xinyun/ComfyUI
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yoinked 2025-11-26 18:07:59 -08:00 committed by GitHub
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commit af7becd2f1
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1 changed files with 4 additions and 4 deletions
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comfy/ops.py
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@ -476,7 +476,7 @@ def scale_hadamard(larger, smaller, k_value=None, divide=False):
expected_shape = (h * k_value, w * k_value)
assert larger.shape == expected_shape, "weight_scale_inv mismatch, skipping"
if divide:
smaller = 1.0 / smaller
smaller = 1.0 / smaller
result = larger.view(h, k_value, w, k_value) * smaller.view(h, 1, w, 1)
return result.reshape(h * k_value, w * k_value)
@ -492,7 +492,7 @@ def scaled_fp8_ops(fp8_matrix_mult=False, scale_input=False, override_dtype=None
def reset_parameters(self):
if not hasattr(self, 'scale_weight'):
self.scale_weight = torch.nn.parameter.Parameter(data=torch.ones((), device=self.weight.device, dtype=torch.float32), requires_grad=False)
if not hasattr(self, 'weight_scale_inv'):
self.weight_scale_inv = torch.nn.parameter.Parameter(data=torch.ones((), device=self.weight.device, dtype=torch.float32), requires_grad=False)
@ -526,11 +526,11 @@ def scaled_fp8_ops(fp8_matrix_mult=False, scale_input=False, override_dtype=None
weight = scale_hadamard(weight, self.weight_scale_inv.to(device=weight.device, dtype=weight.dtype), k_value=None, divide=False)
return weight
else:
return scale_hadamard(weight.to(dtype=torch.float32) * self.scale_weight.to(device=weight.device, dtype=torch.float32),
return scale_hadamard(weight.to(dtype=torch.float32) * self.scale_weight.to(device=weight.device, dtype=torch.float32),
self.weight_scale_inv.to(device=weight.device, dtype=torch.float32), k_value=None, divide=False)
def set_weight(self, weight, inplace_update=False, seed=None, return_weight=False, **kwargs):
weight = comfy.float.stochastic_rounding(scale_hadamard(weight / self.scale_weight.to(device=weight.device, dtype=weight.dtype),
weight = comfy.float.stochastic_rounding(scale_hadamard(weight / self.scale_weight.to(device=weight.device, dtype=weight.dtype),
self.weight_scale_inv.to(device=weight.device, dtype=weight.dtype), k_value=None, divide=True), self.weight.dtype, seed=seed)
if return_weight:
return weight