Hi. When I try to reproduce the behavior you’re describing:
m = torchvision.models.inception_v3(init_weights=False)  # this is for the speedup 
img = torch.randn(1,1,299,299) # dummy image


If use image with  torch.Size([1, 1, 299, 299]), I got this error:
RuntimeError: Given groups=1, weight of size [32, 3, 3, 3], expected input[1, 1, 299, 299] to have 3 channels, but got 1 channels instead
The model doesn’t work with 1 channel images
If you want to predict on the batch size=1, you should put the model in evaluation mode.
To make it work with grayscale image you can try to just copy 1 channel into 2 additional, so to have the correct number of channels and see if it provides meaningful results to you.

This post 18 on how to deal with grayscale image may be of help to you.