Images in Messages (pytorch#1504)

docs/source/api_ref_data.rst

@@ -88,3 +88,5 @@ Miscellaneous helper functions used in modifying data.
 
     validate_messages
     truncate
+    load_image
+    format_content_with_images

tests/test_utils.py

@@ -145,10 +145,14 @@ def tokenize_messages(
         return tokenized_messages, mask
 
     def __call__(self, sample: Mapping[str, Any]) -> Mapping[str, Any]:
-        messages = sample.pop("messages")
+        messages: List[Message] = sample.pop("messages")
+        images = []
+        for message in messages:
+            images += message.get_media()
         tokens, mask = self.tokenize_messages(messages)
         sample["tokens"] = tokens
         sample["mask"] = mask
+        sample["images"] = images
         return sample
 
     @property

tests/torchtune/data/test_data_utils.py

@@ -4,15 +4,20 @@
 # This source code is licensed under the BSD-style license found in the
 # LICENSE file in the root directory of this source tree.
 
+import os
+
 import pytest
+from PIL import Image
+
+from tests.common import ASSETS
 from torchtune.data import (
+    format_content_with_images,
     Message,
     PromptTemplate,
-    split_text_by_image_tag,
     truncate,
     validate_messages,
 )
-from torchtune.data._utils import _get_prompt_template
+from torchtune.data._utils import _get_prompt_template, load_image
 from torchtune.models.llama2 import Llama2ChatTemplate
 
 
@@ -98,47 +103,136 @@ def test_validate_messages():
         validate_messages(messages)
 
 
-def test_split_text_by_image_tag():
+def test_format_content_with_images():
+    test_image_1 = Image.new(mode="RGB", size=(4, 4))
+    test_image_2 = Image.new(mode="RGB", size=(4, 4))
+    test_image_3 = Image.new(mode="RGB", size=(4, 4))
+
     # Test single image tag in the middle
     text = "hello <image>world"
-    assert split_text_by_image_tag(text, "<image>") == [
+    assert format_content_with_images(
+        text,
+        image_tag="<image>",
+        images=[test_image_1],
+    ) == [
         {"type": "text", "content": "hello "},
-        {"type": "image"},
+        {"type": "image", "content": test_image_1},
         {"type": "text", "content": "world"},
     ]
 
     # Test multiple image tags and image tag in beginning
     text = "[image]hello [image]world"
-    assert split_text_by_image_tag(text, "[image]") == [
-        {"type": "image"},
+    assert format_content_with_images(
+        text,
+        image_tag="[image]",
+        images=[test_image_1, test_image_2],
+    ) == [
+        {"type": "image", "content": test_image_1},
         {"type": "text", "content": "hello "},
-        {"type": "image"},
+        {"type": "image", "content": test_image_2},
         {"type": "text", "content": "world"},
     ]
 
     # Test an image tag that is not present in the text
     text = "hello world"
-    assert split_text_by_image_tag(text, "asdfghjkl;") == [
+    assert format_content_with_images(text, image_tag="asdfghjkl;", images=[]) == [
         {"type": "text", "content": "hello world"}
     ]
 
     # Test consecutive image tags
     text = "<image><image>hello <image>world"
-    assert split_text_by_image_tag(text, "<image>") == [
-        {"type": "image"},
-        {"type": "image"},
+    assert format_content_with_images(
+        text,
+        image_tag="<image>",
+        images=[test_image_1, test_image_2, test_image_3],
+    ) == [
+        {"type": "image", "content": test_image_1},
+        {"type": "image", "content": test_image_2},
         {"type": "text", "content": "hello "},
-        {"type": "image"},
+        {"type": "image", "content": test_image_3},
         {"type": "text", "content": "world"},
     ]
 
     # Test image tag at the end
     text = "hello <image>"
-    assert split_text_by_image_tag(text, "<image>") == [
+    assert format_content_with_images(
+        text,
+        image_tag="<image>",
+        images=[test_image_1],
+    ) == [
         {"type": "text", "content": "hello "},
-        {"type": "image"},
+        {"type": "image", "content": test_image_1},
     ]
 
+    # Test errors when the number of images does not match the number of image tags
+    text = "hello <image>world"
+    with pytest.raises(
+        ValueError,
+        match="does not match number of image tags",
+    ):
+        format_content_with_images(
+            text, image_tag="<image>", images=[test_image_1, test_image_2]
+        )
+
+
+def test_load_image(monkeypatch, tmp_path):
+    tmp_image = str(ASSETS / "dog_on_skateboard.jpg")
+
+    # Test loading from local file
+    image = load_image(tmp_image)
+    assert isinstance(image, Image.Image)
+    assert image.size == (580, 403)
+
+    # Test loading from remote file
+    # Mock the urlopen function to return a BytesIO object
+    def mock_urlopen(url):
+        return open(tmp_image, "rb")
+
+    monkeypatch.setattr("urllib.request.urlopen", mock_urlopen)
+    image = load_image("http://example.com/test_image.jpg")
+    assert isinstance(image, Image.Image)
+    assert image.size == (580, 403)
+
+    # Test that a ValueError is raised when the image path is invalid
+    with pytest.raises(ValueError, match="Failed to open image as PIL.Image"):
+        load_image("invalid_path")
+
+    # Test a temporary file with invalid image data
+    image_path = tmp_path / "test_image.jpg"
+    with open(image_path, "w") as f:
+        f.write("Invalid image data")
+
+    # Test that a ValueError is raised when the image data is invalid
+    with pytest.raises(ValueError, match="Failed to open image as PIL.Image"):
+        load_image(str(image_path))
+
+    # Test that a ValueError is raised when there is an HTTP error
+    # Mock the urlopen function to raise an exception
+    def mock_urlopen(url):
+        raise Exception("Failed to load image")
+
+    monkeypatch.setattr("urllib.request.urlopen", mock_urlopen)
+    with pytest.raises(ValueError, match="Failed to load image"):
+        load_image("http://example.com/test_image.jpg")
+
+    # Test that a ValueError is raised when there is an IO error
+    # Create a temporary file that cannot be read
+    image_path = tmp_path / "test_image.jpg"
+    with open(image_path, "w") as f:
+        f.write("Test data")
+    os.chmod(image_path, 0o000)  # Remove read permissions
+    with pytest.raises(ValueError, match="Failed to open image as PIL.Image"):
+        load_image(str(image_path))
+    os.chmod(image_path, 0o644)  # Restore read permissions
+
+    # Test that a ValueError is raised with invalid image data is read
+    # Create a temporary file with invalid image data
+    image_path = tmp_path / "test_image.jpg"
+    with open(image_path, "wb") as f:
+        f.write(b"Invalid image data")
+    with pytest.raises(ValueError, match="Failed to open image as PIL.Image"):
+        load_image(str(image_path))
+
 
 def test_get_prompt_template():
     template = _get_prompt_template("torchtune.models.llama2.Llama2ChatTemplate")

tests/torchtune/data/test_messages.py

@@ -5,6 +5,8 @@
 # LICENSE file in the root directory of this source tree.
 
 import pytest
+
+from PIL import Image
 from tests.test_utils import (
     assert_dialogue_equal,
     CHAT_SAMPLE,
@@ -26,17 +28,21 @@ def text_message(self):
         return Message(role="user", content="hello world")
 
     @pytest.fixture
-    def image_message(self):
+    def test_image(self):
+        return Image.new(mode="RGB", size=(4, 4))
+
+    @pytest.fixture
+    def image_message(self, test_image):
         return Message(
             role="user",
             content=[
                 {"type": "text", "content": "hello"},
-                {"type": "image"},
+                {"type": "image", "content": test_image},
                 {"type": "text", "content": " world"},
             ],
         )
 
-    def test_message_validation(self, text_message):
+    def test_message_validation(self, text_message, test_image):
         message = text_message
         assert message.role == "user"
         assert message.content == [{"type": "text", "content": "hello world"}]
@@ -53,7 +59,7 @@ def test_message_validation(self, text_message):
         ):
             message = Message(
                 role="user",
-                content=[{"type": "image"}],
+                content=[{"type": "image", "content": test_image}],
                 ipython=True,
             )
 
@@ -69,6 +75,10 @@ def test_contains_media(self, text_message, image_message):
         assert not text_message.contains_media
         assert image_message.contains_media
 
+    def test_get_media(self, text_message, image_message, test_image):
+        assert text_message.get_media() == []
+        assert image_message.get_media() == [test_image]
+
     def test_text_content(self, text_message, image_message):
         assert text_message.text_content == "hello world"
         assert image_message.text_content == "hello world"

tests/torchtune/datasets/multimodal/test_llava_instruct_dataset.py

@@ -7,6 +7,8 @@
 from collections import Counter
 from unittest.mock import patch
 
+import PIL
+
 import pytest
 from datasets import Dataset
 
@@ -21,11 +23,22 @@ class TestLLaVAInstructDataset:
     def tokenizer(self):
         return DummyTokenizer()
 
+    @pytest.fixture
+    def test_image_pil(self):
+        return PIL.Image.new(mode="RGB", size=(4, 4))
+
     @patch("torchtune.datasets._sft.load_dataset")
-    def test_label_no_masking(self, load_dataset, tokenizer):
+    @patch("torchtune.datasets.multimodal._llava_instruct.load_image")
+    def test_label_no_masking(
+        self, load_image, load_dataset, tokenizer, test_image_pil
+    ):
         """
         Test whether the input and the labels are correctly created when the input is not masked.
+
+        WARNING: careful with these mocks, they are applied in bottom up order
         """
+        # mock the call to load_image
+        load_image.return_value = test_image_pil
 
         # mock the call to HF datasets
         load_dataset.return_value = Dataset.from_list(
@@ -55,6 +68,7 @@ def test_label_no_masking(self, load_dataset, tokenizer):
             model_transform=tokenizer,
             train_on_input=True,
         )
+
         input, labels, images = ds[0]["tokens"], ds[0]["labels"], ds[0]["images"]
 
         expected_count = {
@@ -76,13 +90,18 @@ def test_label_no_masking(self, load_dataset, tokenizer):
 
         assert Counter(input) == expected_count
         assert Counter(labels) == expected_count
-        assert images == "test_image.jpg"
+        assert images == [test_image_pil]
 
     @patch("torchtune.datasets._sft.load_dataset")
-    def test_label_masking(self, load_dataset, tokenizer):
+    @patch("torchtune.datasets.multimodal._llava_instruct.load_image")
+    def test_label_masking(self, load_image, load_dataset, tokenizer, test_image_pil):
         """
         Test whether the input and the labels are correctly created when the input is masked.
+
+        WARNING: careful with these mocks, they are applied in bottom up order
         """
+        # mock the call to load_image
+        load_image.return_value = test_image_pil
 
         # mock the call to HF datasets
         load_dataset.return_value = Dataset.from_list(
@@ -133,4 +152,4 @@ def test_label_masking(self, load_dataset, tokenizer):
 
         assert Counter(input) == expected_count
         assert labels.count(CROSS_ENTROPY_IGNORE_IDX) == 11
-        assert images == "test_image.jpg"
+        assert images == [test_image_pil]