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Resolve the problem with conv weights #183

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Resolve the problem with conv weights #183

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2 changes: 2 additions & 0 deletions loralib/layers.py
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Original file line number Diff line number Diff line change
Expand Up @@ -247,6 +247,8 @@ class ConvLoRA(nn.Module, LoRALayer):
def __init__(self, conv_module, in_channels, out_channels, kernel_size, r=0, lora_alpha=1, lora_dropout=0., merge_weights=True, **kwargs):
super(ConvLoRA, self).__init__()
self.conv = conv_module(in_channels, out_channels, kernel_size, **kwargs)
for name, param in self.conv.named_parameters():
self.register_parameter(name, param)
LoRALayer.__init__(self, r=r, lora_alpha=lora_alpha, lora_dropout=lora_dropout, merge_weights=merge_weights)
assert isinstance(kernel_size, int)
# Actual trainable parameters
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