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@ -31,13 +31,13 @@ def cast_bias_weight(s, input):
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weight = s.weight_function(weight) |
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return weight, bias |
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class CastWeightBiasOp: |
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comfy_cast_weights = False |
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weight_function = None |
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bias_function = None |
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class disable_weight_init: |
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class Linear(torch.nn.Linear): |
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comfy_cast_weights = False |
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weight_function = None |
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bias_function = None |
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class Linear(torch.nn.Linear, CastWeightBiasOp): |
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def reset_parameters(self): |
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return None |
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@ -51,11 +51,7 @@ class disable_weight_init:
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else: |
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return super().forward(*args, **kwargs) |
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class Conv2d(torch.nn.Conv2d): |
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comfy_cast_weights = False |
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weight_function = None |
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bias_function = None |
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class Conv2d(torch.nn.Conv2d, CastWeightBiasOp): |
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def reset_parameters(self): |
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return None |
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@ -69,11 +65,7 @@ class disable_weight_init:
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else: |
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return super().forward(*args, **kwargs) |
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class Conv3d(torch.nn.Conv3d): |
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comfy_cast_weights = False |
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weight_function = None |
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bias_function = None |
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class Conv3d(torch.nn.Conv3d, CastWeightBiasOp): |
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def reset_parameters(self): |
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return None |
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@ -87,11 +79,7 @@ class disable_weight_init:
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else: |
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return super().forward(*args, **kwargs) |
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class GroupNorm(torch.nn.GroupNorm): |
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comfy_cast_weights = False |
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weight_function = None |
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bias_function = None |
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class GroupNorm(torch.nn.GroupNorm, CastWeightBiasOp): |
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def reset_parameters(self): |
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return None |
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@ -106,11 +94,7 @@ class disable_weight_init:
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return super().forward(*args, **kwargs) |
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class LayerNorm(torch.nn.LayerNorm): |
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comfy_cast_weights = False |
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weight_function = None |
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bias_function = None |
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class LayerNorm(torch.nn.LayerNorm, CastWeightBiasOp): |
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def reset_parameters(self): |
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return None |
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@ -128,11 +112,7 @@ class disable_weight_init:
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else: |
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return super().forward(*args, **kwargs) |
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class ConvTranspose2d(torch.nn.ConvTranspose2d): |
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comfy_cast_weights = False |
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weight_function = None |
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bias_function = None |
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class ConvTranspose2d(torch.nn.ConvTranspose2d, CastWeightBiasOp): |
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def reset_parameters(self): |
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return None |
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