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Addition of SPADE Network + tests and modification of SPADE normalisation #7775

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merged 11 commits into from
Jun 3, 2024
Merged

Addition of SPADE Network + tests and modification of SPADE normalisation #7775

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5e3a3aa
Addition of:
May 16, 2024
a4547fa
Autofix changes.
May 16, 2024
c5834de
Addition of option for activation layer in the SPADE Decoder. It was,…
May 16, 2024
0261386
Ran autofix!
May 16, 2024
e5db55b
mypy fixes
marksgraham May 17, 2024
0fdf990
formatting
marksgraham May 17, 2024
9ada8d2
DCO Remediation Commit for virginiafdez <[email protected]>
May 17, 2024
77a042c
Modification of test_spade_vaegan.py as per review (change of asserts).
May 20, 2024
d69023c
- Modification of the spade_network to include suggested changes: mor…
May 27, 2024
34d7016
Merge branch 'gen-ai-dev' into spade_vae
KumoLiu May 31, 2024
e6b56c6
Clarification of functionality in SPADE network decoder.
Jun 2, 2024
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7 changes: 3 additions & 4 deletions monai/networks/blocks/spade_norm.py
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Original file line number Diff line number Diff line change
Expand Up @@ -15,7 +15,8 @@
import torch.nn as nn
import torch.nn.functional as F

from monai.networks.blocks import ADN, Convolution
from monai.networks.blocks import Convolution
from monai.networks.layers.utils import get_norm_layer


class SPADE(nn.Module):
Expand Down Expand Up @@ -50,9 +51,7 @@ def __init__(
norm_params = {}
if len(norm_params) != 0:
norm = (norm, norm_params)
self.param_free_norm = ADN(
act=None, dropout=0.0, norm=norm, norm_dim=spatial_dims, ordering="N", in_channels=norm_nc
)
self.param_free_norm = get_norm_layer(norm, spatial_dims=spatial_dims, channels=norm_nc)
self.mlp_shared = Convolution(
spatial_dims=spatial_dims,
in_channels=label_nc,
Expand Down
1 change: 1 addition & 0 deletions monai/networks/nets/__init__.py
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Expand Up @@ -110,6 +110,7 @@
)
from .spade_autoencoderkl import SPADEAutoencoderKL
from .spade_diffusion_model_unet import SPADEDiffusionModelUNet
from .spade_network import SPADENet
from .swin_unetr import PatchMerging, PatchMergingV2, SwinUNETR
from .torchvision_fc import TorchVisionFCModel
from .transchex import BertAttention, BertMixedLayer, BertOutput, BertPreTrainedModel, MultiModal, Pooler, Transchex
Expand Down
8 changes: 4 additions & 4 deletions monai/networks/nets/spade_diffusion_model_unet.py
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Expand Up @@ -53,7 +53,7 @@
__all__ = ["SPADEDiffusionModelUNet"]


class SPADEResnetBlock(nn.Module):
class SPADEDiffResBlock(nn.Module):
"""
Residual block with timestep conditioning and SPADE norm.
Enables SPADE normalisation for semantic conditioning (Park et. al (2019): https://github.com/NVlabs/SPADE)
Expand Down Expand Up @@ -238,7 +238,7 @@ def __init__(
resnet_in_channels = prev_output_channel if i == 0 else out_channels

resnets.append(
SPADEResnetBlock(
SPADEDiffResBlock(
spatial_dims=spatial_dims,
in_channels=resnet_in_channels + res_skip_channels,
out_channels=out_channels,
Expand Down Expand Up @@ -356,7 +356,7 @@ def __init__(
resnet_in_channels = prev_output_channel if i == 0 else out_channels

resnets.append(
SPADEResnetBlock(
SPADEDiffResBlock(
spatial_dims=spatial_dims,
in_channels=resnet_in_channels + res_skip_channels,
out_channels=out_channels,
Expand Down Expand Up @@ -491,7 +491,7 @@ def __init__(
resnet_in_channels = prev_output_channel if i == 0 else out_channels

resnets.append(
SPADEResnetBlock(
SPADEDiffResBlock(
spatial_dims=spatial_dims,
in_channels=resnet_in_channels + res_skip_channels,
out_channels=out_channels,
Expand Down
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