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rebuild base modules

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Artiprocher
2024-07-26 12:15:40 +08:00
parent 9471bff8a4
commit e3f8a576cf
76 changed files with 3253 additions and 3563 deletions
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6
diffsynth/models/sd_vae_encoder.py
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@@ -50,6 +50,8 @@ class SDVAEEncoder(torch.nn.Module):
return hidden_states
def forward(self, sample, tiled=False, tile_size=64, tile_stride=32, **kwargs):
original_dtype = sample.dtype
sample = sample.to(dtype=next(iter(self.parameters())).dtype)
# For VAE Decoder, we do not need to apply the tiler on each layer.
if tiled:
return self.tiled_forward(sample, tile_size=tile_size, tile_stride=tile_stride)
@@ -71,6 +73,7 @@ class SDVAEEncoder(torch.nn.Module):
hidden_states = self.quant_conv(hidden_states)
hidden_states = hidden_states[:, :4]
hidden_states *= self.scaling_factor
hidden_states = hidden_states.to(original_dtype)
return hidden_states
@@ -91,7 +94,8 @@ class SDVAEEncoder(torch.nn.Module):
hidden_states = torch.concat(hidden_states, dim=2)
return hidden_states
def state_dict_converter(self):
@staticmethod
def state_dict_converter():
return SDVAEEncoderStateDictConverter()