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Merge branch 'asymmetric-tiling' of https://github.com/carson-katri/InvokeAI into carson-katri-asymmetric-tiling

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Lincoln Stein
2022-10-19 13:46:07 -04:00
parent bc626af6ca 15aa7593f6
commit 92d4dfaabf
5 changed files with 49 additions and 4 deletions
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6
ldm/invoke/args.py
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@ -784,6 +784,12 @@ class Args(object):
action='store_true',
help='Change the model to seamless tiling (circular) mode',
)
special_effects_group.add_argument(
'--seamless_axes',
default=['x', 'y'],
type=list[str],
help='Specify which axes to use circular convolution on.',
)
variation_group.add_argument(
'-v',
'--variation_amount',

30
ldm/invoke/seamless.py Normal file
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@ -0,0 +1,30 @@
import torch.nn as nn
def _conv_forward_asymmetric(self, input, weight, bias):
"""
Patch for Conv2d._conv_forward that supports asymmetric padding
"""
working = nn.functional.pad(input, self.asymmetric_padding['x'], mode=self.asymmetric_padding_mode['x'])
working = nn.functional.pad(working, self.asymmetric_padding['y'], mode=self.asymmetric_padding_mode['y'])
return nn.functional.conv2d(working, weight, bias, self.stride, nn.modules.utils._pair(0), self.dilation, self.groups)
def configure_model_padding(model, seamless, seamless_axes):
"""
Modifies the 2D convolution layers to use a circular padding mode based on the `seamless` and `seamless_axes` options.
"""
for m in model.modules():
if isinstance(m, (nn.Conv2d, nn.ConvTranspose2d)):
if seamless:
m.asymmetric_padding_mode = {}
m.asymmetric_padding = {}
m.asymmetric_padding_mode['x'] = 'circular' if ('x' in seamless_axes) else 'constant'
m.asymmetric_padding['x'] = (m._reversed_padding_repeated_twice[0], m._reversed_padding_repeated_twice[1], 0, 0)
m.asymmetric_padding_mode['y'] = 'circular' if ('y' in seamless_axes) else 'constant'
m.asymmetric_padding['y'] = (0, 0, m._reversed_padding_repeated_twice[2], m._reversed_padding_repeated_twice[3])
m._conv_forward = _conv_forward_asymmetric.__get__(m, nn.Conv2d)
else:
m._conv_forward = nn.Conv2d._conv_forward.__get__(m, nn.Conv2d)
if hasattr(m, 'asymmetric_padding_mode'):
del m.asymmetric_padding_mode
if hasattr(m, 'asymmetric_padding'):
del m.asymmetric_padding