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A high-throughput and memory-efficient inference and serving engine for LLMs

Mirrored from https://github.com/tduncan-lum/Nvidia-Optimization-Stack---VLLM.git

Synced Nov 11, 15:00 UTC

[ROCm][Bugfix] Add MLACommonMetadata to allowed attention types for speculative decoding (#30430)

Signed-off-by: Andreas Karatzas <akaratza@amd.com>

Andreas Karatzas committed Dec 11, 2025 at 13:25 UTC 72aaac5b66f908008efed5ba6874c3ed60e6c90a
1 file changed +6
vllm/v1/spec_decode/eagle.py
+6
@@ -178,6 +178,12 @@ class EagleProposer:
178 )
179
180 rocm_types.append(AiterFlashAttentionMetadata)
181 +
182 + # TRITON_MLA backend support for MLA models (e.g., DeepSeek)
183 + from vllm.v1.attention.backends.mla.common import MLACommonMetadata
184 +
185 + rocm_types.append(MLACommonMetadata)
186 +
187 self.allowed_attn_types = tuple(rocm_types)
188
189 # Parse the speculative token tree.