chore: upgrade sgl-kernel 0.0.9.post2 (#5540)
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@@ -47,7 +47,7 @@ runtime_common = [
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srt = [
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"sglang[runtime_common]",
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"sgl-kernel==0.0.9.post1",
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"sgl-kernel==0.0.9.post2",
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"flashinfer_python==0.2.3",
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"torch==2.5.1",
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"torchvision==0.20.1",
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@@ -93,25 +93,21 @@ class Sampler(nn.Module):
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).clamp(min=torch.finfo(probs.dtype).min)
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max_top_k_round, batch_size = 32, probs.shape[0]
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uniform_samples = torch.rand(
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(max_top_k_round, batch_size), device=probs.device
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)
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if sampling_info.need_min_p_sampling:
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probs = top_k_renorm_prob(probs, sampling_info.top_ks)
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probs = top_p_renorm_prob(probs, sampling_info.top_ps)
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batch_next_token_ids = min_p_sampling_from_probs(
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probs, uniform_samples, sampling_info.min_ps
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probs, sampling_info.min_ps
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)
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else:
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batch_next_token_ids, success = top_k_top_p_sampling_from_probs(
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batch_next_token_ids = top_k_top_p_sampling_from_probs(
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probs,
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uniform_samples,
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sampling_info.top_ks,
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sampling_info.top_ps,
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filter_apply_order="joint",
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)
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if self.use_nan_detection and not torch.all(success):
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if self.use_nan_detection:
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logger.warning("Detected errors during sampling!")
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batch_next_token_ids = torch.zeros_like(batch_next_token_ids)
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