Replace torch.jit.script with torch.compile in get_masked_input_and_mask to fix benchmark underreporting (#8733)
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@@ -26,7 +26,12 @@ from sglang.srt.layers.quantization.base_config import (
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method_has_implemented_embedding,
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)
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from sglang.srt.layers.quantization.unquant import UnquantizedEmbeddingMethod
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from sglang.srt.utils import cpu_has_amx_support, is_cpu, set_weight_attrs
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from sglang.srt.utils import (
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cpu_has_amx_support,
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get_compiler_backend,
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is_cpu,
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set_weight_attrs,
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)
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DEFAULT_VOCAB_PADDING_SIZE = 64
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@@ -117,7 +122,7 @@ class VocabParallelEmbeddingShardIndices:
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assert self.num_added_elements <= self.num_added_elements_padded
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@torch.jit.script
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@torch.compile(dynamic=True, backend=get_compiler_backend())
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def get_masked_input_and_mask(
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input_: torch.Tensor,
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org_vocab_start_index: int,
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@@ -126,7 +131,7 @@ def get_masked_input_and_mask(
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added_vocab_start_index: int,
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added_vocab_end_index: int,
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) -> Tuple[torch.Tensor, torch.Tensor]:
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# torch.jit.script will fuse all of the pointwise ops below
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# torch.compile will fuse all of the pointwise ops below
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# into a single kernel, making it very fast
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org_vocab_mask = (input_ >= org_vocab_start_index) & (input_ < org_vocab_end_index)
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added_vocab_mask = (input_ >= added_vocab_start_index) & (
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