add SRVGGNetCompact arch, update inference

realesrgan/utils.py

@@ -3,7 +3,6 @@ import math
 import numpy as np
 import os
 import torch
-from basicsr.archs.rrdbnet_arch import RRDBNet
 from basicsr.utils.download_util import load_file_from_url
 from torch.nn import functional as F
 
@@ -16,7 +15,7 @@ class RealESRGANer():
     Args:
         scale (int): Upsampling scale factor used in the networks. It is usually 2 or 4.
         model_path (str): The path to the pretrained model. It can be urls (will first download it automatically).
-        model (nn.Module): The defined network. If None, the model will be constructed here. Default: None.
+        model (nn.Module): The defined network. Default: None.
         tile (int): As too large images result in the out of GPU memory issue, so this tile option will first crop
             input images into tiles, and then process each of them. Finally, they will be merged into one image.
             0 denotes for do not use tile. Default: 0.
@@ -35,9 +34,6 @@ class RealESRGANer():
 
         # initialize model
         self.device = torch.device('cuda' if torch.cuda.is_available() else 'cpu')
-        if model is None:
-            model = RRDBNet(num_in_ch=3, num_out_ch=3, num_feat=64, num_block=23, num_grow_ch=32, scale=scale)
-
         # if the model_path starts with https, it will first download models to the folder: realesrgan/weights
         if model_path.startswith('https://'):
             model_path = load_file_from_url(