Comments (1)
well, here is an unofficial solution to this problem. I finally find a way to load your dataset on the code.
first, you can find get_loaders_eval function in dataset.py and add your dataset config in it, mind you are supposed to write your Dataset class carefully and write your transforms for image. then, you should go to AutoEncoder class in model.py to modify the value of self.input_size to your input images' width or height. then you can train your model on your own dataset just need to write the command according to the authors.
from nvae.
Related Issues (20)
- FID score of CelebA-HQ 256x256 HOT 1
- NomalDecoder & num_bits
- TypeError: batch_norm_backward_elemt() missing 1 required positional arguments: "count" HOT 1
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from nvae.