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This commit is contained in:
Patrick von Platen
2022-06-29 11:43:30 +00:00
parent 1899457b24
commit d1f2e3e47b
1 changed files with 4 additions and 4 deletions
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8
src/diffusers/models/resnet.py
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@@ -167,8 +167,8 @@ class Downsample(nn.Module):
# class GlideUpsample(nn.Module):
# """
# An upsampling layer with an optional convolution. # # :param channels: channels in the inputs and outputs. :param
use_conv: a bool determining if a convolution is # applied. :param dims: determines if the signal is 1D, 2D, or 3D. If
3D, then # upsampling occurs in the inner-two dimensions. #"""
# use_conv: a bool determining if a convolution is # applied. :param dims: determines if the signal is 1D, 2D, or 3D. If
# 3D, then # upsampling occurs in the inner-two dimensions. #"""
#
# def __init__(self, channels, use_conv, dims=2, out_channels=None):
# super().__init__()
@@ -193,8 +193,8 @@ use_conv: a bool determining if a convolution is # applied. :param dims: determi
# class LDMUpsample(nn.Module):
# """
# An upsampling layer with an optional convolution. :param channels: channels in the inputs and outputs. :param #
use_conv: a bool determining if a convolution is applied. :param dims: determines if the signal is 1D, 2D, or 3D. # If
3D, then # upsampling occurs in the inner-two dimensions. #"""
# use_conv: a bool determining if a convolution is applied. :param dims: determines if the signal is 1D, 2D, or 3D. # If
# 3D, then # upsampling occurs in the inner-two dimensions. #"""
#
# def __init__(self, channels, use_conv, dims=2, out_channels=None, padding=1):
# super().__init__()