def __init__(self): super().__init__() self.num_classes = num_classes self.num_clusters = num_clusters self.feature_model = resnet_model('resnet50', 'layer4').cuda() self.bin_models = nn.ModuleList([bin_3layer(N0, N1, N2, num_clusters) for i in range(self.num_classes)]).cuda() self.res_models = nn.ModuleList([res_2layer(N0, N3, ndim) for i in range(self.num_classes * self.num_clusters)]).cuda()
def __init__(self): super().__init__() self.num_classes = num_classes self.feature_model = resnet_model('resnet50', 'layer4').cuda() self.pose_models = nn.ModuleList([ bin_3layer(args.N0, args.N1, args.N2, num_clusters) for i in range(self.num_classes) ]).cuda()
def __init__(self, feature_network, num_classes, num_clusters, N0, N1, N2, N3, ndim): super().__init__() self.num_classes = num_classes self.num_clusters = num_clusters self.ndim = ndim self.feature_model = resnet_model('resnet50', 'layer4').cuda() self.bin_model = bin_3layer(N0, N1, N2, num_clusters).cuda() self.res_models = nn.ModuleList([res_2layer(N0, N3, ndim) for i in range(self.num_clusters)]).cuda() self.category_model = nn.Linear(N0, num_classes).cuda()