Nuo Chen
Nuo Chen
I need to calculate an X of several thousand dimensions, and it take a lot of time for each iteration. Is there a way to speed up the algorithm? Like...
/home/conda/feedstock_root/build_artifacts/pytorch-recipe_1664415167092/work/aten/src/ATen/native/cuda/ScatterGatherKernel.cu:144: operator(): block: [35,0,0], thread: [0,0,0] Assertion `idx_dim >= 0 && idx_dim < index_size && "index out of bounds"` failed. /home/conda/feedstock_root/build_artifacts/pytorch-recipe_1664415167092/work/aten/src/ATen/native/cuda/ScatterGatherKernel.cu:144: operator(): block: [35,0,0], thread: [1,0,0] Assertion `idx_dim >= 0...
 I use rectify_maps.h5 for event rectification,and then visualize the corrected events, the code is: “ xy_rect = rectify_map[y,x] x=xy_rect [:,0] y=xy_rect [:,1] img_size = (480,640) img = np.zeros(shape=img_size,dtype=np.uint8) for...