Error on RGB images or channel 3

[deep0learning]

I want to try to implement your code on RGB images where I got the following errors. Can you help me to sort out the problem please?

transform = transforms.Compose([
transforms.Resize((28,28)),
transforms.Grayscale(num_output_channels=3),
transforms.ToTensor(),
transforms.Normalize((0.1307,), (0.3081,))])

File "main.py", line 117, in
predict, reconstruct_img = net(img_batch, label_batch, train=True)
File "/home/user/pytorch_python3/lib/python3.5/site-packages/torch/nn/modules/module.py", line 224, in call
result = self.forward(*input, **kwargs)
File "/media/user/DATA/New_CODE/Working/CapsNet_pytorch/lib/network.py", line 45, in forward
output = self.conv1(x)
File "/home/user/pytorch_python3/lib/python3.5/site-packages/torch/nn/modules/module.py", line 224, in call
result = self.forward(*input, **kwargs)
File "/home/user/pytorch_python3/lib/python3.5/site-packages/torch/nn/modules/conv.py", line 254, in forward
self.padding, self.dilation, self.groups)
File "/home/user/pytorch_python3/lib/python3.5/site-packages/torch/nn/functional.py", line 52, in conv2d
return f(input, weight, bias)
RuntimeError: Need input.size[1] == 1 but got 3 instead.