Can i do train grayscale-imageset?

[edwardcho]

Hello Sir,

I want to train using my-datasets (grayscale).
After change input_dim_a, input_dim_b = 1, I tried to it.

I met some errors.

Traceback (most recent call last):
  File "train.py", line 65, in <module>
    trainer.dis_update(images_a, images_b, config)
  File "/data1/TESTBOARD/additional_networks/generation/MUNIT_NVlabs/trainer.py", line 152, in dis_update
    c_a, _ = self.gen_a.encode(x_a)
  File "/data1/TESTBOARD/additional_networks/generation/MUNIT_NVlabs/networks.py", line 119, in encode
    style_fake = self.enc_style(images)
  File "/home/itsme/anaconda3/lib/python3.7/site-packages/torch/nn/modules/module.py", line 1051, in _call_impl
    return forward_call(*input, **kwargs)
  File "/data1/TESTBOARD/additional_networks/generation/MUNIT_NVlabs/networks.py", line 204, in forward
    return self.model(x)
  File "/home/itsme/anaconda3/lib/python3.7/site-packages/torch/nn/modules/module.py", line 1051, in _call_impl
    return forward_call(*input, **kwargs)
  File "/home/itsme/anaconda3/lib/python3.7/site-packages/torch/nn/modules/container.py", line 139, in forward
    input = module(input)
  File "/home/itsme/anaconda3/lib/python3.7/site-packages/torch/nn/modules/module.py", line 1051, in _call_impl
    return forward_call(*input, **kwargs)
  File "/data1/TESTBOARD/additional_networks/generation/MUNIT_NVlabs/networks.py", line 342, in forward
    x = self.conv(self.pad(x))
  File "/home/itsme/anaconda3/lib/python3.7/site-packages/torch/nn/modules/module.py", line 1051, in _call_impl
    return forward_call(*input, **kwargs)
  File "/home/itsme/anaconda3/lib/python3.7/site-packages/torch/nn/modules/conv.py", line 443, in forward
    return self._conv_forward(input, self.weight, self.bias)
  File "/home/itsme/anaconda3/lib/python3.7/site-packages/torch/nn/modules/conv.py", line 440, in _conv_forward
    self.padding, self.dilation, self.groups)
RuntimeError: Given groups=1, weight of size [64, 1, 7, 7], expected input[1, 3, 262, 262] to have 1 channels, but got 3 channels instead

I checked my datasets several times. My dataset is all grayscale (1ch.)

How to train it?

Thanks,
Edward Cho.