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159a2d1a80
* simple lazy * simple * fix graph and make realize simpler * SHUFFLE_MOVEMENT_OPS already works * MERGE_MOVEMENT_OPS and REMOVE_MOVEMENT_NOPS * it works, but it's slow * constant inlining * cache misses are the reason for loss * fix non determinism * cleanup, a few tests fail * profile * cache lazyop * cleanups * create namedtuple once * bunch of caches * it's not deleting * nograd * caching allocator * reduce_op * fromCPU if you want fromCPU * complain * nvidia fix * realized on Tensor * numpy is very slow * no loads in second run * caching in View * 10ms speedups on batman * remove old profiler * bunch of refactors * contiguous on view * elementwise_op_compile for conv * support ewop after processing op * this still works * conv folding works * all we do is conv conv conv no matter what * all args to the conv * still works * unify conv and ewop * ops_gpu cleanup * move around ops_gpu * remove caching allocator * remove unused * find_conv shorten * gpu refactors * simpler gpu * and that * cmp is fast * 18ms on mac * it's a lot of lines, but it's faster * minor * tests pass * LoadOps.CONTIGUOUS * remove dups * torch converter doesn't support slice * move lazy out for merge * LoadOps are only for lazy