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25 lines
963 B
Python
25 lines
963 B
Python
import modules.lora.network as network
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class ModuleTypeNorm(network.ModuleType):
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def create_module(self, net: network.Network, weights: network.NetworkWeights):
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if all(x in weights.w for x in ["w_norm", "b_norm"]):
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return NetworkModuleNorm(net, weights)
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return None
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class NetworkModuleNorm(network.NetworkModule): # pylint: disable=abstract-method
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def __init__(self, net: network.Network, weights: network.NetworkWeights):
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super().__init__(net, weights)
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self.w_norm = weights.w.get("w_norm")
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self.b_norm = weights.w.get("b_norm")
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def calc_updown(self, target):
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output_shape = self.w_norm.shape
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updown = self.w_norm.to(target.device, dtype=target.dtype)
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if self.b_norm is not None:
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ex_bias = self.b_norm.to(target.device, dtype=target.dtype)
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else:
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ex_bias = None
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return self.finalize_updown(updown, target, output_shape, ex_bias)
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