add pytorch2onnx

scripts/pytorch2onnx.py

@@ -0,0 +1,17 @@
+import torch
+import torch.onnx
+from basicsr.archs.rrdbnet_arch import RRDBNet
+
+# An instance of your model
+model = RRDBNet(num_in_ch=3, num_out_ch=3, num_feat=64, num_block=23, num_grow_ch=32)
+model.load_state_dict(torch.load('experiments/pretrained_models/RealESRGAN_x4plus.pth')['params_ema'])
+# set the train mode to false since we will only run the forward pass.
+model.train(False)
+model.cpu().eval()
+
+# An example input you would normally provide to your model's forward() method
+x = torch.rand(1, 3, 64, 64)
+
+# Export the model
+with torch.no_grad():
+    torch_out = torch.onnx._export(model, x, 'realesrgan-x4.onnx', opset_version=11, export_params=True)