The OCR approach is rephrased as Segmentation Transformer: https://arxiv.org/abs/1909.11065. This is an official implementation of semantic segmentation for HRNet. https://arxiv.org/abs/1908.07919
File "/usr/local/lib/python3.5/dist-packages/torch/optim/sgd.py", line 100, in step
buf.mul(momentum).add(1 - dampening, d_p)
RuntimeError: output with shape [256] doesn't match the broadcast shape [18, 72, 1, 256]
Hello! When I resume from saved checkpoint, the optimizer.state do not match optomizer.param_groups
File "/usr/local/lib/python3.5/dist-packages/torch/optim/sgd.py", line 100, in step buf.mul(momentum).add(1 - dampening, d_p) RuntimeError: output with shape [256] doesn't match the broadcast shape [18, 72, 1, 256]
Hello! When I resume from saved checkpoint, the optimizer.state do not match optomizer.param_groups