[Bug fix] Fix Gemma 2 and fix Gemma 3 multimodal with bs > 1 on NPU (#9871)
Co-authored-by: Maksim <makcum888e@mail.ru>
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@@ -288,16 +288,11 @@ class GemmaRMSNorm(CustomOp):
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x: torch.Tensor,
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residual: Optional[torch.Tensor] = None,
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) -> Union[torch.Tensor, Tuple[torch.Tensor, torch.Tensor]]:
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orig_dtype = x.dtype
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if residual is not None:
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x = x + residual
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residual = x
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x = x.float()
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variance = torch_npu.mean(torch_npu.pow(x, 2), dim=-1, keepdim=True)
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x = x * torch_npu.rsqrt(variance + self.variance_epsilon)
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x = x * (1.0 + self.weight.float())
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x = x.to(orig_dtype)
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x, _ = torch_npu.npu_gemma_rms_norm(x, self.weight, self.variance_epsilon)
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return x if residual is None else (x, residual)
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@@ -46,10 +46,12 @@ from sglang.srt.model_executor.forward_batch_info import (
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ForwardBatch,
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ForwardMode,
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)
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from sglang.srt.utils import dump_to_file, use_intel_amx_backend
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from sglang.srt.utils import dump_to_file, is_npu, use_intel_amx_backend
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logger = logging.getLogger(__name__)
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_is_npu = is_npu()
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@dataclasses.dataclass
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class LogitsProcessorOutput:
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@@ -517,7 +519,12 @@ class LogitsProcessor(nn.Module):
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logits = logits[:, : self.config.vocab_size].float()
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if self.final_logit_softcapping:
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fused_softcap(logits, self.final_logit_softcapping)
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if not _is_npu:
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fused_softcap(logits, self.final_logit_softcapping)
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else:
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logits = self.final_logit_softcapping * torch.tanh(
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logits / self.final_logit_softcapping
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)
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return logits
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@@ -550,7 +550,7 @@ class PrefillAdder:
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)
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else:
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# Make sure at least one page is available
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trunc_len = self.rem_chunk_tokens - self.page_size + 1
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trunc_len = self.rem_chunk_tokens // self.page_size * self.page_size
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if trunc_len <= 0:
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return AddReqResult.OTHER
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