[v1] Support multimodal data training (#10656)

Co-authored-by: Claude Opus 4.8 <noreply@anthropic.com>

tests_v1/plugins/data_plugins/test_converter.py

@@ -71,6 +71,148 @@ def test_sharegpt_converter():
     assert DataConverterPlugin("sharegpt")(example) == expected_data
 
 
+def test_sharegpt_converter_multimodal():
+    example = {
+        "conversations": [
+            {"from": "human", "value": "What is <image> and what happens in <video>?"},
+            {"from": "gpt", "value": "An image and a video."},
+        ],
+        "images": ["/p/a.jpg"],
+        "videos": ["/p/v.mp4"],
+    }
+    expected_data = {
+        "messages": [
+            {
+                "role": "user",
+                "content": [
+                    {"type": "text", "value": "What is "},
+                    {"type": "image_url", "value": "/p/a.jpg"},
+                    {"type": "text", "value": " and what happens in "},
+                    {"type": "video_url", "value": "/p/v.mp4"},
+                    {"type": "text", "value": "?"},
+                ],
+                "loss_weight": 0.0,
+            },
+            {"role": "assistant", "content": [{"type": "text", "value": "An image and a video."}], "loss_weight": 1.0},
+        ]
+    }
+    assert DataConverterPlugin("sharegpt")(example) == expected_data
+
+
+def test_sharegpt_converter_multiple_images_in_order():
+    # images are a sample-level list consumed by <image> tags in document order across turns
+    example = {
+        "conversations": [
+            {"from": "human", "value": "<image><image>Compare these."},
+            {"from": "gpt", "value": "Done."},
+        ],
+        "images": ["/p/a.jpg", "/p/b.jpg"],
+    }
+    user = DataConverterPlugin("sharegpt")(example)["messages"][0]
+    assert user["content"] == [
+        {"type": "image_url", "value": "/p/a.jpg"},
+        {"type": "image_url", "value": "/p/b.jpg"},
+        {"type": "text", "value": "Compare these."},
+    ]
+
+
+def test_sharegpt_converter_no_media_unchanged():
+    # backward compatibility: a scalar (non-list) image column and no tags is normalized; with no
+    # media columns at all the output is byte-identical to the text-only path.
+    example = {"conversations": [{"from": "human", "value": "hi"}, {"from": "gpt", "value": "yo"}]}
+    assert DataConverterPlugin("sharegpt")(example) == {
+        "messages": [
+            {"role": "user", "content": [{"type": "text", "value": "hi"}], "loss_weight": 0.0},
+            {"role": "assistant", "content": [{"type": "text", "value": "yo"}], "loss_weight": 1.0},
+        ]
+    }
+
+
+def test_alpaca_converter_multimodal():
+    example = {"instruction": "Describe <image>", "input": "", "output": "ok", "images": ["/p/a.jpg"]}
+    user = DataConverterPlugin("alpaca")(example)["messages"][0]
+    assert user["content"] == [
+        {"type": "text", "value": "Describe "},
+        {"type": "image_url", "value": "/p/a.jpg"},
+    ]
+
+
+def test_pair_converter_multimodal_shared_media():
+    # chosen and rejected each reference the same sample-level image
+    example = {
+        "chosen": [
+            {"role": "user", "content": "Look at <image>"},
+            {"role": "assistant", "content": "good"},
+        ],
+        "rejected": [
+            {"role": "user", "content": "Look at <image>"},
+            {"role": "assistant", "content": "bad"},
+        ],
+        "images": ["/p/a.jpg"],
+    }
+    out = DataConverterPlugin("pair")(example)
+    for side in ("chosen_messages", "rejected_messages"):
+        assert out[side][0]["content"] == [
+            {"type": "text", "value": "Look at "},
+            {"type": "image_url", "value": "/p/a.jpg"},
+        ]
+
+
+def test_converter_media_count_mismatch():
+    # more tags than media files
+    with pytest.raises(ValueError, match="More <image> tags"):
+        DataConverterPlugin("sharegpt")(
+            {
+                "conversations": [{"from": "human", "value": "<image><image>"}, {"from": "gpt", "value": "x"}],
+                "images": ["/p/a.jpg"],
+            }
+        )
+    # fewer tags than media files
+    with pytest.raises(ValueError, match="Fewer <image> tags"):
+        DataConverterPlugin("sharegpt")(
+            {
+                "conversations": [{"from": "human", "value": "<image>"}, {"from": "gpt", "value": "x"}],
+                "images": ["/p/a.jpg", "/p/b.jpg"],
+            }
+        )
+
+
+def test_converter_audio_column_and_tag():
+    # an <audio> tag consumes the next path from the audios column, lifted into an audio_url block
+    example = {
+        "conversations": [
+            {"from": "human", "value": "hear <audio>What is this?"},
+            {"from": "gpt", "value": "A bell."},
+        ],
+        "audios": ["/p/a.wav"],
+    }
+    user = DataConverterPlugin("sharegpt")(example)["messages"][0]
+    assert user["content"] == [
+        {"type": "text", "value": "hear "},
+        {"type": "audio_url", "value": "/p/a.wav"},
+        {"type": "text", "value": "What is this?"},
+    ]
+
+
+def test_converter_audio_count_mismatch():
+    # more audio tags than files
+    with pytest.raises(ValueError, match="More <audio> tags"):
+        DataConverterPlugin("sharegpt")(
+            {
+                "conversations": [{"from": "human", "value": "<audio><audio>"}, {"from": "gpt", "value": "x"}],
+                "audios": ["/p/a.wav"],
+            }
+        )
+    # fewer audio tags than files
+    with pytest.raises(ValueError, match="Fewer <audio> tags"):
+        DataConverterPlugin("sharegpt")(
+            {
+                "conversations": [{"from": "human", "value": "<audio>"}, {"from": "gpt", "value": "x"}],
+                "audios": ["/p/a.wav", "/p/b.wav"],
+            }
+        )
+
+
 @pytest.mark.parametrize("num_samples", [16])
 def test_pair_converter(num_samples: int):
     data_args = DataArguments(train_dataset="llamafactory/v1-dataset-info/orca-dpo-pairs.yaml")
@@ -117,3 +259,4 @@ def test_pair_converter(num_samples: int):
             ],
         }
         assert data_engine[index] == {"_dataset_name": "tiny_dataset", **expected_data}
+