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 14, 05:30 UTC
[Bugfix] Fix MRoPE dispatch on XPU (#24724)
Signed-off-by: Yan Ma <yan.ma@intel.com>
Yan Ma committed
Sep 12, 2025 at 21:43 UTC
4d7c1d531b89b400b31c9d2e369299d8205980e5
1 file changed
+9
vllm/model_executor/layers/rotary_embedding/mrope.py
+9
@@ -300,6 +300,15 @@ class MRotaryEmbedding(RotaryEmbedding):
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key = torch.cat((key_rot, key_pass), dim=-1).reshape(key_shape)
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return query, key
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+ def forward_xpu(
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+ self,
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+ positions: torch.Tensor,
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+ query: torch.Tensor,
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+ key: Optional[torch.Tensor] = None,
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+ offsets: Optional[torch.Tensor] = None,
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+ ) -> tuple[torch.Tensor, Optional[torch.Tensor]]:
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+ return self.forward_native(positions, query, key, offsets)
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+
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def forward_cpu(
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self,
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positions: torch.Tensor,