Iluvatar-mrv100 SDK 4.3.0

vllm/v1/worker/utils.py

@@ -0,0 +1,29 @@
+# SPDX-License-Identifier: Apache-2.0
+import torch
+
+
+def sanity_check_mm_encoder_outputs(
+    mm_embeddings: object,
+    expected_num_items: int,
+) -> None:
+    """
+    Perform sanity checks for the result of
+    :meth:`vllm.model_executor.models.SupportsMultiModal.get_multimodal_embeddings`.
+    """
+    assert isinstance(mm_embeddings, (list, tuple, torch.Tensor)), (
+        "Expected multimodal embeddings to be a list/tuple of 2D tensors, "
+        f"or a single 3D tensor, but got {type(mm_embeddings)} "
+        "instead. This is most likely due to incorrect implementation "
+        "of the model's `get_multimodal_embeddings` method.")
+
+    assert len(mm_embeddings) == expected_num_items, (
+        "Expected number of multimodal embeddings to match number of "
+        f"input items: {expected_num_items}, but got {len(mm_embeddings)=} "
+        "instead. This is most likely due to incorrect implementation "
+        "of the model's `get_multimodal_embeddings` method.")
+
+    assert all(e.ndim == 2 for e in mm_embeddings), (
+        "Expected multimodal embeddings to be a sequence of 2D tensors, "
+        f"but got tensors with shapes {[e.shape for e in mm_embeddings]} "
+        "instead. This is most likely due to incorrect implementation "
+        "of the model's `get_multimodal_embeddings` method.")