[config] add config files for both CNNs and GANs

bob/learn/pytorch/config/cnn/casianet_casia.py

+
+### DATA ###
+from bob.learn.pytorch.datasets import CasiaWebFaceDataset
+import torchvision.transforms as transforms
+from bob.learn.pytorch.datasets import RollChannels
+from bob.learn.pytorch.datasets import ToTensor
+from bob.learn.pytorch.datasets import Normalize
+dataset = CasiaWebFaceDataset(root_dir='/idiap/project/fargo/xpeng_prepro/CASIA-Webface-crop-128/', 
+                                     transform=transforms.Compose([
+                                       RollChannels(), # bob to skimage:  
+                                       ToTensor(),
+                                       Normalize((0.5, 0.5, 0.5), (0.5, 0.5, 0.5))
+                                     ])
+                                   )
+
+### NETWORK ###
+from bob.learn.pytorch.architectures import CASIANet
+number_of_classes = 10575
+dropout = 0.5
+network = CASIANet(number_of_classes, dropout)

bob/learn/pytorch/config/cnn/cnn8_casia.py

+
+### DATA ###
+from bob.learn.pytorch.datasets import CasiaWebFaceDataset
+import torchvision.transforms as transforms
+from bob.learn.pytorch.datasets import RollChannels
+from bob.learn.pytorch.datasets import ToTensor
+from bob.learn.pytorch.datasets import Normalize
+dataset = CasiaWebFaceDataset(root_dir='/idiap/project/fargo/xpeng_prepro/CASIA-Webface-crop-128/', 
+                                     transform=transforms.Compose([
+                                       RollChannels(), # bob to skimage:  
+                                       ToTensor(),
+                                       Normalize((0.5, 0.5, 0.5), (0.5, 0.5, 0.5))
+                                     ])
+                                   )
+
+### NETWORK ###
+from bob.learn.pytorch.architectures import CNN8
+number_of_classes = 10575
+dropout = 0.5
+network = CNN8(number_of_classes, dropout)

bob/learn/pytorch/config/gan/conditionalgan_multipie.py

+### NETWORK ###
+from bob.learn.pytorch.architectures import ConditionalGAN_generator
+from bob.learn.pytorch.architectures import ConditionalGAN_discriminator
+from bob.learn.pytorch.architectures import weights_init
+
+noise_dim = 100
+conditional_dim = 13
+channels = 3
+ngpu = 1
+
+generator = ConditionalGAN_generator(noise_dim, conditional_dim)
+generator.apply(weights_init)
+discriminator = ConditionalGAN_discriminator(conditional_dim)
+discriminator.apply(weights_init)
+
+
+
+### DATA ###
+from bob.learn.pytorch.datasets.multipie import MultiPIEDataset
+from bob.learn.pytorch.datasets import RollChannels
+from bob.learn.pytorch.datasets import ToTensor
+from bob.learn.pytorch.datasets import Normalize
+import torchvision.transforms as transforms
+
+print("loading data ....")
+
+dataset = MultiPIEDataset(root_dir='/idiap/temp/heusch/data/multipie-cropped-64x64', 
+                                 frontal_only=False, 
+                                 transform=transforms.Compose([
+                                   RollChannels(), # bob to skimage:  
+                                   ToTensor(),
+                                   Normalize((0.5, 0.5, 0.5), (0.5, 0.5, 0.5))
+                                   ])
+                                 )
+
+print("done")

bob/learn/pytorch/config/gan/dcgan_multipie.py

+### DATA ###
+from bob.learn.pytorch.datasets.multipie import MultiPIEDataset
+from bob.learn.pytorch.datasets import RollChannels
+from bob.learn.pytorch.datasets import ToTensor
+from bob.learn.pytorch.datasets import Normalize
+import torchvision.transforms as transforms
+
+dataset = MultiPIEDataset(root_dir='/idiap/temp/heusch/data/multipie-cropped-64x64', 
+                                 frontal_only=True, 
+                                 transform=transforms.Compose([
+                                   RollChannels(), # bob to skimage:  
+                                   ToTensor(),
+                                   Normalize((0.5, 0.5, 0.5), (0.5, 0.5, 0.5))
+                                   ])
+                                 )
+
+### NETWORK ###
+from bob.learn.pytorch.architectures import DCGAN_generator
+from bob.learn.pytorch.architectures import DCGAN_discriminator
+from bob.learn.pytorch.architectures import weights_init
+
+ngpu = 1
+generator = DCGAN_generator(ngpu)
+generator.apply(weights_init)
+discriminator = DCGAN_discriminator(ngpu)
+discriminator.apply(weights_init)
+