake_token_around_image=fake_image_token,
+                            global_img_token=global_img_token,
+                        )
+                        image_prompt_strings.append(image_prompt_string)
 
-                # Place in the image prompt strings where the image tokens are
-                sample = split_sample[0]
-                for i, image_prompt_string in enumerate(image_prompt_strings):
-                    sample += image_prompt_string + split_sample[i + 1]
-                prompt_strings.append(sample)
+                    split_sample = sample.split(image_token)
+                    if len(split_sample) == 0:
+                        raise ValueError("The image token should be present in the text.")
 
-            text_inputs = self.tokenizer(text=prompt_strings, **output_kwargs["text_kwargs"])
+                    # Place in the image prompt strings where the image tokens are
+                    sample = split_sample[0]
+                    for i, image_prompt_string in enumerate(image_prompt_strings):
+                        sample += image_prompt_string + split_sample[i + 1]
+                    prompt_strings.append(sample)
+
+                text_inputs = self.tokenizer(text=prompt_strings, **output_kwargs["text_kwargs"])
+                inputs.update(text_inputs)
+
+        elif text is not None:
+            if any(n_images_in_text):
+                raise ValueError(
+                    f"Found {sum(n_images_in_text)} {self.image_token.content} tokens in the text but no images were passed."
+                )
+            text_inputs = self.tokenizer(text=text, **output_kwargs["text_kwargs"])
             inputs.update(text_inputs)
 
         return inputs

tests/models/idefics3/test_processor_idefics3.py

@@ -505,3 +505,74 @@ def test_unstructured_kwargs(self):
 
         self.assertEqual(inputs["pixel_values"].shape[3], 32)
         self.assertEqual(len(inputs["input_ids"][0]), 120)
+
+    @require_torch
+    @require_vision
+    def test_text_only_inference(self):
+        """Test that the processor works correctly with text-only input."""
+        processor = self.get_processor()
+
+        text = "This is a simple text without images."
+        inputs = processor(text=text)
+
+        tokenized_sentence = processor.tokenizer(text, add_special_tokens=False)
+        expected_input_ids = [[self.bos_token_id] + tokenized_sentence["input_ids"]]
+
+        self.assertEqual(inputs["input_ids"], expected_input_ids)
+        self.assertEqual(inputs["attention_mask"], [[1] * len(expected_input_ids[0])])
+        self.assertTrue("pixel_values" not in inputs)
+        self.assertTrue("pixel_attention_mask" not in inputs)
+
+        # Test batch of texts without image tokens
+        texts = ["First text.", "Second piece of text."]
+        batch_inputs = processor(text=texts, padding=True)
+
+        tokenized_1 = processor.tokenizer(texts[0], add_special_tokens=False)
+        tokenized_2 = processor.tokenizer(texts[1], add_special_tokens=False)
+
+        expected_1 = [self.bos_token_id] + tokenized_1["input_ids"]
+        expected_2 = [self.bos_token_id] + tokenized_2["input_ids"]
+
+        # Pad the shorter sequence
+        pad_len = len(expected_2) - len(expected_1)
+        if pad_len > 0:
+            padded_expected_1 = [self.padding_token_id] * pad_len + expected_1
+            expected_attention_1 = [0] * pad_len + [1] * len(expected_1)
+            self.assertEqual(batch_inputs["input_ids"], [padded_expected_1, expected_2])
+            self.assertEqual(batch_inputs["attention_mask"], [expected_attention_1, [1] * len(expected_2)])
+        else:
+            pad_len = -pad_len
+            padded_expected_2 = [self.padding_token_id] * pad_len + expected_2
+            expected_attention_2 = [0] * pad_len + [1] * len(expected_2)
+            self.assertEqual(batch_inputs["input_ids"], [expected_1, padded_expected_2])
+            self.assertEqual(batch_inputs["attention_mask"], [[1] * len(expected_1), expected_attention_2])
+
+    @require_torch
+    @require_vision
+    def test_missing_images_error(self):
+        """Test that appropriate error is raised when images are referenced but not provided."""
+        processor = self.get_processor()
+
+        # Test single text with image token but no image
+        text = "Let me show you this image: <image> What do you think?"
+        with self.assertRaises(ValueError) as context:
+            processor(text=text)
+        self.assertTrue("tokens in the text but no images were passed" in str(context.exception))
+
+        # Test batch with image tokens but no images
+        texts = [
+            "First text with <image> token.",
+            "Second text <image> with token.",
+        ]
+        with self.assertRaises(ValueError) as context:
+            processor(text=texts)
+        self.assertTrue("tokens in the text but no images were passed" in str(context.exception))
+
+        # Test with None as Images
+        with self.assertRaises(ValueError) as context:
+            processor(text=text, images=None)
+        self.assertTrue("tokens in the text but no images were passed" in str(context.exception))
+
+        with self.assertRaises(ValueError) as context:
+            processor(text=texts, images=None)
+        self.assertTrue("tokens in the text but no images were passed" in str(context.exception))