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adding back skipped layer

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Kent Keirsey 2024-02-13 21:49:42 -05:00
parent 5ed2f6e6c1
commit 30dae0f5aa
1 changed files with 3 additions and 2 deletions
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5
invokeai/backend/model_management/seamless.py
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@ -30,6 +30,8 @@ def set_seamless(model: Union[UNet2DConditionModel, AutoencoderKL], seamless_axe
# Callable: (input: Tensor, weight: Tensor, bias: Optional[Tensor]) -> Tensor # Callable: (input: Tensor, weight: Tensor, bias: Optional[Tensor]) -> Tensor
to_restore: list[tuple[nn.Conv2d | nn.ConvTranspose2d, Callable]] = [] to_restore: list[tuple[nn.Conv2d | nn.ConvTranspose2d, Callable]] = []
try: try:
# Hard coded to skip down block layers, allowing for seamless tiling at the expense of prompt adherence
skipped_layers = 1
for m_name, m in model.named_modules(): for m_name, m in model.named_modules():
if not isinstance(m, (nn.Conv2d, nn.ConvTranspose2d)): if not isinstance(m, (nn.Conv2d, nn.ConvTranspose2d)):
continue continue
@ -40,8 +42,7 @@ def set_seamless(model: Union[UNet2DConditionModel, AutoencoderKL], seamless_axe
block_num = int(block_num) block_num = int(block_num)
resnet_num = int(resnet_num) resnet_num = int(resnet_num)
# Could be configurable to allow skipping arbitrary numbers of down blocks if block_num >= len(model.down_blocks) - skipped_layers:
if block_num >= len(model.down_blocks):
continue continue
# Skip the second resnet (could be configurable) # Skip the second resnet (could be configurable)