Update openaimodel_diffree.py
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@@ -818,7 +818,6 @@ class UNetModel(nn.Module):
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class OMPModule(nn.Module):
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"""
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The full UNet model with attention and timestep embedding.
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:param in_channels: channels in the input Tensor.
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:param model_channels: base channel count for the model.
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:param out_channels: channels in the output Tensor.
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@@ -828,7 +827,7 @@ class OMPModule(nn.Module):
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For example, if this contains 4, then at 4x downsampling, attention
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will be used.
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:param dropout: the dropout probability.
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:param channel_mult: channel multiplier for each level of the UNet.
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:param channel_mult: channel multiplier for each level of the OMPModule.
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:param conv_resample: if True, use learned convolutions for upsampling and
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downsampling.
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:param dims: determines if the signal is 1D, 2D, or 3D.
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