Open aasharma90 opened 5 years ago
Hi! Currently, the code does not support batch size > 1 since the images have different sizes and PyTorch cannot support mini-batch with various sizes.
Not sure if this is considered best practice, but if you really want that batch-size speedup you could just pad/resize all images to shared dimensions in the generator
Hi! Currently, the code does not support batch size > 1 since the images have different sizes and PyTorch cannot support mini-batch with various sizes.
hi i wonder if you use batch size =1 ,how long do u train and u use which epoch to test?
We train the HED model for 40 epochs and use the last epoch's checkpoint for evaluation. It takes ~27hrs with one NVIDIA Geforce GTX Titan X (Maxwell).
Hi @xwjabc,
Thanks for your code!
Could you please tell me if it is possible to have a higher batch-size (>1) for training? I see that when I try this out, I get the following error -
upsample2 = torch.nn.functional.conv_transpose2d(score_dsn2, self.weight_deconv2, stride=2)
Expected tensor for argument #1 'input' to have the same device as tensor for argument #2 'weight'
Just wondering if you know this already.
Thanks, AA