chore: import upstream snapshot with attribution

tests/models/multimodal/processing/test_step3_vl_image_embeds.py

@@ -0,0 +1,58 @@
+# SPDX-License-Identifier: Apache-2.0
+# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
+"""Tests for Step3-VL precomputed image embedding inputs."""
+
+import pytest
+import torch
+
+from vllm.model_executor.models.step3_vl import (
+    Step3VLForConditionalGeneration,
+    Step3VLImageEmbeddingInputs,
+)
+
+
+class _FakeStep3VL:
+    @staticmethod
+    def _process_image_features(image_features: torch.Tensor) -> torch.Tensor:
+        return image_features
+
+
+def test_image_embedding_inputs_construction():
+    """Step3VLImageEmbeddingInputs should store embeddings in the data field."""
+    image_embeds = torch.randn(2, 16, 64)
+
+    inputs = Step3VLImageEmbeddingInputs(
+        type="image_embeds",
+        data=image_embeds,
+    )
+
+    assert inputs["type"] == "image_embeds"
+    assert torch.equal(inputs["data"], image_embeds)
+    assert torch.equal(inputs.data, image_embeds)
+
+
+def test_image_embedding_inputs_validation_rejects_wrong_rank():
+    """Validation should reject tensors with wrong rank."""
+    with pytest.raises(ValueError, match="rank"):
+        Step3VLImageEmbeddingInputs(
+            type="image_embeds",
+            data=torch.randn(16, 64),
+        )
+
+
+def test_process_image_embeds_does_not_require_pixel_input_fields():
+    """The image_embeds branch should not reference patch pixel metadata."""
+    image_embeds = torch.randn(2, 4, 8)
+    image_input = Step3VLImageEmbeddingInputs(
+        type="image_embeds",
+        data=image_embeds,
+    )
+
+    outputs = Step3VLForConditionalGeneration._process_image_input(
+        _FakeStep3VL(),
+        image_input,
+    )
+
+    assert len(outputs) == 2
+    assert torch.equal(outputs[0], image_embeds[0])
+    assert torch.equal(outputs[1], image_embeds[1])