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Fix dummy weight init for tensor subclasses (#29229)

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This commit is contained in:
Aurick Qiao
2026-06-29 01:17:00 +08:00
committed by GitHub
parent c5b9388721
commit ad30a9958e
1 changed files with 4 additions and 1 deletions
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python/sglang/srt/model_loader/weight_utils.py
+4 -1
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@@ -1469,7 +1469,10 @@ def initialize_dummy_weights(
if torch.is_floating_point(param): if torch.is_floating_point(param):
generator = torch.Generator(device=param.data.device) generator = torch.Generator(device=param.data.device)
generator.manual_seed(seed) generator.manual_seed(seed)
if torch.finfo(param.data.dtype).bits < 16: # Tensor subclasses such as MXFP8 wrappers expose a low-bit raw
# storage dtype through `.data`, but their wrapper `uniform_` also
# updates side tensors such as block scales.
if torch.finfo(param.dtype).bits < 16:
# uniform_ doesn't support < 16-bit datatypes (FP8) # uniform_ doesn't support < 16-bit datatypes (FP8)
dtype = param.data.dtype dtype = param.data.dtype
tmp_param = param.data.to(torch.float16) tmp_param = param.data.to(torch.float16)