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19 lines
798 B
Python
19 lines
798 B
Python
import torch
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import comfy.model_management
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RMSNorm = torch.nn.RMSNorm
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def rms_norm(x, weight=None, eps=1e-6, fused=True):
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if not fused: # compatibility mode as torch native rms_norm results are slightly different
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orig_dtype = x.dtype
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normed = x.float() * torch.pow(x.float().pow(2).mean(-1, keepdim=True) + eps, -0.5)
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if weight is not None:
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weight = comfy.model_management.cast_to(weight, dtype=torch.float32, device=x.device)
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normed = normed * weight
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return normed.to(orig_dtype)
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if weight is None:
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return torch.nn.functional.rms_norm(x, (x.shape[-1],), eps=eps)
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else:
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return torch.nn.functional.rms_norm(x, weight.shape, weight=comfy.model_management.cast_to(weight, dtype=x.dtype, device=x.device), eps=eps)
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