ImageProcess/doc_clean_up/vgg19.py

import torchvision.models as models
from torchsummary import summary
import torch

class VGG19(torch.nn.Module):
    def __init__(self):
        super(VGG19, self).__init__()
        vgg_net = models.vgg19(pretrained=True)
        # summary(vgg_net, (3, 224, 224))
        features = vgg_net.features
        self.relu_1_1 = torch.nn.Sequential()
        self.relu_1_2 = torch.nn.Sequential()
        self.relu_2_1 = torch.nn.Sequential()
        self.relu_3_1 = torch.nn.Sequential()
        self.relu_4_1 = torch.nn.Sequential()
        self.relu_5_1 = torch.nn.Sequential()

        for x in range(0, 2):
            self.relu_1_1.add_module(str(x), features[x])
        for x in range(2, 4):
            self.relu_1_2.add_module(str(x), features[x])
        for x in range(4, 7):
            self.relu_2_1.add_module(str(x), features[x])
        for x in range(7, 12):
            self.relu_3_1.add_module(str(x), features[x])
        for x in range(12, 21):
            self.relu_4_1.add_module(str(x), features[x])
        for x in range(21, 30):
            self.relu_5_1.add_module(str(x), features[x])
        
        # don't need the gradients, just want the features
        for param in self.parameters():
            param.requires_grad = False

    def forward(self, pred, gt):
        h_pred = self.relu_1_1(pred)
        h_gt = self.relu_1_1(gt)
        style_pred_1 = h_pred
        style_gt_1 = h_pred

        h_pred = self.relu_1_2(h_pred)        
        h_gt = self.relu_1_2(h_gt)
        content_pred = h_pred
        content_gt = h_gt

        h_pred = self.relu_2_1(h_pred)        
        h_gt = self.relu_2_1(h_gt)
        style_pred_2 = h_pred
        style_gt_2 = h_gt

        h_pred = self.relu_3_1(h_pred)        
        h_gt = self.relu_3_1(h_gt)
        style_pred_3 = h_pred
        style_gt_3 = h_gt

        h_pred = self.relu_4_1(h_pred)        
        h_gt = self.relu_4_1(h_gt)
        style_pred_4 = h_pred
        style_gt_4 = h_gt

        h_pred = self.relu_5_1(h_pred)        
        h_gt = self.relu_5_1(h_gt)
        style_pred_5 = h_pred
        style_gt_5 = h_gt

        contents = (content_pred, content_gt)
        style_gt_list = [style_gt_1, style_gt_2, style_gt_3, style_gt_4, style_gt_5]
        style_pred_list = [style_pred_1, style_pred_2, style_pred_3, style_pred_4, style_pred_5]
        return contents, style_pred_list, style_gt_list