Polygonization-by-Frame-Field-Learning
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Input and weights data type mismatch
ERROR: Input type (torch.FloatTensor) and weight type (torch.cuda.FloatTensor) should be the same or input should be a MKLDNN tensor and weight is a dense tensor
INPUT data:
{'image': tensor([[[[104, 104, 109, ..., 26, 26, 26], [104, 104, 110, ..., 26, 26, 26], [104, 105, 110, ..., 26, 26, 26], ..., [198, 199, 198, ..., 172, 175, 177], [197, 197, 198, ..., 173, 176, 177], [197, 197, 197, ..., 175, 177, 177]],
[[111, 110, 114, ..., 30, 30, 30], [111, 111, 115, ..., 30, 30, 30], [112, 112, 115, ..., 30, 30, 30], ..., [163, 164, 163, ..., 146, 149, 151], [162, 162, 163, ..., 147, 150, 151], [162, 162, 162, ..., 149, 151, 151]],
[[ 80, 79, 83, ..., 41, 41, 41], [ 80, 80, 84, ..., 41, 41, 41], [ 81, 81, 84, ..., 41, 41, 41], ..., [135, 136, 135, ..., 131, 134, 136], [134, 134, 135, ..., 132, 135, 136], [134, 134, 134, ..., 134, 136, 136]]]], device='cuda:0', dtype=torch.uint8), 'image_mean': tensor([[0.3452, 0.3205, 0.2841]], device='cuda:0', dtype=torch.float64), 'image_std': tensor([[0.1883, 0.1543, 0.1420]], device='cuda:0', dtype=torch.float64)} I have tried multiple things like .to('cuda:0') , .to_gpu() etc, nothing worked. CAN SOMEONE PLEASE HELP ME RESOLVE THIS?